耶路撒冷东北25千米的Tell el Sultan是《圣经》上反复出现的一个地名，1870年代，考古发掘证实，这里实际上属于《圣经》中提及次数更多的古城耶利哥（Jericho）的一部分。后来，这一带陆续出土的古人类定居的遗址逐渐超过20处，时间大多超过4 000年。1952-1958年，英国的女考古学家凯瑟琳·凯尼恩（Kathleen Kenyon，1906-1978）主持对新的土层进行系统挖掘，彻底改变了人们对历史的看法：耶利哥的早期人类遗迹超过一万年。
1968年，人们在叙利亚境内的幼发拉底河上建造塔巴水坝（Tabqa Dam）时，挖掘出一个人类居住了近4 000年（1.1万——0.75万年前）的遗址——阿布·胡列伊拉（Tell Abu Hureyra）。这是一个从狩猎采集生活形态向农业种植形态过渡的遗址，这里的生活者也因此被称为世界上最早的农民。在这个遗址，从土壤和动物鱼骨等物质中成功分离出712个种子样本，最终查明属于150类以上食用植物的500多种植物种子。这个叙利亚遗址再现了1.1万年前的人类采集狩猎生活方式，和大约一万年前开始的初步的农业种植生活的轮廓。
卡拉卡山区丰富的可食用植物种子和种植技术，沿着黎巴嫩——以色列——叙利亚——伊拉克，一直传播到地中海沿岸。其中最著名的遗迹包括耶利哥（Jericho）、叙利亚的阿布·胡列伊拉遗址（Tell Abu Hureyra）、土耳其的加泰土丘（Catal Huyuk）。（加泰土丘挖掘时间在1950-1990年，新石器时代的14层遗迹厚度达15米，时间为8 850年前，当时已经进入所谓的金石混用时代（中东学者对青铜时代的称呼），艺术和宗教的文物极其丰富）
这项研究没有取得什么结果。血型和细胞表面蛋白质标记无法确认人的血统世系，也无法落实迁移路线。这是当时的研究技术的限制。但是，斯福扎发现农业并非单纯的文化现象，而是伴随着人口的快速增长，这股风潮从欧洲的东南部向西北部扩散，后来被称为“前进的浪潮”（Wave of Advance）。这种“前进的浪潮”被很多人接受了，但是斯福扎本人并不接受这种观念，因为人们还没有搞清楚欧洲的基因库的起源。
美国国家健康研究院（National Institutes of Health）的迪尔德丽·乔伊（Deirdre Joy）和她的同事发现，疟原虫在5万年前开始多样化，这个时间恰好是人类走出非洲的时期，暗示人类带着疟原虫前往世界各地。乔伊还发现了其他证据，一万年前，疟原虫开始大规模的多样化，这个时间正是新石器革命的农业起源的时间。
G6PD是细胞里的一种酶，可以把葡萄糖转化成一种亚细胞能量包（subcellular energy packet），这种亚细胞能量包名为NADPH，是人类细胞能量活力的来源。我们吃下的谷物——碳水化合物又称多糖类，被转化为单糖（葡萄糖）后，最终变成我们细胞里的三种能量：NADPH、NADH和ATP。所以G6PD极其重要。
威廉·布莱船长（William Bligh，1754-1817）的故事《叛舰喋血记》（The Mutiny of the Bounty）曾5次被搬上银幕。1789年，他率领的“邦蒂号”（Bounty）经过6个月航行抵达塔希提。他一路上都严苛地虐待水手，抵达塔希提后，他强令水手不许寻找当地女人以免传染性病。
第一个指出这种风险的学者是日本裔美国生物学家大野乾（Susumu Ohno，1928-2000），他在1970年所著的《基因重复的进化》（Evolution by GeneDuplication）一书中提出：重复基因时，随心所欲地草率选择，会导致“快速进化”的变异，必须保留备份。他创造出“垃圾DNA”（junk DNA）一词，用以描述基因组里的很多功能不详的DNA。这种垃圾是重复基因的必然宿命，也许毫无意义，也许后果致命。
世界自然遗产大烟山国家公园（Great Smoky Mountains National Park）是美国旅游人数最多的国家公园之一，每年有900万——950万游人。位于田纳西州东部的大型游乐场多莱坞（Dollywood）的游客每年超过200万人。如果我们去大烟山和多莱坞旅游，就会发现几乎处处都是肥胖者。
1991年，美国没有任何一个州的肥胖人口超过20%。仅仅20多年间发生的变化无法用基因变化来解释。现在85%以上的美国人认为，肥胖是一种病。美国疾病控制预防中心（Centers for Disease Control and Prevention）和世界卫生组织的调查确认，肥胖是仅次于吸烟的第二大流行病，并将在10年内成为世界第一大流行病。（现代人的食物远远超过了实际需求。线粒体以氧气为原料，每天制造的ATP能量的重量占人体体重的一半，为人类制造能量的效率为20万倍）
现代饮食中，排名第一位的罪犯是糖。人类的基因因为无法处理过量的糖（碳水化合物），从而导致糖尿病。另一个重要罪犯是添加剂。2002年，埃里克·施洛瑟（Eric Schlosser，1959-）出版了大型调查报告《快餐民族：所有美国人食物的黑暗面》（Fast Food Nation: The Dark Side of the AllAmerican Meal）。这本书列举了很多数据，例如，麦当劳草莓奶昔由60多种添加剂构成，唯独没有任何草莓成分，含糖很多。又如，番茄酱（ketchup）的三分之一是糖。这本调查报告引起巨大轰动，美国涌现大量类似书籍，出现多部电影，批判反思现代饮食文化。
狩猎采集时代的田园牧歌，不可能时光倒流。（北美土著有一句古老格言：善等地球。它不是你父母给你的，它是你的孩子们借给你的。Treat the earth well. It was not given to you by your parents， but is loaned to you by your children.）
农业文化认为，向地球索取可以无穷无尽，尤其最近几个世纪的无限制扩张和掠夺几乎达到疯狂。可是，土地终有尽头，地球终有尽头。 农业文化发展进步的陈旧模式面临资源枯竭的致命挑战，继续维持已不可能。虽然我们无法回到农业以前的时代，但是狩猎采集时代的人类文化值得我们反思和借鉴。 人口与人，完全是两个不同的概念。托马斯·马尔萨斯（Thomas Robert Malthus，1766-1834）说：“人口的力量无限大于索取地球而求生存的人的力量。”
1900年，一场不文明的内战打响了，这是孟德尔的遗传学针对达尔文的自然选择的战争。大部分生物学家认为，这场战争的结果将是一个理论灭绝另一个理论。三个复活了孟德尔的科学家之一，胡戈·德弗里斯（Hugo de Vries）首先发明了突变理论（mutation theory），他认为物种起源是某些罕见的突变引起的。
摩尔根的小小的纽约实验室原本拥挤狭小得滑稽可笑，1928年，成为生物学的“重要人物”之后，他搬到了加利福尼亚州的洛杉矶的宽敞明亮的新实验室里，雄心勃勃地希望建立自己的理论体系，虽然他的果蝇实验和突变理论实际上只是追随别人的实验模式和理论。他在洛杉矶加州理工学院（California Institute of Technology）创建的生物系，先后培育出了7个诺贝尔奖得主。
1952年，更好的证据出现了。阿弗雷德·赫希（Alfred Day Hershey，1908-1997）和他的女助理玛莎·蔡斯（Martha Cowles Chase，1927-2003），在美国纽约的冷泉港实验室（Cold Spring Harbor Laboratory）利用病毒进行的著名的赫希——蔡斯实验（Hershey-Chase experiment），证实了DNA是遗传物质。
1953年，一年之后，剑桥大学的两个年轻人，詹姆斯·沃森和弗朗西斯·克里克终于搞清了DNA的奇特而稳定的化学分子结构。1954年，20个青年学者（代表20种氨基酸）组成RNA领带俱乐部（RNA Tie Club），讨论分析DNA→RNA→蛋白的遗传关系：DNA是双链，RNA是单链，DNA将遗传信息交给“信使”RNA，然后由RNA指令细胞制造蛋白。这个遗传信息的转达和表达过程，转瞬即逝，机理难以查明。DNA→RNA→蛋白的遗传制造过程中，当然也会出现错误，但是细胞通常会立刻修正这些错误，否则这些错误就永久留在DNA里遗传下去。
1958年，DNA结构的两个发现者之一，弗朗西斯·克里克（Francis Crick）发布了著名的“分子生物学中心法则”（Central dogma of molecular biology）。这个中心法则的主要含义是：DNA制造RNA制造蛋白质（DNA makes RNA makes protein）。
（1979年洛夫洛克出版了《盖亚：对地球生命的新看法》（Gaia: A New Look at Life on Earth），这是洛夫洛克出版的“盖亚理论”的第一本书。他出版了多部著作，如： Lovelock， James. Gaia: A New Look at Life on Earth. Oxford University Press， Oxford， England. 洛夫洛克的这个观念，其实并非全新的观念。）
加利福尼亚州的红杉（S e q u o i a gigantea）是生命的最好注解。这些巨树生长在树丛里，高度达到100米以上，寿命超过3 000年。红杉97%的组织是死的，主干和树皮已经死去，只有主干外表的细胞部分是活的。红杉的主干类似地球的岩石圈，只有岩石圈外表薄薄一层生物圈是活的。红杉的树皮类似大气层，保护着这层生物圈，并且进行生物学意义上非常重要的气体交换——二氧化碳和氧气的交换。 毫无疑问，红杉总体上是活的生命，我们不能只把红杉的外层称为红杉，其余部分视为死的木头。
2012年9月5日，人们又一次发现自己错了。 2012年9月5日开始，世界第一大媒体《时代》的一篇报道的题目本身就蕴含认错的含义：《垃圾基因：其实并非无用》（Junk DNA-Not So Useless After All）。这篇报道连续5天占据《时代》网络版头版位置。 这个消息，也是世界所有媒体的头版新闻。
YAP是Y染色体Alu多态性（Y Alu Polymorphism）的简称，Alu是Y染色体上长度约300碱基对（核苷酸）的一个区段，又称阿鲁元素（Alu element），这个无害的Alu重复地插入人类基因组的不同部位，插入模式已经超过100万种并遗传给后裔。约5万年前，一个男人体内的Y染色体上出现了这个300碱基对的区段并遗传给他的后裔。
奴隶制度的拥护者曾经认为，现代人分为很多物种和亚种，殖民者与奴隶不是一个物种。瑞典科学家卡尔·冯·林奈（Carl von Linne）最早提出这一体系。林奈是一个植物学家，他首先用拉丁文命名植物，随后扩展到动物。他把人类命名为智人（Homo sapiens）。他认为所有的人类属于同一物种——智人的不同亚种和地理种，他还认为人的种族是互不相同的、分别诞生的、多元发生的。这种思想起始于希腊时代的人类“多起源说”。
《物种起源》：原书全称《物种起源，通过自然选择的方式或在生存斗争保留优势种群的方式》（On the Origin of Species by Means of Natural Selection， or the Preservation of Favoured Races in the Struggle for Life）（注：这本书英文原名《种的起源》，日文译名也是《种的起源》，国内长期译为《物种起源》，本书沿袭旧译名）。
《人的由来》：原书全称叫作《人的由来，与性关系的选择》（The Descent of Man，and Selection in Relation to Sex）。
1960年代，人类学家的世界最高权威之一、美国体质人类学家协会（American Association of Physical Anthropologists）会长卡尔顿·库恩（Carleton Coon）发表了影响很大的两本著作：《种族的起源》（The Origin of Races）和《人的现存种族》（The Living Races of Man）。库恩在他的权威巨著中，把现代人类进一步细分为互不相同的五大亚种（实际是地理种）： Australoid ：澳大利亚人种（澳大利亚土著，又称棕种人）； Caucasoid ：高加索人种（欧洲——北非——西亚——中亚——南亚，又称白种人，虽然肤色不一）； Negroid ：尼格罗人种（非洲撒哈拉南部，东南亚小岛与山区，又称Congoid或黑种人）； Capoid ：开普敦人种（非洲南部，如布须曼人——桑人）； Mongoloid ：蒙古利亚人种（亚洲大部——北极圈——南北美洲——太平洋诸岛，又称黄种人）。
1987年1月，美国一个在读遗传学女博士丽贝卡·卡恩（Rebecca Cann）和她的同事们在英国《自然》（Nature）杂志发表了一篇论文：《线粒体DNA和人类的演化》（Mitochondrial DNA and Human Evolution）。论文认为：人类起源只有一个，这个起源可能在非洲，时间在20万年以内。尽管几乎不可思议，但DNA数据研究分析却证明了：今天所有的地球人都来自同一个共同祖先。
1987年，英国《自然》（Nature）杂志上发表的著名的mtDNA树：世界147个人的线粒体DNA计算分析。论文的三个署名作者与顺序：丽贝卡·卡恩 Rebecca Cann 马克·斯通尼金 Mark Stoneking 阿伦·威尔逊 Allan Wilson 这是一个里程碑
这就是“线粒体夏娃”的秘密。
1987年，丽贝卡·卡恩和她的同事发表这一结果之后，面对激烈的争议和质疑，他们又开始了一项新的研究。1987年9月，丽贝卡·卡恩和她的同事们又在英国《自然》（Nature）杂志发表了第二篇论文：《有争议的人类群体非洲起源》（DisputedAfrican origin of human populations），再次证实“线粒体夏娃”确实就在非洲。
但是，DNA的这些X射线的照片的形态太奇特了，他们两人很久都没有找到与之相吻合的DNA化学结构。最后，沃森和克里克采用了非常笨拙的“原始”方法，用一条一条的硬纸板和一片一片的金属片和金属丝，构建各式各样的模型，试图重现DNA的结构。他们最后发现有一种双螺旋模型完全吻合X射线的分布。这种模型很简单，像两个螺旋形的梯子扭结在一起。而且这种结构非常稳定——只有稳定的结构才能作为遗传物质。DNA正是一种极其稳定的化学结构，仅由4种核苷酸碱基构成的一种糖类骨架。这4种核苷酸的化学名称如下： A 腺嘌呤 C 胞嘧啶 G 鸟嘌呤 T 胸腺嘧啶
宗族母亲（宗族母亲必须有两个女儿，而不是一个女儿。母系祖先是这8个女人最晚近的共同祖先——她的母亲当然也是此后所有女人的母系祖先，但她母亲不是最晚近的，她本人才是。她的两个女儿也是后继的女人的母系祖先，但没有一个是所有这8个女人的共同母系祖先。也就是说，如果将上图视为一个宗族，只有标为MRCA的这个女人是宗族母亲。不论8个人还是800万人的宗族都适用这同一原则（MRCA，Most Recent Common Ancestor：最晚近的共同先祖））
1996年，美国的《历史频道》（The History Channel）在《最伟大的法老》节目中列举了15位埃及法老，其中第10位伟大法老是图坦卡蒙（Tutankhamun），他的在位时间大约是公元前1334-前1325年：八九岁即位，在位大约10年。这位图坦卡蒙法老，任何“伟大的功业”也没有干过。他的“伟大”之处仅仅在于他的陵墓在3 300多年里没有被盗，是唯一没有被盗的埃及法老陵墓。
帕博（Svante Paabo，1955-，曾经恢复埃及木乃伊的DNA和尼安德特人的DNA）1997年开始任马克斯·普朗克进化人类学研究所（Max Planck Institute for Evolutionary Anthropology）的遗传部主任。马普进化人类学研究所有五个部，属于德国马普研究院（Max Planck Society）。马普研究院有32位诺贝尔奖获得者，包括斯万特·帕博的父亲。1980年代，帕博和他的同行，包括找到“线粒体夏娃”的三个论文作者之一阿伦·威尔逊（Allan Wilson，1934-1991）等人，在德国和美国分别开始了古代DNA领域的研究。他们首先找出埃及木乃伊的DNA序列，然后很快转向化石。
1995年11月，在西班牙巴塞罗那召开的第二届欧洲群体历史会议（Second Euroconference on Population History）上，出现了一场激烈争辩。牛津大学的赛克斯在发言中用线粒体DNA的事实批驳了“欧洲人起源于中东农民”的主流观点。发言结束后的提问时间，“前进的浪潮”的支持者们提出各种意见，但是在DNA数据面前，却又无话可说。斯福扎也在会场，他没有多说什么。会议结束后的五年里，激烈的争论一直没有停止。这是又一场欧洲人的起源之战。
在科学界，巴塞罗那“欧洲群体历史会议”之类的国际会议可以宣布新的发现，但是会议的报告不是真正有效的，必须在科学期刊上发表。发表过程中，一批评审专家将对立题——结果——解释进行彻底的审查，称为同行评审。评审专家必须与作者没有任何利益冲突。牛津大学把报告送到《美国人类遗传学杂志》（American Journal of Human Genetics），受到非同寻常的严格审查。不仅要求对1995年发表的数学化的晦涩难懂的网络构建方法加上一个附录，作出进一步解释，还要求加上传统的群体比较表格。从巴塞罗那会议到论文发表，评审拖延长达8个月。当时世界各国的实验室和大学都在进行DNA的研究，没有统一标准，甚至互相保密，方法不同，DNA的表述和编号也不一致，这一切直到美国的人类基因组工程之后才逐步统一。
达尔文是一位性格平和、实事求是的博物学家，他喜欢观察，喜欢化石。他的名字前面的一长串各式各样的称号，都是后人添加的头衔。在《物种起源》中，达尔文甚至没用“进化”（evolution）一词，而是采用了“更改的后代”（descent with modification）一词，因为他认为，进化一词含有进步的含义，物种的遗传变化只是为了适应变化的环境，并没有进步或退步的含义。达尔文除了收集各个物种的标本，还收集了大量化石。但是，达尔文当时还无法分辨清楚这些化石，也没有条件进行统计学的分析。
但是，正如达尔文的推测，世界上化石最多的地方在非洲。1920年代，非洲的猿人化石开始大量出土，远远超过欧洲和亚洲。1921年，赞比亚发现第一个猿人化石。1922年，雷蒙德·达特（Raymond Dart，1893-1998）被任命为南非威特沃特斯兰德大学（University of the Witwatersrand）的人类学教授，开始组建一个人类学系。1924年，达特确认，在赞比亚发现的是迄今最古老的猿人化石。1959年，在距离赞比亚几千千米的肯尼亚，路易斯·李基（Louis Leakey）发现了一个175万年前的南方古猿（Australopithecus）。这一考古发现，将非洲地区的远古类人猿的生存年代延长了大约一倍。此后的考古发现，非洲人科生物的化石年代越来越久远，分布越来越广泛。
此后的几十年里，越来越多的非洲南方古猿（Southern Ape Man）的化石大量出土，其数量之大，超出世界上其他所有地方的总和。人类起源于非洲的理论，在事实面前逐渐被世界接受。
非洲南方古猿（Southern Ape Man）的年代逐渐向前延伸：300万年，400万年……最新发现的类似黑猩猩的猿人Ardipitbecus（地猿）进一步把非洲猿人的年代延伸到560万年前的中新世（Miocene）。但是，伯克利大学计算出来的“线粒体夏娃”这个现代智人的诞生时间，仅仅不到20万年，这到底是怎么一回事？（1974年11月，露西（Lucy）在埃塞俄比亚出土，她的年龄约20岁，生活年代约320万年前。露西属于南方古猿阿法种（Australopithecus afarensis），这种古猿与现代人的关系目前仍不清楚。露西被列为联合国世界文化遗产）
1994年，诺贝尔奖获得者沃特·吉尔伯特（Walter Gilbert）和罗布·多利特（Rob Dorit）、广濑明石（Hiroshi Akashi）在《科学》上发表了一篇奇特的论文。这篇论文的奇特在于：他们不是报道发现了什么，而是报道没有发现什么，论文的题目是《人类Y染色体在ZFY区段不存在多态性》（Absence ofpolymorphism at the ZFY locus on the human Y-chromosome）。这三个科学家希望能从世界不同地方采样的38个人的Y染色体上找到多态性，但是最终没有找到。他们感到非常惊讶，反复进行核实，结果还是找不到。也就是说，这38个人理论上来自同一个父亲。一位诺贝尔奖得主和两个生物专家，花费很大力气，发现了一个花天酒地的风流男人，他在全世界眠花宿柳，他生下的38个儿子又恰好被搜集到这场科学实验里来了。 这绝对不可能。
此前，列文庭自己也曾根据地理上的“血统”粗略划分了人类： 高加索人（Caucasians ，欧亚大陆的西部） 黑色非洲人（Black Africans，撒哈拉以南的非洲） 蒙古人（Mongoloids，亚洲的东部） 南亚土著（South Asian Aborigines，印度的南部） 美洲人（Amerinds，美洲） 大洋洲和澳大利亚土著（Oceanians and Australian Aborigines）
从效果上看，简约理论为我们提供了一个哲学的时间机器，使我们得以返回早已不复存在的时代，四处探索和欣赏。这个机理，令人陶醉。其实，达尔文也是这个理论的一个懵懵懂懂的早期附和者。赫胥黎（Huxley）曾经批评达尔文本人对于自己的信仰也是稀里糊涂的，他说：“natura non facit saltum（拉丁语：大自然不会产生飞跃）。”
斯福扎和爱德华兹检测了世界各地的15个人群血型频率，用电脑分析了频率检测结果——非洲人之间的差异最大，欧洲人和亚洲人之间频率比较集中。这是人类进化历史中的一个激动人心的清晰证据。斯福扎说，这个分析“只是找到一些感觉”（made some kind of sense）。此外，这个分析结果反映出基因频率的相似性：随着时间的推移，频率呈现有规律的变化。
1980年代，人类在细胞里发现了一个小的结构：线粒体（mitochondrion）。2000年代，人们终于知道，线粒体是十几亿年以前第一批复杂细胞进化过程中留存下来的一类细菌。也就是说，我们的单细胞先祖们曾经吞噬了一种古代细菌，因为这种细菌在细胞内部可以生产能量，最后，这种被吞噬的古代细菌从一种“寄生虫”演变成一座亚细胞能量工厂（sub-cellular power plant）。非常幸运的是，与细菌的基因组类似，线粒体基因组（mitochondrial genome或者mtDNA）只有一套复制品，也就是说，它们不会重组。光明和希望再次出现。
我们再来看看Y染色体。Y染色体活跃基因丧失的情况与线粒体类似，虽然平均每对染色体有1 500个活跃基因，但是Y染色体上只剩下21个活跃基因，其中一些基因还是重复的，随机复制的。更有趣的是，这21个活跃基因只参与一项工程——制造男性。其中一个基因决定性别，称为Y染色体性别决定区，缩写SRY（Sex-determining Region of the Y）。其他的活跃基因负责决定其他男性特征（例如男人的外貌、长相、行为举止等）。Y染色体上的其他基因什么功能也没有，被称为“垃圾DNA”（junk DNA）。这些“垃圾DNA”也许是生物学的垃圾，却是群体遗传学家的金砂。
1991年，斯坦福大学的斯福扎实验室里来了一个应聘的青年人，彼得·安德希尔（Peter Underhill）。安德希尔早年在特拉华大学（University of Delaware）从事海洋生物学研究并获得博士学位，后来到加利福尼亚州，转向研究酶在分子生物学中的应用。1980年代正是生物技术大发展的初期，硅谷是重组DNA的震中。如何用各种各样的酶切割基因——分离基因——黏合基因……各种生物技术与电脑技术相互辉映，电子和生物两大技术领域将旧金山湾区变成了一个朝气蓬勃的全球新兴技术中心。
其他灭绝的类人猿或直立人都没有能力渡过海洋。例如，爪哇直立人距离澳大利亚的连成一片的大陆只有大约100千米，但是它们从未到达澳大利亚。事实上，在澳大利亚从来没有发现任何灵长目的痕迹。只有现代智人具备渡过海洋的能力。当时属于旧石器时代，沿着海岸高速公路零零散散发现的旧石器时代的石器证明，当时非洲人的确是沿着海岸线走到澳大利亚的。虽然印度沿岸的证据沉睡在深深的海底，斯里兰卡的一个山洞（Fa Hien cave）里却出土了大量旧石器时代的石器，证实了远古沿海高速迁移的真实存在。澳大利亚的土著，正是已经部分沉入海洋之下的澳大拉西亚（Australasia）的最早的一批殖民者，在他们的文化里，至今保留着祖传的因素。直到今天，澳大利亚的土著还保留着用歌声呼唤非洲先祖的仪式。
如果群体的增长是停滞的或者缩减的，这个分布会呈现“来回拉锯”的形态，原因是遗传漂变（genetic drift）或自然选择导致某些血统的绝嗣和丧失。如果这种分布形态是平滑的，表示我们现代智人的人口增长速率很高。哈本丁和他的团队采集和分析了世界25个群体的线粒体DNA数据，发现呈现指数增长的群体多达23个。根据这一研究成果，他出版了一本著作《一万年的爆炸》（The 10000 Year Explosion）。亨利·哈本丁认为，这场人口大迁移起始于5万年前，这个时间与人类走出非洲的时间基本吻合。
D NA的复制过程如下： 由一批不同类型的小小复制机器——聚合酶（polymerases），先把双螺旋的两个链条打开，然后辛辛苦苦地分别复制两个链条的互补部分，分别形成另外两个DNA分子的双螺旋，使得一个DNA双螺旋变成了两个DNA双螺旋。这里只有一个简单的不可侵犯的法则：A永远配对T；C永远配对G。（1984年，遗传学家阿莱克·杰弗里斯（Alec Jeffreys，1950-）发现：3-30个碱基对的短核苷酸序列，在基因组里可以重复20-100次。他把这种重复序列组称为“微卫星”，或随机重复变量（VNTRs，variable number of tandem repeats）。人类基因组中这些区段的数量和位置，每个人都不一样。在人类的旅程的探索中，这种“微卫星”技术大量运用，找出了各地的人类群体差别以及群体之内的个体之间的微小差异）
1787年，美国总统托马斯·杰弗逊（Thomas Jefferson）在他的《弗吉尼亚州笔记》（Notes on the State of Virginia）里写道： ……虽然亚洲与美洲是完全分离的，但是，中间只有一个狭窄的海峡……美洲印第安人与亚洲东部的居民之间相似的外貌使我们产生一个猜测，要么前者是后者的后裔，要么后者是前者的后裔……
事情并未到此结束。1986年：著名的《自然》（Nature）刊登了巴西考古学家尼埃德·古伊登（Niede Guidon，1933-）的一篇令人震惊的文章：《碳14显示人类3.2万年前在美洲》（Carbon-14 dates point to man in the Americas 32 000 years ago）。这篇文章介绍了在巴西东北部皮奥伊州（Piaui）的大批洞穴发现的史前遗迹和各种壁画。这些壁画总数超过三万处，除了远古时代的礼仪、舞蹈、狩猎以外，还有最后一次冰河期以前灭绝的动物雕齿兽（Glyptodon）、巨型犰狳（Armadillo）等动物。这里出土了大量陶器，还有绘制的世界最早的船只。这篇文章在美洲迁移史的研究中引起了轩然大波。这些历史遗迹的具体时间，至今仍然在争议中。
1999年，Fabricio Santos和Chris Tyler-Smith在牛津大学，Tanya Karafet和 Mike Hammer在亚利桑那大学（University of Arizona），分别独立地报告，M3的祖先是Y染色体上的一个未加定义的核苷酸改变，这个基因标记叫作92R7。他们发现从欧洲到印度的整个欧亚大陆都有92R7。这个92R7外加其他核苷酸变化，共同证实西伯利亚是美洲土著的来源。这一结论也佐证了线粒体DNA研究的结果。但是，研究者却难以确定92R7血统的年龄，因为这个基因标记太普遍了。
1786 年，在英属印度担任法官的语言学家威廉姆·琼斯爵士（Sir William Jones，1746-1794，发现梵语与拉丁语和希腊语非常相似），在大量研究分析的基础上提出印欧语系（Indo-European language family）的概念，即欧洲到印度的大片地区所有的语言有一个共同起源。这种假设，最终得到广泛承认。
波利尼西亚是太平洋中央几千个岛屿的统称，波利尼西亚人是这些岛屿原住民的统称，从夏威夷的土著到新西兰的毛利人（Maori people）都属于这一范畴。波利尼西亚（Polynesia）一词源自希腊语：poly意为众多，nesoi意为岛屿。1756年法国作家Charles de Brosses（1706-1777）第一次使用这个词，当时泛指太平洋上的所有岛屿。现在的波利尼西亚（Polynesia）的范围也没有严格界定：从美国洛杉矶出发，飞向新西兰首都奥克兰经过的海域就是波利尼西亚，距离约1.2万千米，飞行约14个小时。飞机下面一望无际的辽阔海域散布着数以千计的岛屿。
因为收集的人类DNA样本越多越好，于是，这个计划向尽可能多的人群开放，包括那些背景复杂、遗传形态极其难以识别的群体。任何愿意了解自己DNA的人都可以购买一套自我检测套件——基因图谱工程公众参与套件（Genographic Project Public Participation Kit），把受检者引人入胜的DNA故事加入工程设立在世界各地的11个收集检测中心，最后，所有数据通过互联网进入数据库汇总分析计算。
欧洲的王室家族的近亲婚姻，最典型的例子是哈布斯堡王朝（House of Habsburg）。这个王朝是欧洲历史上最有权势的王朝，起源于奥地利、匈牙利，他们通过婚姻关系扩大政治联盟。哈布斯堡王朝的鼎盛时代几乎联姻到了欧洲的每一个王室，使得16-18世纪的欧洲王室之间的血缘关系极其接近，遗传学效果使他们几乎成为一个“小村庄”。这个王朝不仅一代又一代地遗传财富和权势，也遗传基因标记和各种生理缺陷。按照遗传学意义，这个王朝最后变为同系交配或同族交配（endogamous），越来越差的王室后代正是哈布斯堡王朝最后土崩瓦解的重要原因之一。
M168又被称为“欧亚大陆亚当”（Eurasian Adam）或“走出非洲亚当”（Out of Africe Adam），这个男人的Y染色体突变发生的时间为6万——7.9万年前，地点在东非的埃塞俄比亚——苏丹一带。我们不知道M168是什么人，有些学者认为他“可能是一夫多妻制度下的一位酋长”。走出非洲的男性并非只有M168的后裔，但是M168是迄今为止唯一没有断绝的男性Y染色体血统。
基因图谱工程采用的单倍群编码。图片来源：美国国家地理协会
M 168重要的后裔也有3个人，即M130、YAP和M89。约6万年前，第一批走出非洲的人类是M168的后裔M130。一部分M130沿着海岸线一直走到澳大利亚，还有一些M130留在印度次大陆——东南亚地区，他们继续北上进入亚洲的东部，即青藏高原——中国内地——蒙古——韩国——日本等地，还有一些人进入了北美洲。
第一个DNA证据，正是来自这位大学里的图书管理员韦鲁曼迪。他的一个基因标记名叫RPS4Y，这个缩写名称的全称是Ribsomal Protein S4 on the Y chromosome（Y染色体上的核糖体蛋白质S4）。这个RPS4Y，现在简称M130：Y染色体上发现的第130个基因标记。在印度南部的人群中，M130的频率仅约为5%，包括卡拉尔群体（Kallar）。但是在澳大利亚土著中，M130却成为主导标记，超过50%。在东南亚约为20%。在印度的北部地区也发现了M130。
2010年2月5日，《新西兰先驱》（The New Zealand Herald）刊登了一篇题为《达尔文家族DNA的非洲起源》（Darwin family DNA shows African origin）的报道。1986年，达尔文的直系后裔克里斯·达尔文（Chris Darwin）移居澳大利亚，居住在悉尼西边的Blue Mountains。2010年，克里斯·达尔文接受人类基因图谱工程的DNA分析，证实达尔文的家族约四万年前走出非洲，路线为中东——中亚——欧洲，最后一次冰河时代辗转进入西班牙，然后北上迁移到英国。
Contents PROLOGUE PART I: Human Networks CHAPTER 1: What Is Information? CHAPTER 2: Stories: Unlimited Connections CHAPTER 3: Documents: The Bite of the Paper Tigers CHAPTER 4: Errors: The Fantasy of Infallibility CHAPTER 5: Decisions: A Brief History of Democracy and Totalitarianism PART II: The Inorganic Network CHAPTER 6: The New Members: How Computers Are Different from Printing Presses CHAPTER 7: Relentless: The Network Is Always On CHAPTER 8: Fallible: The Network Is Often Wrong PART III: Computer Politics CHAPTER 9: Democracies: Can We Still Hold a Conversation? CHAPTER 10: Totalitarianism: All Power to the Algorithms? CHAPTER 11: The Silicon Curtain: Global Empire or Global Split? EPILOGUE
Prologue
We have named our species Homo sapiens—the wise human. But it is debatable how well we have lived up to the name. Over the last 100,000 years, we Sapiens have certainly accumulated enormous power. Just listing all our discoveries, inventions, and conquests would fill volumes. But power isn’t wisdom, and after 100,000 years of discoveries, inventions, and conquests humanity has pushed itself into an existential crisis. We are on the verge of ecological collapse, caused by the misuse of our own power. We are also busy creating new technologies like artificial intelligence (AI) that have the potential to escape our control and enslave or annihilate us. Yet instead of our species uniting to deal with these existential challenges, international tensions are rising, global cooperation is becoming more difficult, countries are stockpiling doomsday weapons, and a new world war does not seem impossible. If we Sapiens are so wise, why are we so self-destructive? At a deeper level, although we have accumulated so much information about everything from DNA molecules to distant galaxies, it doesn’t seem that all this information has given us an answer to the big questions of life: Who are we? What should we aspire to? What is a good life, and how should we live it? Despite the stupendous amounts of information at our disposal, we are as susceptible as our ancient ancestors to fantasy and delusion. Nazism and Stalinism are but two recent examples of the mass insanity that occasionally engulfs even modern societies. Nobody disputes that humans today have a lot more information and power than in the Stone Age, but it is far from certain that we understand ourselves and our role in the universe much better.
Why are we so good at accumulating more information and power, but far less successful at acquiring wisdom? Throughout history many traditions have believed that some fatal flaw in our nature tempts us to pursue powers we don’t know how to handle. The Greek myth of Phaethon told of a boy who discovers that he is the son of Helios, the sun god. Wishing to prove his divine origin, Phaethon demands the privilege of driving the chariot of the sun. Helios warns Phaethon that no human can control the celestial horses that pull the solar chariot. But Phaethon insists, until the sun god relents. After rising proudly in the sky, Phaethon indeed loses control of the chariot. The sun veers off course, scorching all vegetation, killing numerous beings, and threatening to burn the earth itself. Zeus intervenes and strikes Phaethon with a thunderbolt. The conceited human drops from the sky like a falling star, himself on fire. The gods reassert control of the sky and save the world.
Two thousand years later, when the Industrial Revolution was making its first steps and machines began replacing humans in numerous tasks, Johann Wolfgang von Goethe published a similar cautionary tale titled “The Sorcerer’s Apprentice.” Goethe’s poem (later popularized as a Walt Disney animation starring Mickey Mouse) tells how an old sorcerer leaves a young apprentice in charge of his workshop and gives him some chores to tend to while he is gone, like fetching water from the river. The apprentice decides to make things easier for himself and, using one of the sorcerer’s spells, enchants a broom to fetch the water for him. But the apprentice doesn’t know how to stop the broom, which relentlessly fetches more and more water, threatening to flood the workshop. In panic, the apprentice cuts the enchanted broom in two with an ax, only to see each half become another broom. Now two enchanted brooms are inundating the workshop with water. When the old sorcerer returns, the apprentice pleads for help: “The spirits that I summoned, I now cannot rid myself of again.” The sorcerer immediately breaks the spell and stops the flood. The lesson to the apprentice—and to humanity—is clear: never summon powers you cannot control.
What do the cautionary fables of the apprentice and of Phaethon tell us in the twenty-first century? We humans have obviously refused to heed their warnings. We have already driven the earth’s climate out of balance and have summoned billions of enchanted brooms, drones, chatbots, and other algorithmic spirits that may escape our control and unleash a flood of unintended consequences.
What should we do, then? The fables offer no answers, other than to wait for some god or sorcerer to save us. This, of course, is an extremely dangerous message. It encourages people to abdicate responsibility and put their faith in gods and sorcerers instead. Even worse, it fails to appreciate that gods and sorcerers are themselves a human invention—just like chariots, brooms, and algorithms. The tendency to create powerful things with unintended consequences started not with the invention of the steam engine or AI but with the invention of religion. Prophets and theologians have repeatedly summoned powerful spirits that were supposed to bring love and joy but ended up flooding the world with blood.
The Phaethon myth and Goethe’s poem fail to provide useful advice because they misconstrue the way humans gain power. In both fables, a single human acquires enormous power, but is then corrupted by hubris and greed. The conclusion is that our flawed individual psychology makes us abuse power. What this crude analysis misses is that human power is never the outcome of individual initiative. Power always stems from cooperation between large numbers of humans.
Accordingly, it isn’t our individual psychology that causes us to abuse power. After all, alongside greed, hubris, and cruelty, humans are also capable of love, compassion, humility, and joy. True, among the worst members of our species, greed and cruelty reign supreme and lead bad actors to abuse power. But why would human societies choose to entrust power to their worst members? Most Germans in 1933, for example, were not psychopaths. So why did they vote for Hitler?
Our tendency to summon powers we cannot control stems not from individual psychology but from the unique way our species cooperates in large numbers. The main argument of this book is that humankind gains enormous power by building large networks of cooperation, but the way these networks are built predisposes them to use power unwisely. Our problem, then, is a network problem.
Even more specifically, it is an information problem. Information is the glue that holds networks together. But for tens of thousands of years, Sapiens built and maintained large networks by inventing and spreading fictions, fantasies, and mass delusions—about gods, about enchanted broomsticks, about AI, and about a great many other things. While each individual human is typically interested in knowing the truth about themselves and the world, large networks bind members and create order by relying on fictions and fantasies. That’s how we got, for example, to Nazism and Stalinism. These were exceptionally powerful networks, held together by exceptionally deluded ideas. As George Orwell famously put it, ignorance is strength.
The fact that the Nazi and Stalinist regimes were founded on cruel fantasies and shameless lies did not make them historically exceptional, nor did it preordain them to collapse. Nazism and Stalinism were two of the strongest networks humans ever created. In late 1941 and early 1942, the Axis powers came within reach of winning World War II. Stalin eventually emerged as the victor of that war,1 and in the 1950s and 1960s he and his heirs also had a reasonable chance of winning the Cold War. By the 1990s liberal democracies had gained the upper hand, but this now seems like a temporary victory. In the twenty-first century, some new totalitarian regime may well succeed where Hitler and Stalin failed, creating an all-powerful network that could prevent future generations from even attempting to expose its lies and fictions. We should not assume that delusional networks are doomed to failure. If we want to prevent their triumph, we will have to do the hard work ourselves.
THE NAIVE VIEW OF INFORMATION
It is difficult to appreciate the strength of delusional networks because of a broader misunderstanding about how big information networks—whether delusional or not—operate. This misunderstanding is encapsulated in something I call “the naive view of information.” While fables like the myth of Phaethon and “The Sorcerer’s Apprentice” present an overly pessimistic view of individual human psychology, the naive view of information disseminates an overly optimistic view of large-scale human networks.
The naive view argues that by gathering and processing much more information than individuals can, big networks achieve a better understanding of medicine, physics, economics, and numerous other fields, which makes the network not only powerful but also wise. For example, by gathering information on pathogens, pharmaceutical companies and health-care services can determine the true causes of many diseases, which enables them to develop more effective medicines and to make wiser decisions about their usage. This view posits that in sufficient quantities information leads to truth, and truth in turn leads to both power and wisdom. Ignorance, in contrast, seems to lead nowhere. While delusional or deceitful networks might occasionally arise in moments of historical crisis, in the long term they are bound to lose to more clear-sighted and honest rivals. A health-care service that ignores information about pathogens, or a pharmaceutical giant that deliberately spreads disinformation, will ultimately lose out to competitors that make wiser use of information. The naive view thus implies that delusional networks must be aberrations and that big networks can usually be trusted to handle power wisely.
The naive view of information
Of course, the naive view acknowledges that many things can go wrong on the path from information to truth. We might make honest mistakes in gathering and processing the information. Malicious actors motivated by greed or hate might hide important facts or try to deceive us. As a result, information sometimes leads to error rather than truth. For example, partial information, faulty analysis, or a disinformation campaign might lead even experts to misidentify the true cause of a particular disease.
However, the naive view assumes that the antidote to most problems we encounter in gathering and processing information is gathering and processing even more information. While we are never completely safe from error, in most cases more information means greater accuracy. A single doctor wishing to identify the cause of an epidemic by examining a single patient is less likely to succeed than thousands of doctors gathering data on millions of patients. And if the doctors themselves conspire to hide the truth, making medical information more freely available to the public and to investigative journalists will eventually reveal the scam. According to this view, the bigger the information network, the closer it must be to the truth.
Naturally, even if we analyze information accurately and discover important truths, this does not guarantee we will use the resulting capabilities wisely. Wisdom is commonly understood to mean “making right decisions,” but what “right” means depends on value judgments that differ between diverse people, cultures, or ideologies. Scientists who discover a new pathogen may develop a vaccine to protect people. But if the scientists—or their political overlords—believe in a racist ideology that advocates that some races are inferior and should be exterminated, the new medical knowledge might be used to develop a biological weapon that kills millions.
In this case too, the naive view of information holds that additional information offers at least a partial remedy. The naive view thinks that disagreements about values turn out on closer inspection to be the fault of either the lack of information or deliberate disinformation. According to this view, racists are ill-informed people who just don’t know the facts of biology and history. They think that “race” is a valid biological category, and they have been brainwashed by bogus conspiracy theories. The remedy to racism is therefore to provide people with more biological and historical facts. It may take time, but in a free market of information sooner or later truth will prevail.
The naive view is of course more nuanced and thoughtful than can be explained in a few paragraphs, but its core tenet is that information is an essentially good thing, and the more we have of it, the better. Given enough information and enough time, we are bound to discover the truth about things ranging from viral infections to racist biases, thereby developing not only our power but also the wisdom necessary to use that power well.
This naive view justifies the pursuit of ever more powerful information technologies and has been the semiofficial ideology of the computer age and the internet. In June 1989, a few months before the fall of the Berlin Wall and of the Iron Curtain, Ronald Reagan declared that “the Goliath of totalitarian control will rapidly be brought down by the David of the microchip” and that “the biggest of Big Brothers is increasingly helpless against communications technology.… Information is the oxygen of the modern age.… It seeps through the walls topped with barbed wire. It wafts across the electrified, booby-trapped borders. Breezes of electronic beams blow through the Iron Curtain as if it was lace.”2 In November 2009, Barack Obama spoke in the same spirit on a visit to Shanghai, telling his Chinese hosts, “I am a big believer in technology and I’m a big believer in openness when it comes to the flow of information. I think that the more freely information flows, the stronger the society becomes.”3
Entrepreneurs and corporations have often expressed similarly rosy views of information technology. Already in 1858 an editorial in The New Englander about the invention of the telegraph stated, “It is impossible that old prejudices and hostilities should longer exist, while such an instrument has been created for an exchange of thought between all the nations of the earth.”4 Nearly two centuries and two world wars later, Mark Zuckerberg said that Facebook’s goal “is to help people to share more in order to make the world more open and to help promote understanding between people.”5
In his 2024 book, The Singularity Is Nearer, the eminent futurologist and entrepreneur Ray Kurzweil surveys the history of information technology and concludes that “the reality is that nearly every aspect of life is getting progressively better as a result of exponentially improving technology.” Looking back at the grand sweep of human history, he cites examples like the invention of the printing press to argue that by its very nature information technology tends to spawn “a virtuous circle advancing nearly every aspect of human well-being, including literacy, education, wealth, sanitation, health, democratization and reduction in violence.”6
The naive view of information is perhaps most succinctly captured in Google’s mission statement “to organize the world’s information and make it universally accessible and useful.” Google’s answer to Goethe’s warnings is that while a single apprentice pilfering his master’s secret spell book is likely to cause disaster, when a lot of apprentices are given free access to all the world’s information, they will not only create useful enchanted brooms but also learn to handle them wisely.
GOOGLE VERSUS GOETHE
It must be stressed that there are numerous cases when having more information has indeed enabled humans to understand the world better and to make wiser use of their power. Consider, for example, the dramatic reduction in child mortality. Johann Wolfgang von Goethe was the eldest of seven siblings, but only he and his sister Cornelia got to celebrate their seventh birthday. Disease carried off their brother Hermann Jacob at age six, their sister Catharina Elisabeth at age four, their sister Johanna Maria at age two, their brother Georg Adolf at age eight months, and a fifth, unnamed brother was stillborn. Cornelia then died from disease aged twenty-six, leaving Johann Wolfgang as the sole survivor from their family.7
Johann Wolfgang von Goethe went on to have five children of his own, of whom all but the eldest son—August—died within two weeks of their birth. In all probability the cause was incompatibility between the blood groups of Goethe and his wife, Christiane, which after the first successful pregnancy led the mother to develop antibodies to the fetal blood. This condition, known as rhesus disease, is nowadays treated so effectively that the mortality rate is less than 2 percent, but in the 1790s it had an average mortality rate of 50 percent, and for Goethe’s four younger children it was a death sentence.8
Altogether in the Goethe family—a well-to-do German family in the late eighteenth century—the child survival rate was an abysmal 25 percent. Only three out of twelve children reached adulthood. This horrendous statistic was not exceptional. Around the time Goethe wrote “The Sorcerer’s Apprentice” in 1797, it is estimated that only about 50 percent of German children reached age fifteen,9 and the same was probably true in most other parts of the world.10 By 2020, 95.6 percent of children worldwide lived beyond their fifteenth birthday,11 and in Germany that figure was 99.5 percent.12 This momentous achievement would not have been possible without collecting, analyzing, and sharing massive amounts of medical data about things like blood groups. In this case, then, the naive view of information proved to be correct.
However, the naive view of information sees only part of the picture, and the history of the modern age was not just about reducing child mortality. In recent generations humanity has experienced the greatest increase ever in both the amount and the speed of our information production. Every smartphone contains more information than the ancient Library of Alexandria13 and enables its owner to instantaneously connect to billions of other people throughout the world. Yet with all this information circulating at breathtaking speeds, humanity is closer than ever to annihilating itself.
Despite—or perhaps because of—our hoard of data, we are continuing to spew greenhouse gases into the atmosphere, pollute rivers and oceans, cut down forests, destroy entire habitats, drive countless species to extinction, and jeopardize the ecological foundations of our own species. We are also producing ever more powerful weapons of mass destruction, from thermonuclear bombs to doomsday viruses. Our leaders don’t lack information about these dangers, yet instead of collaborating to find solutions, they are edging closer to a global war.
Would having even more information make things better—or worse? We will soon find out. Numerous corporations and governments are in a race to develop the most powerful information technology in history—AI. Some leading entrepreneurs, like the American investor Marc Andreessen, believe that AI will finally solve all of humanity’s problems. On June 6, 2023, Andreessen published an essay titled “Why AI Will Save the World,” peppered with bold statements like “I am here to bring the good news: AI will not destroy the world, and in fact may save it” and “AI can make everything we care about better.” He concluded, “The development and proliferation of AI—far from a risk that we should fear—is a moral obligation that we have to ourselves, to our children, and to our future.”14
Ray Kurzweil concurs, arguing in The Singularity Is Nearer that “AI is the pivotal technology that will allow us to meet the pressing challenges that confront us, including overcoming disease, poverty, environmental degradation, and all of our human frailties. We have a moral imperative to realize this promise of new technologies.” Kurzweil is keenly aware of the technology’s potential perils, and analyzes them at length, but believes they could be mitigated successfully.15
Others are more skeptical. Not only philosophers and social scientists but also many leading AI experts and entrepreneurs like Yoshua Bengio, Geoffrey Hinton, Sam Altman, Elon Musk, and Mustafa Suleyman have warned the public that AI could destroy our civilization.16 A 2024 article co-authored by Bengio, Hinton, and numerous other experts noted that “unchecked AI advancement could culminate in a large-scale loss of life and the biosphere, and the marginalization or even extinction of humanity.”17 In a 2023 survey of 2,778 AI researchers, more than a third gave at least a 10 percent chance to advanced AI leading to outcomes as bad as human extinction.18 In 2023 close to thirty governments—including those of China, the United States, and the U.K.—signed the Bletchley Declaration on AI, which acknowledged that “there is potential for serious, even catastrophic, harm, either deliberate or unintentional, stemming from the most significant capabilities of these AI models.”19 By using such apocalyptic terms, experts and governments have no wish to conjure a Hollywood image of killer robots running in the streets and shooting people. Such a scenario is unlikely, and it merely distracts people from the real dangers. Rather, experts warn about two other scenarios.
First, the power of AI could supercharge existing human conflicts, dividing humanity against itself. Just as in the twentieth century the Iron Curtain divided the rival powers in the Cold War, so in the twenty-first century the Silicon Curtain—made of silicon chips and computer codes rather than barbed wire—might come to divide rival powers in a new global conflict. Because the AI arms race will produce ever more destructive weapons, even a small spark might ignite a cataclysmic conflagration.
Second, the Silicon Curtain might come to divide not one group of humans from another but rather all humans from our new AI overlords. No matter where we live, we might find ourselves cocooned by a web of unfathomable algorithms that manage our lives, reshape our politics and culture, and even reengineer our bodies and minds—while we can no longer comprehend the forces that control us, let alone stop them. If a twenty-first-century totalitarian network succeeds in conquering the world, it may be run by nonhuman intelligence, rather than by a human dictator. People who single out China, Russia, or a post-democratic United States as their main source for totalitarian nightmares misunderstand the danger. In fact, Chinese, Russians, Americans, and all other humans are together threatened by the totalitarian potential of nonhuman intelligence.
Given the magnitude of the danger, AI should be of interest to all human beings. While not everyone can become an AI expert, we should all keep in mind that AI is the first technology in history that can make decisions and create new ideas by itself. All previous human inventions have empowered humans, because no matter how powerful the new tool was, the decisions about its usage always remained in our hands. Knives and bombs do not themselves decide whom to kill. They are dumb tools, lacking the intelligence necessary to process information and make independent decisions. In contrast, AI has the required intelligence to process information by itself, and therefore replace humans in decision making.
Its mastery of information also enables AI to independently generate new ideas, in fields ranging from music to medicine. Gramophones played our music, and microscopes revealed the secrets of our cells, but gramophones couldn’t compose new symphonies, and microscopes couldn’t synthesize new drugs. AI is already capable of producing art and making scientific discoveries by itself. In the next few decades, it will likely gain the ability even to create new life-forms, either by writing genetic code or by inventing an inorganic code animating inorganic entities.
Even at the present moment, in the embryonic stage of the AI revolution, computers already make decisions about us—whether to give us a mortgage, to hire us for a job, to send us to prison. This trend will only increase and accelerate, making it more difficult to understand our own lives. Can we trust computer algorithms to make wise decisions and create a better world? That’s a much bigger gamble than trusting an enchanted broom to fetch water. And it is more than just human lives we are gambling on. AI could alter the course not just of our species’ history but of the evolution of all life-forms.
WEAPONIZING INFORMATION
In 2016, I published Homo Deus, a book that highlighted some of the dangers posed to humanity by the new information technologies. That book argued that the real hero of history has always been information, rather than Homo sapiens, and that scientists increasingly understand not just history but also biology, politics, and economics in terms of information flows. Animals, states, and markets are all information networks, absorbing data from the environment, making decisions, and releasing data back. The book warned that while we hope better information technology will give us health, happiness, and power, it may actually take power away from us and destroy both our physical and our mental health. Homo Deus hypothesized that if humans aren’t careful, we might dissolve within the torrent of information like a clump of earth within a gushing river, and that in the grand scheme of things humanity will turn out to have been just a ripple within the cosmic dataflow.
In the years since Homo Deus was published, the pace of change has only accelerated, and power has indeed been shifting from humans to algorithms. Many of the scenarios that sounded like science fiction in 2016—such as algorithms that can create art, masquerade as human beings, make crucial life decisions about us, and know more about us than we know about ourselves—are everyday realities in 2024.
Many other things have changed since 2016. The ecological crisis has intensified, international tensions have escalated, and a populist wave has undermined the cohesion of even the most robust democracies. Populism has also mounted a radical challenge to the naive view of information. Populist leaders such as Donald Trump and Jair Bolsonaro, and populist movements and conspiracy theories such as QAnon and the anti-vaxxers, have argued that all traditional institutions that gain authority by claiming to gather information and discover truth are simply lying. Bureaucrats, judges, doctors, mainstream journalists, and academic experts are elite cabals that have no interest in the truth and are deliberately spreading disinformation to gain power and privileges for themselves at the expense of “the people.” The rise of politicians like Trump and movements like QAnon has a specific political context, unique to the conditions of the United States in the late 2010s. But populism as an antiestablishment worldview long predated Trump and is relevant to numerous other historical contexts now and in the future. In a nutshell, populism views information as a weapon.20
The populist view of information
In its more extreme versions, populism posits that there is no objective truth at all and that everyone has “their own truth,” which they wield to vanquish rivals. According to this worldview, power is the only reality. All social interactions are power struggles, because humans are interested only in power. The claim to be interested in something else—like truth or justice—is nothing more than a ploy to gain power. Whenever and wherever populism succeeds in disseminating the view of information as a weapon, language itself is undermined. Nouns like “facts” and adjectives like “accurate” and “truthful” become elusive. Such words are not taken as pointing to a common objective reality. Rather, any talk of “facts” or “truth” is bound to prompt at least some people to ask, “Whose facts and whose truth are you referring to?”
It should be stressed that this power-focused and deeply skeptical view of information isn’t a new phenomenon and it wasn’t invented by anti-vaxxers, flat-earthers, Bolsonaristas, or Trump supporters. Similar views have been propagated long before 2016, including by some of humanity’s brightest minds.21 In the late twentieth century, for example, intellectuals from the radical left like Michel Foucault and Edward Said claimed that scientific institutions like clinics and universities are not pursuing timeless and objective truths but are instead using power to determine what counts as truth, in the service of capitalist and colonialist elites. These radical critiques occasionally went as far as arguing that “scientific facts” are nothing more than a capitalist or colonialist “discourse” and that people in power can never be really interested in truth and can never be trusted to recognize and correct their own mistakes.22
This particular line of radical leftist thinking goes back to Karl Marx, who argued in the mid-nineteenth century that power is the only reality, that information is a weapon, and that elites who claim to be serving truth and justice are in fact pursuing narrow class privileges. In the words of the 1848 Communist Manifesto, “The history of all hitherto existing societies is the history of class struggles. Freeman and slave, patrician and plebeian, lord and serf, guildmaster and journeyman, in a word, oppressor and oppressed stood in constant opposition to one another, carried on an uninterrupted, now hidden, now open, fight.” This binary interpretation of history implies that every human interaction is a power struggle between oppressors and oppressed. Accordingly, whenever anyone says anything, the question to ask isn’t, “What is being said? Is it true?” but rather, “Who is saying this? Whose privileges does it serve?”
Of course, right-wing populists such as Trump and Bolsonaro are unlikely to have read Foucault or Marx, and indeed present themselves as fiercely anti-Marxist. They also greatly differ from Marxists in their suggested policies in fields like taxation and welfare. But their basic view of society and of information is surprisingly Marxist, seeing all human interactions as a power struggle between oppressors and oppressed. For example, in his inaugural address in 2017 Trump announced that “a small group in our nation’s capital has reaped the rewards of government while the people have borne the cost.”23 Such rhetoric is a staple of populism, which the political scientist Cas Mudde has described as an “ideology that considers society to be ultimately separated into two homogeneous and antagonistic groups, ‘the pure people’ versus ‘the corrupt elite.’ ”24 Just as Marxists claimed that the media functions as a mouthpiece for the capitalist class, and that scientific institutions like universities spread disinformation in order to perpetuate capitalist control, populists accuse these same institutions of working to advance the interests of the “corrupt elites” at the expense of “the people.”
Present-day populists also suffer from the same incoherency that plagued radical antiestablishment movements in previous generations. If power is the only reality, and if information is just a weapon, what does it imply about the populists themselves? Are they too interested only in power, and are they too lying to us to gain power?
Populists have sought to extricate themselves from this conundrum in two different ways. Some populist movements claim adherence to the ideals of modern science and to the traditions of skeptical empiricism. They tell people that indeed you should never trust any institutions or figures of authority—including self-proclaimed populist parties and politicians. Instead, you should “do your own research” and trust only what you can directly observe by yourself.25 This radical empiricist position implies that while large-scale institutions like political parties, courts, newspapers, and universities can never be trusted, individuals who make the effort can still find the truth by themselves.
This approach may sound scientific and may appeal to free-spirited individuals, but it leaves open the question of how human communities can cooperate to build health-care systems or pass environmental regulations, which demand large-scale institutional organization. Is a single individual capable of doing all the necessary research to decide whether the earth’s climate is heating up and what should be done about it? How would a single person go about collecting climate data from throughout the world, not to mention obtaining reliable records from past centuries? Trusting only “my own research” may sound scientific, but in practice it amounts to believing that there is no objective truth. As we shall see in chapter 4, science is a collaborative institutional effort rather than a personal quest.
An alternative populist solution is to abandon the modern scientific ideal of finding the truth via “research” and instead go back to relying on divine revelation or mysticism. Traditional religions like Christianity, Islam, and Hinduism have typically characterized humans as untrustworthy power-hungry creatures who can access the truth only thanks to the intervention of a divine intelligence. In the 2010s and early 2020s populist parties from Brazil to Turkey and from the United States to India have aligned themselves with such traditional religions. They have expressed radical doubt about modern institutions while declaring complete faith in ancient scriptures. The populists claim that the articles you read in The New York Times or in Science are just an elitist ploy to gain power, but what you read in the Bible, the Quran, or the Vedas is absolute truth.26
A variation on this theme calls on people to put their trust in charismatic leaders like Trump and Bolsonaro, who are depicted by their supporters either as the messengers of God27 or as possessing a mystical bond with “the people.” While ordinary politicians lie to the people in order to gain power for themselves, the charismatic leader is the infallible mouthpiece of the people who exposes all the lies.28 One of the recurrent paradoxes of populism is that it starts by warning us that all human elites are driven by a dangerous hunger for power, but often ends by entrusting all power to a single ambitious human.
We will explore populism at greater depth in chapter 5, but at this point it is important to note that populists are eroding trust in large-scale institutions and international cooperation just when humanity confronts the existential challenges of ecological collapse, global war, and out-of-control technology. Instead of trusting complex human institutions, populists give us the same advice as the Phaethon myth and “The Sorcerer’s Apprentice”: “Trust God or the great sorcerer to intervene and make everything right again.” If we take this advice, we’ll likely find ourselves in the short term under the thumb of the worst kind of power-hungry humans, and in the long term under the thumb of new AI overlords. Or we might find ourselves nowhere at all, as Earth becomes inhospitable for human life.
If we wish to avoid relinquishing power to a charismatic leader or an inscrutable AI, we must first gain a better understanding of what information is, how it helps to build human networks, and how it relates to truth and power. Populists are right to be suspicious of the naive view of information, but they are wrong to think that power is the only reality and that information is always a weapon. Information isn’t the raw material of truth, but it isn’t a mere weapon, either. There is enough space between these extremes for a more nuanced and hopeful view of human information networks and of our ability to handle power wisely. This book is dedicated to exploring that middle ground.
THE ROAD AHEAD
The first part of this book surveys the historical development of human information networks. It doesn’t attempt to present a comprehensive century-by-century account of information technologies like script, printing presses, and radio. Instead, by studying a few examples, it explores key dilemmas that people in all eras faced when trying to construct information networks, and it examines how different answers to these dilemmas shaped contrasting human societies. What we usually think of as ideological and political conflicts often turn out to be clashes between opposing types of information networks.
Part 1 begins by examining two principles that have been essential for large-scale human information networks: mythology and bureaucracy. Chapters 2 and 3 describe how large-scale information networks—from ancient kingdoms to present-day states—have relied on both mythmakers and bureaucrats. The stories of the Bible, for example, were essential for the Christian Church, but there would have been no Bible if church bureaucrats hadn’t curated, edited, and disseminated these stories. A difficult dilemma for every human network is that mythmakers and bureaucrats tend to pull in different directions. Institutions and societies are often defined by the balance they manage to find between the conflicting needs of their mythmakers and their bureaucrats. The Christian Church itself split into rival churches, like the Catholic and Protestant churches, which struck different balances between mythology and bureaucracy.
Chapter 4 then focuses on the problem of erroneous information and on the benefits and drawbacks of maintaining self-correcting mechanisms, such as independent courts or peer-reviewed journals. The chapter contrasts institutions that relied on weak self-correcting mechanisms, like the Catholic Church, with institutions that developed strong self-correcting mechanisms, like scientific disciplines. Weak self-correcting mechanisms sometimes result in historical calamities like the early modern European witch hunts, while strong self-correcting mechanisms sometimes destabilize the network from within. Judged in terms of longevity, spread, and power, the Catholic Church has been perhaps the most successful institution in human history, despite—or perhaps because of—the relative weakness of its self-correcting mechanisms.
After part 1 surveys the roles of mythology and bureaucracy, and the contrast between strong and weak self-correcting mechanisms, chapter 5 concludes the historical discussion by focusing on another contrast—between distributed and centralized information networks. Democratic systems allow information to flow freely along many independent channels, whereas totalitarian systems strive to concentrate information in one hub. Each choice has both advantages and shortcomings. Understanding political systems like the United States and the U.S.S.R. in terms of information flows can explain much about their differing trajectories.
This historical part of the book is crucial for understanding present-day developments and future scenarios. The rise of AI is arguably the biggest information revolution in history. But we cannot understand it unless we compare it with its predecessors. History isn’t the study of the past; it is the study of change. History teaches us what remains the same, what changes, and how things change. This is as relevant to information revolutions as to every other kind of historical transformation. Thus, understanding the process through which the allegedly infallible Bible was canonized provides valuable insight about present-day claims for AI infallibility. Similarly, studying the early modern witch hunts and Stalin’s collectivization offers stark warnings about what might go wrong as we give AIs greater control over twenty-first-century societies. A deep knowledge of history is also vital to understand what is new about AI, how it is fundamentally different from printing presses and radio sets, and in what specific ways future AI dictatorship could be very unlike anything we have seen before.
The book doesn’t argue that studying the past enables us to predict the future. As emphasized repeatedly in the following pages, history is not deterministic, and the future will be shaped by the choices we all make in coming years. The whole point of writing this book is that by making informed choices, we can prevent the worst outcomes. If we cannot change the future, why waste time discussing it?
Building upon the historical survey in part 1, the book’s second part—“The Inorganic Network”—examines the new information network we are creating today, focusing on the political implications of the rise of AI. Chapters 6–8 discuss recent examples from throughout the world—such as the role of social media algorithms in instigating ethnic violence in Myanmar in 2016–17—to explain in what ways AI is different from all previous information technologies. Examples are taken mostly from the 2010s rather than the 2020s, because we have gained a modicum of historical perspective on events of the 2010s.
Part 2 argues that we are creating an entirely new kind of information network, without pausing to reckon with its implications. It emphasizes the shift from organic to inorganic information networks. The Roman Empire, the Catholic Church, and the U.S.S.R. all relied on carbon-based brains to process information and make decisions. The silicon-based computers that dominate the new information network function in radically different ways. For better or worse, silicon chips are free from many of the limitations that organic biochemistry imposes on carbon neurons. Silicon chips can create spies that never sleep, financiers that never forget, and despots that never die. How will this change society, economics, and politics?
The third and final part of the book—“Computer Politics”—examines how different kinds of societies might deal with the threats and promises of the inorganic information network. Will carbon-based life-forms like us have a chance of understanding and controlling the new information network? As noted above, history isn’t deterministic, and for at least a few more years we Sapiens still have the power to shape our future.
Accordingly, chapter 9 explores how democracies might deal with the inorganic network. How, for example, can flesh-and-blood politicians make financial decisions if the financial system is increasingly controlled by AI and the very meaning of money comes to depend on inscrutable algorithms? How can democracies maintain a public conversation about anything—be it finance or gender—if we can no longer know whether we are talking with another human or with a chatbot masquerading as a human?
Chapter 10 explores the potential impact of the inorganic network on totalitarianism. While dictators would be happy to get rid of all public conversations, they have their own fears of AI. Autocracies are based on terrorizing and censoring their own agents. But how can a human dictator terrorize an AI, censor its unfathomable processes, or prevent it from seizing power to itself?
Finally, chapter 11 explores how the new information network could influence the balance of power between democratic and totalitarian societies on the global level. Will AI tilt the balance decisively in favor of one camp? Will the world split into hostile blocs whose rivalry makes all of us easy prey for an out-of-control AI? Or can we unite in defense of our common interests?
But before we explore the past, present, and possible futures of information networks, we need to start with a deceptively simple question. What exactly is information?
PART I Human Networks
CHAPTER 1 What Is Information?
It is always tricky to define fundamental concepts. Since they are the basis for everything that follows, they themselves seem to lack any basis of their own. Physicists have a hard time defining matter and energy, biologists have a hard time defining life, and philosophers have a hard time defining reality.
Information is increasingly seen by many philosophers and biologists, and even by some physicists, as the most basic building block of reality, more elementary than matter and energy.1 No wonder that there are many disputes about how to define information, and how it is related to the evolution of life or to basic ideas in physics such as entropy, the laws of thermodynamics, and the quantum uncertainty principle.2 This book will make no attempt to resolve—or even explain—these disputes, nor will it offer a universal definition of information applicable to physics, biology, and all other fields of knowledge. Since it is a work of history, which studies the past and future development of human societies, it will focus on the definition and role of information in history.
In everyday usage, information is associated with human-made symbols like spoken or written words. Consider, for example, the story of Cher Ami and the Lost Battalion. In October 1918, when the American Expeditionary Forces was fighting to liberate northern France from the Germans, a battalion of more than five hundred American soldiers was trapped behind enemy lines. American artillery, which was trying to provide them with cover fire, misidentified their location and dropped the barrage directly on them. The battalion’s commander, Major Charles Whittlesey, urgently needed to inform headquarters of his true location, but no runner could break through the German line. According to several accounts, as a last resort Whittlesey turned to Cher Ami, an army carrier pigeon. On a tiny piece of paper, Whittlesey wrote, “We are along the road paralell [sic] 276.4. Our artillery is dropping a barrage directly on us. For heaven’s sake stop it.” The paper was inserted into a canister on Cher Ami’s right leg, and the bird was released into the air. One of the battalion’s soldiers, Private John Nell, recalled years later, “We knew without a doubt this was our last chance. If that one lonely, scared pigeon failed to find its loft, our fate was sealed.”
Witnesses later described how Cher Ami flew into heavy German fire. A shell exploded directly below the bird, killing five men and severely injuring the pigeon. A splinter tore through Cher Ami’s chest, and his right leg was left hanging by a tendon. But he got through. The wounded pigeon flew the forty kilometers to division headquarters in about forty-five minutes, with the canister containing the crucial message attached to the remnant of his right leg. Though there is some controversy about the exact details, it is clear that the American artillery adjusted its barrage, and an American counterattack rescued the Lost Battalion. Cher Ami was tended by army medics, sent to the United States as a hero, and became the subject of numerous articles, short stories, children’s books, poems, and even movies. The pigeon had no idea what information he was conveying, but the symbols inked on the piece of paper he carried helped save hundreds of men from death and captivity.3
Information, however, does not have to consist of human-made symbols. According to the biblical myth of the Flood, Noah learned that the water had finally receded because the pigeon he sent out from the ark returned with an olive branch in her mouth. Then God set a rainbow in the clouds as a heavenly record of his promise never to flood the earth again. Pigeons, olive branches, and rainbows have since become iconic symbols of peace and tolerance. Objects that are even more remote than rainbows can also be information. For astronomers the shape and movement of galaxies constitute crucial information about the history of the universe. For navigators the North Star indicates which way is north. For astrologers the stars are a cosmic script, conveying information about the future of individual humans and entire societies.
Of course, defining something as “information” is a matter of perspective. An astronomer or astrologer might view the Libra constellation as “information,” but these distant stars are far more than just a notice board for human observers. There might be an alien civilization up there, totally oblivious to the information we glean from their home and to the stories we tell about it. Similarly, a piece of paper marked with ink splotches can be crucial information for an army unit, or dinner for a family of termites. Any object can be information—or not. This makes it difficult to define what information is.
The ambivalence of information has played an important role in the annals of military espionage, when spies needed to communicate information surreptitiously. During World War I, northern France was not the only major battleground. From 1915 to 1918 the British and Ottoman Empires fought for control of the Middle East. After repulsing an Ottoman attack on the Sinai Peninsula and the Suez Canal, the British in turn invaded the Ottoman Empire, but were held at bay until October 1917 by a fortified Ottoman line stretching from Beersheba to Gaza. British attempts to break through were repulsed at the First Battle of Gaza (March 26, 1917) and the Second Battle of Gaza (April 17–19, 1917). Meanwhile, pro-British Jews living in Palestine set up a spy network code-named NILI to inform the British about Ottoman troop movements. One method they developed to communicate with their British operators involved window shutters. Sarah Aaronsohn, a NILI commander, had a house overlooking the Mediterranean. She signaled British ships by closing or opening a particular shutter, according to a predetermined code. Numerous people, including Ottoman soldiers, could obviously see the shutter, but nobody other than NILI agents and their British operators understood it was vital military information.4 So, when is a shutter just a shutter, and when is it information?
The Ottomans eventually caught the NILI spy ring due in part to a strange mishap. In addition to shutters, NILI used carrier pigeons to convey coded messages. On September 3, 1917, one of the pigeons diverted off course and landed in—of all places—the house of an Ottoman officer. The officer found the coded message but couldn’t decipher it. Nevertheless, the pigeon itself was crucial information. Its existence indicated to the Ottomans that a spy ring was operating under their noses. As Marshall McLuhan might have put it, the pigeon was the message. NILI agents learned about the capture of the pigeon and immediately killed and buried all the remaining birds they had, because the mere possession of carrier pigeons was now incriminating information. But the massacre of the pigeons did not save NILI. Within a month the spy network was uncovered, several of its members were executed, and Sarah Aaronsohn committed suicide to avoid divulging NILI’s secrets under torture.5 When is a pigeon just a pigeon, and when is it information?
Clearly, then, information cannot be defined as specific types of material objects. Any object—a star, a shutter, a pigeon—can be information in the right context. So exactly what context defines such objects as “information”? The naive view of information argues that objects are defined as information in the context of truth seeking. Something is information if people use it to try to discover the truth. This view links the concept of information with the concept of truth and assumes that the main role of information is to represent reality. There is a reality “out there,” and information is something that represents that reality and that we can therefore use to learn about reality. For example, the information NILI provided the British was meant to represent the reality of Ottoman troop movements. If the Ottomans massed ten thousand soldiers in Gaza—the centerpiece of their defenses—a piece of paper with symbols representing “ten thousand” and “Gaza” was important information that could help the British win the battle. If, on the other hand, there were actually twenty thousand Ottoman troops in Gaza, that piece of paper did not represent reality accurately, and could lead the British to make a disastrous military mistake.
Put another way, the naive view argues that information is an attempt to represent reality, and when this attempt succeeds, we call it truth. While this book takes many issues with the naive view, it agrees that truth is an accurate representation of reality. But this book also holds that most information is not an attempt to represent reality and that what defines information is something entirely different. Most information in human society, and indeed in other biological and physical systems, does not represent anything.
I want to spend a little longer on this complex and crucial argument, because it constitutes the theoretical basis of the book.
WHAT IS TRUTH?
Throughout this book, “truth” is understood as something that accurately represents certain aspects of reality. Underlying the notion of truth is the premise that there exists one universal reality. Anything that has ever existed or will ever exist in the universe—from the North Star, to the NILI pigeon, to web pages on astrology—is part of this single reality. This is why the search for truth is a universal project. While different people, nations, or cultures may have competing beliefs and feelings, they cannot possess contradictory truths, because they all share a universal reality. Anyone who rejects universalism rejects truth.
Truth and reality are nevertheless different things, because no matter how truthful an account is, it can never represent reality in all its aspects. If a NILI agent wrote that there are ten thousand Ottoman soldiers in Gaza, and there were indeed ten thousand soldiers there, this accurately pointed to a certain aspect of reality, but it neglected many other aspects. The very act of counting entities—whether apples, oranges, or soldiers—necessarily focuses attention on the similarities between these entities while discounting differences.6 For example, saying only that there were ten thousand Ottoman soldiers in Gaza neglected to specify whether some were experienced veterans and others were green recruits. If there were a thousand recruits and nine thousand old hands, the military reality was quite different from if there were nine thousand rookies and a thousand battle-hardened veterans.
There were many other differences between the soldiers. Some were healthy; others were sick. Some Ottoman troops were ethnically Turkish, while others were Arabs, Kurds, or Jews. Some were brave, others cowardly. Indeed, each soldier was a unique human being, with different parents and friends and individual fears and hopes. World War I poets like Wilfred Owen famously attempted to represent these latter aspects of military reality, which mere statistics never conveyed accurately. Does this imply that writing “ten thousand soldiers” is always a misrepresentation of reality, and that to describe the military situation around Gaza in 1917, we must specify the unique history and personality of every soldier?
Another problem with any attempt to represent reality is that reality contains many viewpoints. For example, present-day Israelis, Palestinians, Turks, and Britons have different perspectives on the British invasion of the Ottoman Empire, the NILI underground, and the activities of Sarah Aaronsohn. That does not mean, of course, that there are several entirely separate realities, or that there are no historical facts. There is just one reality, but it is complex.
Reality includes an objective level with objective facts that don’t depend on people’s beliefs; for example, it is an objective fact that Sarah Aaronsohn died on October 9, 1917, from self-inflicted gunshot wounds. Saying that “Sarah Aaronsohn died in an airplane crash on May 15, 1919,” is an error.
Reality also includes a subjective level with subjective facts like the beliefs and feelings of various people, but in this case too facts can be separated from errors. For example, it is a fact that Israelis tend to regard Aaronsohn as a patriotic hero. Three weeks after her suicide, the information NILI supplied helped the British finally break the Ottoman line at the Battle of Beersheba (October 31, 1917) and the Third Battle of Gaza (November 1–2, 1917). On November 2, 1917, the British foreign secretary, Arthur Balfour, issued the Balfour Declaration, announcing that the British government “view with favor the establishment in Palestine of a national home for the Jewish people.” Israelis credit this in part to NILI and Sarah Aaronsohn, whom they admire for her sacrifice. It is another fact that Palestinians evaluate things very differently. Rather than admiring Aaronsohn, they regard her—if they’ve heard about her at all—as an imperialist agent. Even though we are dealing here with subjective views and feelings, we can still distinguish truth from falsehood. For views and feelings—just like stars and pigeons—are a part of the universal reality. Saying that “Sarah Aaronsohn is admired by everyone for her role in defeating the Ottoman Empire” is an error, not in line with reality.
Nationality is not the only thing that affects people’s viewpoint. Israeli men and Israeli women may see Aaronsohn differently, and so do left-wingers and right-wingers, or Orthodox and secular Jews. Since suicide is forbidden by Jewish religious law, Orthodox Jews have difficulty seeing Aaronsohn’s suicide as a heroic act (she was actually denied burial in the hallowed ground of a Jewish cemetery). Ultimately, each individual has a different perspective on the world, shaped by the intersection of different personalities and life histories. Does this imply that when we wish to describe reality, we must always list all the different viewpoints it contains and that a truthful biography of Sarah Aaronsohn, for example, must specify how every single Israeli and Palestinian has felt about her?
Taken to extremes, such a pursuit of accuracy may lead us to try to represent the world on a one-to-one scale, as in the famous Jorge Luis Borges story “On Exactitude in Science” (1946). In this story Borges tells of a fictitious ancient empire that became obsessed with producing ever more accurate maps of its territory, until eventually it produced a map with a one-to-one scale. The entire empire was covered with a map of the empire. So many resources were wasted on this ambitious representational project that the empire collapsed. Then the map too began to disintegrate, and Borges tells us that only “in the western Deserts, tattered fragments of the map are still to be found, sheltering an occasional beast or beggar.”7 A one-to-one map may look like the ultimate representation of reality, but tellingly it is no longer a representation at all; it is the reality.
The point is that even the most truthful accounts of reality can never represent it in full. There are always some aspects of reality that are neglected or distorted in every representation. Truth, then, isn’t a one-to-one representation of reality. Rather, truth is something that brings our attention to certain aspects of reality while inevitably ignoring other aspects. No account of reality is 100 percent accurate, but some accounts are nevertheless more truthful than others.
WHAT INFORMATION DOES
As noted above, the naive view sees information as an attempt to represent reality. It is aware that some information doesn’t represent reality well, but it dismisses this as unfortunate cases of “misinformation” or “disinformation.” Misinformation is an honest mistake, occurring when someone tries to represent reality but gets it wrong. Disinformation is a deliberate lie, occurring when someone consciously intends to distort our view of reality.
The naive view further believes that the solution to the problems caused by misinformation and disinformation is more information. This idea, sometimes called the counterspeech doctrine, is associated with the U.S. Supreme Court justice Louis D. Brandeis, who wrote in Whitney v. California (1927) that the remedy to false speech is more speech and that in the long term free discussion is bound to expose falsehoods and fallacies. If all information is an attempt to represent reality, then as the amount of information in the world grows, we can expect the flood of information to expose the occasional lies and errors and to ultimately provide us with a more truthful understanding of the world.
On this crucial point, this book strongly disagrees with the naive view. There certainly are instances of information that attempt to represent reality and succeed in doing so, but this is not the defining characteristic of information. A few pages ago I referred to stars as information and casually mentioned astrologers alongside astronomers. Adherents of the naive view of information probably squirmed in their chairs when they read it. According to the naive view, astronomers derive “real information” from the stars, while the information that astrologers imagine to read in constellations is either “misinformation” or “disinformation.” If only people were given more information about the universe, surely they would abandon astrology altogether. But the fact is that for thousands of years astrology has had a huge impact on history, and today millions of people still check their star signs before making the most important decisions of their lives, like what to study and whom to marry. As of 2021, the global astrology market was valued at $12.8 billion.8
No matter what we think about the accuracy of astrological information, we should acknowledge its important role in history. It has connected lovers, and even entire empires. Roman emperors routinely consulted astrologers before making decisions. Indeed, astrology was held in such high esteem that casting the horoscope of a reigning emperor was a capital offense. Presumably, anyone casting such a horoscope could foretell when and how the emperor would die.9 Rulers in some countries still take astrology very seriously. In 2005 the junta of Myanmar allegedly moved the country’s capital from Yangon to Naypyidaw based on astrological advice.10 A theory of information that cannot account for the historical significance of astrology is clearly inadequate.
What the example of astrology illustrates is that errors, lies, fantasies, and fictions are information, too. Contrary to what the naive view of information says, information has no essential link to truth, and its role in history isn’t to represent a preexisting reality. Rather, what information does is to create new realities by tying together disparate things—whether couples or empires. Its defining feature is connection rather than representation, and information is whatever connects different points into a network. Information doesn’t necessarily inform us about things. Rather, it puts things in formation. Horoscopes put lovers in astrological formations, propaganda broadcasts put voters in political formations, and marching songs put soldiers in military formations.
As a paradigmatic case, consider music. Most symphonies, melodies, and tunes don’t represent anything, which is why it makes no sense to ask whether they are true or false. Over the years people have created a lot of bad music, but not fake music. Without representing anything, music nevertheless does a remarkable job in connecting large numbers of people and synchronizing their emotions and movements. Music can make soldiers march in formation, clubbers sway together, church congregations clap in rhythm, and sports fans chant in unison.11
The role of information in connecting things is of course not unique to human history. A case can be made that this is the chief role of information in biology too.12 Consider DNA, the molecular information that makes organic life possible. Like music, DNA doesn’t represent reality. Though generations of zebras have been fleeing lions, you cannot find in the zebra DNA a string of nucleobases representing “lion” nor another string representing “flight.” Similarly, zebra DNA contains no representation of the sun, wind, rain, or any other external phenomena that zebras encounter during their lives. Nor does DNA represent internal phenomena like body organs or emotions. There is no combination of nucleobases that represents a heart, or fear.
Instead of trying to represent preexisting things, DNA helps to produce entirely new things. For instance, various strings of DNA nucleobases initiate cellular chemical processes that result in the production of adrenaline. Adrenaline too doesn’t represent reality in any way. Rather, adrenaline circulates through the body, initiating additional chemical processes that increase the heart rate and direct more blood to the muscles.13 DNA and adrenaline thereby help to connect cells in the heart, cells in the leg muscles, and trillions of other cells throughout the body to form a functioning network that can do remarkable things, like run away from a lion.
If DNA represented reality, we could have asked questions like “Does zebra DNA represent reality more accurately than lion DNA?” or “Is the DNA of one zebra telling the truth about the world, while another zebra is misled by her fake DNA?” These, of course, are nonsensical questions. We might evaluate DNA by the fitness of the organism it produces, but not by truthfulness. While it is common to talk about DNA “errors,” this refers only to mutations in the process of copying DNA—not to a failure to represent reality accurately. A genetic mutation that inhibits the production of adrenaline reduces the fitness of a particular zebra, ultimately causing the network of cells to disintegrate, as when the zebra is killed by a lion and its trillions of cells lose connection with one another and decompose. But this kind of network failure means disintegration, not disinformation. That’s true of countries, political parties, and news networks as much as of zebras.
Crucially, errors in the copying of DNA don’t always reduce fitness. Once in a blue moon, they increase fitness. Without such mutations, there would be no process of evolution. All life-forms exist thanks to genetic “errors.” The wonders of evolution are possible because DNA doesn’t represent any preexisting realities; it creates new realities.
Let us pause to digest the implications of this. Information is something that creates new realities by connecting different points into a network. This still includes the view of information as representation. Sometimes, a truthful representation of reality can connect humans, as when 600 million people sat glued to their television sets in July 1969, watching Neil Armstrong and Buzz Aldrin walking on the moon.14 The images on the screens accurately represented what was happening 384,000 kilometers away, and seeing them gave rise to feelings of awe, pride, and human brotherliness that helped connect people.
However, such fraternal feelings can be produced in other ways, too. The emphasis on connection leaves ample room for other types of information that do not represent reality well. Sometimes erroneous representations of reality might also serve as a social nexus, as when millions of followers of a conspiracy theory watch a YouTube video claiming that the moon landing never happened. These images convey an erroneous representation of reality, but they might nevertheless give rise to feelings of anger against the establishment or pride in one’s own wisdom that help create a cohesive new group.
Sometimes networks can be connected without any attempt to represent reality, neither accurate nor erroneous, as when genetic information connects trillions of cells or when a stirring musical piece connects thousands of humans.
As a final example, consider Mark Zuckerberg’s vision of the Metaverse. The Metaverse is a virtual universe made entirely of information. Unlike the one-to-one map built by Jorge Luis Borges’s imaginary empire, the Metaverse isn’t an attempt to represent our world, but rather an attempt to augment or even replace our world. It doesn’t offer us a digital replica of Buenos Aires or Salt Lake City; it invites people to build new virtual communities with novel landscapes and rules. As of 2024 the Metaverse seems like an overblown pipe dream, but within a couple of decades billions of people might migrate to live much of their lives in an augmented virtual reality, holding there most of their social and professional activities. People might come to build relationships, join movements, hold jobs, and experience emotional ups and downs in environments made of bits rather than atoms. Perhaps only in some remote deserts, tattered fragments of the old reality could still be found, sheltering an occasional beast or beggar.
INFORMATION IN HUMAN HISTORY
Viewing information as a social nexus helps us understand many aspects of human history that confound the naive view of information as representation. It explains the historical success not only of astrology but of much more important things, like the Bible. While some may dismiss astrology as a quaint sideshow in human history, nobody can deny the central role the Bible has played. If the main job of information had been to represent reality accurately, it would have been hard to explain why the Bible became one of the most influential texts in history.
The Bible makes many serious errors in its description of both human affairs and natural processes. The book of Genesis claims that all human groups—including, for example, the San people of the Kalahari Desert and the Aborigines of Australia—descend from a single family that lived in the Middle East about four thousand years ago.15 According to Genesis, after the Flood all Noah’s descendants lived together in Mesopotamia, but following the destruction of the Tower of Babel they spread to the four corners of the earth and became the ancestors of all living humans. In fact, the ancestors of the San people lived in Africa for hundreds of thousands of years without ever leaving the continent, and the ancestors of the Aborigines settled Australia more than fifty thousand years ago.16 Both genetic and archaeological evidence rule out the idea that the entire ancient populations of South Africa and Australia were annihilated about four thousand years ago by a flood and that these areas were subsequently repopulated by Middle Eastern immigrants.
An even graver distortion involves our understanding of infectious diseases. The Bible routinely depicts epidemics as divine punishment for human sins17 and claims they can be stopped or prevented by prayers and religious rituals.18 However, epidemics are of course caused by pathogens and can be stopped or prevented by following hygiene rules and using medicines and vaccines. This is today widely accepted even by religious leaders like the pope, who during the COVID-19 pandemic advised people to self-isolate, instead of congregating to pray together.19
Yet while the Bible has done a poor job in representing the reality of human origins, migrations, and epidemics, it has nevertheless been very effective in connecting billions of people and creating the Jewish and Christian religions. Like DNA initiating chemical processes that bind billions of cells into organic networks, the Bible initiated social processes that bonded billions of people into religious networks. And just as a network of cells can do things that single cells cannot, so a religious network can do things that individual humans cannot, like building temples, maintaining legal systems, celebrating holidays, and waging holy wars.
To conclude, information sometimes represents reality, and sometimes doesn’t. But it always connects. This is its fundamental characteristic. Therefore, when examining the role of information in history, although it sometimes makes sense to ask “How well does it represent reality? Is it true or false?” often the more crucial questions are “How well does it connect people? What new network does it create?”
It should be emphasized that rejecting the naive view of information as representation does not force us to reject the notion of truth, nor does it force us to embrace the populist view of information as a weapon. While information always connects, some types of information—from scientific books to political speeches—may strive to connect people by accurately representing certain aspects of reality. But this requires a special effort, which most information does not make. This is why the naive view is wrong to believe that creating more powerful information technology will necessarily result in a more truthful understanding of the world. If no additional steps are taken to tilt the balance in favor of truth, an increase in the amount and speed of information is likely to swamp the relatively rare and expensive truthful accounts by much more common and cheap types of information.
When we look at the history of information from the Stone Age to the Silicon Age, we therefore see a constant rise in connectivity, without a concomitant rise in truthfulness or wisdom. Contrary to what the naive view believes, Homo sapiens didn’t conquer the world because we are talented at turning information into an accurate map of reality. Rather, the secret of our success is that we are talented at using information to connect lots of individuals. Unfortunately, this ability often goes hand in hand with believing in lies, errors, and fantasies. This is why even technologically advanced societies like Nazi Germany and the Soviet Union have been prone to hold delusional ideas, without their delusions necessarily weakening them. Indeed, the mass delusions of Nazi and Stalinist ideologies about things like race and class actually helped them make tens of millions of people march together in lockstep.
In chapters 2–5 we’ll take a closer look at the history of information networks. We’ll discuss how, over tens of thousands of years, humans invented various information technologies that greatly improved connectivity and cooperation without necessarily resulting in a more truthful representation of the world. These information technologies—invented centuries and millennia ago—still shape our world even in the era of the internet and AI. The first information technology we’ll examine, which is also the first information technology developed by humans, is the story.
CHAPTER 2 Stories: Unlimited Connections
We Sapiens rule the world not because we are so wise but because we are the only animals that can cooperate flexibly in large numbers. I have explored this idea in my previous books Sapiens and Homo Deus, but a brief recap is inescapable.
The Sapiens’ ability to cooperate flexibly in large numbers has precursors among other animals. Some social mammals like chimpanzees display significant flexibility in the way they cooperate, while some social insects like ants cooperate in very large numbers. But neither chimps nor ants establish empires, religions, or trade networks. Sapiens are capable of doing such things because we are far more flexible than chimps and can simultaneously cooperate in even larger numbers than ants. In fact, there is no upper limit to the number of Sapiens who can cooperate with one another. The Catholic Church has about 1.4 billion members. China has a population of about 1.4 billion. The global trade network connects about 8 billion Sapiens.
This is surprising given that humans cannot form long-term intimate bonds with more than a few hundred individuals.1 It takes many years and common experiences to get to know someone’s unique character and history and to cultivate ties of mutual trust and affection. Consequently, if Sapiens networks were connected only by personal human-to-human bonds, our networks would have remained very small. This is the situation among our chimpanzee cousins, for example. Their typical community numbers 20–60 members, and on rare occasions the number might increase to 150–200.2 This appears to have been the situation also among ancient human species like Neanderthals and archaic Homo sapiens. Each of their bands numbered a few dozen individuals, and different bands rarely cooperated.3
About seventy thousand years ago, Homo sapiens bands began displaying an unprecedented capacity to cooperate with one another, as evidenced by the emergence of inter-band trade and artistic traditions and by the rapid spread of our species from our African homeland to the entire globe. What enabled different bands to cooperate is that evolutionary changes in brain structure and linguistic abilities apparently gave Sapiens the aptitude to tell and believe fictional stories and to be deeply moved by them. Instead of building a network from human-to-human chains alone—as the Neanderthals, for example, did—stories provided Homo sapiens with a new type of chain: human-to-story chains. In order to cooperate, Sapiens no longer had to know each other personally; they just had to know the same story. And the same story can be familiar to billions of individuals. A story can thereby serve like a central connector, with an unlimited number of outlets into which an unlimited number of people can plug. For example, the 1.4 billion members of the Catholic Church are connected by the Bible and other key Christian stories; the 1.4 billion citizens of China are connected by the stories of communist ideology and Chinese nationalism; and the 8 billion members of the global trade network are connected by stories about currencies, corporations, and brands.
Even charismatic leaders who have millions of followers are an example of this rule rather than an exception. It may seem that in the case of ancient Chinese emperors, medieval Catholic popes, or modern corporate titans it has been a single flesh-and-blood human—rather than a story—that has served as a nexus linking millions of followers. But, of course, in all these cases almost none of the followers has had a personal bond with the leader. Instead, what they have connected to has been a carefully crafted story about the leader, and it is in this story that they have put their faith.
Joseph Stalin, who stood at the nexus of one of the biggest personality cults in history, understood this well. When his troublesome son Vasily exploited his famous name to frighten and awe people, Stalin berated him. “But I’m a Stalin too,” protested Vasily. “No, you’re not,” replied Stalin. “You’re not Stalin and I’m not Stalin. Stalin is Soviet power. Stalin is what he is in the newspapers and the portraits, not you, no—not even me!”4
Present-day influencers and celebrities would concur. Some have hundreds of millions of online followers, with whom they communicate daily through social media. But there is very little authentic personal connection there. The social media accounts are usually run by a team of experts, and every image and word is professionally crafted and curated to manufacture what is nowadays called a brand.5
A “brand” is a specific type of story. To brand a product means to tell a story about that product, which may have little to do with the product’s actual qualities but which consumers nevertheless learn to associate with the product. For example, over the decades the Coca-Cola corporation has invested tens of billions of dollars in advertisements that tell and retell the story of the Coca-Cola drink.6 People have seen and heard the story so often that many have come to associate a certain concoction of flavored water with fun, happiness, and youth (as opposed to tooth decay, obesity, and plastic waste). That’s branding.7
As Stalin knew, it is possible to brand not only products but also individuals. A corrupt billionaire can be branded as the champion of the poor; a bungling imbecile can be branded as an infallible genius; and a guru who sexually abuses his followers can be branded as a chaste saint. People think they connect to the person, but in fact they connect to the story told about the person, and there is often a huge gulf between the two.
Even the story of Cher Ami, the heroic pigeon, was partly the product of a branding campaign aimed at enhancing the public image of the U.S. Army’s Pigeon Service. A 2021 revisionist study by the historian Frank Blazich found that though there is no doubt Cher Ami sustained severe injuries while transporting a message somewhere in Northern France, several key features of the story are doubtful or inaccurate. First, relying on contemporary military records, Blazich demonstrated that headquarters learned about the exact location of the Lost Battalion about twenty minutes prior to the pigeon’s arrival. It was not the pigeon that put a stop to the barrage of friendly fire decimating the Lost Battalion. Even more crucially, there is simply no proof that the pigeon carrying Major Whittlesey’s message was Cher Ami. It might well have been another bird, while Cher Ami might have sustained his wounds a couple of weeks later, during an altogether different battle.
According to Blazich, the doubts and inconsistencies in Cher Ami’s story were overshadowed by its propaganda value to the army and its appeal to the public. Over the years the story was retold so many times that facts became hopelessly enmeshed with fiction. Journalists, poets, and filmmakers added fanciful details to it, for example that the pigeon lost an eye as well as a leg and that it was awarded the Distinguished Service Cross. In the 1920s and 1930s Cher Ami became the most famous bird in the world. When he died, his carefully preserved corpse was placed on display at the Smithsonian Museum, where it became a pilgrimage site for American patriots and World War I veterans. As the story grew in the telling, it took over even the recollections of survivors of the Lost Battalion, who came to accept the popular narrative at face value. Blazich recounts the case of Sherman Eager, an officer in the Lost Battalion, who decades after the war brought his children to see Cher Ami at the Smithsonian and told them, “You all owe your lives to that pigeon.” Whatever the facts may be, the story of the self-sacrificing winged saviour proved irresistible.8
As a much more extreme example, consider Jesus. Two millennia of storytelling have encased Jesus within such a thick cocoon of stories that it is impossible to recover the historical person. Indeed, for millions of devout Christians merely raising the possibility that the real person was different from the story is blasphemy. As far as we can tell, the real Jesus was a typical Jewish preacher who built a small following by giving sermons and healing the sick. After his death, however, Jesus became the subject of one of the most remarkable branding campaigns in history. This little-known provincial guru, who during his short career gathered just a handful of disciples and who was executed as a common criminal, was rebranded after death as the incarnation of the cosmic god who created the universe.9 Though no contemporary portrait of Jesus has survived, and though the Bible never describes what he looked like, imaginary renderings of him have become some of the most recognizable icons in the world.
It should be stressed that the creation of the Jesus story was not a deliberate lie. People like Saint Paul, Tertullian, Saint Augustine, and Martin Luther didn’t set out to deceive anyone. They projected their deeply felt hopes and feelings on the figure of Jesus, in the same way that all of us routinely project our feelings on our parents, lovers, and leaders. While branding campaigns are occasionally a cynical exercise of disinformation, most of the really big stories of history have been the result of emotional projections and wishful thinking. True believers play a key role in the rise of every major religion and ideology, and the Jesus story changed history because it gained an immense number of true believers.
By gaining all those believers, the story of Jesus managed to have a much bigger impact on history than the person of Jesus. The person of Jesus walked from village to village on his two feet, talking with people, eating and drinking with them, placing his hands on their sick bodies. He made a difference to the lives of perhaps several thousand individuals, all living in one minor Roman province. In contrast, the story of Jesus flew around the whole world, first on the wings of gossip, anecdote, and rumor; then via parchment texts, paintings, and statues; and eventually as blockbuster movies and internet memes. Billions of people not only heard the Jesus story but came to believe in it too, which created one of the biggest and most influential networks in the world.
Stories like the one about Jesus can be seen as a way of stretching preexisting biological bonds. Family is the strongest bond known to humans. One way that stories build trust between strangers is by making these strangers reimagine each other as family. The Jesus story presented Jesus as the heavenly father of all humans, encouraged hundreds of millions of Christians to see each other as brothers and sisters, and created a shared pool of family memories. While most Christians were not physically present at the Last Supper, they have heard the story so many times, and they have seen so many images of the event, that they “remember” it more vividly than they remember most of the family dinners in which they actually participated.
Interestingly, Jesus’s last supper was the Jewish Passover meal, which according to the Gospel accounts Jesus shared with his disciples just before his crucifixion. In Jewish tradition, the whole purpose of the Passover meal is to create and reenact artificial memories. Every year Jewish families sit together on the eve of Passover to eat and reminisce about “their” exodus from Egypt. They are supposed not only to tell the story of how the descendants of Jacob escaped slavery in Egypt but to remember how they personally suffered at the hands of the Egyptians, how they personally saw the sea part, and how they personally received the Ten Commandments from Jehovah at Mount Sinai.
The Jewish tradition doesn’t mince words here. The text of the Passover ritual (the Haggadah) insists that “in every generation a person is obligated to regard himself as if he personally had come out of Egypt.” If anyone objects that this is a fiction, and that they didn’t personally come out of Egypt, Jewish sages have a ready answer. They claim that the souls of all Jews throughout history were created by Jehovah long before they were born and all these souls were present at Mount Sinai.10 As Salvador Litvak, a Jewish social media influencer, explained to his online followers in 2018, “You and I were there together.… When we fulfill the obligation to see ourselves as if we personally left Egypt, it’s not a metaphor. We don’t imagine the Exodus, we remember it.”11
So every year, in the most important celebration of the Jewish calendar, millions of Jews put on a show that they remember things that they didn’t witness and that in all probability never happened at all. As numerous modern studies show, repeatedly retelling a fake memory eventually causes the person to adopt it as a genuine recollection.12 When two Jews encounter each other for the first time, they can immediately feel that they both belong to the same family, that they were together slaves in Egypt, and that they were together at Mount Sinai. That’s a powerful bond that sustained the Jewish network over many centuries and continents.
INTERSUBJECTIVE ENTITIES
The Jewish Passover story builds a large network by taking existing biological kin bonds and stretching them way beyond their biological limits. But there is an even more revolutionary way for stories to build networks. Like DNA, stories can create entirely new entities. Indeed, stories can even create an entirely new level of reality. As far as we know, prior to the emergence of stories the universe contained just two levels of reality. Stories added a third.
The two levels of reality that preceded storytelling are objective reality and subjective reality. Objective reality consists of things like stones, mountains, and asteroids—things that exist whether we are aware of them or not. An asteroid hurtling toward planet Earth, for example, exists even if nobody knows it’s out there. Then there is subjective reality: things like pain, pleasure, and love that aren’t “out there” but rather “in here.” Subjective things exist in our awareness of them. An unfelt ache is an oxymoron.
But some stories are able to create a third level of reality: intersubjective reality. Whereas subjective things like pain exist in a single mind, intersubjective things like laws, gods, nations, corporations, and currencies exist in the nexus between large numbers of minds. More specifically, they exist in the stories people tell one another. The information humans exchange about intersubjective things doesn’t represent anything that had already existed prior to the exchange of information; rather, the exchange of information creates these things.
When I tell you that I am in pain, telling you about it doesn’t create the pain. And if I stop talking about the pain, it doesn’t make the pain go away. Similarly, when I tell you that I saw an asteroid, this doesn’t create the asteroid. The asteroid exists whether people talk about it or not. But when lots of people tell one another stories about laws, gods, or currencies, this is what creates these laws, gods, or currencies. If people stop talking about them, they disappear. Intersubjective things exist in the exchange of information.
Let’s take a closer look. The calorific value of pizza doesn’t depend on our beliefs. A typical pizza contains between fifteen hundred and twenty-five hundred calories.13 In contrast, the financial value of money—and pizzas—depends entirely on our beliefs. How many pizzas can you purchase for a dollar, or for a bitcoin? In 2010, Laszlo Hanyecz bought two pizzas for 10,000 bitcoins. It was the first known commercial transaction involving bitcoin—and with hindsight, also the most expensive pizza ever. By November 2021, a single bitcoin was valued at more than $69,000, so the bitcoins Hanyecz paid for his two pizzas were worth $690 million, enough to purchase millions of pizzas.14 While the calorific value of pizza is an objective reality that remained the same between 2010 and 2021, the financial value of bitcoin is an intersubjective reality that changed dramatically during the same period, depending on the stories people told and believed about bitcoin.
Another example. Suppose I ask, “Does the Loch Ness Monster exist?” This is a question about the objective level of reality. Some people believe that dinosaur-like animals really do inhabit Loch Ness. Others dismiss the idea as a fantasy or a hoax. Over the years, many attempts have been made to resolve the disagreement once and for all, using scientific methods such as sonar scans and DNA surveys. If huge animals live in the lake, they should appear on sonar, and they should leave DNA traces. Based on the available evidence, the scientific consensus is that the Loch Ness Monster does not exist. (A DNA survey conducted in 2019 found genetic material from three thousand species, but no monster. At most, Loch Ness may contain some five-kilo eels.15) Many people may nevertheless continue to believe that the Loch Ness Monster exists, but believing it doesn’t change objective reality.
In contrast to animals, whose existence can be verified or disproved through objective tests, states are intersubjective entities. We normally don’t notice it, because everybody takes the existence of the United States, China, Russia, or Brazil for granted. But there are cases when people disagree about the existence of certain states, and then their intersubjective status emerges. The Israeli-Palestinian conflict, for example, revolves around this matter, because some people and governments refuse to acknowledge the existence of Israel and others refuse to acknowledge the existence of Palestine. As of 2024, the governments of Brazil and China, for example, say that both Israel and Palestine exist; the governments of the United States and Cameroon recognize only Israel’s existence; whereas the governments of Algeria and Iran recognize only Palestine. Other cases range from Kosovo, which as of 2024 is recognized as a state by around half of the 193 UN members,16 to Abkhazia, which almost all governments see as a sovereign territory of Georgia, but which is recognized as a state by Russia, Venezuela, Nicaragua, Nauru, and Syria.17
Indeed, almost all states pass at least temporarily through a phase during which their existence is contested, when struggling for independence. Did the United States come into existence on July 4, 1776, or only when other states like France and finally the U.K. recognized it? Between the declaration of U.S. independence on July 4, 1776, and the signing of the Treaty of Paris on September 3, 1783, some people like George Washington believed the United States existed, while other people like King George III vehemently rejected this idea.
Disagreements about the existence of states cannot be resolved by an objective test, such as a DNA survey or a sonar scan. Unlike animals, states are not an objective reality. When we ask whether a particular state exists, we are raising a question about intersubjective reality. If enough people agree that a particular state exists, then it does. It can then do things like sign legally binding treaties with other governments as well as NGOs and private corporations.
Of all genres of stories, those that create intersubjective realities have been the most crucial for the development of large-scale human networks. Implanting fake family memories is certainly helpful, but no religions or empires managed to survive for long without a strong belief in the existence of a god, a nation, a law code, or a currency. For the formation of the Christian Church, for example, it was important that people recollect what Jesus said at the Last Supper, but the crucial step was making people believe that Jesus was a god rather than just an inspiring rabbi. For the formation of the Jewish religion, it was helpful that Jews “remembered” how they together escaped slavery in Egypt, but the really decisive step was making all Jews adhere to the same religious law code, the Halakha.
Intersubjective things like laws, gods, and currencies are extremely powerful within a particular information network and utterly meaningless outside it. Suppose a billionaire crashes his private jet on a deserted island and finds himself alone with a suitcase full of banknotes and bonds. When he was in São Paulo or Mumbai, he could use these papers to make people feed him, clothe him, protect him, and build him a private jet. But once he is cut off from other members of our information network, his banknotes and bonds immediately become worthless. He cannot use them to get the island’s monkeys to provide him with food or to build him a raft.
THE POWER OF STORIES
Whether through implanting fake memories, forming fictional relationships, or creating intersubjective realities, stories produced large-scale human networks. These networks in turn completely changed the balance of power in the world. Story-based networks made Homo sapiens the most powerful of all animals, giving it a crucial edge not only over lions and mammoths but also over other ancient human species like Neanderthals.
Neanderthals lived in small isolated bands, and to the best of our knowledge different bands cooperated with one another only rarely and weakly, if at all.18 Stone Age Sapiens too lived in small bands of a few dozen individuals. But following the emergence of storytelling, Sapiens bands no longer lived in isolation. Bands were connected by stories about things like revered ancestors, totem animals, and guardian spirits. Bands that shared stories and intersubjective realities constituted a tribe. Each tribe was a network connecting hundreds or even thousands of individuals.19
Belonging to a large tribe had an obvious advantage in times of conflict. Five hundred Sapiens could easily defeat fifty Neanderthals.20 But tribal networks had many additional advantages. If we live in an isolated band of fifty people and a severe drought hits our home territory, many of us might starve to death. If we try to migrate elsewhere, we are likely to encounter hostile groups, and we might also find it difficult to forage for food, water, and flint (to make tools) in unfamiliar territory. However, if our band is part of a tribal network, in times of need at least some of us could go live with our distant friends. If our shared tribal identity is strong enough, they would welcome us and teach us about the local dangers and opportunities. A decade or two later, we might reciprocate. The tribal network, then, acted like an insurance policy. It minimized risk by spreading it across a lot more people.21
Even in quiet times Sapiens could benefit enormously from exchanging information not just with a few dozen members of a small band but with an entire tribal network. If one of the tribe’s bands discovered a better way to make spear points, learned how to heal wounds with some rare medicinal herb, or invented a needle to sew clothes, that knowledge could be quickly passed to the other bands. Even though individually Sapiens might not have been more intelligent than Neanderthals, five hundred Sapiens together were far more intelligent than fifty Neanderthals.22
All this was made possible by stories. The power of stories is often missed or denied by materialist interpretations of history. In particular, Marxists tend to view stories as merely a smoke screen for underlying power relations and material interests. According to Marxist theories, people are always motivated by objective material interests and use stories only to camouflage these interests and confound their rivals. For example, in this reading the Crusades, World War I, and the Iraq War were all fought for the economic interests of powerful elites rather than for religious, nationalist, or liberal ideals. Understanding these wars means setting aside all the mythological fig leaves—about God, patriotism, or democracy—and observing power relations in their nakedness.
This Marxist view, however, is not only cynical but wrong. While materialist interests certainly played a role in the Crusades, World War I, the Iraq War, and most other human conflicts, that does not mean that religious, national, and liberal ideals played no role at all. Moreover, materialist interests by themselves cannot explain the identities of the rival camps. Why is it that in the twelfth century landowners and merchants from France, Germany, and Italy united to conquer territories and trade routes in the Levant—instead of landowners and merchants from France and North Africa uniting to conquer Italy? And why is it that in 2003, the United States and Britain sought to conquer the oil fields of Iraq, rather than the gas fields of Norway? Can this really be explained by purely materialist considerations, without any recourse to people’s religious and ideological beliefs?
In fact, all relations between large-scale human groups are shaped by stories, because the identities of these groups are themselves defined by stories. There are no objective definitions for who is British, American, Norwegian, or Iraqi; all these identities are shaped by national and religious myths that are constantly challenged and revised. Marxists may claim that large-scale groups have objective identities and interests, independent of stories. If that is so, how can we explain that only humans have large-scale groups like tribes, nations, and religions, whereas chimpanzees lack them? After all, chimpanzees share with humans all our objective material interests; they too need to drink, eat, and protect themselves from diseases. They too want sex and social power. But chimpanzees cannot maintain large-scale groups, because they are unable to create the stories that connect such groups and define their identities and interests. Contrary to Marxist thinking, large-scale identities and interests in history are always intersubjective; they are never objective.
This is good news. If history had been shaped solely by material interests and power struggles, there would be no point talking to people who disagree with us. Any conflict would ultimately be the result of objective power relations, which cannot be changed merely by talking. In particular, if privileged people can see and believe only those things that enshrine their privileges, how can anything except violence persuade them to renounce those privileges and alter their beliefs? Luckily, since history is shaped by intersubjective stories, sometimes we can avert conflict and make peace by talking with people, changing the stories in which they and we believe, or coming up with a new story that everyone can accept.
Take, for example, the rise of Nazism. There certainly were material interests that drove millions of Germans to support Hitler. The Nazis would probably never have come to power if it wasn’t for the economic crisis of the early 1930s. However, it is wrong to think that the Third Reich was the inevitable outcome of underlying power relations and material interests. Hitler won the 1933 elections because during the economic crisis millions of Germans came to believe the Nazi story rather than one of the alternative stories on offer. This wasn’t the inevitable result of Germans pursuing their material interests and protecting their privileges; it was a tragic mistake. We can confidently say that it was a mistake, and that Germans could have chosen better stories, because we know what happened next. Twelve years of Nazi rule didn’t foster the Germans’ material interests. Nazism led to the destruction of Germany and the deaths of millions. Later, when Germans adopted liberal democracy, this did lead to a lasting improvement in their lives. Couldn’t the Germans have skipped the failed Nazi experiment and put their faith in liberal democracy already in the early 1930s? The position of this book is that they could have. History is often shaped not by deterministic power relations, but rather by tragic mistakes that result from believing in mesmerizing but harmful stories.
THE NOBLE LIE
The centrality of stories reveals something fundamental about the power of our species, and it explains why power doesn’t always go hand in hand with wisdom. The naive view of information says that information leads to truth, and knowing the truth helps people to gain both power and wisdom. This sounds reassuring. It implies that people who ignore the truth are unlikely to have much power, whereas people who respect the truth can gain much power, but that power would be tempered by wisdom. For example, people who ignore the truth about human biology might believe racist myths but will not be able to produce powerful medicines and bioweapons, whereas people who understand biology will have that kind of power but will not use it in the service of racist ideologies. If this had indeed been the case, we could sleep calmly, trusting our presidents, high priests, and CEOs to be wise and honest. A politician, a movement, or a country might conceivably get ahead here and there with the help of lies and deceptions, but in the long term that would be a self-defeating strategy.
Unfortunately, this is not the world in which we live. In history, power stems only partially from knowing the truth. It also stems from the ability to maintain social order among a large number of people. Suppose you want to make an atom bomb. To succeed, you obviously need some accurate knowledge of physics. But you also need lots of people to mine uranium ore, build nuclear reactors, and provide food for the construction workers, miners, and physicists. The Manhattan Project directly employed about 130,000 people, with millions more working to sustain them.23 Robert Oppenheimer could devote himself to his equations because he relied on thousands of miners to extract uranium at the Eldorado mine in northern Canada and the Shinkolobwe mine in the Belgian Congo24—not to mention the farmers who grew potatoes for his lunch. If you want to make an atom bomb, you must find a way to make millions of people cooperate.
It is the same with all ambitious projects that humans undertake. A Stone Age band going to hunt a mammoth obviously needed to know some true facts about mammoths. If they believed they could kill a mammoth by casting spells, their hunting expedition would have failed. But just knowing facts about mammoths wasn’t enough, either. The hunters also needed to make sure all of them agreed on the same plan and bravely did their bit even in the face of mortal danger. If they believed that by pronouncing a spell they could guarantee a good afterlife for dead hunters, their hunting expeditions had a much higher chance of success. Even if objectively the spell was powerless and did not benefit dead hunters in any way, by fortifying the courage and solidarity of living hunters, it nevertheless made a crucial contribution to the hunt’s success.25
While power depends on both truth and order, in most cases it is the people who know how to maintain order who call the shots, giving instructions to the people who merely know the truth about things like mammoths or nuclear physics. Robert Oppenheimer obeyed Franklin Delano Roosevelt rather than the other way around. Similarly, Werner Heisenberg obeyed Adolf Hitler, Igor Kurchatov deferred to Joseph Stalin, and in contemporary Iran experts in nuclear physics follow the orders of experts in Shiite theology.
What the people at the top know, which nuclear physicists don’t always realize, is that telling the truth about the universe is hardly the most efficient way to produce order among large numbers of humans. It is true that E = mc², and it explains a lot of what happens in the universe, but knowing that E = mc² usually doesn’t resolve political disagreements or inspire people to make sacrifices for a common cause. Instead, what holds human networks together tends to be fictional stories, especially stories about intersubjective things like gods, money, and nations. When it comes to uniting people, fiction enjoys two inherent advantages over the truth. First, fiction can be made as simple as we like, whereas the truth tends to be complicated, because the reality it is supposed to represent is complicated. Take, for example, the truth about nations. It is difficult to grasp that the nation to which one belongs is an intersubjective entity that exists only in our collective imagination. You rarely hear politicians say such things in their political speeches. It is far easier to believe that our nation is God’s chosen people, entrusted by the Creator with some special mission. This simple story has been repeatedly told by countless politicians from Israel to Iran and from the United States to Russia.
Second, the truth is often painful and disturbing, and if we try to make it more comforting and flattering, it will no longer be the truth. In contrast, fiction is highly malleable. The history of every nation contains some dark episodes that citizens don’t like to acknowledge and remember. An Israeli politician who in her election speeches details the miseries inflicted on Palestinian civilians by the Israeli occupation is unlikely to get many votes. In contrast, a politician who builds a national myth by ignoring uncomfortable facts, focusing on glorious moments in the Jewish past, and embellishing reality wherever necessary may well sweep to power. That’s the case not just in Israel but in all countries. How many Italians or Indians want to hear the unblemished truth about their nations? An uncompromising adherence to the truth is essential for scientific progress, and it is also an admirable spiritual practice, but it is not a winning political strategy.
Already in his Republic, Plato imagined that the constitution of his utopian state would be based on “the noble lie”—a fictional story about the origin of the social order, one that secures the citizens’ loyalty and prevents them from questioning the constitution. Citizens should be told, Plato wrote, that they were all born out of the earth, that the land is their mother, and that they therefore owe filial loyalty to the motherland. They should further be told that when they were conceived, the gods intermingled different metals—gold, silver, bronze, and iron—into them, which justifies a natural hierarchy between golden rulers and bronze servants. While Plato’s utopia was never realized in practice, numerous polities through the ages told their inhabitants variations of this noble lie.
Plato’s noble lie notwithstanding, we should not conclude that all politicians are liars or that all national histories are deceptions. The choice isn’t simply between telling the truth and lying. There is a third option. Telling a fictional story is lying only when you pretend that the story is a true representation of reality. Telling a fictional story isn’t lying when you avoid such pretense and acknowledge that you are trying to create a new intersubjective reality rather than represent a preexisting objective reality.
For example, on September 17, 1787, the Constitutional Convention signed the U.S. Constitution, which came into force in 1789. The Constitution didn’t reveal any preexisting truth about the world, but crucially it wasn’t a lie, either. Rejecting Plato’s recommendation, the authors of the text didn’t deceive anyone about the text’s origins. They didn’t pretend that the text came down from heaven or that it had been inspired by some god. Rather, they acknowledged that it was an extremely creative legal fiction generated by fallible human beings.
“We the People of the United States,” says the Constitution about its own origins, “in Order to form a more perfect Union … do ordain and establish this Constitution.” Despite the acknowledgment that it is a human-made legal fiction, the U.S. Constitution indeed managed to form a powerful union. It maintained for more than two centuries a surprising degree of order among many millions of people who belonged to a wide range of religious, ethnic, and cultural groups. The U.S. Constitution has thus functioned like a tune that without claiming to represent anything has nevertheless made numerous people act together in order.
It is crucial to note that “order” should not be confused with fairness or justice. The order created and maintained by the U.S. Constitution condoned slavery, the subordination of women, the expropriation of indigenous people, and extreme economic inequality. The genius of the U.S. Constitution is that by acknowledging that it is a legal fiction created by human beings, it was able to provide mechanisms to reach agreement on amending itself and remedying its own injustices (as chapter 5 explores in greater depth). The Constitution’s Article V details how people can propose and ratify such amendments, which “shall be valid to all Intents and Purposes, as Part of this Constitution.” Less than a century after the Constitution was written, the Thirteenth Amendment abolished slavery.
In this, the U.S. Constitution was fundamentally different from stories that denied their fictive nature and claimed divine origin, such as the Ten Commandments. Like the U.S. Constitution, the Ten Commandments endorsed slavery. The Tenth Commandment says, “You shall not covet your neighbor’s house. You shall not covet your neighbor’s wife, or his male slave or female slave” (Exodus 20:17). This implies that God is perfectly okay with people holding slaves, and objects only to the coveting of slaves belonging to someone else. But unlike the U.S. Constitution, the Ten Commandments failed to provide any amendment mechanism. There is no Eleventh Commandment that says, “You can amend commandments by a two-thirds majority vote.”
This crucial difference between the two texts is clear from their opening gambits. The U.S. Constitution opens with “We the People.” By acknowledging its human origin, it invests humans with the power to amend it. The Ten Commandments open with “I am the Lord your God.” By claiming divine origin, it precludes humans from changing it. As a result, the biblical text still endorses slavery even today.
All human political systems are based on fictions, but some admit it, and some do not. Being truthful about the origins of our social order makes it easier to make changes in it. If humans like us invented it, we can amend it. But such truthfulness comes at a price. Acknowledging the human origins of the social order makes it harder to persuade everyone to agree on it. If humans like us invented it, why should we accept it? As we shall see in chapter 5, until the late eighteenth century the lack of mass communication technology made it extremely difficult to conduct open debates between millions of people about the rules of the social order. To maintain order, Russian tsars, Muslim caliphs, and Chinese sons of heaven therefore claimed that the fundamental rules of society came down from heaven and were not open to human amendment. In the early twenty-first century, many political systems still claim superhuman authority and oppose open debates that may result in unwelcome changes.
THE PERENNIAL DILEMMA
After we understand the key role of fiction in history, it is finally possible to present a more complete model of information networks, which goes beyond both the naive view of information and the populist critique of that view. Contrary to the naive view, information isn’t the raw material of truth, and human information networks aren’t geared only to discover the truth. But contrary to the populist view, information isn’t just a weapon, either. Rather, to survive and flourish, every human information network needs to do two things simultaneously: discover truth and create order. Accordingly, as history unfolded, human information networks have been developing two distinct sets of skills. On the one hand, as the naive view expects, the networks have learned how to process information to gain a more accurate understanding of things like medicine, mammoths, and nuclear physics. At the same time, the networks have also learned how to use information to maintain stronger social order among larger populations, by using not just truthful accounts but also fictions, fantasies, propaganda, and—occasionally—downright lies.
The naive view of informationA more complete historical view of information
Having a lot of information doesn’t in and of itself guarantee either truth or order. It is a difficult process to use information to discover the truth and simultaneously use it to maintain order. What makes things worse is that these two processes are often contradictory, because it is frequently easier to maintain order through fictions. Sometimes—as in the case of the U.S. Constitution—fictional stories may acknowledge their fictionality, but more often they disavow it. Religions, for example, always claim to be an objective and eternal truth rather than a fictional story invented by humans. In such cases, the search for truth threatens the foundations of the social order. Many societies require their populations not to know their true origins: ignorance is strength. What happens, then, when people get uncomfortably close to the truth? What happens when the same bit of information reveals an important fact about the world, and also undermines the noble lie that holds society together? In such cases society may seek to preserve order by placing limits on the search for truth.
One obvious example is Darwin’s theory of evolution. Understanding evolution greatly advances our understanding of the origins and biology of species, including Homo sapiens, but it also undermines the central myths that maintain order in numerous societies. No wonder that various governments and churches have banned or limited the teaching of evolution, preferring to sacrifice truth for the sake of order.26
A related problem is that an information network may allow and even encourage people to search for truth, but only in specific fields that help generate power without threatening the social order. The result can be a very powerful network that is singularly lacking in wisdom. Nazi Germany, for example, cultivated many of the world’s leading experts in chemistry, optics, engineering, and rocket science. It was largely Nazi rocket science that later brought the Americans to the moon.27 This scientific prowess helped the Nazis build an extremely powerful war machine, which was then deployed in the service of a deranged and murderous mythology. Under Nazi rule Germans were encouraged to develop rocket science, but they were not free to question racist theories about biology and history.
That’s a major reason why the history of human information networks isn’t a triumphant march of progress. While over the generations human networks have grown increasingly powerful, they have not necessarily grown increasingly wise. If a network privileges order over truth, it can become very powerful but use that power unwisely.
Instead of a march of progress, the history of human information networks is a tightrope walk trying to balance truth with order. In the twenty-first century we aren’t much better at finding the right balance than our ancestors were in the Stone Age. Contrary to what the mission statements of corporations like Google and Facebook imply, simply increasing the speed and efficiency of our information technology doesn’t necessarily make the world a better place. It only makes the need to balance truth and order more urgent. The invention of the story taught us this lesson already tens of thousands of years ago. And the same lesson would be taught again, when humans came up with their second great information technology: the written document.
CHAPTER 3 Documents: The Bite of the Paper Tigers
Stories were the first crucial information technology developed by humans. They laid the foundation for all large-scale human cooperation and made humans the most powerful animals on earth. But as an information technology, stories have their limitations.
To appreciate this, consider the role storytelling plays in the formation of nations. Many nations have first been conceived in the imagination of poets. Sarah Aaronsohn and the NILI underground are remembered by present-day Israelis as some of the first Zionists who risked their lives in the 1910s to establish a Jewish state in Palestine, but from where did NILI members get this idea in the first place? They were inspired by an earlier generation of poets, thinkers, and visionaries such as Theodor Herzl and Hayim Nahman Bialik.
In the 1890s and first decade of the twentieth century, Bialik, a Ukrainian Jew, published numerous poems and stories bewailing the persecution and weakness of European Jews and calling on them to take their fate in their hands—to defend themselves by force of arms, immigrate to Palestine, and there establish their own state. One of his most stirring poems was written following the Kishinev Pogrom of 1903, in which forty-nine Jews were murdered and dozens more were injured.1 “In the City of Slaughter” condemned the murderous antisemitic mob who perpetrated the atrocities, but it also criticized the Jews themselves for their pacifism and helplessness.
In one heart-wrenching scene, Bialik described how Jewish women were gang-raped, while their husbands and brothers hid nearby, afraid to intervene. The poem compares the Jewish men to terrified mice and imagines how they quietly prayed to God to perform some miracle, which failed to materialize. The poem then tells how even after the pogrom was over, the survivors had no thought of arming themselves and instead entered Talmudic disputations about whether the raped women were now ritualistically “defiled” or whether they were still “pure.” This poem is mandatory reading in many Israeli schools today. It is also mandatory reading for anyone wishing to understand how after two millennia of being one of the most pacifist groups in history, Jews built one of the most formidable armies in the world. Not for nothing was Bialik named Israel’s national poet.2
The fact that Bialik lived in Ukraine, and was intimately familiar with the persecution of Ashkenazi Jews in eastern Europe but had little understanding of conditions in Palestine, contributed to the subsequent conflict there between Jews and Arabs. Bialik’s poems inspired Jews to see themselves as victims in dire need of developing their military might and building their own country, but hardly considered the catastrophic consequences for the Arab inhabitants of Palestine, or indeed for the Mizrahi Jewish communities native to the Middle East. When the Arab-Israeli conflict exploded in the late 1940s, hundreds of thousands of Palestinians and hundreds of thousands of Mizrahi Jews were driven out of their ancestral homes in the Middle East, partly as a result of poems composed half a century earlier in Ukraine.3
While Bialik was writing in Ukraine, the Hungarian Jew Theodor Herzl was busy organizing the Zionist movement in the 1890s and early years of the twentieth century. As a central part of his political activism, Herzl published two books. The Jewish State (1896) was a manifesto outlining Herzl’s idea of establishing a Jewish state in Palestine, and The Old New Land (1902) was a utopian novel set in the year 1923 describing the prosperous Jewish state that Herzl envisioned. The two books—which fatefully also tended to ignore realities on the ground in Palestine—were immensely influential in shaping the Zionist movement. The Old New Land appeared in Hebrew under the title Tel Aviv (a loose Hebrew translation of “Old New Land”). The city of Tel Aviv, established seven years after the book’s publication, took its name from the book. While Bialik is Israel’s national poet, Herzl is known as the visionary of the state.
The yarns Bialik and Herzl wove ignored many crucial facts about contemporary reality, most notably that around 1900 the Jews of Palestine comprised only 6–9 percent of the region’s total population of about 600,000 people.4 While disregarding such demographic facts, Bialik and Herzl accorded great importance to mythology, most notably the stories of the Bible, without which modern Zionism is unimaginable. Bialik and Herzl were also influenced by the nationalist myths that were created in the nineteenth century by almost every other ethnic group in Europe. The Ukrainian Jew Bialik and the Hungarian Jew Herzl did for Zionism what was earlier done by the poets Taras Shevchenko for Ukrainian nationalism,5 Sándor Petőfi for Hungarian nationalism,6 and Adam Mickiewicz for Polish nationalism.7 Observing the growth of other national movements all around, Herzl wrote that nations arise “out of dreams, songs, fantasies.”8
But dreams, songs, and fantasies, however inspiring, are not enough to create a functioning nation-state. Bialik inspired generations of Jewish fighters, but to equip and maintain an army, it is also necessary to raise taxes and buy guns. Herzl’s utopian book laid the foundations for the city of Tel Aviv, but to keep the city going, it was also necessary to dig a sewage system. When all is said and done, the essence of patriotism isn’t reciting stirring poems about the beauty of the motherland, and it certainly isn’t making hate-filled speeches against foreigners and minorities. Rather, patriotism means paying your taxes so that people on the other side of the country also enjoy the benefit of a sewage system, as well as security, education, and health care.
To manage all these services and raise the necessary taxes, enormous amounts of information need to be collected, stored, and processed: information about properties, payments, exemptions, discounts, debts, inventories, shipments, budgets, bills, and salaries. This, however, is not the kind of information that can be turned into a memorable poem or a captivating myth. Instead, tax records come in the shape of various types of lists, ranging from a simple item-by-item record to more elaborate tables and spreadsheets. No matter how intricate these data sets may become, they eschew narrative in favor of dryly listing amounts owed and amounts paid. Poets can afford to ignore such mundane facts, but tax collectors cannot.
Lists are crucial not only for national taxation systems but also for almost all other complex financial institutions. Corporations, banks, and stock markets cannot exist without them. A church, a university, or a library that wants to balance its budget soon realizes that in addition to priests and poets who can mesmerize people with stories, it needs accountants who know their way around the various types of lists.
Lists and stories are complementary. National myths legitimize the tax records, while the tax records help transform aspirational stories into concrete schools and hospitals. Something analogous happens in the field of finance. The dollar, the pound sterling, and the bitcoin all come into being by persuading people to believe a story, and tales told by bankers, finance ministers, and investment gurus raise or lower their value. When the chairperson of the Federal Reserve wants to curb inflation, when a finance minister wants to pass a new budget, and when a tech entrepreneur wants to draw investors, they all turn to storytelling. But to actually manage a bank, a budget, or a start-up, lists are essential.
The big problem with lists, and the crucial difference between lists and stories, is that lists tend to be far more boring than stories, which means that while we easily remember stories, we find it difficult to remember lists. This is an important fact about how the human brain processes information. Evolution has adapted our brains to be good at absorbing, retaining, and processing even very large quantities of information when they are shaped into a story. The Ramayana, one of the foundational tales of Hindu mythology, is twenty-four thousand verses long and runs to about seventeen hundred pages in modern editions, yet despite its enormous length generations of Hindus succeeded in remembering and reciting it by heart.9
In the twentieth and twenty-first centuries, the Ramayana was repeatedly adapted for film and television. In 1987–88, a seventy-eight-episode version (running to about 2,730 hours) was the most watched television series in the world, with more than 650 million viewers. According to a BBC report, when episodes were aired, “streets would be deserted, shops would be closed, and people would bathe and garland their TV sets.” During the 2020 COVID-19 lockdown the series was re-aired and again became the most watched show in the world.10 While modern TV audiences need not memorize any texts by heart, it is noteworthy how easy they find it to follow the intricate plots of epic dramas, detective thrillers, and soap operas, recalling who each character is and how they are related to numerous others. We are so accustomed to performing such feats of memory that we seldom consider how extraordinary they are.
What makes us so good at remembering epic poems and long-running TV series is that long-term human memory is particularly adapted to retaining stories. As Kendall Haven writes in his 2007 book Story Proof: The Science Behind the Startling Power of Story, “Human minds … rely on stories and on story architecture as the primary roadmap for understanding, making sense of, remembering, and planning our lives.… Lives are like stories because we think in story terms.” Haven references more than 120 academic studies, concluding that “research overwhelmingly, convincingly, and without opposition provides the evidence” that stories are a highly efficient “vehicle for communicating factual, conceptual, emotional, and tacit information.”11
In contrast, most people find it hard to remember lists by heart, and few people would be interested in watching a TV recitation of India’s tax records or annual budget. Mnemonic methods used to memorize lists of items often work by weaving the items into a plot, thereby turning the list into a story.12 But even with the help of such mnemonic devices, who could remember their country’s tax records or budget? The information may be vital—determining what quality of health care, education, and welfare services citizens enjoy—but our brains are not adapted to remembering such things. Unlike national poems and myths, which can be stored in our brains, complex national taxation and administration systems have required a unique nonorganic information technology in order to function. This technology is the written document.
TO KILL A LOAN
The written document was invented many times in many places. Some of the earliest examples come from ancient Mesopotamia. A cuneiform clay tablet dated to the twenty-eighth day of the tenth month of the forty-first year of the reign of King Shulgi of Ur (ca. 2053/4 BCE) recorded the monthly deliveries of sheep and goats. Fifteen sheep were delivered on the second day of the month, 7 sheep on the third day, 11 sheep on the fourth, 219 on the fifth, 47 on the sixth, and so on until 3 sheep were delivered on the twenty-eighth. In total, says the clay tablet, 896 animals were received that month. Remembering all these deliveries was important for the royal administration, to monitor people’s obedience and to keep track of available resources. While doing so in one’s head was a formidable challenge, it was easy for a learned scribe to write them down on a clay tablet.13
Like stories and like all other information technologies in history, written documents didn’t necessarily represent reality accurately. The Ur tablet, for example, contained a mistake. The document says that a total of 896 animals were received during that month, but when modern scholars added up all the individual entries they reached a total of 898. The scribe who wrote the document apparently made a mistake when he calculated the overall tally, and the tablet preserved this mistake for posterity.
But whether true or false, written documents created new realities. By recording lists of properties, taxes, and payments, they made it far easier to create administrative systems, kingdoms, religious organizations, and trade networks. More specifically, documents changed the method used for creating intersubjective realities. In oral cultures, intersubjective realities were created by telling a story that many people repeated with their mouths and remembered in their brains. Brain capacity consequently placed a limit on the kinds of intersubjective realities that humans created. Humans couldn’t forge an intersubjective reality that their brains couldn’t remember.
This limit could be transcended, however, by writing documents. The documents didn’t represent an objective empirical reality; the reality was the documents themselves. As we shall see in later chapters, written documents thereby provided precedents and models that would eventually be used by computers. The ability of computers to create intersubjective realities is an extension of the power of clay tablets and pieces of paper.
As a key example, consider ownership. In oral communities that lacked written documents, ownership was an intersubjective reality created through the words and behaviors of the community members. To own a field meant that your neighbors agreed that this field was yours and behaved accordingly. They didn’t build a hut on that field, graze their livestock there, or pick fruits there without first asking your permission. Ownership was created and maintained by people continuously saying or signaling things to one another. This made ownership the affair of a local community and placed a limit on the ability of a distant central authority to control all landownership. No king, minister, or priest could remember who owned each field in hundreds of distant villages. This also placed a limit on the ability of individuals to claim and exercise absolute property rights, and instead favored various forms of communal property rights. For example, your neighbors might acknowledge your right to cultivate a field but not your right to sell it to foreigners.14
In a literate state, to own a field increasingly came to mean that it is written on some clay tablet, bamboo strip, piece of paper, or silicon chip that you own that field. If your neighbors have been grazing their sheep for years on a piece of land, and none of them ever said that you own it, but you can somehow produce an official document that says it is yours, you have a good chance of enforcing your claim. Conversely, if all the neighbors agree that it is your field but you don’t have any official document that proves it, tough luck. Ownership is still an intersubjective reality created by exchanging information, but the information now takes the form of a written document (or a computer file) rather than of people talking and gesturing to each other. This means that ownership can now be determined by a central authority that produces and holds the relevant documents. It also means that you can sell your field without asking your neighbors’ permission, simply by transferring the crucial document to someone else.
The power of documents to create intersubjective realities was beautifully manifested in the Old Assyrian dialect, which treated documents as living things that could also be killed. Loan contracts were “killed” (duākum) when the debt was repaid. This was done by destroying the tablet, adding some mark to it, or breaking its seal. The loan contract didn’t represent reality; it was the reality. If somebody repaid the loan but failed to “kill the document,” the debt was still owed. Conversely, if somebody didn’t repay the loan but the document “died” in some other way—perhaps the dog ate it—the debt was no more.15 The same happens with money. If your dog eats a hundred-dollar bill, those hundred dollars cease to exist.
In Shulgi’s Ur, in ancient Assyria, and in numerous subsequent polities, social, economic, and political relations relied on documents that create reality instead of merely representing it. When writing constitutions, peace treaties, and commercial contracts, lawyers, politicians, and businesspeople wrangle for weeks and even months over each word—because they know that these pieces of paper can wield enormous power.
BUREAUCRACY
Every new information technology has its unexpected bottlenecks. It solves some old problems but creates new ones. In the early 1730s BCE, Narâmtani, a priestess in the Mesopotamian city of Sippar, wrote a letter (on a clay tablet) to a relative, asking him to send her a few clay tablets he kept in his house. She explained that her claim to an inheritance was being contested and she couldn’t prove her case in court without those documents. She ended her message with a plea: “Now, do not neglect me!”16
We don’t know what happened next, but just imagine the situation if the relative searched his house but could not find the missing tablets. As people produced more and more documents, finding them turned out to be far from easy. This was a particular challenge for kings, priests, merchants, and anyone else who accumulated thousands of documents in their archives. How do you find the right tax record, payment receipt, or business contract when you need it? Written documents were much better than human brains in recording certain types of information. But they created a new and very thorny problem: retrieval.17
The brain is remarkably efficient in retrieving whatever information is stored in its network of tens of billions of neurons and trillions of synapses. Though our brain archives countless complex stories about our personal life, our national history, and our religious mythology, healthy people can retrieve information about any of them in less than a second. What did you eat for breakfast? Who was your first crush? When did your country gain its independence? What’s the first verse in the Bible?
How did you retrieve all these pieces of information? What mechanism activates the right neurons and synapses to rapidly call up the necessary information? Though neuroscientists have made some progress in the study of memory, nobody yet understands what memories are, or how exactly they are stored and retrieved.18 What we do know is that millions of years of evolution streamlined the brain’s retrieval processes. However, once humans have outsourced memories from organic brains to inorganic documents, retrieval could no longer rely on that streamlined biological system. Nor could it rely on the foraging abilities that humans evolved over millions of years. Evolution has adapted humans for finding fruits and mushrooms in a forest, but not for finding documents in an archive.
Foragers locate fruits and mushrooms in a forest, because evolution has organized forests according to a discernible organic order. Fruit trees photosynthesize, so they require sunlight. Mushrooms feed on dead organic matter, which can usually be found in the ground. So mushrooms are usually down at soil level, whereas fruits grow further up. Another common rule is that apples grow on apple trees, whereas figs grow on figs trees. So if you are looking for an apple, you first need to locate an apple tree, and then look up. When living in a forest, humans learn this organic order.
It is very different with archives. Since documents aren’t organisms, they don’t obey any biological laws, and evolution didn’t organize them for us. Tax reports don’t grow on a tax-report shelf. They need to be placed there. For that, somebody first needs to come up with the idea of categorizing information by shelves, and to decide which documents should go on which shelf. Unlike foragers, who need merely to discover the preexisting order of the forest, archivists need to devise a new order for the world. That order is called bureaucracy.
Bureaucracy is the way people in large organizations solved the retrieval problem and thereby created bigger and more powerful information networks. But like mythology, bureaucracy too tends to sacrifice truth for order. By inventing a new order and imposing it on the world, bureaucracy distorted people’s understanding of the world in unique ways. Many of the problems of our twenty-first-century information networks—like biased algorithms that mislabel people, or rigid protocols that ignore human needs and feelings—are not new problems of the computer age. They are quintessential bureaucratic problems that have existed long before anyone even dreamed of computers.
BUREAUCRACY AND THE SEARCH FOR TRUTH
Bureaucracy literally means “rule by writing desk.” The term was invented in eighteenth-century France, when the typical official sat next to a writing desk with drawers—a bureau.19 At the heart of the bureaucratic order, then, is the drawer. Bureaucracy seeks to solve the retrieval problem by dividing the world into drawers, and knowing which document goes into which drawer.
The principle remains the same regardless of whether the document is placed into a drawer, a shelf, a basket, a jar, a computer folder, or any other receptacle: divide and rule. Divide the world into containers, and keep the containers separate so the documents don’t get mixed up. This principle, however, comes with a price. Instead of focusing on understanding the world as it is, bureaucracy is often busy imposing a new and artificial order on the world. Bureaucrats begin by inventing various drawers, which are intersubjective realities that don’t necessarily correspond to any objective divisions in the world. The bureaucrats then try to force the world to fit into these drawers, and if the fit isn’t very good, the bureaucrats push harder. Anyone who ever filled out an official form knows this only too well. When you fill out the form, and none of the listed options fits your circumstances, you must adapt yourself to the form, rather than the form adapting to you. Reducing the messiness of reality to a limited number of fixed drawers helps bureaucrats keep order, but it comes at the expense of truth. Because they are fixated on their drawers—even when reality is far more complex—bureaucrats often develop a distorted understanding of the world.
The urge to divide reality into rigid drawers also leads bureaucrats to pursue narrow goals irrespective of the wider impact of their actions. A bureaucrat tasked with increasing industrial production is likely to ignore environmental considerations that fall outside her purview, and perhaps dump toxic waste into a nearby river, leading to an ecological disaster downstream. If the government then establishes a new department to combat pollution, its bureaucrats are likely to push for ever more stringent regulations, even if this results in economic ruin for communities upstream. Ideally, someone should be able to take into account all the different considerations and aspects, but such a holistic approach requires transcending or abolishing the bureaucratic division.
The distortions created by bureaucracy affect not only government agencies and private corporations but also scientific disciplines. Consider, for example, how universities are divided into different faculties and departments. History is separate from biology and from mathematics. Why? Certainly this division doesn’t reflect objective reality. It is the intersubjective invention of academic bureaucrats. The COVID-19 pandemic, for example, was at one and the same time a historical, biological, and mathematical event. But the academic study of pandemics is divided between the separate departments of history, biology, and mathematics (among others). Students pursuing an academic degree must usually decide to which of these departments they belong. Their decision limits their choice of courses, which in turn shapes their understanding of the world. Mathematics students learn how to predict future morbidity levels from present rates of infection; biology students learn how viruses mutate over time; and history students learn how religious and political beliefs affect people’s willingness to follow government instructions. To fully understand COVID-19 requires taking into account mathematical, biological, and historical phenomena, but academic bureaucracy doesn’t encourage such a holistic approach.
As you climb the academic ladder, the pressure to specialize only increases. The academic world is ruled by the law of publish or perish. If you want a job, you must publish in peer-reviewed journals. But journals are divided by discipline, and publishing an article on virus mutations in a biology journal demands following different conventions from publishing an article on the politics of pandemics in a history journal. There are different jargons, different citation rules, and different expectations. Historians should have a deep understanding of culture and know how to read and interpret historical documents. Biologists should have a deep understanding of evolution and know how to read and interpret DNA molecules. Things that fall in between categories—like the interplay between human political ideologies and virus evolution—are often left unaddressed.20
To appreciate how academics force a messy and fluid world into rigid bureaucratic categories, let’s dig a little deeper in the specific discipline of biology. Before Darwin could explain the origin of species, earlier scholars like Carl Linnaeus first had to define what a species is and classify all living organisms into species. To argue that lions and tigers evolved from a common feline ancestor, you first have to define “lions” and “tigers.”21 This turned out to be a difficult and never-ending job, because animals, plants, and other organisms often trespass the boundaries of their allotted drawers.
Evolution cannot be easily contained in any bureaucratic schema. The whole point of evolution is that species continually change, which means that putting each species in one unchanging drawer distorts biological reality. For example, it is an open question when Homo erectus ended and Homo sapiens began. Were there once two Erectus parents whose child was the first Sapiens?22 Species also keep intermingling, with animals belonging to seemingly separate species not only having sex but even siring fertile offspring. Most Sapiens living today have about 1–3 percent Neanderthal DNA,23 indicating that there once was a child whose father was a Neanderthal and whose mother was a Sapiens (or vice versa). So are Sapiens and Neanderthals the same species or different species? And is “species” an objective reality that biologists discover, or is it an intersubjective reality that biologists impose?24
There are numerous other examples of animals breaking out of their drawers, so the neat bureaucratic division fails to accurately categorize ring species, fusion species, and hybrids.25 Grizzly bears and polar bears sometimes produce pizzly bears and grolar bears.26 Lions and tigers produce ligers and tigons.27
When we shift our attention from mammals and other multicellular organisms to the world of single-cell bacteria and archaea, we discover that anarchy reigns. In a process known as horizontal gene transfer, single-cell organisms routinely exchange genetic material not only with organisms from related species but also with organisms from entirely different genera, kingdoms, orders, and even domains. Bacteriologists have a very difficult job keeping tabs on these chimeras.28
And when we reach the very edge of life and consider viruses like SARS-CoV-2 (responsible for COVID-19), things become even more complicated. Viruses straddle the supposed rigid boundary between living beings and lifeless matter—between biology and chemistry. Unlike bacteria, viruses aren’t single-cell organisms. They aren’t cells at all, and don’t possess any cellular machinery of their own. Viruses don’t eat or metabolize, and cannot reproduce by themselves. They are tiny packets of genetic code, which are able to penetrate cells, hijack their cellular machinery, and instruct them to produce more copies of that alien genetic code. The new copies burst out of the cell to infect and hijack more cells, which is how the alien code turns viral. Scientists argue endlessly about whether viruses should count as life-forms or whether they fall outside the boundary of life.29 But this boundary isn’t an objective reality; it is an intersubjective convention. Even if biologists reach a consensus that viruses are life-forms, it wouldn’t change anything about how viruses behave; it will only change how humans think about them.
Of course, intersubjective conventions are themselves part of reality. As we humans become more powerful, so our intersubjective beliefs become more consequential for the world outside our information networks. For example, scientists and legislators have categorized species according to the threat of extinction they face, on a scale ranging from “least concern” through “vulnerable” and “endangered” to “extinct.” Defining a particular population of animals as an “endangered species” is an intersubjective human convention, but it can have far-reaching consequences, for instance by imposing legal restrictions on hunting those animals or destroying their habitat. A bureaucratic decision about whether a certain animal belongs in the “endangered species” drawer or in the “vulnerable species” drawer could make the difference between life and death. As we shall see time and again in subsequent chapters, when a bureaucracy puts a label on you, even though the label might be pure convention, it can still determine your fate. That’s true whether the bureaucrat is a flesh-and-blood expert on animals; a flesh-and-blood expert on humans; or an inorganic AI.
THE DEEP STATE
In defense of bureaucracy it should be noted that while it sometimes sacrifices truth and distorts our understanding of the world, it often does so for the sake of order, without which it would be hard to maintain any large-scale human network. While bureaucracies are never perfect, is there a better way to manage big networks? For example, if we decided to abolish all conventional divisions in the academic world, all departments and faculties and specialized journals, would every prospective doctor be expected to devote several years to the study of history, and would people who studied the impact of the Black Death on Christian theology be considered expert virologists? Would it lead to better health-care systems?
Anyone who fantasizes about abolishing all bureaucracies in favor of a more holistic approach to the world should reflect on the fact that hospitals too are bureaucratic institutions. They are divided into different departments, with hierarchies, protocols, and lots of forms to fill out. They suffer from many bureaucratic illnesses, but they still manage to cure us of many of our biological illnesses. The same goes for almost all the other services that make our life better, from our schools to our sewage system.
When you flush the toilet, where does the waste go? It goes into the deep state. There is an intricate subterranean web of pipes, pumps, and tunnels that runs under our houses and collects our waste, separates it from the supply of drinking water, and either treats or safely disposes of it. Somebody needs to design, construct, and maintain that deep web, plug holes in it, monitor pollution levels, and pay the workers. That too is bureaucratic work, and we would face a lot of discomfort and even death if we abolished that particular department. Sewage water and drinking water are always in danger of mixing, but luckily for us there are bureaucrats who keep them separate.
Prior to the establishment of modern sewage systems, waterborne infectious diseases like dysentery and cholera killed millions of people around the world.30 In 1854 hundreds of London residents began dying of cholera. It was a relatively small outbreak, but it proved to be a turning point in the history of cholera, of epidemics more generally, and of sewage. The leading medical theory of the day argued that cholera epidemics were caused by “bad air.” But the physician John Snow suspected that the cause was the water supply. He painstakingly tracked and listed all known cholera patients, their place of residence, and their source of water. The resulting data led him to identify the water pump on Broad Street in Soho as the epicenter of the outbreak.
This was tedious bureaucratic work—collecting data, categorizing it, and mapping it—but it saved lives. Snow explained his findings to local officials, persuading them to disable the Broad Street pump, which effectively ended the outbreak. Subsequent research discovered that the well providing water to the Broad Street pump was dug less than a meter from a cholera-infected cesspit.31
Snow’s discovery, and the work of many subsequent scientists, engineers, lawyers, and officials, resulted in a sprawling bureaucracy regulating cesspits, water pumps, and sewage lines. In today’s England, digging wells and constructing cesspits require filling out forms and getting licenses, which ensure that drinking water doesn’t come from a well someone dug next to a cesspit.32
It is easy to forget about this system when it works well, but since 1854 it has saved millions of lives, and it is one of the most important services provided by modern states. In 2014, Prime Minister Narendra Modi of India identified the lack of toilets as one of India’s biggest problems. Open defecation is a major cause for spreading diseases like cholera, dysentery, and diarrhea, as well as exposing women and girls to sexual assaults. As part of his flagship Clean India Mission, Modi promised to provide all Indian citizens with access to toilets, and between 2014 and 2020 the Indian state invested around ten billion dollars in the project, building more than 100 million new latrines.33 Sewage isn’t the stuff of epic poems, but it is a test of a well-functioning state.
THE BIOLOGICAL DRAMAS
Mythology and bureaucracy are the twin pillars of every large-scale society. Yet while mythology tends to inspire fascination, bureaucracy tends to inspire suspicion. Despite the services they provide, even beneficial bureaucracies often fail to win the public’s trust. For many people, the very word “bureaucracy” carries negative connotations. This is because it is inherently difficult to know whether a bureaucratic system is beneficial or malicious. For all bureaucracies—good or bad—share one key characteristic: it is hard for humans to understand them.
Any kid can tell the difference between a friend and a bully. You know if someone shares their lunch with you or instead takes yours. But when the tax collector comes to take a cut from your earnings, how can you tell whether it goes to build a new public sewage system or a new private dacha for the president? It is hard to get all the relevant information, and even harder to interpret it. It is similarly difficult for citizens to understand the bureaucratic procedures determining how pupils are admitted to schools, how patients are treated in hospitals, or how garbage is collected and recycled. It takes a minute to tweet allegations of bias, fraud, or corruption, and many weeks of arduous work to prove or disprove them.
Documents, archives, forms, licenses, regulations, and other bureaucratic procedures have changed the way information flows in society, and with it the way power works. This made it far more difficult to understand power. What is happening behind the closed doors of offices and archives, where anonymous officials analyze and organize piles of documents and determine our fate with a stroke of a pen or a click of a mouse?
In tribal societies that lack written documents and bureaucracies, the human network is composed of only human-to-human and human-to-story chains. Authority belongs to the people who control the junctions that link the various chains. These junctions are the tribe’s foundational myths. Charismatic leaders, orators, and mythmakers know how to use these stories in order to shape identities, build alliances, and sway emotions.34
In human networks connected by written documents and bureaucratic procedures—from ancient Ur to modern India—society relies in part on the interaction between humans and documents. In addition to human-to-human and human-to-story chains, such societies are held together by human-to-document chains. When we observe a bureaucratic society at work, we still see humans telling stories to other humans, as when millions of Indians watch the Ramayana series, but we also see humans passing documents to other humans, as when TV networks are required to apply for broadcasting licenses and fill out tax reports. Looked at from a different perspective, what we see is documents compelling humans to engage with other documents.
This led to shifts in authority. As documents became a crucial nexus linking many social chains, considerable power came to be invested in these documents, and experts in the arcane logic of documents emerged as new authority figures. Administrators, accountants, and lawyers mastered not just reading and writing but also the skills of composing forms, separating drawers, and managing archives. In bureaucratic systems, power often comes from understanding how to manipulate obscure budgetary loopholes and from knowing your way around the labyrinths of offices, committees, and subcommittees.
This shift in authority changed the balance of power in the world. For better or worse, literate bureaucracies tended to strengthen the central authority at the expense of ordinary citizens. It’s not just that documents and archives made it easier for the center to tax, judge, and conscript everybody. The difficulty of understanding bureaucratic power simultaneously made it harder for the masses to influence, resist, or evade the central authority. Even when bureaucracy was a benign force, providing people with sewage systems, education, and security, it still tended to increase the gap between rulers and ruled. The system enabled the center to collect and record a lot more information about the people it governed, while the latter found it much more difficult to understand how the system itself worked.
Art, which helps us understand many other aspects of life, offered only limited assistance in this case. Poets, playwrights, and moviemakers have occasionally focused on the dynamics of bureaucratic power. However, this has proven to be a very difficult story to communicate. Artists usually work with a limited set of story lines that are rooted in our biology, but none of these biological dramas sheds much light on the workings of bureaucracy, because they have all been scripted by evolution millions of years before the emergence of documents and archives. To understand what “biological dramas” are, and why they are a poor guide for understanding bureaucracy, let’s consider in detail the plot of one of humanity’s greatest artistic masterpieces—the Ramayana.
One important plotline of the Ramayana concerns the relations between the eponymous prince, Rama, his father, King Dasharatha, and his stepmother, Queen Kaikeyi. Though Rama, being the eldest son, is the rightful heir to the kingdom, Kaikeyi persuades the king to banish Rama to the wilderness and bestow the succession instead on her son Bharata. Underlying this plotline are several biological dramas that go back hundreds of millions of years in mammalian and avian evolution.
All mammal and bird offspring depend on their parents in the first stage of life, seek parental care, and fear parental neglect or hostility. Life and death hang in the balance. A cub or chick pushed out of the nest too soon is in danger of death from starvation or predation. Among humans, the fear of being neglected or abandoned by one’s parents is a template not just for children’s stories like Snow White,Cinderella, and Harry Potter but also for some of our most influential national and religious myths. The Ramayana is far from being the sole example. In Christian theology damnation is conceived as losing all contact with the mother church and the heavenly father. Hell is a lost child crying for his or her missing parents.
A related biological drama, which is also familiar to human children, mammalian cubs, and avian chicks, is “Father loves me more than he loves you.” Biologists and geneticists have identified sibling rivalry as one of the key processes of evolution.35 Siblings routinely compete for food and parental attention, and in some species the killing of one sibling by another is commonplace. About a quarter of spotted hyena cubs are killed by their siblings, who typically enjoy greater parental care as a result.36 Among sand tiger sharks, females hold numerous embryos in their uterus. The first embryo that reaches about ten centimeters in length then eats all the others.37 The dynamics of sibling rivalry are manifested in numerous myths in addition to the Ramayana, for instance in the stories of Cain and Abel, King Lear, and the TV series Succession. Entire nations—like the Jewish people—may base their identity on the claim that “we are Father’s favorite children.”
The second major plotline of the Ramayana focuses on the romantic triangle formed by Prince Rama, his lover, Sita, and the demon-king Ravana, who kidnaps Sita. “Boy meets girl” and “boy fights boy over girl” are also biological dramas that have been enacted by countless mammals, birds, reptiles, and fish for hundreds of millions of years. We are mesmerized by these stories because understanding them has been essential for our ancestors’ survival. Human storytellers like Homer, Shakespeare, and Valmiki—the purported author of the Ramayana—have displayed an amazing capacity to elaborate on the biological dramas, but even the greatest poetical narratives usually copy their basic plotline from the handbook of evolution.
A third theme recurring in the Ramayana is the tension between purity and impurity, with Sita being the paragon of purity in Hindu culture. The cultural obsession with purity originates in the evolutionary struggle to avoid pollution. All animals are torn between the need to try new food and the fear of being poisoned. Evolution therefore equipped animals with both curiosity and the capacity to feel disgust on coming into contact with something toxic or otherwise dangerous.38 Politicians and prophets have learned how to manipulate these disgust mechanisms. In nationalist and religious myths, countries or churches are depicted as a biological body in danger of being polluted by impure intruders. For centuries bigots have often said that ethnic and religious minorities spread diseases,39 that LGBTQ people are a source of pollution,40 or that women are impure.41 During the Rwanda genocide of 1994, Hutu propaganda referred to the Tutsis as cockroaches. The Nazis compared Jews to rats. Experiments have shown that chimpanzees, too, react with disgust to images of unfamiliar chimpanzees from another band.42
Perhaps in no other culture was the biological drama of “purity versus impurity” carried to greater extremes than in traditional Hinduism. It constructed an intersubjective system of castes ranked by their supposed level of purity, with the pure Brahmins at the top and the allegedly impure Dalit (formerly known as untouchables) at the bottom. Professions, tools, and everyday activities have also been classified by their level of purity, and strict rules have forbidden “impure” persons to marry “pure” people, touch them, prepare food for them, or even come near them.
The modern state of India still struggles with this legacy, which influences almost all aspects of life. For example, fears of impurity created various complications for the aforementioned Clean India Mission, because allegedly “pure” people were reluctant to get involved in “impure” activities such as building, maintaining, and cleaning toilets, or to share public latrines with allegedly “impure” persons.43 On September 25, 2019, two Dalit children—twelve-year-old Roshni Valmiki and her ten-year-old nephew Avinash—were lynched in the Indian village of Bhakhedi for defecating near the house of a family from the higher Yadav caste. They were forced to defecate in public because their houses lacked functioning toilets. A local official later explained that their household—while being among the poorest in the village—was nevertheless excluded from the list of families eligible for government aid to build toilets. The children routinely suffered from other caste-based discrimination, for example being forced to bring separate mats and utensils to school and to sit apart from the other pupils, so as not to “pollute” them.44
The list of biological dramas that press our emotional buttons includes several additional classics, such as “Who will be alpha?” “Us versus them,” and “Good versus evil.” These dramas, too, feature prominently in the Ramayana, and all of them are well known to wolf packs and chimpanzee bands as well as to human societies. Together, these biological dramas form the backbone of almost all human art and mythology. But art’s dependence on the biological dramas have made it difficult for artists to explain the mechanisms of bureaucracy. The Ramayana is set within the context of large agrarian kingdoms, but it shows little interest in how such kingdoms register property, collect taxes, catalog archives, or finance wars. Sibling rivalry and romantic triangles aren’t a good guide for the dynamics of documents, which have no siblings and no romantic life.
Storytellers like Franz Kafka, who focused on the often surreal ways that bureaucracy shapes human lives, pioneered new nonbiological plotlines. In Kafka’s Trial, the bank clerk K. is arrested by unidentified officials of an unfathomable agency for an unnamed crime. Despite his best efforts, he never understands what is happening to him or uncovers the aims of the agency that is crushing him. While sometimes taken as an existential or theological reference to the human condition in the universe and to the unfathomability of God, on a more mundane level the story highlights the potentially nightmarish character of bureaucracies, which as an insurance lawyer Kafka knew all too well.
In bureaucratic societies, the lives of ordinary people are often upended by unidentified officials of an unfathomable agency for incomprehensible reasons. Whereas stories about heroes who confront monsters—from the Ramayana to Spider-Man—repackage the biological dramas of confronting predators and romantic rivals, the unique horror of Kafkaesque stories comes from the unfathomability of the threat. Evolution has primed our minds to understand death by a tiger. Our mind finds it much more difficult to understand death by a document.
Some portrayals of bureaucracy are satirical. Joseph Heller’s iconic 1961 novel, Catch-22, illustrated the central role bureaucracy plays in war. The ex–private first class Wintergreen in the mail room—who decides which letters to forward—is a more powerful figure than any general.45 The 1980s British sitcoms Yes Minister and Yes, Prime Minister showed the ways that civil servants use arcane regulations, obscure subcommittees, and piles of documents to manipulate and control their political bosses. The 2015 comedy-drama The Big Short (based on a 2010 book by Michael Lewis) explored the bureaucratic roots of the 2007–8 financial crisis. The movie’s arch-villains are not humans but collateralized debt obligations (CDOs), which are financial devices invented by investment bankers and understood by nobody else in the world. These bureaucratic Godzillas slumbered unnoticed in the depths of bank portfolios, until they suddenly emerged in 2007 to wreak havoc on the lives of billions of people by instigating a major financial crisis.
Artworks like these have had some success in shaping perceptions of how bureaucratic power works, but this is an uphill battle, because since the Stone Age our minds have been primed to focus on biological dramas rather than bureaucratic ones. Most Hollywood and Bollywood blockbusters are not about CDOs. Rather, even in the twenty-first century, most blockbusters are essentially Stone Age stories about the hero who fights the monster to win the girl. Similarly, when depicting the dynamics of political power, TV series like Game of Thrones, The Crown, and Succession focus on the family intrigues of the dynastic court rather than on the bureaucratic labyrinth that sustains—and sometimes curbs—the dynasty’s power.
LET’S KILL ALL THE LAWYERS
The difficulty of depicting and understanding bureaucratic realities has had unfortunate results. On the one hand, it leaves people feeling helpless in the face of harmful powers they do not understand, like the hero of Kafka’s Trial. On the other hand, it also leaves people with the impression that bureaucracy is a malign conspiracy, even in cases when it is in fact a benign force providing us with health care, security, and justice.
In the sixteenth century, Ludovico Ariosto described the allegorical figure of Discord as a woman who walks around in a cloud of “sheaves of summonses and writs, cross-examinations and powers of attorney, and great piles of glosses, counsel’s opinions and precedents—all of which tended to the greater insecurity of impoverished folk. In front and behind her and on either side she was hemmed in by notaries, attorneys and barristers.”46
In his description of Jack Cade’s Rebellion (1450) in Henry VI, Part 2, Shakespeare has a commoner rebel called Dick the Butcher take the antipathy to bureaucracy to its logical conclusion. Dick has a plan to establish a better social order. “The first thing we do,” advises Dick, “let’s kill all the lawyers.” The rebel leader, Jack Cade, runs with Dick’s proposal in a forceful attack on bureaucracy and in particular on written documents: “Is not this a lamentable thing, that of the skin of an innocent lamb should be made parchment? That parchment, being scribbled o’er, should undo a man? Some say the bee stings: but I say, ’tis the bee’s wax; for I did but seal once to a thing, and I was never mine own man since.” Just then the rebels capture a clerk and accuse him of being able to write and read. After a short interrogation that establishes his “crime,” Cade orders his men, “Hang him with his pen and inkhorn about his neck.”47
Seventy years prior to Jack Cade’s Rebellion, during the even bigger 1381 Peasants’ Revolt, the rebels focused their ire not only on flesh-and-blood bureaucrats but also on their documents, destroying numerous archives, burning court rolls, charters, and administrative and legal records. In one incident, they made a bonfire of the archives of the University of Cambridge. An old woman named Margery Starr scattered the ashes to the winds while crying, “Away with the learning of the clerks, away with it!” Thomas Walsingham, a monk in St. Albans Abbey who witnessed the destruction of the abbey’s archive firsthand, described how the rebels “set fire to all court rolls and muniments, so that after they had got rid of these records of their ancient service their lords would not be able to claim any right at all against them at some future time.”48 Killing the documents erased the debts.
Similar attacks on archives characterized numerous other insurgencies throughout history. For example, during the Great Jewish Revolt in 66 CE, one of the first things the rebels did upon capturing Jerusalem was to set fire to the central archive in order to destroy records of debts, thereby wining the support of the populace.49 During the French Revolution in 1789, numerous local and regional archives were destroyed for comparable reasons.50 Many rebels might have been illiterate, but they knew that without the documents the bureaucratic machine couldn’t function.
I can sympathize with the suspicion of government bureaucracies and of the power of official documents, because they have played an important role in my own family. My maternal grandfather had his life upended by a government census and by the inability to find a crucial document. My grandfather Bruno Luttinger was born in 1913 in Chernivtsi. Today this town is in Ukraine, but in 1913 it was part of the Habsburg Empire. Bruno’s father disappeared in World War I, and he was raised by his mother, Chaya-Pearl. When the war was over, Chernivtsi was annexed to Romania. In the late 1930s, as Romania became a fascist dictatorship, an important plank of its new antisemitic policy was to conduct a Jewish census.
In 1936 official statistics said that 758,000 Jews lived in Romania, constituting 4.2 percent of the population. The same official statistics said that the total number of refugees from the U.S.S.R., Jews and non-Jews, was about 11,000. In 1937 a new fascist government came to power, headed by Prime Minister Octavian Goga. Goga was a renowned poet as well as a politician, but he quickly graduated from patriotic poetry to fake statistics and oppressive bureaucracy. He and his colleagues ignored the official statistics and claimed that hundreds of thousands of Jewish refugees were flooding into Romania. In several interviews Goga claimed that half a million Jews had entered Romania illegally and that the total number of Jews in the country was 1.5 million. Government organs, far-right statisticians, and popular newspapers regularly cited even higher figures. The Romanian embassy in Paris, for example, claimed there were a million Jewish refugees in Romania. Christian Romanians were gripped by mass hysteria that they would soon be replaced or become a minority in a Jewish-led country.
Goga’s government stepped in to offer a solution to the imaginary problem invented by its own propaganda. On January 22, 1938, the government issued a law ordering all Jews in Romania to provide documented proof that they were born in Romanian territory and were entitled to Romanian citizenship. Jews who failed to provide proof would lose their citizenship, along with all rights to residence and employment.
Suddenly Romania’s Jews found themselves in a bureaucratic hell. Many had to travel to their birthplace to look for the relevant documents, only to discover that the municipal archives were destroyed during World War I. Jews born in territories annexed to Romania only after 1918—like Chernivtsi—faced special difficulties, because they lacked Romanian birth certificates and because many other documents about their families were archived in the former Habsburg capitals of Vienna and Budapest instead of in Bucharest. Jews often didn’t even know which documents they were supposed to be looking for, because the census law didn’t specify which documents were considered sufficient “proof.”
Clerks and archivists gained a new and lucrative source of income as frantic Jews offered to pay large bribes to get their hands on the right document. Even if no bribes were involved, the process was extremely costly: any request for documentation, as well as filing the citizenship request with the authorities, involved paying fees. Finding and filing the right document did not guarantee success. A difference of a single letter between how a name was spelled on the birth certificate and on the citizenship papers was enough for the authorities to revoke the citizenship.
Many Jews could not clear these bureaucratic hurdles and didn’t even file a citizenship request. Of those who did, only 63 percent got their citizenship approved. Altogether, out of 758,000 Romanian Jews, 367,000 lost their citizenship.51 My grandfather Bruno was among them. When the new census law was passed in Bucharest, Bruno did not think much about it. He was born in Chernivtsi and lived there all his life. The thought that he needed to prove to some bureaucrat that he was not an alien struck him as ridiculous. Moreover, in early 1938 his mother fell ill and died, and Bruno felt he had much bigger things to worry about than chasing documents.
In December 1938 an official letter arrived from Bucharest canceling Bruno’s citizenship, and as an alien he was promptly fired from his job in a Chernivtsi radio shop. Bruno was now not only alone and jobless but also stateless and without much prospect for alternative employment. Nine months later World War II erupted, and the danger for paperless Jews was mounting. Of the Romanian Jews who lost their citizenship in 1938, the vast majority would be murdered over the next few years by the Romanian fascists and their Nazi allies (Jews who retained their citizenship had a much higher survival rate).52
My grandfather repeatedly tried to escape the tightening noose, but it was difficult without the right papers. Several times he smuggled himself onto trains and ships, only to be caught and arrested. In 1940 he finally managed to board one of the last ships bound for Palestine before the gates of hell slammed shut. When he arrived in Palestine, he was immediately imprisoned by the British as an illegal immigrant. After two months in prison, the British offered a deal: stay in jail and risk deportation, or enlist in the British army and get Palestinian citizenship. My grandfather grabbed the offer with both hands and from 1941 to 1945 served in the British army in the North African and Italian campaigns. In exchange, he got his papers.
In our family it became a sacred duty to preserve documents. Bank statements, electricity bills, expired student cards, letters from the municipality—if it had an official-looking stamp on it, it would be filed in one of the many folders in our cupboard. You never knew which of these documents might one day save your life.
THE MIRACLE DOCUMENT
Should we love the bureaucratic information network or hate it? Stories like that of my grandfather indicate the dangers inherent in bureaucratic power. Stories like that of the London cholera epidemic indicate its potential benevolence. All powerful information networks can do both good and ill, depending on how they are designed and used. Merely increasing the quantity of information in a network doesn’t guarantee its benevolence, nor make it any easier to find the right balance between truth and order. That is a key historical lesson for the designers and users of the new information networks of the twenty-first century.
Future information networks, particularly those based on AI, will be different from previous networks in many ways. While in part 1 we are examining how mythology and bureaucracy have been essential for large-scale information networks, in part 2 we will see how AI is taking up the role of both bureaucrats and mythmakers. AI tools know how to find and process data better than flesh-and-blood bureaucrats, and AI is also acquiring the ability to compose stories better than most humans.
But before we explore the new AI-based information networks of the twenty-first century, and before we examine the threats and promises of AI mythmakers and AI bureaucrats, there is one more thing we need to understand about the long-term history of information networks. We have now seen that information networks don’t maximize truth, but rather seek to find a balance between truth and order. Bureaucracy and mythology are both essential for maintaining order, and both are happy to sacrifice truth for the sake of order. What mechanisms, then, ensure that bureaucracy and mythology don’t lose touch with truth altogether, and what mechanisms enable information networks to identify and correct their own mistakes, even at the price of some disorder?
The way human information networks have dealt with the problem of errors will be the main subject of the next two chapters. We’ll start by considering the invention of another information technology: the holy book. Holy books like the Bible and the Quran are an information technology that is meant to both include all the vital information society needs and be free from all possibility of error. What happens when an information network believes itself to be utterly incapable of any error? The history of allegedly infallible holy books highlights some of the limitations of all information networks and holds important lessons for the attempt to create infallible AIs in the twenty-first century.
CHAPTER 4 Errors: The Fantasy of Infallibility
As Saint Augustine famously said, “To err is human; to persist in error is diabolical.”1 The fallibility of human beings, and the need to correct human errors, have played key roles in every mythology. According to Christian mythology, the whole of history is an attempt to correct Adam and Eve’s original sin. According to Marxist-Leninist thinking, even the working class is likely to be fooled by its oppressors and misidentify its own interests, which is why it requires the leadership of a wise party vanguard. Bureaucracy, too, is constantly on the lookout for errors, from misplaced documents to inefficient procedures. Complex bureaucratic systems usually contain self-disciplinary bodies, and when a major catastrophe occurs—like a military defeat or a financial meltdown—commissions of inquiry are set up to understand what went wrong and make sure the same mistake is not repeated.
In order to function, self-correcting mechanisms need legitimacy. If humans are prone to error, how can we trust the self-correcting mechanisms to be free from error? To escape this seemingly endless loop, humans have often fantasized about some superhuman mechanism, free from all error, that they can rely upon to identify and correct their own mistakes. Today one might hope that AI could provide such a mechanism, as when in April 2023 Elon Musk announced, “I’m going to start something, which I call TruthGPT or a maximum truth-seeking AI that tries to understand the nature of the universe.”2 We will see in later chapters why this is a dangerous fantasy. In previous eras, such fantasies took a different form—religion.
In our personal lives, religion can fulfill many different functions, like providing solace or explaining the mysteries of life. But historically, the most important function of religion has been to provide superhuman legitimacy for the social order. Religions like Judaism, Christianity, Islam, and Hinduism propose that their ideas and rules were established by an infallible superhuman authority, and are therefore free from all possibility of error, and should never be questioned or changed by fallible humans.
TAKING HUMANS OUT OF THE LOOP
At the heart of every religion lies the fantasy of connecting to a superhuman and infallible intelligence. This is why, as we shall explore in chapter 8, studying the history of religion is highly relevant to present-day debates about AI. In the history of religion, a recurrent problem is how to convince people that a certain dogma indeed originated from an infallible superhuman source. Even if in principle I am eager to submit to the gods’ will, how do I know what the gods really want?
Throughout history many humans claimed to convey messages from the gods, but the messages often contradicted each other. One person said a god appeared to her in a dream; another person said she was visited by an angel; a third recounted how he met a spirit in a forest—and each preached a different message. The anthropologist Harvey Whitehouse recounts how when he was doing fieldwork among the Baining people of New Britain in the late 1980s, a young man called Tanotka fell sick, and in his feverish delirium began making cryptic statements like “I am Wutka” and “I am a post.” Most of these statements were heard only by Tanotka’s older brother, Baninge, who began telling about them to other people and interpreting them in a creative way. Baninge said that his brother was possessed by an ancestral spirit called Wutka and that he was divinely chosen to be the main support of the community, just as local houses were supported by a central post.
After Tanotka recovered, he continued to deliver cryptic messages from Wutka, which were interpreted by Baninge in ever more elaborate ways. Baninge also began having dreams of his own, which allegedly revealed additional divine messages. He claimed that the end of the world was imminent, and convinced many of the locals to grant him dictatorial powers so that he could prepare the community for the coming apocalypse. Baninge proceeded to waste almost all the community’s resources on extravagant feasts and rituals. When the apocalypse didn’t materialize and the community almost starved, Baninge’s power collapsed. Though some locals continued to believe that he and Tanotka were divine messengers, many others concluded that the two were charlatans—or perhaps the servants of the Devil.3
How could people distinguish the true will of the gods from the inventions or imaginations of fallible humans? Unless you had a personal divine revelation, knowing what the gods said meant trusting what fallible humans like Tanotka and Baninge claimed the gods said. But how can you trust these humans, especially if you don’t know them personally? Religion wants to take fallible humans out of the loop and give people access to infallible superhuman laws, but religion repeatedly boiled down to trusting this or that human.
One way around this problem was to create religious institutions that vetted the purported divine messengers. Already in tribal societies communication with superhuman entities like tribal spirits was often the domain of religious experts. Among the Baining people, specialized spirit mediums known as agungaraga were traditionally responsible for communicating with the spirits and thereby learning the hidden causes of misfortunes ranging from illness to crop failure. Their membership in an established institution made the agungaraga more trustworthy than Tanotka and Baninge, and made their authority more stable and widely acknowledged.4 Among the Kalapalo tribe of Brazil religious rituals were organized by hereditary ritual officers known as the anetaū. In ancient Celtic and Hindu societies similar duties were the preserve of druids and Brahmins.5 As human societies grew and became more complex, so did their religious institutions. Priests and oracles had to train long and hard for the important task of representing the gods, so people no longer needed to trust just any layperson who claimed to have met an angel or to carry a divine message.6 In ancient Greece, for example, if you wanted to know what the gods said, you went to an accredited expert like the Pythia—the high priestess at the temple of Apollo in Delphi.
But as long as religious institutions like oracular temples were staffed by fallible humans, they too were open to error and corruption. Herodotus recounts that when Athens was ruled by the tyrant Hippias, the pro-democracy faction bribed the Pythia to help them. Whenever any Spartan came to the Pythia to consult the gods on either official or private matters, the Pythia invariably replied that the Spartans must first free Athens from the tyrant. The Spartans, who were Hippias’s allies, eventually submitted to the alleged will of the gods and sent an army to Athens that deposed Hippias in 510 BCE, leading to the establishment of Athenian democracy.7
If a human prophet could falsify the words of a god, then the key problem of religion wasn’t solved by creating religious institutions like temples and priestly orders. People still needed to trust fallible humans in order to access the supposedly infallible gods. Was it possible to somehow bypass the humans altogether?
THE INFALLIBLE TECHNOLOGY
Holy books like the Bible and the Quran are a technology to bypass human fallibility, and religions of the book—like Judaism, Christianity, and Islam—have been built around that technological artifact. To appreciate how this technology is meant to work, we should begin by explaining what a book is and what makes books different from other kinds of written texts. A book is a fixed block of texts—such as chapters, stories, recipes, or epistles—that always go together and have many identical copies. This makes a book something different from oral tales, from bureaucratic documents, and from archives. When telling a story orally, every time we tell the story it might be a little different, and if many people tell the story over a long time, significant variations are bound to creep in. In contrast, all copies of a book are supposed to be identical. As for bureaucratic documents, they tend to be relatively short, and often exist only as a single copy in one archive. If a long document has many copies placed in numerous archives, we would normally call it a book. Finally, a book that contains many texts is also different from an archive, because each archive contains a different collection of texts, whereas all copies of a book contain the same chapters, the same stories, or the same recipes. The book thereby ensures that many people in many times and places can access the same database.
The book became an important religious technology in the first millennium BCE. After tens of thousands of years in which gods spoke to humans via shamans, priests, prophets, oracles, and other human messengers, religious movements like Judaism began arguing that the gods speak through this novel technology of the book. There is one specific book whose many chapters allegedly contain all the divine words about everything from the creation of the universe to food regulations. Crucially, no priest, prophet, or human institution can forget or change these divine words, because you can always compare what the fallible humans are telling you with what the infallible book records.
But religions of the book had their own set of problems. Most obviously, who decides what to include in the holy book? The first copy didn’t come down from heaven. It had to be compiled by humans. Still, the faithful hoped that this thorny problem could be solved by a once-and-for-all supreme effort. If we could get together the wisest and most trustworthy humans, and they could all agree on the contents of the holy book, from that moment onward we could excise humans from the loop, and the divine words would forever be safe from human interference.
Many objections can be raised against this procedure: Who selects the wisest humans? On the basis of what criteria? What if they cannot reach a consensus? What if they later change their minds? Nevertheless, this was the procedure used to compile holy books like the Hebrew Bible.
THE MAKING OF THE HEBREW BIBLE
During the first millennium BCE, Jewish prophets, priests, and scholars produced an extensive collection of stories, documents, prophecies, poems, prayers, and chronicles. The Bible as a single holy book didn’t exist in biblical times. King David or the prophet Isaiah never saw a copy of the Bible.
It is sometimes claimed, erroneously, that the oldest surviving copy of the Bible comes from the Dead Sea Scrolls. These scrolls are a collection of about nine hundred different documents, written mostly in the last two centuries BCE and found in various caves around Qumran, a village near the Dead Sea.8 Most scholars believe they constituted the archive of a Jewish sect that lived nearby.9
Significantly, none of the scrolls contains a copy of the Bible, and no scroll indicates that the twenty-four books of the Old Testament were considered a single and complete database. Some of the scrolls certainly record texts that are today part of the canonical Bible. For example, nineteen scrolls and fragmentary manuscripts preserve parts of the book of Genesis.10 But many scrolls record texts that were later excluded from the Bible. For example, more than twenty scrolls and fragments preserve parts of the book of Enoch—a book allegedly written by the patriarch Enoch, the great-grandfather of Noah, and containing the history of the angels and demons as well as a prophecy about the coming of the Messiah.11 The Jews of Qumran apparently gave great importance to both Genesis and Enoch, and did not think that Genesis was canonical while Enoch was apocryphal.12 Indeed, to this day some Ethiopian Jewish and Christian sects consider Enoch part of their canon.13
Even the scrolls that record future canonical texts sometimes differ from the present-day canonical version. For example, the canonical text of Deuteronomy 32:8 says that God divided the nations of the earth according to “the number of the sons of Israel.” The version recorded in the Dead Sea Scrolls has “the number of the sons of God” instead, implying a rather startling notion that God has multiple sons.14 In Deuteronomy 8:6 the canonical text requires the faithful to fear God, whereas the Dead Sea version asks them to love God.15 Some variations are much more substantial than just a single word here or there. The Psalms scrolls contain several entire psalms that are missing from the canonical Bible (most notably Psalms 151, 154, 155).16
Similarly, the oldest translation of the Bible—the Greek Septuagint—completed between the third and the first centuries BCE, is different in many ways from the later canonical version.17 It includes, for example, the books of Tobit, Judith, Sirach, Maccabees, the Wisdom of Solomon, the Psalms of Solomon, and Psalm 151.18 It also has longer versions of Daniel and Esther.19 Its book of Jeremiah is 15 percent shorter than the canonical version.20 Finally, in Deuteronomy 32:8 most Septuagint manuscripts have either “sons of God” or “angels of God” rather than “sons of Israel.”21
It took centuries of hairsplitting debates among learned Jewish sages—known as rabbis—to streamline the canonical database and to decide which of the many texts in circulation would get into the Bible as the official word of Jehovah and which would be excluded. By the time of Jesus agreement was probably reached on most of the texts, but even a century later rabbis were still arguing whether the Song of Songs should be part of the canon or not. Some rabbis condemned that text as secular love poetry, while Rabbi Akiva (d. 135 CE) defended it as the divinely inspired creation of King Solomon. Akiva famously said that “the Song of Songs is the Holy of Holies.”22 By the end of the second century CE widespread consensus was apparently reached among Jewish rabbis about which texts were part of the biblical canon and which were not, but debates about this matter, and about the precise wordings, spelling, and pronunciation of each text, were not finally resolved until the Masoretic era (seventh to tenth centuries CE).23
This process of canonization decided that Genesis was the word of Jehovah, but the book of Enoch, the Life of Adam and Eve, and the Testament of Abraham were human fabrications.24 The Psalms of King David were canonized (minus psalms 151–55), but the Psalms of King Solomon were not. The book of Malachi got the seal of approval; the book of Baruch did not. Chronicles, yes; Maccabees, no.
Interestingly, some books mentioned in the Bible itself failed to get into the canon. For example, the books of Joshua and Samuel both refer to a very ancient sacred text known as the book of Jasher (Joshua 10:13, 2 Samuel 1:18). The book of Numbers refers to “the Book of the Wars of the Lord” (Numbers 21:14). And when 2 Chronicles surveys the reign of King Solomon, it concludes by saying that “the rest of the acts of Solomon, first and last, are written in the chronicles of Nathan the prophet, and in the prophecy of Ahijah the Shilonite, and in the visions of Iddo the seer” (2 Chronicles 9:29). The books of Iddo, Ahijah, and Nathan, as well as the books of Jasher and the Wars of the Lord, aren’t in the canonical Bible. Apparently, they were not excluded on purpose; they just got lost.25
After the canon was sealed, most Jews gradually forgot the role of human institutions in the messy process of compiling the Bible. Jewish Orthodoxy maintained that God personally handed down to Moses at Mount Sinai the entire first part of the Bible, the Torah. Many rabbis further argued that God created the Torah at the very dawn of time so that even biblical characters who lived before Moses—like Noah and Adam—read and studied it.26 The other parts of the Bible also came to be seen as a divinely created or divinely inspired text, totally different from ordinary human compilations. Once the holy book was sealed, it was hoped that Jews now had direct access to Jehovah’s exact words, which no fallible human or corrupt institution could erase or alter.
Anticipating the blockchain idea by two thousand years, Jews began making numerous copies of the holy code, and every Jewish community was supposed to have at least one in its synagogue or its bet midrash (house of study).27 This was meant to achieve two things. First, disseminating many copies of the holy book promised to democratize religion and place strict limits on the power of would-be human autocrats. Whereas the archives of Egyptian pharaohs and Assyrian kings empowered the unfathomable kingly bureaucracy at the expense of the masses, the Jewish holy book seemed to give power to the masses, who could now hold even the most brazen leader accountable to God’s laws.
Second, and more important, having numerous copies of the same book prevented any meddling with the text. If there were thousands of identical copies in numerous locations, any attempt to change even a single letter in the holy code could easily be exposed as a fraud. With numerous Bibles available in far-flung locations, Jews replaced human despotism with divine sovereignty. The social order was now guaranteed by the infallible technology of the book. Or so it seemed.
THE INSTITUTION STRIKES BACK
Even before the process of canonizing the Bible was completed, the biblical project had run into further difficulties. Agreeing on the precise contents of the holy book was not the only problem with this supposedly infallible technology. Another obvious problem concerned copying the text. For the holy book to work its magic, Jews needed to have many copies wherever they lived. With Jewish centers emerging not only in Palestine but also in Mesopotamia and Egypt, and with new Jewish communities extending from central Asia to the Atlantic, how to make sure that copyists working thousands of kilometers apart would not change the holy book either on purpose or by mistake?
To forestall such problems, the rabbis who canonized the Bible devised painstaking regulations for copying the holy book. For example, a scribe was not allowed to pause at certain critical moments in the copying process. When writing the name of God, the scribe “may not respond even if the king greets him. If he was about to write two or three divine names successively, he may pause between them and respond.”28 Rabbi Yishmael (second century CE) told one copyist, “You are doing Heaven’s work, and if you delete one letter or add one letter—you destroy the entire world.”29 In truth, copying errors crept in without destroying the entire world, and no two ancient Bibles were identical.30
A second and much bigger problem concerned interpretation. Even when people agree on the sanctity of a book and on its exact wording, they can still interpret the same words in different ways. The Bible says that you should not work on the Sabbath. But it doesn’t clarify what counts as “work.” Is it okay to water your field on the Sabbath? What about watering your flowerpot or herd of goats? Is it okay to read a book on the Sabbath? How about writing a book? How about tearing a piece of paper? The rabbis ruled that reading a book isn’t work, but tearing paper is work, which is why nowadays Orthodox Jews prepare a stack of already ripped toilet paper to use on the Sabbath.
The holy book also says that you should not cook a young goat in its mother’s milk (Exodus 23:19). Some people interpreted this quite literally: if you slaughter a young goat, don’t cook it in the milk of its own mother. But it’s fine to cook it in the milk of an unrelated goat, or in the milk of a cow. Other people interpreted this prohibition much more broadly to mean that meat and dairy products should never be mixed, so you are not allowed to have a milkshake after fried chicken. As unlikely as this may sound, most rabbis ruled that the second interpretation is the correct one, even though chickens don’t lactate.
More problems resulted from the fact that even if the technology of the book succeeded in limiting changes to the holy words, the world beyond the book continued to spin, and it was unclear how to relate old rules to new situations. Most biblical texts focused on the lives of Jewish shepherds and farmers in the hill country of Palestine and in the sacred city of Jerusalem. But by the second century CE, most Jews lived elsewhere. A particularly large Jewish community grew in the port of Alexandria, one of the richest metropolises of the Roman Empire. A Jewish shipping magnate living in Alexandria would have found that many of the biblical laws were irrelevant to his life while many of his pressing questions had no clear answers in the holy text. He couldn’t obey the commandments about worshipping in the Jerusalem temple, because not only did he not live near Jerusalem, but the temple didn’t even exist anymore. In contrast, when he contemplated whether it was kosher for him to sail his Rome-bound grain ships on the Sabbath, it turned out that long sea voyages were not considered by the authors of Leviticus and Deuteronomy.31
Inevitably, the holy book spawned numerous interpretations, which were far more consequential than the book itself. As Jews increasingly argued over the interpretation of the Bible, rabbis gained more power and prestige. Writing down the word of Jehovah was supposed to limit the authority of the old priestly institution, but it gave rise to the authority of a new rabbinical institution. Rabbis became the Jewish technocratic elite, developing their rational and rhetorical skills through years of philosophical debates and legal disputations. The attempt to bypass fallible human institutions by relying on a new information technology backfired, because of the need for a human institution to interpret the holy book.
When the rabbis eventually reached some consensus about how to interpret the Bible, Jews saw another chance to get rid of the fallible human institution. They imagined that if they wrote the agreed interpretation in a new holy book, and made numerous copies of it, that would eliminate the need for any further human intercession between them and the divine code. So after much back-and-forth about which rabbinical opinions should be included and which should be ignored, a new holy book was canonized in the third century CE: the Mishnah.32
As the Mishnah became more authoritative than the plain text of the Bible, Jews began to believe that the Mishnah could not possibly have been created by humans. It too must have been inspired by Jehovah, or perhaps even composed by the infallible deity in person. Today many Orthodox Jews firmly believe that the Mishnah was handed to Moses by Jehovah on Mount Sinai, passed orally from generation to generation, until it was written down in the third century CE.33
Alas, no sooner had the Mishnah been canonized and copied than Jews began arguing about the correct interpretation of the Mishnah. And when a consensus was reached about the interpretation of the Mishnah and canonized in the fifth to sixth centuries as a third holy book—the Talmud—Jews began disagreeing about the interpretation of the Talmud.34
The dream of bypassing fallible human institutions through the technology of the holy book never materialized. With each iteration, the power of the rabbinical institution only increased. “Trust the infallible book” turned into “trust the humans who interpret the book.” Judaism was shaped by the Talmud far more than by the Bible, and rabbinical arguments about the interpretation of the Talmud became even more important than the Talmud itself.35
This is inevitable, because the world keeps changing. The Mishnah and Talmud dealt with questions raised by second-century Jewish shipping magnates that had no clear answer in the Bible. Modernity too raised many new questions that have no straightforward answers in the Mishnah and Talmud. For example, when electrical appliances developed in the twentieth century, Jews struggled with numerous unprecedented questions such as whether it is okay to press the electrical buttons of an elevator on the Sabbath?
The Orthodox answer is no. As noted earlier, the Bible forbids working on the Sabbath, and rabbis argued that pressing an electrical button is “work,” because electricity is akin to fire, and it has long been established that kindling a fire is “work.” Does this mean that elderly Jews living in a Brooklyn high-rise must climb a hundred steps to their apartment in order to avoid working on the Sabbath? Well, Orthodox Jews invented a “Sabbath elevator,” which continually goes up and down buildings, stopping on every floor, without you having to perform any “work” by pressing an electrical button.36 The invention of AI gives another twist to this old story. By relying on facial recognition, an AI can quickly direct the elevator to your floor, without making you desecrate the Sabbath.37
This profusion of texts and interpretations has, over time, caused a profound change in Judaism. Originally, it was a religion of priests and temples, focused on rituals and sacrifices. In biblical times, the quintessential Jewish scene was a priest in blood-splattered robes sacrificing a lamb on the altar of Jehovah. Over the centuries, however, Judaism became an “information religion,” obsessed with texts and interpretations. From second-century Alexandria to twenty-first-century Brooklyn, the quintessential Jewish scene became a group of rabbis arguing about the interpretation of a text.
This change was extremely surprising given that almost nowhere in the Bible itself do you find anyone arguing about the interpretation of any text. Such debates were not part of biblical culture itself. For example, when Korah and his followers challenged the right of Moses to lead the people of Israel, and demanded a more equitable division of power, Moses reacted not by entering a learned discussion or by quoting some scriptural passage. Rather, Moses called upon God to perform a miracle, and the moment he finished speaking, the ground split, “and the earth opened its mouth and swallowed them and their households” (Numbers 16:31–32). When Elijah was challenged by 450 prophets of Baal and 400 prophets of Asherah to a public test in front of the people of Israel, he proved the superiority of Jehovah over Baal and Asherah first by miraculously summoning fire from the sky and then by slaughtering the pagan prophets. Nobody read any text, and nobody engaged in any rational debate (1 Kings 18).
As Judaism replaced sacrifices with texts, it gravitated toward a view of information as the most fundamental building block of reality, anticipating current ideas in physics and computer science. The flood of texts generated by rabbis was increasingly seen as more important, and even more real, than plowing a field, baking a loaf of bread, or sacrificing a lamb in a temple. After the temple in Jerusalem was destroyed by the Romans and all temple rituals ceased, rabbis nevertheless devoted enormous efforts to writing texts about the proper way to conduct temple rituals and then arguing about the correct interpretation of these texts. Centuries after the temple was no more, the amount of information concerning these virtual rituals only continued to increase. The rabbis weren’t oblivious to this seeming gap between text and reality. Rather, they maintained that writing texts about the rituals and arguing about these texts were far more important than actually performing the rituals.38 This eventually led the rabbis to believe that the entire universe was an information sphere—a realm composed of words and running on the alphabetical code of the Hebrew letters. They further maintained that this informational universe was created so that Jews could read texts and argue about their interpretation, and that if Jews ever stop reading these texts and arguing about them, the universe will cease to exist.39 In everyday life, this view meant that for the rabbis words in texts were often more important than facts in the world. Or more accurately, which words appeared in sacred texts became some of the most important facts about the world, shaping the lives of individuals and entire communities.
THE SPLIT BIBLE
The above description of the canonization of the Bible, and the creation of the Mishnah and Talmud, ignores one very important fact. The process of canonizing the word of Jehovah created not one chain of texts but several competing chains. There were people who believed in Jehovah, but not in the rabbis. Most of these dissenters did accept the first block in the biblical chain—which they called the Old Testament. But already before the rabbis sealed this block, the dissenters rejected the authority of the entire rabbinical institution, which led them to subsequently reject the Mishnah and Talmud, too. These dissenters were the Christians.
When Christianity emerged in the first century CE, it was not a unified religion, but rather a variety of Jewish movements that didn’t agree on much, except that they all regarded Jesus Christ—rather than the rabbinical institution—as the ultimate authority on Jehovah’s words.40 Christians accepted the divinity of texts like Genesis, Samuel, and Isaiah, but they argued that the rabbis misunderstood these texts, and only Jesus and his disciples knew the true meaning of passages like “the Lord himself will give you a sign: the almah will conceive and give birth to a son, and will call him Immanuel” (Isaiah 7:14). The rabbis said almah meant “young woman,” Immanuel meant “God with us” (in Hebrew immanu means “with us” and el means “God”), and the entire passage was interpreted as a divine promise to help the Jewish people in their struggle against oppressive foreign empires. In contrast, the Christians argued that almah meant “virgin,” that Immanuel meant that God will literally be born among humans, and that this was a prophecy about the divine Jesus being born on earth to the Virgin Mary.41
However, by rejecting the rabbinical institution while simultaneously accepting the possibility of new divine revelations, the Christians opened the door to chaos. In the first century CE, and even more so in the second and third centuries CE, different Christians came up with radically new interpretations for books like Genesis and Isaiah, as well as with a plethora of new messages from God. Since they rejected the authority of the rabbis, since Jesus was dead and couldn’t adjudicate between them, and since a unified Christian church didn’t yet exist, who could decide which of all these interpretations and messages was divinely inspired?
Thus, it was not just John who described the end of the world in his Apocalypse (the book of Revelation). We have many additional apocalypses from that era, for example the Apocalypse of Peter, the Apocalypse of James, and even the Apocalypse of Abraham.42 As for the life and teachings of Jesus, in addition to the four Gospels of Matthew, Mark, Luke, and John, early Christians had the Gospel of Peter, the Gospel of Mary, the Gospel of Truth, the Gospel of the Savior, and numerous others.43 Similarly, aside from the Acts of the Apostles, there were at least a dozen other Acts such as the Acts of Peter and the Acts of Andrew.44 Letters were even more prolific. Most present-day Christian Bibles contain fourteen epistles attributed to Paul, three attributed to John, two to Peter, and one each to James and Jude. Ancient Christians were familiar not only with additional Pauline letters (such as the Epistle to the Laodiceans) but with numerous other epistles supposedly written by other disciples and saints.45
As Christians composed more and more gospels, epistles, prophecies, parables, prayers, and other texts, it became harder to know which ones to pay attention to. Christians needed a curation institution. That’s how the New Testament was created. At roughly the same time that debates among Jewish rabbis were producing the Mishnah and Talmud, debates between Christian priests, bishops, and theologians were producing the New Testament. In a letter from 367 CE, Bishop Athanasius of Alexandria recommended twenty-seven texts that faithful Christians should read—a rather eclectic collection of stories, letters, and prophecies written by different people in different times and places. Athanasius recommended the Apocalypse of John, but not that of Peter or Abraham. He approved of Paul’s Epistle to the Galatians, but not of Paul’s Epistle to the Laodiceans. He endorsed the Gospels of Matthew, Mark, Luke, and John, but rejected the Gospel of Thomas and the Gospel of Truth.46
A generation later, in the Councils of Hippo (393) and Carthage (397), gatherings of bishops and theologians formally canonized this list of recommendations, which became known as the New Testament.47 When Christians talk about “the Bible,” they mean the Old Testament together with the New Testament. In contrast, Judaism never accepted the New Testament, and when Jews talk about “the Bible,” they mean only the Old Testament, which is supplemented by the Mishnah and Talmud. Interestingly, Hebrew to this day lacks a word to describe the Christian holy book, which contains both the Old Testament and the New Testament. Jewish thought sees them as two utterly unrelated books and simply refuses to acknowledge that there might be a single book encompassing both, even though it is probably the most common book in the world.
It is crucial to note that the people who created the New Testament weren’t the authors of the twenty-seven texts it contains; they were the curators. Due to the paucity of evidence from the period, we do not know if Athanasius’s list of texts reflected his personal judgment, or whether it originated with earlier Christian thinkers. What we do know is that prior to the Councils of Hippo and Carthage there were rival recommendation lists for Christians. The earliest such list was codified by Marcion of Sinope in the middle of the second century. The Marcion canon included only the Gospel of Luke and ten epistles of Paul. Even these eleven texts were somewhat different from the versions later canonized at Hippo and Carthage. Either Marcion was unaware of other texts like the Gospel of John and the book of Revelation, or he did not think highly of them.48
The church father Saint John Chrysostom, a contemporary of Bishop Athanasius’s, recommended only twenty-two books, leaving 2 Peter, 2 John, 3 John, Jude, and Revelation out of his list.49 Some Christian churches in the Middle East to this day follow Chrysostom’s shorter list.50 The Armenian Church took about a thousand years to make up its mind about the book of Revelation, while it included in its canon the Third Epistle to the Corinthians, which other churches—like the Catholic and Protestant churches—consider a forgery.51 The Ethiopian Church endorsed Athanasius’s list in full, but added four other books: Sinodos, the book of Clement, the book of the Covenant, and the Didascalia.52 Other lists endorsed the two epistles of Clement, the visions of the Shepherd of Hermas, the Epistle of Barnabas, the Apocalypse of Peter, and various other texts that didn’t make it into Athanasius’s selection.53
We do not know the precise reasons why specific texts were endorsed or rejected by different churches, church councils, and church fathers. But the consequences were far-reaching. While churches made decisions about texts, the texts themselves shaped the churches. As a key example, consider the role of women in the church. Some early Christian leaders saw women as intellectually and ethically inferior to men, and argued that women should be restricted to subordinate roles in society and in the Christian community. These views were reflected in texts like the First Epistle to Timothy.
In one of its passages, this text, attributed to Saint Paul, says, “A woman should learn in quietness and full submission. I do not permit a woman to teach or to assume authority over a man; she must be quiet. For Adam was formed first, then Eve. And Adam was not the one deceived; it was the woman who was deceived and became a sinner. But women will be saved through childbearing—if they continue in faith, love and holiness with propriety” (2:11–15). But modern scholars as well as some ancient Christian leaders like Marcion have considered this letter a second-century forgery, ascribed to Saint Paul but actually written by someone else.54
In opposition to 1 Timothy, during the second, third, and fourth centuries CE there were important Christian texts that saw women as equal to men, and even authorized women to occupy leadership roles, like the Gospel of Mary55 or the Acts of Paul and Thecla. The latter text was written at about the same time as 1 Timothy, and for a time was extremely popular.56 It narrates the adventures of Saint Paul and his female disciple Thecla, describing how Thecla not only performed numerous miracles but also baptized herself with her own hands and often preached. For centuries, Thecla was one of the most revered Christian saints and was seen as evidence that women could baptize, preach, and lead Christian communities.57
Before the Councils of Hippo and Carthage, it wasn’t clear that 1 Timothy was more authoritative than the Acts of Paul and Thecla. By choosing to include 1 Timothy in their recommendation list while rejecting the Acts of Paul and Thecla, the assembled bishops and theologians shaped Christian attitudes toward women down to the present day. We can only hypothesize what Christianity might have looked like if the New Testament had included the Acts of Paul and Thecla instead of 1 Timothy. Perhaps in addition to church fathers like Athanasius, the church would have had mothers, while misogyny would have been labeled a dangerous heresy perverting Jesus’s message of universal love.
Just as most Jews forgot that rabbis curated the Old Testament, so most Christians forgot that church councils curated the New Testament, and came to view it simply as the infallible word of God. But while the holy book was seen as the ultimate source of authority, the process of curating the book placed real power in the hands of the curating institution. In Judaism the canonization of the Old Testament and Mishnah went hand in hand with creating the institution of the rabbinate. In Christianity the canonization of the New Testament went hand in hand with the creation of a unified Christian church. Christians trusted church officials—like Bishop Athanasius—because of what they read in the New Testament, but they had faith in the New Testament because this is what the bishops told them to read. The attempt to invest all authority in an infallible superhuman technology led to the rise of a new and extremely powerful human institution—the church.
THE ECHO CHAMBER
As time passed, problems of interpretation increasingly tilted the balance of power between the holy book and the church in favor of the institution. Just as the need to interpret Jewish holy books empowered the rabbinate, so the need to interpret Christian holy books empowered the church. The same saying of Jesus or the same Pauline epistle could be understood in various ways, and it was the institution that decided which reading was correct. The institution in turn was repeatedly shaken by struggles over the authority to interpret the holy book, which resulted in institutional schisms such as that between the Western Catholic Church and the Eastern Orthodox Church.
All Christians read the Sermon on the Mount in the Gospel of Matthew and learned that we should love our enemies, that we should turn the other cheek, and that the meek shall inherit the earth. But what did that actually mean? Christians could read this as a call to reject all use of military force,58 or to reject all social hierarchies.59 The Catholic Church, however, viewed such pacifists and egalitarian readings as heresies. It interpreted Jesus’s words in a way that allowed the church to become the richest landowner in Europe, to launch violent crusades, and to establish murderous inquisitions. Catholic theology accepted that Jesus told us to love our enemies, but explained that burning heretics was an act of love, because it deterred additional people from adopting heretical views, thereby saving them from the flames of hell. The French inquisitor Jacques Fournier wrote in the early fourteenth century an entire treatise on the Sermon on the Mount that explained how the text provided justification for hunting heretics.60 Fournier’s view was not a fringe notion. He went on to become Pope Benedict XII (1334–42).
Fournier’s task as inquisitor, and later as pope, was to ensure that the Catholic Church’s interpretation of the holy book would prevail. In this, Fournier and his fellow churchmen used not only violent coercion but also their control of book production. Prior to the advent of letterpress printing in Europe in the fifteenth century, making many copies of a book was a prohibitive enterprise for all but the most wealthy individuals and institutions. The Catholic Church used its power and wealth to disseminate copies of its favored texts while prohibiting the production and spread of what it considered erroneous ones.
Of course, the church couldn’t prevent the occasional freethinker from formulating heretical ideas. But because it controlled key nodes in the medieval information network—such as copying workshops, archives, and libraries—it could prevent such a heretic from making and distributing a hundred copies of her book. To get an idea of the difficulties faced by a heretical author seeking to disseminate her views, consider that when Leofric was made bishop of Exeter in 1050, he found just five books in the cathedral’s library. He immediately established a copying workshop in the cathedral, but in the twenty-two years before he died in 1072, his copyists produced only sixty-six additional volumes.61 In the thirteenth century the library of Oxford University consisted of a few books kept in a chest under St. Mary’s Church. In 1424 the library of Cambridge University boasted a grand total of only 122 books.62 An Oxford University decree from 1409 stipulated that “all recent texts” studied at the university must be unanimously approved “by a panel of twelve theologians appointed by the archbishop.”63
The church sought to lock society inside an echo chamber, allowing the spread only of those books that supported it, and people trusted the church because almost all the books supported it. Even illiterate laypersons who didn’t read books were still awed by recitations of these precious texts or expositions on their content. That’s how the belief in a supposedly infallible superhuman technology like the New Testament led to the rise of an extremely powerful but fallible human institution like the Catholic Church that crushed all opposing views as “erroneous” while allowing no one to question its own views.
Catholic information experts such as Jacques Fournier spent their days reading Thomas Aquinas’s interpretation of Augustine’s interpretation of Saint Paul’s epistles and composing additional interpretations of their own. All those interrelated texts didn’t represent reality; they created a new information sphere even bigger and more powerful than that created by the Jewish rabbis. Medieval Europeans were cocooned inside that information sphere, their daily activities, thoughts, and emotions shaped by texts about texts about texts.
PRINT, SCIENCE, AND WITCHES
The attempt to bypass human fallibility by investing authority in an infallible text never succeeded. If anyone thought this was due to some unique flaw of the Jewish rabbis or the Catholic priests, the Protestant Reformation repeated the experiment again and again—always getting the same results. Luther, Calvin, and their successors argued that there was no need for any fallible human institution to interpose itself between ordinary people and the holy book. Christians should abandon all the parasitical bureaucracies that grew around the Bible and reconnect to the original word of God. But the word of God never interpreted itself, which is why not only Lutherans and Calvinists but numerous other Protestant sects eventually established their own church institutions and invested them with the authority to interpret the text and persecute heretics.64
If infallible texts merely lead to the rise of fallible and oppressive churches, how then to deal with the problem of human error? The naive view of information posits that the problem can be solved by creating the opposite of a church—namely, a free market of information. The naive view expects that if all restrictions on the free flow of information are removed, error will inevitably be exposed and displaced by truth. As noted in the prologue, this is wishful thinking. Let’s delve a little deeper to understand why. As a test case, consider what happened during one of the most celebrated epochs in the history of information networks: the European print revolution. The introduction of the printing press to Europe in the mid-fifteenth century made it possible to mass-produce texts relatively quickly, cheaply, and secretly, even if the Catholic Church disapproved of them. It is estimated that in the forty-six years from 1454 to 1500 more than twelve million volumes were printed in Europe. By contrast, in the previous thousand years only about eleven million volumes were hand copied.65 By 1600, all kinds of fringe people—heretics, revolutionaries, proto-scientists—could disseminate their writings much more rapidly, widely, and easily than ever before.
In the history of information networks, the print revolution of early modern Europe is usually hailed as a moment of triumph, breaking the stranglehold that the Catholic Church had maintained over the European information network. Allegedly, by allowing people to exchange information much more freely than before, it led to the scientific revolution. There is a grain of truth in this. Without print, it would certainly have been much harder for Copernicus, Galileo, and their colleagues to develop and spread their ideas.
But print wasn’t the root cause of the scientific revolution. The only thing the printing press did was to faithfully reproduce texts. The machine had no ability to come up with any new ideas of its own. Those who connect print to science assume that the mere act of producing and spreading more information inevitably leads people to the truth. In fact, print allowed the rapid spread not only of scientific facts but also of religious fantasies, fake news, and conspiracy theories. Perhaps the most notorious example of the latter was the belief in a worldwide conspiracy of satanic witches, which led to the witch-hunt craze that engulfed early modern Europe.66
Belief in magic and in witches has characterized human societies in all continents and eras, but different societies imagined witches and reacted to them in very different ways. Some societies believed that witches controlled spirits, talked with the dead, and predicted the future; others imagined that witches stole cattle and located hidden treasure. In one community witches were thought to cause disease, blight cornfields, and concoct love potions, while in another community they supposedly entered houses at night, performed household chores, and stole milk. In some locales witches were thought to be mostly female, while in others they were generally imagined to be male. Some cultures were terrified of witches and persecuted them violently, but others tolerated or even honored them. Finally, there were societies in every continent and era that gave witches little importance.67
For most of the Middle Ages, most European societies belonged to the latter category and were not overly concerned about witches. The medieval Catholic Church didn’t see them as a major threat to humanity, and some churchmen actively discouraged witch-hunting. According to the influential tenth-century text Canon Episcopi—which defined medieval church doctrine on the matter—witchcraft was mostly illusion, and belief in the reality of witchcraft was an unchristian superstition.68 The European witch-hunt craze was a modern rather than a medieval phenomenon.
In the 1420s and 1430s churchmen and scholars operating mainly in the Alps region took elements from Christian religion, local folklore, and Greco-Roman heritage and amalgamated them into a new theory of witchcraft.69 Previously, even when witches were dreaded, they were considered a strictly local problem—isolated criminals who, inspired by personal malevolence, used magical means to commit theft and murder. In contrast, the new scholarly model argued that witches were a far more formidable threat to society. There was allegedly a global conspiracy of witches, led by Satan, which constituted an institutionalized anti-Christian religion. Its purpose was nothing less than the complete destruction of the social order and of humankind. Witches were said to gather at night in huge demonic assemblies, where they worshipped Satan, killed children, ate human flesh, engaged in orgies, and cast spells that caused storms, epidemics, and other catastrophes.
Inspired by such ideas, the first mass witch hunts and witch trials were led by local churchmen and noblemen in the Valais region of the western Alps between 1428 and 1436, leading to the execution of more than two hundred supposed male and female witches. From this Alpine heartland, rumors about the global witch conspiracy trickled to other parts of Europe, but the belief was still far from mainstream, the Catholic establishment did not embrace it, and other regions didn’t launch large-scale witch hunts like those in the Valais.
In 1485, a Dominican friar and inquisitor called Heinrich Kramer embarked on a witch-hunting expedition in another Alpine region—the Austrian Tyrol. Kramer was a fervent convert to the new belief in a global satanic conspiracy.70 He also seems to have been mentally unhinged, and his accusations of satanic witchcraft were colored by rabid misogyny and odd sexual fixations. Local church authorities, led by the bishop of Brixen, were skeptical of Kramer’s accusations and alarmed by his activities. They stopped his inquisition, released the suspects he arrested, and expelled him from the area.71
Kramer hit back through the printing press. Within two years of his banishment, he compiled and published the Malleus Maleficarum—The Hammer of the Witches. This was a do-it-yourself guidebook to exposing and killing witches in which Kramer described in detail the worldwide conspiracy and the means by which honest Christians could uncover and foil the witches. In particular, he recommended the use of horrific methods of torture in order to extract confessions from people suspected of witchcraft, and was adamant that the only punishment for the guilty was execution.
Kramer organized and codified previous ideas and stories and added many details from his own fertile and hate-filled imagination. Relying on ancient Christian misogynist teachings like those of 1 Timothy, Kramer sexualized witchcraft. He argued that witches were typically female, because witchcraft originated in lust, which was supposedly stronger in women. He warned readers that sex could cause a pious woman to become a witch and her husband to become bewitched.72
An entire chapter of the Hammer is dedicated to the ability of witches to steal men’s penises. Kramer discusses at length whether the witches are really able to take away the male member from its owner, or whether they are only able to create an illusion of castration in men’s minds. Kramer asks, “What is to be thought of those witches who in this way sometimes collect male organs in great numbers, as many as twenty or thirty members together, and put them in a bird’s nest, or shut them up in a box, where they move themselves like living members, and eat oats and corn, as has been seen by many?” He then relates a story he heard from one man: “When he had lost his member, he approached a known witch to ask her to restore it to him. She told the afflicted man to climb a certain tree, and that he might take which he liked out of the nest in which there were several members. And when he tried to take a big one, the witch said: You must not take that one; adding, because it belongs to a parish priest.”73 Numerous notions about witches that are still popular today—for instance, that witches are predominantly women, that witches engage in wild sexual activities, and that witches kill and mutilate children—were given their canonical form by Kramer’s book.
Like the bishop of Brixen, other churchmen were initially skeptical of Kramer’s wild ideas, and there was some resistance to the book among church experts.74 But The Hammer of the Witches became one of the biggest best sellers of early modern Europe. It catered to people’s deepest fears, as well as to their lurid interest in hearing about orgies, cannibalism, child murders, and satanic conspiracies. The book had gone through eight editions by 1500, another five by 1520, and sixteen more by 1670, with many vernacular translations.75 It became the definitive work on witchcraft and witch-hunting and inspired a host of imitations and elaborations. As Kramer’s fame grew, his work was embraced by the church experts. Kramer was appointed papal representative and made inquisitor of Bohemia and Moravia in 1500. Even today his ideas continue to shape the world, and many current theories about a global satanic conspiracy—like QAnon—draw upon and perpetuate his fantasies.
While it would be an exaggeration to argue that the invention of print caused the European witch-hunt craze, the printing press played a pivotal role in the rapid dissemination of the belief in a global satanic conspiracy. As Kramer’s ideas gained popularity, printing presses produced not only many additional copies of The Hammer of the Witches and copycat books but also a torrent of cheap one-page pamphlets, whose sensational texts were often accompanied by illustrations depicting people attacked by demons or witches burned at the stake.76 These publications also gave fantastic statistics about the size of the witches’ conspiracy. For example, the Burgundian judge and witch-hunter Henri Boguet (1550–1619) speculated that there were 300,000 witches in France alone and 1.8 million in all of Europe.77 Such claims fueled mass hysteria, which in the sixteenth and seventeenth centuries led to the torture and execution of between 40,000 and 50,000 innocent people who were accused of witchcraft.78 The victims included individuals from all walks of life and ages, including children as young as five.79
People began denouncing one another for witchcraft on the flimsiest evidence, often to avenge personal slights or to gain economic and political advantage. Once an official investigation began, the accused were often doomed. The inquisitorial methods recommended by The Hammerof the Witches were truly diabolical. If the accused confessed to being a witch, they were executed and their property divided between the accuser, the executioner, and the inquisitors. If the accused refused to confess, this was taken as evidence of their demonic obstinacy, and they were then tortured in horrendous ways, their fingers broken, their flesh cut with hot pincers, their bodies stretched to the breaking point or submerged in boiling water. Sooner or later they could stand it no longer and confessed—and were duly executed.80
To take one example, in 1600 authorities in Munich arrested on suspicion of witchcraft the Pappenheimer family—father Paulus, mother Anna, two grown sons, and a ten-year-old boy, Hansel. The inquisitors began by torturing little Hansel. The protocol of the interrogation, which can still be read in the Munich archives, has a note from one of the interrogators regarding the ten-year-old boy: “May be tortured to the limit so that he incriminates his mother.”81 After being tortured in unspeakable ways, the Pappenheimers confessed to numerous crimes including killing 265 people by sorcery and causing fourteen destructive storms. They were all condemned to death.
The bodies of each of the four adult family members were torn with red-hot pincers, the men’s limbs were broken on the wheel, the father was impaled on a stake, the mother’s breasts were cut off, and all were then burned alive. The ten-year-old Hansel was forced to watch all this. Four months later, he too was executed.82 The witch-hunters were extremely thorough in their search for the devil and his accomplices. But if the witch-hunters really wanted to find diabolical evil, they just had to look in the mirror.
THE SPANISH INQUISITION TO THE RESCUE
Witch hunts seldom ended by killing just one person or one family. Since the underlying model postulated a global conspiracy, people accused of witchcraft were tortured to name accomplices. This was then used as evidence to imprison, torture, and execute others. If any officials, scholars, or churchmen voiced objections to these absurd methods, this could be seen as proof that they too must be witches—which led to their own arrest and torture.
For example, in 1453—when belief in the satanic conspiracy was just beginning to take hold—a French doctor of theology called Guillaume Edelin bravely sought to quash it before it spread. He repeated the claims of the medieval Canon Episcopi that witchcraft was an illusion and that witches couldn’t really fly at night to meet Satan and make a pact with him. Edelin was then himself accused of being a witch and arrested. Under torture he confessed that he personally had flown on a broomstick and signed a pact with the devil and that it was Satan who commissioned him to preach that witchcraft was an illusion. His judges were lenient with him; he was spared execution and got life imprisonment instead.83
The witch hunts illustrate the dark side of creating an information sphere. As with rabbinical discussions of the Talmud and scholastic discussions of Christian scriptures, the witch hunts were fueled by an expanding ocean of information that instead of representing reality created a new reality. Witches were not an objective reality. Nobody in early modern Europe had sex with Satan or was capable of flying on broomsticks and creating hailstorms. But witches became an intersubjective reality. Like money, witches were made real by exchanging information about witches.
An entire witch-hunting bureaucracy dedicated itself to such exchanges. Theologians, lawyers, inquisitors, and the owners of printing presses made a living by collecting and producing information about witches, cataloging different species of witches, investigating how witches behaved, and recommending how they could be exposed and defeated. Professional witch-hunters offered their services to governments and municipalities, charging large sums of money. Archives were filled by detailed reports of witch-hunting expeditions, protocols of witch trials, and lengthy confessions extracted from the alleged witches.
Expert witch-hunters used all that data to refine their theories further. Like scholars arguing about the correct interpretation of scripture, the witch-hunters debated the correct interpretation of The Hammer of the Witches and other influential books. The witch-hunting bureaucracy did what bureaucracy often does: it invented the intersubjective category of “witches” and imposed it on reality. It even printed forms, with standard accusations and confessions of witchcraft and blank spaces left for dates, names, and the signature of the accused. All that information produced a lot of order and power; it was a means for certain people to gain authority and for society as a whole to discipline its members. But it produced zero truth and zero wisdom.
As the witch-hunting bureaucracy generated more and more information, it became harder to dismiss all that information as pure fantasy. Could it be that the entire silo of witch-hunting data did not contain a single grain of truth in it? What about all the books written by learned churchmen? What about all the protocols of trials conducted by esteemed judges? What about the tens of thousands of documented confessions?
The new intersubjective reality was so convincing that even some people accused of witchcraft came to believe that they were indeed part of a worldwide satanic conspiracy. If everybody said so, it must be true. As discussed in chapter 2, humans are susceptible to adopting fake memories. At least some early modern Europeans dreamed or fantasized about summoning devils, having sex with Satan, and practicing witchcraft, and when accused of being witches, they confused their dreams and fantasies with reality.84
Consequently, even as the witch hunts reached their ghastly crescendo in the early seventeenth century, and many people suspected that something was clearly wrong, it was difficult to reject the whole thing as pure fantasy. One of the worst witch-hunting episodes in early modern Europe occurred in the towns of Bamberg and Würzburg in southern Germany in the late 1620s. In Bamberg, a city of fewer than 12,000 at the time,85 up to 900 innocent people were executed from 1625 to 1631.86 In Würzburg another 1,200 people were tortured and killed, out of a population of around 11,500.87 In August 1629, the chancellor of the prince-bishop of Würzburg wrote a letter to a friend about the ongoing witch hunt, in which he confessed his doubts about the matter. The letter is worth quoting at length:
As to the affair of the witches … it has started up afresh, and no words can do justice to it. Ah, the woe and the misery of it—there are still four hundred in the city, high and low, of every rank and sex, nay, even clerics, so strongly accused that they may be arrested at any hour.… The Prince-Bishop has over forty students who are soon to be pastors; among them thirteen or fourteen are said to be witches. A few days ago a Dean was arrested; two others who were summoned have fled. The notary of our Church consistory, a very learned man, was yesterday arrested and put to the torture. In a word, a third part of the city is surely involved. The richest, most attractive, most prominent, of the clergy are already executed. A week ago a maiden of nineteen was executed, of whom it is everywhere said that she was the fairest in the whole city, and was held by everybody a girl of singular modesty and purity. She will be followed by seven or eight others of the best and most attractive persons.… And thus many are put to death for renouncing God and being at the witch-dances, against whom nobody has ever else spoken a word.
To conclude this wretched matter, there are children of three and four years, to the number of three hundred, who are said to have had intercourse with the Devil. I have seen put to death children of seven, promising students of ten, twelve, fourteen, and fifteen.… [B]ut I cannot and must not write more of this misery.
The chancellor then added this interesting postscript to the letter:
Though there are many wonderful and terrible things happening, it is beyond doubt that, at a place called the Fraw-Rengberg, the Devil in person, with eight thousand of his followers, held an assembly and celebrated mass before them all, administering to his audience (that is, the witches) turnip-rinds and parings in place of the Holy Eucharist. There took place not only foul but most horrible and hideous blasphemies, whereof I shudder to write.88
Even after expressing his horror at the insanity of the witch hunt in Würzburg, the chancellor nevertheless expressed his firm belief in the satanic conspiracy of witches. He didn’t witness any witchcraft firsthand, but so much information about witches was circulating that it was difficult for him to doubt all of it. Witch hunts were a catastrophe caused by the spread of toxic information. They are a prime example of a problem that was created by information, and was made worse by more information.
This was a conclusion reached not just by modern scholars but also by some perceptive observers at the time. Alonso de Salazar Frías, a Spanish inquisitor, made a thorough investigation of witch hunts and witch trials in the early seventeenth century. He concluded that “I have not found one single proof nor even the slightest indication from which to infer that one act of witchcraft has actually taken place,” and that “there were neither witches nor bewitched until they were talked and written about.”89 Salazar Frías well understood the meaning of intersubjective realities and correctly identified the entire witch-hunting industry as an intersubjective information sphere.
The history of the early modern European witch craze demonstrates that releasing barriers to the flow of information doesn’t necessarily lead to the discovery and spread of truth. It can just as easily lead to the spread of lies and fantasies and to the creation of toxic information spheres. More specifically, a completely free market of ideas may incentivize the dissemination of outrage and sensationalism at the expense of truth. It is not difficult to understand why. Printers and booksellers made a lot more money from the lurid tales of The Hammer of the Witches than they did from the dull mathematics of Copernicus’s On the Revolutions of the Heavenly Spheres. The latter was one of the founding texts of the modern scientific tradition. It is credited with earth-shattering discoveries that displaced our planet from the center of the universe and thereby initiated the Copernican revolution. But when it was first published in 1543, its initial print run of four hundred failed to sell out, and it took until 1566 for a second edition to be published in a similar-sized print run. The third edition did not appear until 1617. As Arthur Koestler quipped, it was an all-time worst seller.90 What really got the scientific revolution going was neither the printing press nor a completely free market of information, but rather a novel approach to the problem of human fallibility.
THE DISCOVERY OF IGNORANCE
The history of print and witch-hunting indicates that an unregulated information market doesn’t necessarily lead people to identify and correct their errors, because it may well prioritize outrage over truth. For truth to win, it is necessary to establish curation institutions that have the power to tilt the balance in favor of the facts. However, as the history of the Catholic Church indicates, such institutions might use their curation power to quash any criticism of themselves, labeling all alternative views erroneous and preventing the institution’s own errors from being exposed and corrected. Is it possible to establish better curation institutions that use their power to further the pursuit of truth rather than to accumulate more power for themselves?
Early modern Europe saw the foundation of exactly such curation institutions, and it was these institutions—rather than the printing press or specific books like On the Revolutions of the Heavenly Spheres—that constituted the bedrock of the scientific revolution. These key curation institutions were not the universities. Many of the most important leaders of the scientific revolution were not university professors. Nicolaus Copernicus, Robert Boyle, Tycho Brahe, and René Descartes, for example, held no academic positions. Nor did Spinoza, Leibniz, Locke, Berkeley, Voltaire, Diderot, or Rousseau.
The curation institutions that played a central role in the scientific revolution connected scholars and researchers both in and out of universities, forging an information network that spanned the whole of Europe and eventually the world. For the scientific revolution to gather pace, scientists had to trust information published by colleagues in distant lands. This kind of trust in the work of people whom one had never met was evident in scientific associations like the Royal Society of London for Improving Natural Knowledge, founded in 1660, and the French Académie des Sciences (1666); scientific journals like the Philosophical Transactions of the Royal Society (1665) and the Histoire de l’Académie Royale des Sciences (1699); and scientific publishers like the architects of the Encyclopédie (1751–72). These institutions curated information on the basis of empirical evidence, bringing attention to the discoveries of Copernicus rather than to the fantasies of Kramer. When a paper was submitted to the Philosophical Transactions of the Royal Society, the lead question the editors asked was not, “How many people would pay to read this?” but, “What proof is there that it is true?”
At first, these new institutions seemed as flimsy as cobwebs, lacking the power necessary to reshape human society. Unlike the witch-hunting experts, the editors of the Philosophical Transactions of the Royal Society could not torture and execute anyone. And unlike the Catholic Church, the Académie des Sciences did not command huge territories and budgets. But scientific institutions did accrue influence thanks to a very original claim to trust. A church typically told people to trust it because it possessed the absolute truth, in the form of an infallible holy book. A scientific institution, in contrast, gained authority because it had strong self-correcting mechanisms that exposed and rectified the errors of the institution itself. It was these self-correcting mechanisms, not the technology of printing, that were the engine of the scientific revolution.
In other words, the scientific revolution was launched by the discovery of ignorance.91 Religions of the book assumed that they had access to an infallible source of knowledge. The Christians had the Bible, the Muslims had the Quran, the Hindus had the Vedas, and the Buddhists had the Tipitaka. Scientific culture has no comparable holy book, nor does it claim that any of its heroes are infallible prophets, saints, or geniuses. The scientific project starts by rejecting the fantasy of infallibility and proceeding to construct an information network that takes error to be inescapable. Sure, there is much talk about the genius of Copernicus, Darwin, and Einstein, but none of them is considered faultless. They all made mistakes, and even the most celebrated scientific tracts are sure to contain errors and lacunae.
Since even geniuses suffer from confirmation bias, you cannot trust them to correct their own errors. Science is a team effort, relying on institutional collaboration rather than on individual scientists or, say, a single infallible book. Of course, institutions too are prone to error. Scientific institutions are nevertheless different from religious institutions, inasmuch as they reward skepticism and innovation rather than conformity. Scientific institutions are also different from conspiracy theories, inasmuch as they reward self-skepticism. Conspiracy theorists tend to be extremely skeptical regarding the existing consensus, but when it comes to their own beliefs, they lose all their skepticism and fall prey to confirmation bias.92 The trademark of science is not merely skepticism but self-skepticism, and at the heart of every scientific institution we find a strong self-correcting mechanism. Scientific institutions do reach a broad consensus about the accuracy of certain theories—such as quantum mechanics or the theory of evolution—but only because these theories have managed to survive intense efforts to disprove them, launched not only by outsiders but by members of the institution itself.
SELF-CORRECTING MECHANISMS
As an information technology, the self-correcting mechanism is the polar opposite of the holy book. The holy book is supposed to be infallible. The self-correcting mechanism embraces fallibility. By self-correcting, I refer to mechanisms that an entity uses to correct itself. A teacher correcting a student’s essay is not a self-correcting mechanism; the student isn’t correcting their own essay. A judge sending a criminal to prison is not a self-correcting mechanism; the criminal isn’t exposing their own crime. When the Allies defeated and dismantled the Nazi regime, this was not a self-correcting mechanism; left to its own devices, Germany would not have denazified itself. But when a scientific journal publishes a paper correcting a mistake that appeared in a previous paper, that’s an example of an institution self-correcting its own errors.
Self-correcting mechanisms are ubiquitous in nature. Children learn how to walk thanks to them. You make a wrong move, you fall, you learn from your mistake, you try doing it a little differently. Sure, sometimes parents and teachers give the child a hand or offer advice, but a child who relies entirely on such external corrections or keeps excusing mistakes instead of learning from them will find it very difficult to walk. Indeed, even as adults, every time we walk, our body engages in an intricate process of self-correction. As our body navigates through space, internal feedback loops between brain, limbs, and sensory organs keep our legs and hands in their proper place and our balance just right.93
Many other bodily processes require constant self-correction. Our blood pressure, temperature, sugar levels, and numerous other parameters must be given some leeway to change in accordance with varying circumstances, but they should never go above or below certain critical thresholds. Our blood pressure needs to increase when we run, to decrease when we sleep, but must always keep within certain bounds.94 Our body manages this delicate biochemical dance through a host of homeostatic self-correcting mechanisms. If our blood pressure goes too high, the self-correcting mechanisms lower it. If our blood pressure is dangerously low, the self-correcting mechanisms raise it. If the self-correcting mechanisms go out of order, we could die.95
Institutions, too, die without self-correcting mechanisms. These mechanisms start with the realization that humans are fallible and corruptible. But instead of despairing of humans and looking for a way to bypass them, the institution actively seeks its own errors and corrects them. All institutions that manage to endure beyond a handful of years possess such mechanisms, but institutions differ greatly in the strength and visibility of their self-correcting mechanisms.
For example, the Catholic Church is an institution with relatively weak self-correcting mechanisms. Since it claims infallibility, it cannot admit institutional mistakes. It is occasionally willing to acknowledge that some of its members have erred or sinned, but the institution itself allegedly remains perfect. For example, in the Second Vatican Council in 1964, the Catholic Church acknowledged that “Christ summons the Church to continual reformation as she sojourns here on earth. The Church is always in need of this, insofar as she is an institution of men here on earth. Thus if, in various times and circumstances, there have been deficiencies in moral conduct or in church discipline, or even in the way that church teaching has been formulated—to be carefully distinguished from the deposit of faith itself—these can and should be set right at the opportune moment.”96
This admission sounds promising, but the devil is in the details, specifically in the refusal to countenance the possibility of any deficiency in “the deposit of faith.” In Catholic dogma “the deposit of faith” refers to the body of revealed truth that the church has received from scriptures and from its sacred tradition of interpreting scripture. The Catholic Church acknowledges that priests are fallible humans who can sin and can also make mistakes in the way they formulate church teachings. However, the holy book itself can never err. What does this imply about the entire church as an institution that combines fallible humans with an infallible text?
According to Catholic dogma, biblical infallibility and divine guidance trump human corruption, so even though individual members of the church may err and sin, the Catholic Church as an institution is never wrong. Allegedly, never in history did God allow the majority of church leaders to make a serious mistake in their interpretation of the holy book. This principle is common to many religions. Jewish Orthodoxy accepted the possibility that the rabbis who composed the Mishnah and Talmud might have erred in personal matters, but when they came to decree religious doctrine, God ensured that they would make no mistake.97 In Islam there is an analogous principle known as Ijma. According to one important Hadith, Muhammad said that “Allah will ensure my community will never agree on error.”98
In Catholicism, alleged institutional perfection is enshrined most clearly in the doctrine of papal infallibility, which says that while in personal matters popes may err, in their institutional role they are infallible.99 For example, Pope Alexander VI erred in breaking his vow of celibacy, having a mistress and siring several children, yet when defining official church teachings on matters of ethics or theology, he was incapable of mistake.
In line with these views, the Catholic Church has always employed a self-correcting mechanism to supervise its human members in their personal affairs, but it never developed a mechanism for amending the Bible or for amending its “deposit of faith.” This attitude is manifest in the few formal apologies the Catholic Church issued for its past conduct. In recent decades, several popes apologized for the mistreatment of Jews, women, non-Catholic Christians, and indigenous cultures, as well as for more specific events such as the sacking of Constantinople in 1204 and the abuse of children in Catholic schools. It is commendable that the Catholic Church made such apologies at all; religious institutions rarely do so. Nevertheless, in all these cases, the popes were careful to shift responsibility away from scriptures and from the church as an institution. Instead, the blame was laid on the shoulders of individual churchmen who misinterpreted scriptures and deviated from the true teachings of the church.
For example, in March 2000, Pope John Paul II conducted a special ceremony in which he asked forgiveness for a long list of historical crimes against Jews, heretics, women, and indigenous people. He apologized “for the use of violence that some have committed in the service of truth.” This terminology implied that the violence was the fault of “some” misguided individuals who didn’t understand the truth taught by the church. The pope didn’t accept the possibility that perhaps these individuals understood exactly what the church was teaching and that these teachings just were not the truth.100
Similarly, when Pope Francis apologized in 2022 for the abuses against indigenous people in Canada’s church-run residential schools, he said, “I ask for forgiveness, in particular, for the ways in which many members of the church … cooperated … in projects of cultural destruction and forced assimilation.”101 Note his careful shifting of responsibility. The fault lay with “many members of the church,” not with the church and its teachings. As if it were never official church doctrine to destroy indigenous cultures and forcefully convert people.
In fact, it wasn’t a few wayward priests who launched the Crusades, imposed laws that discriminated against Jews and women, or orchestrated the systematic annihilation of indigenous religions throughout the world.102 The writings of many revered church fathers, and the official decrees of many popes and church councils, are full of passages disparaging “pagan” and “heretical” religions, calling for their destruction, discriminating against their members, and legitimizing the use of violence to convert people to Christianity.103 For example, in 1452 Pope Nicholas V issued the Dum Diversas bull, addressed to King Afonso V of Portugal and other Catholic monarchs. The bull said, “We grant you by these present documents, with our Apostolic Authority, full and free permission to invade, search out, capture, and subjugate the Saracens and pagans and any other unbelievers and enemies of Christ wherever they may be, as well as their kingdoms, duchies, counties, principalities, and other property … and to reduce their persons into perpetual servitude.”104 This official proclamation, repeated numerous times by subsequent popes, laid the theological basis for European imperialism and the destruction of native cultures across the world. Of course, though the church doesn’t acknowledge it officially, over time it has changed its institutional structures, its core teachings, and its interpretation of scripture. The Catholic Church of today is far less antisemitic and misogynist than it was in medieval and early modern times. Pope Francis is far more tolerant of indigenous cultures than Pope Nicholas V. There is an institutional self-correcting mechanism at work here, which reacts both to external pressures and to internal soul-searching. But what characterizes self-correcting in institutions like the Catholic Church is that even when it happens, it is denied rather than celebrated. The first rule of changing church teachings is that you never admit changing church teachings.
You would never hear a pope announcing to the world, “Our experts have just discovered a really big error in the Bible. We’ll soon issue an updated edition.” Instead, when asked about the church’s more generous attitude to Jews or women, popes imply that this was always what the church really taught, even if some individual churchmen previously failed to understand the message correctly. Denying the existence of self-correction doesn’t entirely stop it from happening, but it does weaken and slow it. Because the correction of past mistakes is not acknowledged, let alone celebrated, when the faithful encounter another serious problem in the institution and its teachings, they are paralyzed by fear of changing something that is supposedly eternal and infallible. They cannot benefit from the example of previous changes.
For instance, when Catholics like Pope Francis himself are now reconsidering the church’s teachings on homosexuality,105 they find it difficult to simply acknowledge past mistakes and change the teachings. If eventually a future pope would issue an apology for the mistreatment of LGBTQ people, the way to do it would be to again shift the blame to the shoulders of some overzealous individuals who misunderstood the gospel. To maintain its religious authority the Catholic Church has had no choice but to deny the existence of institutional self-correction. For the church fell into the infallibility trap. Once it based its religious authority on a claim to infallibility, any public admission of institutional error—even on relatively minor issues—could completely destroy its authority.
THE DSM AND THE BIBLE
In contrast to the Catholic Church, the scientific institutions that emerged in early modern Europe have been built around strong self-correcting mechanisms. Scientific institutions maintain that even if most scientists in a particular period believe something to be true, it may yet turn out to be inaccurate or incomplete. In the nineteenth century most physicists accepted Newtonian physics as a comprehensive account of the universe, but in the twentieth century the theory of relativity and quantum mechanics exposed the inaccuracies and limitations of Newton’s model.106 The most celebrated moments in the history of science are precisely those moments when accepted wisdom is overturned and new theories are born.
Crucially, scientific institutions are willing to admit their institutional responsibility for major mistakes and crimes. For example, present-day universities routinely give courses, and professional journals routinely publish articles, that expose the institutional racism and sexism that characterized the scientific study of subjects like biology, anthropology, and history in the nineteenth and much of the twentieth centuries. Research on individual test cases such as the Tuskegee Syphilis Study, and on governmental policies ranging from the White Australia policy to the Holocaust, have repeatedly and extensively studied how flawed biological, anthropological, and historical theories developed in leading scientific institutions were used to justify and facilitate discrimination, imperialism, and even genocide. These crimes and errors are not blamed on a few misguided scholars. They are seen as an institutional failure of entire academic disciplines.107
The willingness to admit major institutional errors contributes to the relatively fast pace at which science is developing. When the available evidence justifies it, dominant theories are often discarded within a few generations, to be replaced by new theories. What students of biology, anthropology, and history learn at university in the early twenty-first century is very different from what they learned there a century previously.
Psychiatry offers numerous similar examples for strong self-correcting mechanisms. On the shelf of most psychiatrists you can find the DSM—the Diagnostic and Statistical Manual of Mental Disorders. It is occasionally nicknamed the psychiatrists’ bible. But there is a crucial difference between the DSM and the Bible. First published in 1952, the DSM is revised every decade or two, with the fifth edition appearing in 2013. Over the years, the definition of many disorders has changed, new ones have been added, while others have been deleted. Homosexuality, for example, was listed in 1952 as a sociopathic personality disturbance, but removed from the DSM in 1974. It took just twenty-two years to correct this error in the DSM. That’s not a holy book. That’s a scientific text.
Today the discipline of psychiatry doesn’t try to reinterpret the 1952 definition of homosexuality in a more benign spirit. Rather, it views the 1952 definition as a downright error. More important, the error is not attributed to the shortcomings of a few homophobic professors. Rather, it is acknowledged to be the result of deep institutional biases in the discipline of psychiatry.108 Confessing the past institutional errors of their discipline makes psychiatrists today more careful not to commit new such errors, as evidenced in the heated debate regarding transgender people and people on the autistic spectrum. Of course, no matter how careful they are, psychiatrists are still likely to make institutional mistakes. But they are also likely to acknowledge and correct them.109
PUBLISH OR PERISH
What makes scientific self-correcting mechanisms particularly strong is that scientific institutions are not just willing to admit institutional error and ignorance; they are actively seeking to expose them. This is evident in the institutions’ incentive structure. In religious institutions, members are incentivized to conform to existing doctrine and be suspicious of novelty. You become a rabbi, imam, or priest by professing doctrinal loyalty, and you can advance up the ranks to become pope, chief rabbi, or grand ayatollah without criticizing your predecessors or advancing any radical new notions. Indeed, many of the most powerful and admired religious leaders of recent times—such as Pope Benedict XVI, Chief Rabbi of Israel David Lau, and Ayatollah Khamenei of Iran—have won fame and supporters by strict resistance to new ideas and trends like feminism.110
In science it works the other way around. Hiring and promotions in scientific institutions are based on the principle of “publish or perish,” and to publish in prestigious journals, you must expose some mistake in existing theories or discover something your predecessors and teachers didn’t know. Nobody wins a Nobel Prize for faithfully repeating what previous scholars said and opposing every new scientific theory.
Of course, just as religion has room for self-correcting, so science has ample room for conformism, too. Science is an institutional enterprise, and scientists rely on the institution for almost everything they know. For example, how do I know what medieval and early modern Europeans thought about witchcraft? I have not visited all the relevant archives myself, nor have I read all the relevant primary sources. In fact, I am incapable of reading many of these sources directly, because I do not know all the necessary languages, nor am I skilled in deciphering medieval and early modern handwriting. Instead, I have relied on books and articles published by other scholars, such as Ronald Hutton’s book The Witch: A History of Fear, which was published by Yale University Press in 2017.
I haven’t met Ronald Hutton, who is a professor of history at the University of Bristol, nor do I personally know the Bristol officials who hired him or the Yale editorial team who published his book. I nevertheless trust what I read in Hutton’s book, because I understand how institutions like the University of Bristol and Yale University Press operate. Their self-correcting mechanisms have two crucial features: First, the self-correcting mechanisms are built into the core of the institutions rather than being a peripheral add-on. Second, these institutions publicly celebrate self-correcting instead of denying it. It is of course possible that some of the information I gained from Hutton’s book may be incorrect, or I myself may misinterpret it. But experts on the history of witchcraft who have read Hutton’s book and who might be reading the present book will hopefully spot any such errors and expose them.
Populist critics of scientific institutions may counter that, in fact, these institutions use their power to stifle unorthodox views and launch their own witch hunts against dissenters. It is certainly true that if a scholar opposes the current orthodox view of their discipline, it might sometimes have negative consequences: articles rejected, research grants denied, nasty ad hominem attacks, and in rare cases even getting fired from their job.111 I do not wish to belittle the suffering such things cause, but it is still a far cry from being physically tortured and burned at the stake.
Consider, for example, the story of the chemist Dan Shechtman. In April 1982, while observing through an electron microscope, Shechtman saw something that all contemporary theories in chemistry claimed simply could not exist: the atoms in a mixed sample of aluminum and manganese were crystallized in a pattern with a five-fold rotational symmetry. At the time, scientists knew of various possible symmetrical structures in solid crystals, but five-fold symmetry was considered against the very laws of nature. Shechtman’s discovery of what came to be called quasicrystals sounded so outlandish that it was difficult to find a peer-reviewed journal willing to publish it. It didn’t help that Shechtman was at the time a junior scientist. He didn’t even have his own laboratory; he was working in someone’s else facility. But the editors of the journal Physical Review Letters, after reviewing the evidence, eventually published Shechtman’s article in 1984.112 And then, as he describes it, “all hell broke loose.”
Shechtman’s claims were dismissed by most of his colleagues, and he was blamed for mismanaging his experiments. The head of his laboratory also turned on Shechtman. In a dramatic gesture, he placed a chemistry textbook on Shechtman’s desk and told him, “Danny, please read this book and you will understand that what you are saying cannot be.” Shechtman boldly replied that he saw the quasicrystals in the microscope—not in the book. As a result, he was kicked out of the lab. Worse was to come. Linus Pauling, a two-time Nobel laureate and one of the most eminent scientists of the twentieth century, led a brutal personal attack on Shechtman. In a conference attended by hundreds of scientists, Pauling proclaimed, “Danny Shechtman is talking nonsense, there are no quasicrystals, just quasi-scientists.”
But Shechtman was not imprisoned or killed. He got a place in another lab. The evidence he presented turned out to be more convincing than the existing chemistry textbooks and the views of Linus Pauling. Several colleagues repeated Shechtman’s experiments and replicated his findings. A mere ten years after Shechtman saw the quasicrystals through his microscope, the International Union of Crystallography—the leading scientific association in the field—altered its definition of what a crystal is. Chemistry textbooks were changed accordingly, and an entire new scientific field emerged—the study of quasicrystals. In 2011, Shechtman was awarded the Nobel Prize in Chemistry for his discovery.113 The Nobel Committee said that “his discovery was extremely controversial [but] eventually forced scientists to reconsider their conception of the very nature of matter.”114
Shechtman’s story is hardly exceptional. The annals of science are full of similar cases. Before the theory of relativity and quantum mechanics became the cornerstones of twentieth-century physics, they initially provoked bitter controversies, including personal assaults by the old guard on the proponents of the new theories. Similarly, when Georg Cantor developed in the late nineteenth century his theory of infinite numbers, which became the basis for much of twentieth-century mathematics, he was personally attacked by some of the leading mathematicians of his day like Henri Poincaré and Leopold Kronecker. Populists are right to think that scientists suffer from the same human biases as everyone else. However, thanks to institutional self-correcting mechanisms these biases can be overcome. If enough empirical evidence is provided, it often takes just a few decades for an unorthodox theory to upend established wisdom and become the new consensus.
As we shall see in the next chapter, there were times and places where scientific self-correcting mechanisms ceased functioning and academic dissent could lead to physical torture, imprisonment, and death. In the Soviet Union, for example, questioning official dogma on any matter—economics, genetics, or history—could lead not only to dismissal but even to a couple of years in the gulag or an executioner’s bullet.115 A famous case involved the bogus theories of the agronomist Trofim Lysenko. He rejected mainstream genetics and the theory of evolution by natural selection and advanced his own pet theory, which said that “re-education” could change the traits of plants and animals, and even transform one species into another. Lysenkoism greatly appealed to Stalin, who had ideological and political reasons for believing in the almost limitless potential of “re-education.” Thousands of scientists who opposed Lysenko and continued to uphold the theory of evolution by natural selection were dismissed from their jobs, and some were imprisoned or executed. Nikolai Vavilov, a botanist and geneticist who was Lysenko’s former mentor turned critic, was tried in July 1941 along with the botanist Leonid Govorov, the geneticist Georgii Karpechenko, and the agronomist Aleksandr Bondarenko. The latter three were shot, while Vavilov died in a camp in Saratov in 1943.116 Under pressure from the dictator, the Lenin All-Union Academy of Agricultural Sciences eventually announced in August 1948 that henceforth Soviet institutions would teach Lysenkoism as the only correct theory.117
But for precisely this reason, the Lenin All-Union Academy of Agricultural Sciences ceased being a scientific institution, and Soviet dogma on genetics was an ideology rather than a science. An institution can call itself by whatever name it wants, but if it lacks a strong self-correcting mechanism, it is not a scientific institution.
THE LIMITS OF SELF-CORRECTION
Does all this mean that in self-correcting mechanisms we have found the magic bullet that protects human information networks from error and bias? Unfortunately, things are far more complicated. There is a reason why institutions like the Catholic Church and the Soviet Communist Party eschewed strong self-correcting mechanisms. While such mechanisms are vital for the pursuit of truth, they are costly in terms of maintaining order. Strong self-correcting mechanisms tend to create doubts, disagreements, conflicts, and rifts and to undermine the myths that hold the social order together.
Of course, order by itself isn’t necessarily good. For example, the social order of early modern Europe endorsed, among other things, not only witch hunts but also the exploitation of millions of peasants by a handful of aristocrats, the systematic mistreatment of women, and widespread discrimination against Jews, Muslims, and other minorities. But even when the social order is highly oppressive, undermining it doesn’t necessarily lead to a better place. It could just lead to chaos and worse oppression. The history of information networks has always involved maintaining a balance between truth and order. Just as sacrificing truth for the sake of order comes with a cost, so does sacrificing order for truth.
Scientific institutions have been able to afford their strong self-correcting mechanisms because they leave the difficult job of preserving the social order to other institutions. If a thief breaks into a chemistry lab, or a psychiatrist receives death threats, they don’t complain to a peer-reviewed journal; they call the police. Is it possible, then, to maintain strong self-correcting mechanisms in institutions other than academic disciplines? In particular, can such mechanisms exist in institutions like police forces, armies, political parties, and governments that are charged with maintaining the social order?
We’ll explore this question in the next chapter, which focuses on the political aspects of information flows and examines the long-term history of democracies and dictatorships. As we shall see, democracies believe that it is possible to maintain strong self-correcting mechanisms even in politics. Dictatorships disavow such mechanisms. Thus, at the height of the Cold War, newspapers and universities in the democratic United States openly exposed and criticized American war crimes in Vietnam. Newspapers and universities in the totalitarian Soviet Union were also happy to criticize American crimes, but they remained silent about Soviet crimes in Afghanistan and elsewhere. Soviet silence was scientifically unjustifiable, but it made political sense. American self-flagellation about the Vietnam War continues even today to divide the American public and to undermine America’s reputation throughout the world, whereas Soviet and Russian silence about the Afghanistan War has helped dim its memory and limit its reputational costs.
Only after understanding the politics of information in historical systems like ancient Athens, the Roman Empire, the United States, and the Soviet Union will we be ready to explore the revolutionary implications of the rise of AI. For one of the biggest questions about AI is whether it will favor or undermine democratic self-correcting mechanisms.
CHAPTER 5 Decisions: A Brief History of Democracy and Totalitarianism
Democracy and dictatorship are typically discussed as contrasting political and ethical systems. This chapter seeks to shift the terms of the discussion, by surveying the history of democracy and dictatorship as contrasting types of information networks. It examines how information in democracies flows differently than in dictatorial systems and how inventing new information technologies helps different kinds of regimes flourish.
Dictatorial information networks are highly centralized.1 This means two things. First, the center enjoys unlimited authority, hence information tends to flow to the central hub, where the most important decisions are made. In the Roman Empire all roads led to Rome, in Nazi Germany information flowed to Berlin, and in the Soviet Union it streamed to Moscow. Sometimes the central government attempts to concentrate all information in its hands and to dictate all decisions by itself, controlling the totality of people’s lives. This totalizing form of dictatorship, practiced by the likes of Hitler and Stalin, is known as totalitarianism. As we shall see, technical difficulties often prevent dictators from becoming totalitarian. The Roman emperor Nero, for example, didn’t have the technology necessary to micromanage the lives of millions of peasants in remote provincial villages. In many dictatorial regimes considerable autonomy is therefore left to individuals, corporations, and communities. However, the dictators always retain the authority to intervene in people’s lives. In Nero’s Rome freedom was not an ideal but a by-product of the government’s inability to exert totalitarian control.
The second characteristic of dictatorial networks is that they assume the center is infallible. They therefore dislike any challenge to the center’s decisions. Soviet propaganda depicted Stalin as an infallible genius, and Roman propaganda treated emperors as divine beings. Even when Stalin or Nero made a patently disastrous decision, there were no robust self-correcting mechanisms in the Soviet Union or the Roman Empire that could expose the mistake and push for a better course of action.
In theory, a highly centralized information network could try to maintain strong self-correcting mechanisms, like independent courts and elected legislative bodies. But if they functioned well, these would challenge the central authority and thereby decentralize the information network. Dictators always see such independent power hubs as threats and seek to neutralize them. This is what happened to the Roman Senate, whose power was whittled away by successive Caesars until it became little more than a rubber stamp for imperial whims.2 The same fate befell the Soviet judicial system, which never dared resist the will of the Communist Party. Stalinist show trials, as their name indicates, were theater with preordained results.3
To summarize, a dictatorship is a centralized information network, lacking strong self-correcting mechanisms. A democracy, in contrast, is a distributed information network, possessing strong self-correcting mechanisms. When we look at a democratic information network, we do see a central hub. The government is the most important executive power in a democracy, and government agencies therefore gather and store vast quantities of information. But there are many additional information channels that connect lots of independent nodes. Legislative bodies, political parties, courts, the press, corporations, local communities, NGOs, and individual citizens communicate freely and directly with one another so that most information never passes through any government agency and many important decisions are made elsewhere. Individuals choose for themselves where to live, where to work, and whom to marry. Corporations make their own choices about where to open a branch, how much to invest in certain projects, and how much to charge for goods and services. Communities decide for themselves about organizing charities, sporting events, and religious festivals. Autonomy is not a consequence of the government’s ineffectiveness; it is the democratic ideal.
Even if it possesses the technology necessary to micromanage people’s lives, a democratic government leaves as much room as possible for people to make their own choices. A common misconception is that in a democracy everything is decided by majority vote. In fact, in a democracy as little as possible is decided centrally, and only the relatively few decisions that must be made centrally should reflect the will of the majority. In a democracy, if 99 percent of people want to dress in a particular way and worship a particular god, the remaining 1 percent should still be free to dress and worship differently.
Of course, if the central government doesn’t intervene at all in people’s lives, and doesn’t provide them with basic services like security, it isn’t a democracy; it is anarchy. In all democracies the center raises taxes and maintains an army, and in most modern democracies it also provides at least some level of health care, education, and welfare. But any intervention in people’s lives demands an explanation. In the absence of a compelling reason, a democratic government should leave people to their own devices.
Another crucial characteristic of democracies is that they assume everyone is fallible. Therefore, while democracies give the center the authority to make some vital decisions, they also maintain strong mechanisms that can challenge the central authority. To paraphrase President James Madison, since humans are fallible, a government is necessary, but since government too is fallible, it needs mechanisms to expose and correct its errors, such as holding regular elections, protecting the freedom of the press, and separating the executive, legislative, and judicial branches of government.
Consequently, while a dictatorship is about one central information hub dictating everything, a democracy is an ongoing conversation between diverse information nodes. The nodes often influence each other, but in most matters they are not obliged to reach a consensus. Individuals, corporations, and communities can continue to think and behave in different ways. There are, of course, cases when everyone must behave the same, and diversity cannot be tolerated. For example, when in 2002–3 Americans disagreed about whether to invade Iraq, everyone ultimately had to abide by a single decision. It was unacceptable that some Americans would maintain a private peace with Saddam Hussein while others declared war. Whether good or bad, the decision to invade Iraq committed every American citizen. So also when initiating national infrastructure projects or defining criminal offenses. No country can function well if every person is allowed to lay a separate rail network or to have their own definition of murder.
In order to make decisions on such collective matters, a countrywide public conversation must first be held, following which the people’s representatives—elected in free and fair elections—make a choice. But even after that choice has been made, it should remain open to reexamination and correction. While the network cannot change its previous choices, it can elect a different government next time.
MAJORITY DICTATORSHIP
The definition of democracy as a distributed information network with strong self-correcting mechanisms stands in sharp contrast to a common misconception that equates democracy only with elections. Elections are a central part of the democratic tool kit, but they are not democracy. In the absence of additional self-correcting mechanisms, elections can easily be rigged. Even if the elections are completely free and fair, by itself this too doesn’t guarantee democracy. For democracy is not the same thing as majority dictatorship.
Suppose that in a free and fair election 51 percent of voters choose a government that subsequently sends 1 percent of voters to be exterminated in death camps, because they belong to some hated religious minority. Is this democratic? Clearly it is not. The problem isn’t that genocide demands a special majority of more than 51 percent. It’s not that if the government gets the backing of 60 percent, 75 percent, or even 99 percent of voters, then its death camps finally become democratic. A democracy is not a system in which a majority of any size can decide to exterminate unpopular minorities; it is a system in which there are clear limits on the power of the center.
Suppose 51 percent of voters choose a government that then takes away the voting rights of the other 49 percent of voters, or perhaps of just 1 percent of them. Is that democratic? Again the answer is no, and it has nothing to do with the numbers. Disenfranchising political rivals dismantles one of the vital self-correcting mechanisms of democratic networks. Elections are a mechanism for the network to say, “We made a mistake; let’s try something else.” But if the center can disenfranchise people at will, that self-correcting mechanism is neutered.
These two examples may sound outlandish, but they are unfortunately within the realm of the possible. Hitler began sending Jews and communists to concentration camps within months of rising to power through democratic elections, and in the United States numerous democratically elected governments have disenfranchised African Americans, Native Americans, and other oppressed populations. Of course, most assaults on democracy are more subtle. The careers of strongmen like Vladimir Putin, Viktor Orbán, Recep Tayyip Erdoğan, Rodrigo Duterte, Jair Bolsonaro, and Benjamin Netanyahu demonstrate how a leader who uses democracy to rise to power can then use his power to undermine democracy. As Erdoğan once put it, “Democracy is like a tram. You ride it until you arrive at your destination, then you step off.”4
The most common method strongmen use to undermine democracy is to attack its self-correcting mechanisms one by one, often beginning with the courts and the media. The typical strongman either deprives courts of their powers or packs them with his loyalists and seeks to close all independent media outlets while building his own omnipresent propaganda machine.5
Once the courts are no longer able to check the government’s power by legal means, and once the media obediently parrots the government line, all other institutions or persons who dare oppose the government can be smeared and persecuted as traitors, criminals, or foreign agents. Academic institutions, municipalities, NGOs, and private businesses are either dismantled or brought under government control. At that stage, the government can also rig the elections at will, for example by jailing popular opposition leaders, preventing opposition parties from participating in the elections, gerrymandering election districts, or disenfranchising voters. Appeals against these antidemocratic measures are dismissed by the government’s handpicked judges. Journalists and academics who criticize these measures are fired. The remaining media outlets, academic institutions, and judicial authorities all praise these measures as necessary steps to protect the nation and its allegedly democratic system from traitors and foreign agents. The strongmen don’t usually take the final step of abolishing the elections outright. Instead, they keep them as a ritual that serves to provide legitimacy and maintain a democratic facade, as happens, for example, in Putin’s Russia.
Supporters of strongmen often don’t see this process as antidemocratic. They are genuinely baffled when told that electoral victory doesn’t grant them unlimited power. Instead, they see any check on the power of an elected government as undemocratic. However, democracy doesn’t mean majority rule; rather, it means freedom and equality for all. Democracy is a system that guarantees everyone certain liberties, which even the majority cannot take away.
Nobody disputes that in a democracy the representatives of the majority are entitled to form the government and to advance their preferred policies in myriad fields. If the majority wants war, the country goes to war. If the majority wants peace, the country makes peace. If the majority wants to raise taxes, taxes are raised. If the majority wants to lower taxes, taxes are lowered. Major decisions about foreign affairs, defense, education, taxation, and numerous other policies are all in the hands of the majority.
But in a democracy, there are two baskets of rights that are protected from the majority’s grasp. One contains human rights. Even if 99 percent of the population wants to exterminate the remaining 1 percent, in a democracy this is forbidden, because it violates the most basic human right—the right to life. The basket of human rights contains many additional rights, such as the right to work, the right to privacy, freedom of movement, and freedom of religion. These rights enshrine the decentralized nature of democracy, making sure that as long as people don’t harm anyone, they can live their lives as they see fit.
The second crucial basket of rights contains civil rights. These are the basic rules of the democratic game, which enshrine its self-correcting mechanisms. An obvious example is the right to vote. If the majority were permitted to disenfranchise the minority, then democracy would be over after a single election. Other civil rights include freedom of the press, academic freedom, and freedom of assembly, which enable independent media outlets, universities, and opposition movements to challenge the government. These are the key rights that strongmen seek to violate. While sometimes it is necessary to make changes to a country’s self-correcting mechanisms—for example, by expanding the franchise, regulating the media, or reforming the judicial system—such changes should be made only on the basis of a broad consensus including both majority and minority groups. If a small majority could unilaterally change civil rights, it could easily rig elections and get rid of all other checks on its power.
An important thing to note about both human rights and civil rights is that they don’t just limit the power of the central government; they also impose on it many active duties. It is not enough for a democratic government to abstain from infringing on human and civil rights. It must take actions to ensure them. For example, the right to life imposes on a democratic government the duty to protect citizens from criminal violence. If a government doesn’t kill anyone, but also makes no effort to protect citizens from murder, this is anarchy rather than democracy.
THE PEOPLE VERSUS THE TRUTH
Of course, in every democracy, there are lengthy discussions concerning the exact limits of human and civil rights. Even the right to life has limits. There are democratic countries like the United States that impose the death penalty, thereby denying some criminals the right to life. And every country allows itself the prerogative to declare war, thereby sending people to kill and be killed. So where exactly does the right to life end? There are also complicated and ongoing discussions concerning the list of rights that should be included in the two baskets. Who determined that freedom of religion is a basic human right? Should internet access be defined as a civil right? And what about animal rights? Or the rights of AI?
We cannot resolve these matters here. Both human and civil rights are intersubjective conventions that humans invent rather than discover, and they are determined by historical contingencies rather than universal reason. Different democracies can adopt somewhat different lists of rights. At least from the viewpoint of information flows, what defines a system as “democratic” is only that its center doesn’t have unlimited authority and that the system possesses robust mechanisms to correct the center’s mistakes. Democratic networks assume that everyone is fallible, and that includes even the winners of elections and the majority of voters.
It is particularly crucial to remember that elections are not a method for discovering truth. Rather, they are a method for maintaining order by adjudicating between people’s conflicting desires. Elections establish what the majority of people desire, rather than what the truth is. And people often desire the truth to be other than what it is. Democratic networks therefore maintain some self-correcting mechanisms to protect the truth even from the will of the majority.
For example, during the 2002–3 debate over whether to invade Iraq in the wake of the September 11 attacks, the Bush administration claimed that Saddam Hussein was developing weapons of mass destruction and that the Iraqi people were eager to establish an American-style democracy and would welcome the Americans as liberators. These arguments carried the day. In October 2002 the elected representatives of the American people in Congress voted overwhelmingly to authorize the invasion. The resolution passed with a 296 to 133 majority (69 percent) in the House of Representatives and a 77 to 23 majority (77 percent) in the Senate.6 In the early days of the war in March 2003, polls found that the elected representatives were indeed in tune with the mass of voters and that 72 percent of American citizens supported the invasion.7 The will of the American people was clear.
But the truth turned out to be different from what the government said and what the majority believed. As the war progressed, it became evident that Iraq had no weapons of mass destruction and that many Iraqis had no wish to be “liberated” by the Americans or to establish a democracy. By August 2004 another poll found that 67 percent of Americans believed that the invasion was based on incorrect assumptions. As the years went by, most Americans acknowledged that the decision to invade was a catastrophic mistake.8
In a democracy the majority has every right to make momentous decisions like starting wars, and that includes the right to make momentous errors. But the majority should at least acknowledge its own fallibility and protect the freedom of minorities to hold and publicize unpopular views, which might turn out to be correct.
As another example, consider the case of a charismatic leader who is accused of corruption. His loyal supporters obviously wish these accusations to be false. But even if most voters support the leader, their desires should not prevent judges from investigating the accusations and getting to the truth. As with the justice system, so also with science. A majority of voters might deny the reality of climate change, but they should not have the power to dictate scientific truth or to prevent scientists from exploring and publishing inconvenient facts. Unlike parliaments, departments of environmental studies should not reflect the will of the majority.
Of course, when it comes to making policy decisions about climate change, in a democracy the will of the voters should reign supreme. Acknowledging the reality of climate change does not tell us what to do about it. We always have options, and choosing between them is a question of desire, not truth. One option might be to immediately cut greenhouse gas emissions, even at the cost of slowing economic growth. This means incurring some difficulties today but saving people in 2050 from more severe hardship, saving the island nation of Kiribati from drowning, and saving the polar bears from extinction. A second option might be to continue with business as usual. This means having an easier life today, but making life harder for the next generation, flooding Kiribati, and driving the polar bears—as well as numerous other species—to extinction. Choosing between these two options is a question of desire, and should therefore be done by all voters rather than by a limited group of experts.
But the one option that should not be on offer in elections is hiding or distorting the truth. If the majority prefers to consume whatever amount of fossil fuels it wishes with no regard to future generations or other environmental considerations, it is entitled to vote for that. But the majority should not be entitled to pass a law stating that climate change is a hoax and that all professors who believe in climate change must be fired from their academic posts. We can choose what we want, but we shouldn’t deny the true meaning of our choice.
Naturally, academic institutions, the media, and the judiciary may themselves be compromised by corruption, bias, or error. But subordinating them to a governmental Ministry of Truth is likely to make things worse. The government is already the most powerful institution in developed societies, and it often has the greatest interest in distorting or hiding inconvenient facts. Allowing the government to supervise the search for truth is like appointing the fox to guard the chicken coop.
To discover the truth, it is better to rely on two other methods. First, academic institutions, the media, and the judiciary have their own internal self-correcting mechanisms for fighting corruption, correcting bias, and exposing error. In academia, peer-reviewed publication is a far better check on error than supervision by government officials, because academic promotion often depends on uncovering past mistakes and discovering unknown facts. In the media, free competition means that if one outlet decides not to break a scandal, perhaps for self-serving reasons, others are likely to jump at the scoop. In the judiciary, a judge that takes bribes may be tried and punished just like any other citizen.
Second, the existence of several independent institutions that seek the truth in different ways allows these institutions to check and correct one another. For example, if powerful corporations manage to break down the peer-review mechanism by bribing a sufficiently large number of scientists, investigative journalists and courts can expose and punish the perpetrators. If the media or the courts are afflicted by systematic racist biases, it is the job of sociologists, historians, and philosophers to expose these biases. None of these mechanisms are completely fail-safe, but no human institution is. Government certainly isn’t.
THE POPULIST ASSAULT
If all this sounds complicated, it is because democracy should be complicated. Simplicity is a characteristic of dictatorial information networks in which the center dictates everything and everybody silently obeys. It’s easy to follow this dictatorial monologue. In contrast, democracy is a conversation with numerous participants, many of them talking at the same time. It can be hard to follow such a conversation.
Moreover, the most important democratic institutions tend to be bureaucratic behemoths. Whereas citizens avidly follow the biological dramas of the princely court and the presidential palace, they often find it difficult to understand how parliaments, courts, newspapers, and universities function. This is what helps strongmen mount populist attacks on institutions, dismantle all self-correcting mechanisms, and concentrate power in their hands. We discussed populism briefly in the prologue, to help explain the populist challenge to the naive view of information. Here we need to revisit populism, get a broader understanding of its worldview, and explain its appeal to antidemocratic strongmen.
The term “populism” derives from the Latin populus, which means “the people.” In democracies, “the people” is considered the sole legitimate source of political authority. Only representatives of the people should have the authority to declare wars, pass laws, and raise taxes. Populists cherish this basic democratic principle, but somehow conclude from it that a single party or a single leader should monopolize all power. In a curious political alchemy, populists manage to base a totalitarian pursuit of unlimited power on a seemingly impeccable democratic principle. How does it happen?
The most novel claim populists make is that they alone truly represent the people. Since in democracies only the people should have political power, and since allegedly only the populists represent the people, it follows that the populist party should have all political power to itself. If some party other than the populists wins elections, it does not mean that this rival party won the people’s trust and is entitled to form a government. Rather, it means that the elections were stolen or that the people were deceived to vote in a way that doesn’t express their true will.
It should be stressed that for many populists, this is a genuinely held belief rather than a propaganda gambit. Even if they win just a small share of votes, populists may still believe they alone represent the people. An analogous case are communist parties. In the U.K., for example, the Communist Party of Great Britain (CPGB) never won more than 0.4 percent of votes in a general election,9 but was nevertheless adamant that it alone truly represented the working class. Millions of British workers, they claimed, were voting for the Labour Party or even for the Conservative Party rather than for the CPGB because of “false consciousness.” Allegedly, through their control of the media, universities, and other institutions, the capitalists managed to deceive the working class into voting against its true interests, and only the CPGB could see through this deception. In like fashion, populists can believe that the enemies of the people have deceived the people to vote against its true will, which the populists alone represent.
A fundamental part of this populist credo is the belief that “the people” is not a collection of flesh-and-blood individuals with various interests and opinions, but rather a unified mystical body that possesses a single will—“the will of the people.” Perhaps the most notorious and extreme manifestation of this semireligious belief was the Nazi motto “Ein Volk, ein Reich, ein Führer,” which means “One People, One Country, One Leader.” Nazi ideology posited that the Volk (people) had a single will, whose sole authentic representative was the Führer (leader). The leader allegedly had an infallible intuition for how the people felt and what the people wanted. If some German citizens disagreed with the leader, it didn’t mean that the leader might be in the wrong. Rather, it meant that the dissenters belonged to some treasonous outsider group—Jews, communists, liberals—instead of to the people.
The Nazi case is of course extreme, and it is grossly unfair to accuse all populists of being crypto-Nazis with genocidal inclinations. However, many populist parties and politicians deny that “the people” might contain a diversity of opinions and interest groups. They insist that the real people has only one will and that they alone represent this will. In contrast, their political rivals—even when the latter enjoy substantial popular support—are depicted as “alien elites.” Thus, Hugo Chávez ran for the presidency in Venezuela with the slogan “Chávez is the people!”10 President Erdoğan of Turkey once railed against his domestic critics, saying, “We are the people. Who are you?”—as if his critics weren’t Turks, too.11
How can you tell, then, whether someone is part of the people or not? Easy. If they support the leader, they are part of the people. This, according to the German political philosopher Jan-Werner Müller, is the defining feature of populism. What turns someone into a populist is claiming that they alone represent the people and that anyone who disagrees with them—whether state bureaucrats, minority groups, or even the majority of voters—either suffers from false consciousness or isn’t really part of the people.12
This is why populism poses a deadly threat to democracy. While democracy agrees that the people is the only legitimate source of power, democracy is based on the understanding that the people is never a unitary entity and, therefore, cannot possess a single will. Every people—whether Germans, Venezuelans, or Turks—is composed of many different groups, with a plurality of opinions, wills, and representatives. No group, including the majority group, is entitled to exclude other groups from membership in the people. This is what makes democracy a conversation. Holding a conversation presupposes the existence of several legitimate voices. If, however, the people has only one legitimate voice, there can be no conversation. Rather, the single voice dictates everything. Populism may therefore claim adherence to the democratic principle of “people’s power,” but it effectively empties democracy of meaning and seeks to establish a dictatorship.
Populism undermines democracy in another, more subtle, but equally dangerous way. Having claimed that they alone represent the people, populists argue that the people is not just the sole legitimate source of political authority but the sole legitimate source of all authority. Any institution that derives its authority from something other than the will of the people is antidemocratic. As the self-proclaimed representatives of the people, populists consequently seek to monopolize not just political authority but all types of authority and to take control of institutions such as media outlets, courts, and universities. By taking the democratic principle of “people’s power” to its extreme, populists turn totalitarian.
In fact, while democracy means that authority in the political sphere comes from the people, it doesn’t deny the validity of alternative sources of authority in other spheres. As discussed above, in a democracy independent media outlets, courts, and universities are essential self-correcting mechanisms that protect the truth even from the will of the majority. Biology professors claim that humans evolved from apes because the evidence supports this, even if the majority wills it to be otherwise. Journalists can reveal that a popular politician took a bribe, and if compelling evidence is presented in court, a judge may send that politician to jail, even if most people don’t want to believe these accusations.
Populists are suspicious of institutions that in the name of objective truths override the supposed will of the people. They tend to see this as a smoke screen for elites grabbing illegitimate power. This drives populists to be skeptical of the pursuit of truth, and to argue—as we saw in the prologue—that “power is the only reality.” They thereby seek to undercut or appropriate the authority of any independent institutions that might oppose them. The result is a dark and cynical view of the world as a jungle and of human beings as creatures obsessed with power alone. All social interactions are seen as power struggles, and all institutions are depicted as cliques promoting the interests of their own members. In the populist imagination, courts don’t really care about justice; they only protect the privileges of the judges. Yes, the judges talk a lot about justice, but this is a ploy to grab power for themselves. Newspapers don’t care about facts; they spread fake news to mislead the people and benefit the journalists and the cabals that finance them. Even scientific institutions aren’t committed to the truth. Biologists, climatologists, epidemiologists, economists, historians, and mathematicians are just another interest group feathering its own nest—at the expense of the people.
In all, it’s a rather sordid view of humanity, but two things nevertheless make it appealing to many. First, since it reduces all interactions to power struggles, it simplifies reality and makes events like wars, economic crises, and natural disasters easy to understand. Anything that happens—even a pandemic—is about elites pursuing power. Second, the populist view is attractive because it is sometimes correct. Every human institution is indeed fallible and suffers from some level of corruption. Some judges do take bribes. Some journalists do intentionally mislead the public. Academic disciplines are occasionally plagued by bias and nepotism. That is why every institution needs self-correcting mechanisms. But since populists are convinced that power is the only reality, they cannot accept that a court, a media outlet, or an academic discipline would ever be inspired by the value of truth or justice to correct itself.
While many people embrace populism because they see it as an honest account of human reality, strongmen are attracted to it for a different reason. Populism offers strongmen an ideological basis for making themselves dictators while pretending to be democrats. It is particularly useful when strongmen seek to neutralize or appropriate the self-correcting mechanisms of democracy. Since judges, journalists, and professors allegedly pursue political interests rather than truth, the people’s champion—the strongman—should control these positions instead of allowing them to fall into the hands of the people’s enemies. Similarly, since even the officials in charge of arranging elections and publicizing their results may be part of a nefarious conspiracy, they too should be replaced by the strongman’s loyalists.
In a well-functioning democracy, citizens trust the results of elections, the decisions of courts, the reports of media outlets, and the findings of scientific disciplines because citizens believe these institutions are committed to the truth. Once people think that power is the only reality, they lose trust in all these institutions, democracy collapses, and the strongmen can seize total power. Of course, populism could lead to anarchy rather than totalitarianism, if it undermines trust in the strongmen themselves. If no human is interested in truth or justice, doesn’t this apply to Mussolini or Putin too? And if no human institution can have effective self-correcting mechanisms, doesn’t this include Mussolini’s National Fascist Party or Putin’s United Russia party? How can a deep-seated distrust of all elites and institutions be squared with unwavering admiration for one leader and party? This is why populists ultimately depend on the mystical notion that the strongman embodies the people. When trust in bureaucratic institutions like election boards, courts, and newspapers is particularly low, an enhanced reliance on mythology is the only way to preserve order.
MEASURING THE STRENGTH OF DEMOCRACIES
Strongmen who claim to represent the people may well rise to power through democratic means, and often rule behind a democratic facade. Rigged elections in which they win overwhelming majorities serve as proof of the mystical bond between the leader and the people. Consequently, to measure how democratic an information network is, we cannot use a simple yardstick like whether elections are being held regularly. In Putin’s Russia, in Iran, and even in North Korea elections are held like clockwork. Rather, we need to ask much more complex questions like “What mechanisms prevent the central government from rigging the elections?” “How safe is it for leading media outlets to criticize the government?” and “How much authority does the center appropriate to itself?” Democracy and dictatorship aren’t binary opposites, but rather a continuum. To decide whether a network is closer to the democratic or the dictatorial end of the continuum, we need to understand how information flows in the network and what shapes the political conversation.
If one person dictates all the decisions, and even their closest advisers are terrified to voice a dissenting view, no conversation is taking place. Such a network is situated at the extreme dictatorial end of the spectrum. If nobody can voice unorthodox opinions publicly, but behind closed doors a small circle of party bosses or senior officials are able to freely express their views, then this is still a dictatorship, but it has taken a baby step in the direction of democracy. If 10 percent of the population participate in the political conversation by airing their opinions, voting in fair elections, and running for office, that may be considered a limited democracy, as was the case in many ancient city-states like Athens, or in the early days of the United States, when only wealthy white men had such political rights. As the percentage of people taking part in the conversation rises, so the network becomes more democratic.
The focus on conversations rather than elections raises a host of interesting questions. For example, where does that conversation take place? North Korea, for example, has the Mansudae Assembly Hall in Pyongyang, where the 687 members of the Supreme People’s Assembly meet and talk. However, while this Assembly is officially known as North Korea’s legislature, and while elections to the Assembly are held every five years, this body is widely considered a rubber stamp, executing decisions taken elsewhere. The anodyne discussions follow a predetermined script, and they aren’t geared to change anyone’s mind about anything.13
Is there perhaps another, more private hall in Pyongyang where the crucial conversations take place? Do Politburo members ever dare criticize Kim Jong Un’s policies during formal meetings? Perhaps it can be done in unofficial dinner parties or in unofficial think tanks? Information in North Korea is so concentrated and so tightly controlled that we cannot provide clear answers to these questions.14 Similar questions can be asked about the United States. In the United States, unlike in North Korea, people are free to say almost anything they want. Scathing public attacks on the government are a daily occurrence. But where is the room where the crucial conversations happen, and who sits there? The U.S. Congress was designed to fulfill this function, with the people’s representatives meeting to converse and try to convince one another. But when was the last time that an eloquent speech in Congress by a member of one party persuaded members of the other party to change their minds about anything? Wherever the conversations that shape American politics now take place, it is definitely not in Congress. Democracies die not only when people are not free to talk but also when people are not willing or able to listen.
STONE AGE DEMOCRACIES
Based on the above definition of democracy, we can now turn to the historical record and examine how changes in information technology and information flows have shaped the history of democracy. To judge by the archaeological and anthropological evidence, democracy was the most typical political system among archaic hunter-gatherers. Stone Age bands obviously didn’t have formal institutions like elections, courts, and media outlets, but their information networks were usually distributed and gave ample opportunities for self-correction. In bands numbering just a few dozen people information could easily be shared among all group members, and when the band decided where to pitch camp, where to go hunting, or how to handle a conflict with another band, everyone could take part in the conversation and dispute each other. Bands usually belonged to a larger tribe that included hundreds or even thousands of people. But when important choices affecting the whole tribe had to be made, such as whether to go to war, tribes were usually still small enough for a large percentage of their members to gather in one place and converse.15
While bands and tribes sometimes had dominant leaders, these tended to exercise only limited authority. Leaders had no standing armies, police forces, or governmental bureaucracies at their disposal, so they couldn’t just impose their will by force.16 Leaders also found it difficult to control the economic basis of people’s lives. In modern times, dictators like Vladimir Putin and Saddam Hussein have often based their political power on monopolizing economic assets like oil wells.17 In medieval and classical antiquity, Chinese emperors, Greek tyrants, and Egyptian pharaohs dominated society by controlling granaries, silver mines, and irrigation canals. In contrast, in a hunter-gatherer economy such centralized economic control was possible only under special circumstances. For example, along the northwestern coast of North America some hunter-gatherer economies relied on catching and preserving large numbers of salmon. Since salmon runs peaked for a few weeks in specific creeks and rivers, a powerful chief could monopolize this asset.18
But this was exceptional. Most hunter-gatherer economies were far more diversified. One leader, even supported by a few allies, could not corral the savanna and prevent people from gathering plants and hunting animals there. If all else failed, hunter-gatherers could therefore vote with their feet. They had few possessions, and their most important assets were their personal skills and personal friends. If a chief turned dictatorial, people could just walk away.19
Even when hunter-gatherers did end up ruled by a domineering chief, as happened among the salmon-fishing people of northwestern America, at least that chief was accessible. He didn’t live in a faraway fortress surrounded by an unfathomable bureaucracy and a cordon of armed guards. If you wanted to voice a complaint or a suggestion, you could usually get within earshot of him. The chief couldn’t control public opinion, nor could he shut himself off from it. In other words, there was no way for a chief to force all information to flow through the center, or to prevent people from talking with one another, criticizing him, or organizing against him.20
In the millennia following the agricultural revolution, and especially after writing helped create large bureaucratic polities, it became easier to centralize the flow of information and harder to maintain the democratic conversation. In small city-states like those of ancient Mesopotamia and Greece, autocrats like Lugal-Zagesi of Umma and Pisistratus of Athens relied on bureaucrats, archives, and a standing army to monopolize key economic assets and information about ownership, taxation, diplomacy, and politics. It simultaneously became harder for the mass of citizens to keep in direct touch with one another. There was no mass communication technology like newspapers or radio, and it was not easy to squeeze tens of thousands of citizens into the main city square to hold a communal discussion.
Democracy was still an option for these small city-states, as the history of both early Sumer and classical Greece clearly indicates.21 However, the democracy of ancient city-states tended to be less inclusive than the democracy of archaic hunter-gatherer bands. Probably the most famous example of ancient city-state democracy is Athens in the fifth and fourth centuries BCE. All adult male citizens could participate in the Athenian assembly, vote on public policy, and be elected to public offices. But women, slaves, and noncitizen residents of the city did not enjoy these privileges. Only about 25–30 percent of the adult population of Athens enjoyed full political rights.22
As the size of polities continued to increase, and city-states were superseded by larger kingdoms and empires, even Athenian-style partial democracy disappeared. All the famous examples of ancient democracies are city-states such as Athens and Rome. In contrast, we don’t know of any large-scale kingdom or empire that operated along democratic lines.
For example, when in the fifth century BCE Athens expanded from a city-state into an empire, it did not grant citizenship and political rights to those it conquered. The city of Athens remained a limited democracy, but the much bigger Athenian Empire was ruled autocratically from the center. All the important decisions about taxes, diplomatic alliances, and military expeditions were taken in Athens. Subject lands like the islands of Naxos and Thasos had to obey the orders of the Athenian popular assembly and elected officials, without the Naxians and Thasians being able to vote in that assembly or be elected to office. It was also difficult for Naxos, Thasos, and other subject lands to coordinate a united opposition to the decisions taken in the Athenian center, and if they tried to do so, it would have brought ruthless Athenian reprisals. Information in the Athenian Empire flowed to and from Athens.23
When the Roman Republic built its empire, conquering first the Italian Peninsula and eventually the entire Mediterranean basin, the Romans took a somewhat different course. Rome gradually did extend citizenship to the conquered people. It began by granting citizenship to the inhabitants of Latium, then to the inhabitants of other Italian regions, and finally to inhabitants of even distant provinces like Gallia and Syria. However, as citizenship was extended to more people, the political rights of citizens were simultaneously restricted.
The ancient Romans had a clear understanding of what democracy means, and they were originally fiercely committed to the democratic ideal. After expelling the last king of Rome in 509 BCE, the Romans developed a deep dislike for monarchy and a fear of giving unlimited power to any single individual or institution. Supreme executive power was therefore shared by two consuls who balanced each other. These consuls were chosen by citizens in free elections, held office for a single year, and were additionally checked by the powers of the popular assembly, of the Senate, and of other elected officials like the tribunes.
But when Rome extended citizenship to Latins, Italians, and finally to Gauls and Syrians, the power of the popular assembly, the tribunes, the Senate, and even the two consuls was gradually reduced, until in the late first century BCE the Caesar family established its autocratic rule. Anticipating present-day strongmen like Putin, Augustus didn’t crown himself king, and pretended that Rome was still a republic. The Senate and the popular assembly continued to convene, and every year citizens continued to choose consuls and tribunes. But these institutions were emptied of real power.24
In 212 CE, the emperor Caracalla—the offspring of a Phoenician family from North Africa—took a seemingly momentous step and granted automatic Roman citizenship to all free adult males throughout the vast empire. Rome in the third century CE accordingly had tens of millions of citizens.25 But by that time, all the important decisions were made by a single unelected emperor. While consuls were still ceremonially chosen every year, Caracalla inherited power from his father Septimius Severus, who became emperor by winning a civil war. To cement his rule, the most important step Caracalla took was murdering his brother and rival Geta.
When Caracalla ordered the murder of Geta, decided to devalue the Roman currency, or declared war on the Parthian Empire, he had no need to ask permission from the Roman people. All of Rome’s self-correcting mechanisms had been neutralized long before. If Caracalla made some error in foreign or domestic policy, neither the Senate nor any officials like the consuls or tribunes could intervene to correct it, except by rising in rebellion or assassinating him. And when Caracalla was indeed assassinated in 217, it only led to a new round of civil wars culminating in the rise of new autocrats. Rome in the third century CE, like Russia in the eighteenth century, was, in the words of Madame de Staël, “autocracy tempered by strangulation.”
By the third century CE, not only the Roman Empire but all other major human societies on earth were centralized information networks lacking strong self-correcting mechanisms. This was true of the Parthian and Sassanian Empires in Persia, of the Kushan and Gupta Empires in India, and of China’s Han Empire and its successor Three Kingdoms.26 Thousands of more small-scale societies continued to function democratically in the third century CE and beyond, but it seemed that distributed democratic networks were simply incompatible with large-scale societies.
CAESAR FOR PRESIDENT!
Were large-scale democracies really unworkable in the ancient world? Or did autocrats like Augustus and Caracalla deliberately sabotage them? This question is important not only for our understanding of ancient history but also for our view of democracy’s future in the age of AI. How do we know whether democracies fail because they are undermined by strongmen or because of much deeper structural and technological reasons?
To answer that question, let’s take a closer look at the Roman Empire. The Romans were clearly familiar with the democratic ideal, and it continued to be important to them even after the Caesar family rose to power. Otherwise, Augustus and his heirs would not have bothered to maintain seemingly democratic institutions like the Senate or annual elections to the consulate and other offices. So why did power end up in the hands of an unelected emperor?
In theory, even after Roman citizenship was expanded to tens of millions of people throughout the Mediterranean basin, wasn’t it possible to hold empire-wide elections for the position of emperor? This would surely have required very complicated logistics, and it would have taken several months to learn the results of the elections. But was that really a deal breaker?
The key misconception here is equating democracy with elections. If the Roman Empire wanted to, it could technically have held empire-wide elections for emperor. But the real question we should ask is whether the Roman Empire could have held an ongoing empire-wide political conversation. In present-day North Korea no democratic conversation takes place because people aren’t free to talk, yet we could well imagine a situation when this freedom is guaranteed—as it is in South Korea. In the present-day United States the democratic conversation is endangered by people’s inability to listen to and respect their political rivals, yet this can presumably still be fixed. By contrast, in the Roman Empire there was simply no way to conduct or sustain a democratic conversation, because the technological means to hold such a conversation did not exist.
To hold a conversation, it is not enough to have the freedom to talk and the ability to listen. There are also two technical preconditions. First, people need to be within hearing range of each other. This means that the only way to hold a political conversation in a territory the size of the United States or the Roman Empire is with the help of some kind of information technology that can swiftly convey what people say over long distances.
Second, people need at least a rudimentary understanding of what they are talking about. Otherwise, they are just making noise, not holding a meaningful conversation. People usually have a good understanding of political issues of which they have direct experience. Poor people have many insights about poverty that escape economics professors, and ethnic minorities understand racism in a much more profound way than people who never suffered from it, for example. However, if lived experience were the only way to understand crucial political issues, large-scale political conversations would be impossible. For then every group of people could talk meaningfully only about its own experiences. Even worse, nobody else could understand what they were saying. If lived experience is the sole possible source of knowledge, then merely listening to the insights gained from someone else’s lived experience cannot impart these insights to me.
The only way to have a large-scale political conversation among diverse groups of people is if people can gain some understanding of issues that they have never experienced firsthand. In a large polity, it is a crucial role of the education system and the media to inform people about things they have never faced themselves. If there is no education system or media platforms to perform this role, no meaningful large-scale conversations can take place.
In a small Neolithic town of a few thousand inhabitants people might sometimes have been afraid to say what they thought, or might have refused to listen to their rivals, but it was relatively easy to satisfy the more fundamental technical preconditions for meaningful discourse. First, people lived in proximity to one another, so they could easily meet most other community members and hear their voices. Second, everybody had intimate knowledge of the dangers and opportunities that the town faced. If an enemy war party approached, everyone could see it. If the river flooded the fields, everyone witnessed the economic effects. When people talked about war and hunger, they knew what they were saying.
In the fourth century BCE, the city-state of Rome was still small enough to allow a large percentage of its citizens to congregate in the Forum in times of emergency, listen to respected leaders, and voice their personal views on the matter at hand. When in 390 BCE Gallic invaders attacked Rome, almost everyone lost a relative in the defeat at the Battle of the Allia and lost property when the victorious Gauls then sacked Rome. The desperate Romans appointed Marcus Camillus as dictator. In Rome, the dictator was a public official appointed in times of emergency who had unlimited powers but only for a short predetermined period, following which he was held accountable for his actions. After Camillus led the Romans to victory, everybody could see that the emergency was over, and Camillus stepped down.27
In contrast, by the third century CE, the Roman Empire had a population of between sixty and seventy-five million people,28 spread over five million square kilometers.29 Rome lacked mass communication technology like radio or daily newspapers. Only 10–20 percent of adults had reading skills,30 and there was no organized education system that could inform them about the geography, history, and economy of the empire. True, many people across the empire did share some cultural ideas, such as a strong belief in the superiority of Roman civilization over the barbarians. These shared cultural beliefs were crucial in preserving order and holding the empire together. But their political implications were far from clear, and in times of crisis there was no possibility to hold a public conversation about what should be done.
How could Syrian merchants, British shepherds, and Egyptian villagers converse about the ongoing wars in the Middle East or about the immigration crisis brewing along the Danube? The lack of a meaningful public conversation was not the fault of Augustus, Nero, Caracalla, or any of the other emperors. They didn’t sabotage Roman democracy. Given the size of the empire and the available information technology, democracy was simply unworkable. This was acknowledged already by ancient philosophers like Plato and Aristotle, who argued that democracy can work only in small-scale city-states.31
If the absence of Roman democracy had merely been the fault of particular autocrats, we should have at least seen large-scale democracies flourishing in other places, like in Sassanian Persia, Gupta India, or Han China. But prior to the development of modern information technology, there are no examples of large-scale democracies anywhere.
It should be stressed that in many large-scale autocracies local affairs were often managed democratically. The Roman emperor didn’t have the information needed to micromanage hundreds of cities across the empire, whereas local citizens in each city could continue to hold a meaningful conversation about municipal politics. Consequently, long after the Roman Empire became an autocracy, many of its cities continued to be governed by local assemblies and elected officials. At a time when elections to the consulship in Rome became ceremonial affairs, elections to municipal offices in small cities like Pompeii were hotly contested.
Pompeii was destroyed in the eruption of Vesuvius in 79 CE, during the reign of the emperor Titus. Archaeologists uncovered about fifteen hundred graffiti concerned with various local election campaigns. One coveted office was that of the city’s aedile—the magistrate in charge of maintaining the city’s infrastructure and public buildings.32 Lucretius Fronto’s supporters drew the graffiti “If honest living is thought to be any recommendation, then Lucretius Fronto is worthy of being elected.” One of his opponents, Gaius Julius Polybius, ran with the slogan “Elect Gaius Julius Polybius to the office of aedile. He provides good bread.”
There were also endorsements by religious groups and professional associations, such as “The worshippers of Isis demand the election of Gnaeus Helvius Sabinus” and “All the mule drivers request that you elect Gaius Julius Polybius.” There was dirty work, too. Someone who clearly wasn’t Marcus Cerrinius Vatia drew the graffiti “All the drunkards ask you to elect Marcus Cerrinius Vatia” and “The petty thieves ask you to elect Vatia.”33 Such electioneering indicates that the position of aedile had power in Pompeii and that the aedile was chosen in relatively free and fair elections, rather than appointed by the imperial autocrat in Rome.
Even in empires whose rulers never had any democratic pretensions, democracy could still flourish in local settings. In the Tsarist Empire, for example, the daily lives of millions of villagers were managed by rural communes. Going back at least to the eleventh century, each commune usually included fewer than a thousand people. They were subject to a landlord and bore many obligations to their lord and to the central Tsarist state, but they had considerable autonomy in managing their internal affairs and in deciding how to discharge their external obligations, such as paying taxes and providing military recruits. The commune mediated local disputes, provided emergency relief, enforced social norms, oversaw the distribution of land to individual households, and regulated access to shared resources like forests and pastures. Decisions on important matters were made in communal meetings in which the heads of local households expressed their views and chose the commune’s elder. Resolutions at least tried to reflect the majority’s will.34
In Tsarist villages and Roman cities a form of democracy was possible because a meaningful public conversation was possible. Pompeii was a city of about eleven thousand people in 79 CE,35 so everybody could supposedly judge for themselves whether Lucretius Fronto was an honest man and whether Marcus Cerrinius Vatia was a drunken thief. But democracy at a scale of millions became possible only in the modern age, when mass media changed the nature of large-scale information networks.
MASS MEDIA MAKES MASS DEMOCRACY POSSIBLE
Mass media can be defined as the ability to quickly connect millions of people even when they are separated by large distances. The printing press was a crucial step in that direction. Print made it possible to cheaply and quickly produce large numbers of books and pamphlets, which enabled more people to voice their opinions and be heard over a large territory, even if the process still took time. This sustained some of the first experiments in large-scale democracy, such as the Polish-Lithuanian Commonwealth established in 1569 and the Dutch Republic established in 1579.
Some may contest the characterization of these polities as “democratic,” since only a minority of relatively wealthy citizens enjoyed full political rights. In the Polish-Lithuanian Commonwealth, political rights were reserved for adult male members of the szlachta—the nobility. These numbered up to 300,000 individuals, or about 5 percent of the total adult population.36 One of the szlachta’s prerogatives was to elect the king, but since voting required traveling long distances to a national convention, few exercised their right. In the sixteenth and seventeenth centuries participation in royal elections usually ranged between 3,000 and 7,000 voters, except for the 1669 elections in which 11,271 participated.37 While this hardly sounds democratic in the twenty-first century, it should be remembered that all large-scale democracies until the twentieth century limited political rights to a small circle of relatively wealthy men. Democracy is never a matter of all or nothing. It is a continuum, and late sixteenth-century Poles and Lithuanians explored previously unknown regions of that continuum.
Aside from electing its king, Poland-Lithuania had an elected parliament (the Sejm) that approved or blocked new legislation and had the power to veto royal decisions on taxation and foreign affairs. Moreover, citizens enjoyed a list of inviolable rights such as freedom of assembly and freedom of religion. In the late sixteenth and early seventeenth centuries, when most of Europe suffered from bitter religious conflicts and persecutions, Poland-Lithuania was a tolerant haven, where Catholics, Greek Orthodox, Lutherans, Calvinists, Jews, and even Muslims coexisted in relative harmony.38 In 1616, more than a hundred mosques functioned in the commonwealth.39
In the end, however, the Polish-Lithuanian experiment in decentralization proved to be impractical. The country was Europe’s second-largest state (after Russia), covering almost a million square kilometers and including most of the territory of today’s Poland, Lithuania, Belarus, and Ukraine. It lacked the information, communication, and education systems necessary to hold a meaningful political conversation between Polish aristocrats, Lithuanian noblemen, Ukrainian Cossacks, and Jewish rabbis spread from the Baltic Sea to the Black Sea. Its self-correcting mechanisms were also too costly, paralyzing the power of the central government. In particular, every single Sejm deputy was given the right to veto all parliamentary legislation, which led to political deadlock. The combination of a large and diverse polity with a weak center proved fatal. The commonwealth was torn apart by centrifugal forces, and its pieces were then divided between the centralized autocracies of Russia, Austria, and Prussia.
The Dutch experiment fared better. In some ways the Dutch United Provinces were even less centralized than the Polish-Lithuanian Commonwealth, since they lacked a monarch, and were a union of seven autonomous provinces, which were in turn made up of self-governing towns and cities.40 This decentralized nature is reflected in the plural form of how the country was known abroad—the Netherlands in English, Les Pays-Bas in French, Los Países Bajos in Spanish, and so on.
However, taken together the United Provinces were twenty-five times smaller in landmass than Poland-Lithuania and possessed a much better information, communication, and education system that tied its constituent parts closely together.41 The United Provinces also pioneered a new information technology with a big future. In June 1618 a pamphlet titled Courante uyt Italien, Duytslandt &c. appeared in Amsterdam. As its title indicated, it carried news from the Italian Peninsula, the German lands, and other places. There was nothing remarkable about this particular pamphlet, except that new issues were published in the following weeks, too. They appeared regularly until 1670, when the Courante uyt Italien, Duytslandt &c. merged with other serial pamphlets into the Amsterdamsche Courant, which appeared until 1903, when it was merged into De Telegraaf—the Netherlands’ largest newspaper to this day.42
The newspaper is a periodic pamphlet, and it was different from earlier one-off pamphlets because it had a much stronger self-correcting mechanism. Unlike one-off publications, a weekly or daily newspaper has a chance to correct its mistakes and an incentive to do so in order to win the public’s trust. Shortly after the Courante uyt Italien, Duytslandt &c. appeared, a competing newspaper titled Tijdinghen uyt Verscheyde Quartieren (Tidings from Various Quarters) made its debut. The Courante was generally considered more reliable, because it tried to check its stories before publishing them, and because the Tijdinghen was accused of being overly patriotic and reporting only news favorable to the Netherlands. Nevertheless, both newspapers survived, because, as one reader explained, “one can always find something in one newspaper that is not available in the other.” In the following decades dozens of additional newspapers were published in the Netherlands, which became Europe’s journalistic hub.43
Newspapers that succeeded in gaining widespread trust became the architects and mouthpieces of public opinion. They created a far more informed and engaged public, which changed the nature of politics, first in the Netherlands and later around the world.44 The political influence of newspapers was so crucial that newspaper editors often became political leaders. Jean-Paul Marat rose to power in revolutionary France by founding and editing L’Ami du People; Eduard Bernstein helped create Germany’s Social Democratic Party by editing Der Sozialdemokrat; Vladimir Lenin’s most important position before becoming Soviet dictator was editor of Iskra; and Benito Mussolini rose to fame first as a socialist journalist in Avanti! and later as founder and editor of the firebrand right-wing paper Il Popolo d’Italia.
Newspapers played a crucial role in the formation of early modern democracies like the United Provinces in the Low Countries, the United Kingdom in the British Isles, and the United States in North America. As the names themselves indicate, these were not city-states like ancient Athens and Rome but amalgams of different regions glued together in part by this new information technology. For example, when on December 6, 1825, President John Quincy Adams gave his First Annual Message to the U.S. Congress, the text of the address and summaries of the main points were published over the next weeks by newspapers from Boston to New Orleans (at the time, hundreds of newspapers and magazines were being published in the United States45).
Adams declared his administration’s intentions of initiating numerous federal projects ranging from the construction of roads to the founding of an astronomical observatory, which he poetically named “light-house of the skies.” His speech ignited a fierce public debate, much of it conducted in print between those who supported such “big government” plans as essential for the development of the United States and many who preferred a “small government” approach and saw Adams’s plans as federal overreach and an encroachment on states’ rights.
Northern supporters of the “small government” camp complained that it was unconstitutional for the federal government to tax the citizens of richer states in order to build roads in poorer states. Southerners feared that a federal government that claims the power to build a lighthouse of the sky in their backyard may one day claim the power to free their slaves, too. Adams was accused of harboring dictatorial ambitions, while the erudition and sophistication of his speech were criticized as elitist and disconnected from ordinary Americans. The public debates over the 1825 message to Congress dealt a severe blow to the reputation of the Adams administration and helped pave the way to Adams’s subsequent electoral defeat. In the 1828 presidential elections, Adams lost to Andrew Jackson—a rich slaveholding planter from Tennessee who was successfully rebranded in numerous newspaper columns as “the man of the people” and who claimed that the previous elections were in fact stolen by Adams and by the corrupt Washington elites.46
Newspapers of the time were of course still slow and limited compared with the mass media of today. Newspapers traveled at the pace of a horse or sailboat, and relatively few people read them regularly. There were no newsstands or street vendors, so people had to buy subscriptions, which were expensive; average annual subscriptions cost around one week’s wages for a skilled journeyman. As a result, the total number of subscribers to all U.S. newspapers in 1830 is estimated at just seventy-eight thousand. Since some subscribers were associations or businesses rather than individuals, and since every copy was probably read by several people, it seems reasonable to assume that regular newspaper readership numbered in the hundreds of thousands. But millions more rarely, if ever, read newspapers.47
No wonder that American democracy in those days was a limited affair—and the domain of wealthy white men. In the 1824 elections that brought Adams to power, 1.3 million Americans were theoretically eligible to vote, out of an adult population of about 5 million (or around 25 percent). Only 352,780 people—7 percent of the total adult population—actually made use of their right. Adams didn’t even win a majority of those who voted. Owing to the quirks of the U.S. electoral system, he became president thanks to the support of just 113,122 voters, or not much more than 2 percent of adults, and 1 percent of the total population.48 In Britain at the same time, only about 400,000 people were eligible to vote for Parliament, or around 6 percent of the adult population. Moreover, 30 percent of parliamentary seats were not even contested.49
You may wonder whether we are talking about democracies at all. At a time when the United States had more slaves than voters (more than 1.5 million Americans were enslaved in the early 1820s),50 was the United States really a democracy? This is a question of definitions. As with the late sixteenth-century Polish-Lithuanian Commonwealth, so also with the early nineteenth-century United States, “democracy” is a relative term. As noted earlier, democracy and autocracy aren’t absolutes; they are part of a continuum. In the early nineteenth century, out of all large-scale human societies, the United States was probably the closest to the democratic end of the continuum. Giving 25 percent of adults the right to vote doesn’t sound like much today, but in 1824 that was a far higher percentage than in the Tsarist, Ottoman, or Chinese Empires, in which nobody had the right to vote.51
Besides, as emphasized throughout this chapter, voting is not the only thing that counts. An even more important reason to consider the United States in 1824 a democracy is that compared with most other polities of its day, the new country possessed much stronger self-correcting mechanisms. The Founding Fathers were inspired by ancient Rome—witness the Senate and the Capitol in Washington—and they were well aware that the Roman Republic eventually turned into an autocratic empire. They feared that some American Caesar would do something similar to their republic, and constructed multiple overlapping self-correcting mechanisms, known as the system of checks and balances. One of these was a free press. In ancient Rome, the self-correcting mechanisms stopped functioning as the republic enlarged its territory and population. In the United States, modern information technology combined with freedom of the press helped the self-correcting mechanisms survive even as the country extended from the Atlantic to the Pacific.
It was these self-correcting mechanisms that gradually enabled the United States to expand the franchise, abolish slavery, and turn itself into a more inclusive democracy. As noted in chapter 3, the Founding Fathers committed enormous mistakes—such as endorsing slavery and denying women the vote—but they also provided the tools for their descendants to correct these mistakes. That was their greatest legacy.
THE TWENTIETH CENTURY: MASS DEMOCRACY, BUT ALSO MASS TOTALITARIANISM
Printed newspapers were just the first harbinger of the mass media age. During the nineteenth and twentieth centuries, a long list of new communication and transportation technologies such as the telegraph, telephone, television, radio, trains, steamships, and airplanes supercharged the power of mass media.
When Demosthenes gave a public speech in Athens around 350 BCE, it was aimed primarily at the limited audience actually present in the Athenian agora. When John Quincy Adams gave his First Annual Message in 1825, his words spread at the pace of a horse. When Abraham Lincoln gave his Gettysburg Address on November 19, 1863, telegraphs, locomotives, and steamships conveyed his words much faster throughout the Union and beyond. The very next day The New York Times had already reprinted the speech in full,52 as had numerous other newspapers from The Portland Daily Press in Maine to the Ottumwa Courier in Iowa.53
As befitting a democracy with strong self-correcting mechanisms in place, the president’s speech sparked a lively conversation rather than universal applause. Most newspapers lauded it, but some expressed their doubts. The Chicago Times wrote on November 20 that “the cheek of every American must tingle with shame as he reads the silly, flat and dishwatery utterances” of President Lincoln.54 The Patriot & Union, a local newspaper in Harrisburg, Pennsylvania, also blasted “the silly remarks of the President” and hoped that “the veil of oblivion shall be dropped over them and that they shall be no more repeated or thought of.”55 Though the country was in the midst of a civil war, journalists were free to publicly criticize—and even ridicule—the president.
Fast-forward a century, and things really picked up speed. For the first time in history, new technologies allowed masses of people, spread over vast swaths of territory, to connect in real time. In 1960, about seventy million Americans (39 percent of the total population), dispersed over the North American continent and beyond, watched the Nixon-Kennedy presidential debates live on television, with millions more listening on the radio.56 The only effort viewers and listeners had to make was to press a button while sitting in their homes. Large-scale democracy had now become feasible. Millions of people separated by thousands of kilometers could conduct informed and meaningful public debates about the rapidly evolving issues of the day. By 1960, all adult Americans were theoretically eligible to vote, and close to seventy million (about 64 percent of the electorate) actually did so—though millions of Blacks and other disenfranchised groups were prevented from voting through various voter-suppression schemes.57
As always, we should beware of technological determinism and of concluding that the rise of mass media led to the rise of large-scale democracy. Mass media made large-scale democracy possible, rather than inevitable. And it also made possible other types of regimes. In particular, the new information technologies of the modern age opened the door for large-scale totalitarian regimes. Like Nixon and Kennedy, Stalin and Khrushchev could say something over the radio and be heard instantaneously by hundreds of millions of people from Vladivostok to Kaliningrad. They could also receive daily reports by phone and telegraph from millions of secret police agents and informers. If a newspaper in Vladivostok or Kaliningrad wrote that the supreme leader’s latest speech was silly (as happened to Lincoln’s Gettysburg Address), then everyone involved—from the editor in chief to the typesetters—would likely have received a visit from the KGB.
A BRIEF HISTORY OF TOTALITARIANISM
Totalitarian systems assume their own infallibility, and seek total control over the totality of people’s lives. Before the invention of the telegraph, radio, and other modern information technology, large-scale totalitarian regimes were impossible. Roman emperors, Abbasid caliphs, and Mongol khans were often ruthless autocrats who believed they were infallible, but they did not have the apparatus necessary to impose totalitarian control over large societies. To understand this, we should first clarify the difference between totalitarian regimes and less extreme autocratic regimes. In an autocratic network, there are no legal limits on the will of the ruler, but there are nevertheless a lot of technical limits. In a totalitarian network, many of these technical limits are absent.58
For example, in autocratic regimes like the Roman Empire, the Abbasid Empire, and the Mongol Empire, rulers could usually execute any person who displeased them, and if some law got in their way, they could ignore or change the law. The emperor Nero arranged the murder of his mother, Agrippina, and his wife, Octavia, and forced his mentor Seneca to commit suicide. Nero also executed or exiled some of the most respected and powerful Roman aristocrats merely for voicing dissent or telling jokes about him.59
While autocratic rulers like Nero could execute anyone who did or said something that displeased them, they couldn’t know what most people in their empire were doing or saying. Theoretically, Nero could issue an order that any person in the Roman Empire who criticized or insulted the emperor must be severely punished. Yet there were no technical means for implementing such an order. Roman historians like Tacitus portray Nero as a bloodthirsty tyrant who instigated an unprecedented reign of terror. But this was a very limited type of terror. Although he executed or exiled a number of family members, aristocrats, and senators within his orbit, ordinary Romans in the city’s slums and provincials in distant towns like Jerusalem and Londinium could speak their mind much more freely.60
Modern totalitarian regimes like the Stalinist U.S.S.R. instigated terror on an altogether different scale. Totalitarianism is the attempt to control what every person throughout the country is doing and saying every moment of the day, and potentially even what every person is thinking and feeling. Nero might have dreamed about such powers, but he lacked the means to realize them. Given the limited tax base of the agrarian Roman economy, Nero couldn’t employ many people in his service. He could place informers at the dinner parties of Roman senators, but he had only about 10,000 imperial administrators61 and 350,000 soldiers62 to control the rest of the empire, and he lacked the technology to communicate with them swiftly.
Nero and his fellow emperors had an even bigger problem ensuring the loyalty of the administrators and soldiers they did have on their payroll. No Roman emperor was ever toppled by a democratic revolution like the ones that deposed Louis XVI, Nicolae Ceauşescu, or Hosni Mubarak. Instead, dozens of emperors were assassinated or deposed by their own generals, officials, bodyguards, or family members.63 Nero himself was overthrown by a revolt of the governor of Hispania, Galba. Six months later Galba was ousted by Otho, the governor of Lusitania. Within three months, Otho was deposed by Vittelius, commander of the Rhine army. Vitellius lasted about eight months before he was defeated and killed by Vespasian, commander of the army in Judaea. Being killed by a rebellious subordinate was the biggest occupational hazard not just for Roman emperors but for almost all premodern autocrats.
Emperors, caliphs, shahs, and kings found it a huge challenge to keep their subordinates in check. Rulers consequently focused their attention on controlling the military and the taxation system. Roman emperors had the authority to interfere in the local affairs of any province or city, and they sometimes exercised that authority, but this was usually done in response to a specific petition sent by a local community or official,64 rather than as part of some empire-wide totalitarian Five-Year Plan. If you were a mule driver in Pompeii or a shepherd in Roman Britain, Nero didn’t want to control your daily routines or to police the jokes you told. As long as you paid your taxes and didn’t resist the legions, that was good enough for Nero.
SPARTA AND QIN
Some scholars claim that despite the technological difficulties there were attempts to establish totalitarian regimes in ancient times. The most common example cited is Sparta. According to this interpretation, Spartans were ruled by a totalitarian regime that micromanaged every aspect of their lives—from whom they married to what they ate. However, while the Spartan regime was certainly draconian, it actually included several self-correcting mechanisms that prevented power from being monopolized by a single person or faction. Political authority was divided between two kings, five ephors (senior magistrates), twenty-eight members of the Gerousia council, and the popular assembly. Important decisions—such as whether to go to war—often involved fierce public debates.
Moreover, irrespective of how we evaluate the nature of Sparta’s regime, it is clear that the same technological limitations that confined ancient Athenian democracy to a single city also limited the scope of the Spartan political experiment. After winning the Peloponnesian War, Sparta installed military garrisons and pro-Spartan governments in numerous Greek cities, requiring them to follow its lead in foreign policy and sometimes also pay tribute. But unlike the U.S.S.R. after World War II, Sparta after the Peloponnesian War did not try to expand or export its system. Sparta couldn’t construct an information network big and dense enough to control the lives of ordinary people in every Greek town and village.65
A much more ambitious totalitarian project might have been launched by the Qin dynasty in ancient China (221–206 BCE). After defeating all the other Warring States, the Qin ruler Qin Shi Huang controlled a huge empire with tens of millions of subjects, who belonged to numerous different ethnic groups, spoke diverse languages, and were loyal to various local traditions and elites. To cement its power, the victorious Qin regime tried to dismantle any regional powers that might challenge its authority. It confiscated the lands and wealth of local aristocrats and forced regional elites to move to the imperial capital of Xiangyang, thereby separating them from their power base and monitoring them more easily.
The Qin regime also embarked on a ruthless campaign of centralization and homogenization. It created a new simplified script to be used throughout the empire and standardized coinage, weights, and measurements. It built a road network radiating out of Xiangyang, with standardized rest houses, relay stations, and military checkpoints. People needed written permits in order to enter or leave the capital region or frontier zones. Even the width of axles was standardized to ensure that carts and chariots could run in the same ruts.
Every action, from tilling fields to getting married, was supposed to serve some military need, and the type of military discipline that Rome reserved for the legions was imposed by the Qin on the entire population. The envisioned reach of this system can be exemplified by one Qin law that specified the punishment an official faced if he neglected a granary under his supervision. The law discusses the number of rat holes in the granary that would warrant fining or berating the official. “For three or more rat holes the fine is [the purchase of] one shield [for the army] and for two or fewer [the responsible official] is berated. Three mouse holes are equal to one rat hole.”66
To facilitate this totalitarian system, the Qin attempted to create a militarized social order. Every male subject had to belong to a five-man unit. These units were aggregated into larger formations, from local hamlets (li), through cantons (xiang) and counties (xian), all the way to the large imperial commanderies (jun). People were forbidden to change their residence without permit, to the extent that guests could not even stay overnight at a friend’s house without proper identification and authorization.
Every Qin male subject was also given a rank, just as every soldier in an army has a rank. Obedience to the state resulted in promotion to higher ranks, which brought with it economic and legal privileges, while disobedience could result in demotion or punishment. People in each formation were supposed to supervise one another, and if any individual committed some misdeed, all could be punished for it. Anyone who failed to report a criminal—even their own relatives—would be killed. Those who reported crimes were rewarded with higher ranks and other perks.
It is highly questionable to what extent the regime managed to implement all these totalitarian measures. Bureaucrats writing documents in a government office often invent elaborate rules and regulations, which then turn out to be impractical. Did conscientious government officials really go around the entire Qin Empire counting rat holes in every granary? Were peasants in every remote mountain hamlet really organized into five-man squads? Probably not. Nevertheless, the Qin Empire outdid other ancient empires in its totalitarian ambitions.
The Qin regime even tried to control what its subjects were thinking and feeling. During the Warring States period Chinese thinkers were relatively free to develop myriad ideologies and philosophies, but the Qin adopted the doctrine of Legalism as the official state ideology. Legalism posited that humans were naturally greedy, cruel, and egotistical. It emphasized the need for strict control, argued that punishments and rewards were the most effective means of control, and insisted that state power not be curtailed by any moral consideration. Might was right, and the good of the state was the supreme good.67 The Qin proscribed other philosophies, such as Confucianism and Daoism, which believed humans were more altruistic and which emphasized the importance of virtue rather than violence.68 Books espousing such soft views were banned, as well as books that contradicted the official Qin version of history.
When one scholar argued that Qin Shi Huang should emulate the founder of the ancient Zhou dynasty and decentralize state power, the Qin chief minister, Li Si, countered that scholars should stop criticizing present-day institutions by idealizing the past. The regime ordered the confiscation of all books that romanticized antiquity or otherwise criticized the Qin. Such problematic texts were stored in the imperial library and could be studied only by official scholars.69
The Qin Empire was probably the most ambitious totalitarian experiment in human history prior to the modern age, and its scale and intensity would prove to be its ruin. The attempt to regiment tens of millions of people along military lines, and to monopolize all resources for military purposes, led to severe economic problems, wastefulness, and popular resentment. The regime’s draconian laws, along with its hostility to regional elites and its voracious appetite for taxes and recruits, fanned the flames of this resentment even further. Meanwhile, the limited resources of an ancient agrarian society couldn’t support all the bureaucrats and soldiers that the Qin needed to contain this resentment, and the low efficiency of their information technology made it impossible to control every town and village from distant Xiangyang. Not surprisingly, in 209 BCE a series of revolts broke out, led by regional elites, disgruntled commoners, and even some of the empire’s own newly minted officials.
According to one account, the first serious revolt started when a group of conscripted peasants sent to work in a frontier zone were delayed by rain and flooding. They feared they would be executed for this dereliction of duty, and felt they had nothing to lose. They were quickly joined by numerous other rebels. Just fifteen years after reaching the apogee of power, the Qin Empire collapsed under the weight of its totalitarian ambitions, splintering into eighteen kingdoms.
After several years of war, a new dynasty—the Han—reunited the empire. But the Han then adopted a more realistic, less draconian attitude. Han emperors were certainly autocratic, but they were not totalitarian. They did not recognize any limits on their authority, but they did not try to micromanage everyone’s lives. Instead of following Legalist ideas of surveillance and control, the Han turned to Confucian ideas of encouraging people to act loyally and responsibly out of inner moral convictions. Like their contemporaries in the Roman Empire, Han emperors sought to control only some aspects of society from the center, while leaving considerable autonomy to provincial aristocrats and local communities. Due largely to the limitations imposed by the available information technology, premodern large-scale polities like the Roman and Han Empires gravitated toward nontotalitarian autocracy.70 Full-blown totalitarianism might have been dreamed about by the likes of the Qin, but its implementation had to wait for the development of modern technology.
THE TOTALITARIAN TRINITY
Just as modern technology enabled large-scale democracy, it also made large-scale totalitarianism possible. Beginning in the nineteenth century, the rise of industrial economies allowed governments to employ many more administrators, and new information technologies—such as the telegraph and radio—made it possible to quickly connect and supervise all these administrators. This facilitated an unprecedented concentration of information and power, for those who dreamed about such things.
When the Bolsheviks seized control of Russia after the 1917 revolution, they were driven by exactly such a dream. The Bolsheviks craved unlimited power because they believed they had a messianic mission. Marx taught that for millennia, all human societies were dominated by corrupt elites who oppressed the people. The Bolsheviks claimed they knew how to finally end all oppression and create a perfectly just society on earth. But to do so, they had to overcome numerous enemies and obstacles, which, in turn, required all the power they could get. They refused to countenance any self-correcting mechanisms that might question either their vision or their methods. Like the Catholic Church, the Bolshevik Party was convinced that though its individual members might err, the party itself was always right. Belief in their own infallibility led the Bolsheviks to destroy Russia’s nascent democratic institutions—like elections, independent courts, the free press, and opposition parties—and to create a one-party totalitarian regime. Bolshevik totalitarianism did not start with Stalin. It was evident from the very first days of the revolution. It stemmed from the doctrine of party infallibility, rather than from the personality of Stalin.
In the 1930s and 1940s, Stalin perfected the totalitarian system he inherited. The Stalinist network was composed of three main branches. First, there was the governmental apparatus of state ministries, regional administrations, and regular Red Army units, which in 1939 comprised 1.6 million civilian officials71 and 1.9 million soldiers.72 Second, there was the apparatus of the Communist Party of the Soviet Union and its ubiquitous party cells, which in 1939 included 2.4 million party members.73 Third, there was the secret police: first known as the Cheka, in Stalin’s days it was called the OGPU, NKVD, and MGB, and after Stalin’s death it morphed into the KGB. Its post-Soviet successor organization is known since 1995 as the FSB. In 1937, the NKVD had 270,000 agents and millions of informers.74
The three branches operated in parallel. Just as democracy is maintained by having overlapping self-correcting mechanisms that keep each other in check, modern totalitarianism created overlapping surveillance mechanisms that keep each other in order. The governor of a Soviet province was constantly watched by the local party commissar, and neither of them knew who among their staff was an NKVD informer. A testimony to the effectiveness of the system is that modern totalitarianism largely solved the perennial problem of premodern autocracies—revolts by provincial subordinates. While the U.S.S.R. had its share of court coups, not once did a provincial governor or a Red Army front commander rebel against the center.75 Much of the credit for that goes to the secret police, which kept a close eye on the mass of citizens, on provincial administrators, and even more so on the party and the Red Army.
While in most polities throughout history the army had wielded enormous political power, in twentieth-century totalitarian regimes the regular army ceded much of its clout to the secret police—the information army. In the U.S.S.R., the Cheka, OGPU, NKVD, and KGB lacked the firepower of the Red Army, but had more influence in the Kremlin and could terrorize and purge even the army brass. The East German Stasi and the Romanian Securitate were similarly stronger than the regular armies of these countries.76 In Nazi Germany, the SS was more powerful than the Wehrmacht, and the SS chief, Heinrich Himmler, was higher up the pecking order than Wilhelm Keitel, chief of the Wehrmacht high command.
In none of these cases could the secret police defeat the regular army in traditional warfare, of course; what made the secret police powerful was its command of information. It had the information necessary to preempt a military coup and to arrest the commanders of tank brigades or fighter squadrons before they knew what hit them. During the Stalinist Great Terror of the late 1930s, out of 144,000 Red Army officers about 10 percent were shot or imprisoned by the NKVD. This included 154 of 186 divisional commanders (83 percent), eight of nine admirals (89 percent), thirteen of fifteen full generals (87 percent), and three of five marshals (60 percent).77
The party leadership fared just as badly. Of the revered Old Bolsheviks, people who joined the party before the 1917 revolution, about a third didn’t survive the Great Terror.78 Of the thirty-three men who served on the Politburo between 1919 and 1938, fourteen were shot (42 percent). Of the 139 members and candidate members of the party’s Central Committee in 1934, 98 (70 percent) were shot. Only 2 percent of the delegates who took part in the Seventeenth Party Congress in 1934 evaded execution, imprisonment, expulsion, or demotion, and attended the Eighteenth Party Congress in 1939.79
The secret police—which did all the purging and killing—was itself divided into several competing branches that closely watched and purged each other. Genrikh Yagoda, the NKVD head who orchestrated the beginning of the Great Terror and supervised the killing of hundreds of thousands of victims, was executed in 1938 and replaced by Nikolai Yezhov. Yezhov lasted for two years, killing and imprisoning millions of people before being executed in 1940.
Perhaps most telling is the fate of the thirty-nine people who in 1935 held the rank of general in the NKVD (called commissars of state security in Soviet nomenclature). Thirty-five of them (90 percent) were arrested and shot by 1941, one was assassinated, and one—the head of the NKVD’s Far East regional office—saved himself by defecting to Japan, but was killed by the Japanese in 1945. Of the original cohort of thirty-nine NKVD generals, only two men were left standing by the end of World War II. The remorseless logic of totalitarianism eventually caught up with them too. During the power struggles that followed Stalin’s death in 1953, one of them was shot, while the other was consigned to a psychiatric hospital, where he died in 1960.80 Serving as an NKVD general in Stalin’s day was one of the most dangerous jobs in the world. At a time when American democracy was improving its many self-correcting mechanisms, Soviet totalitarianism was refining its triple self-surveilling and self-terrorizing apparatus.
TOTAL CONTROL
Totalitarian regimes are based on controlling the flow of information and are suspicious of any independent channels of information. When military officers, state officials, or ordinary citizens exchange information, they can build trust. If they come to trust each other, they can organize resistance to the regime. Therefore, a key tenet of totalitarian regimes is that wherever people meet and exchange information, the regime should be there too, to keep an eye on them. In the 1930s, this was one principle that Hitler and Stalin shared.
On March 31, 1933, two months after Hitler became chancellor, the Nazis passed the Coordination Act (Gleichschaltungsgesetz). This stipulated that by April 30, 1933, all political, social, and cultural organizations throughout Germany—from municipalities to football clubs and local choirs—must be run according to Nazi ideology, as organs of the Nazi state. It upended life in every city and hamlet in Germany.
For example, in the small Alpine village of Oberstdorf, the democratically elected municipal council met for the last time on April 21, 1933, and three days later it was replaced by an unelected Nazi council that appointed a Nazi mayor. Since the Nazis alone allegedly knew what the people really wanted, who other than Nazis could implement the people’s will? Oberstdorf also had about fifty associations and clubs, ranging from a beekeeping society to an alpinist club. They all had to conform to the Coordination Act, adjusting their boards, membership, and statutes to Nazi demands, hoisting the swastika flag, and concluding every meeting with the “Horst Wessel Song,” the Nazi Party’s anthem. On April 6, 1933, the Oberstdorf fishing society banned Jews from its ranks. None of the thirty-two members was Jewish, but they felt they had to prove their Aryan credentials to the new regime.81
Things were even more extreme in Stalin’s U.S.S.R. Whereas the Nazis still allowed church organizations and private businesses some partial freedom of action, the Soviets made no exceptions. By 1928 and the launch of the first Five-Year Plan, there were government officials, party functionaries, and secret police informants in every neighborhood and village, and between them they controlled every aspect of life: all businesses from power plants to cabbage farms; all newspapers and radio stations; all universities, schools, and youth groups; all hospitals and clinics; all voluntary and religious organizations; all sporting and scientific associations; all parks, museums, and cinemas.
If a dozen people came together to play football, hike in the woods, or do some charity work, the party and the secret police had to be there too, represented by the local party cell or NKVD agent. The speed and efficiency of modern information technology meant that all these party cells and NKVD agents were always just a telegram or phone call away from Moscow. Information about suspicious persons and activities was fed into a countrywide, cross-referenced system of card catalogs. Known as kartoteki, these catalogs contained information from work records, police files, residence cards, and other forms of social registrations and, by the 1930s, had become the primary mechanism for surveilling and controlling the Soviet population.82
This made it feasible for Stalin to seek control over the totality of Soviet life. One crucial example was the campaign to collectivize Soviet farming. For centuries, economic, social, and private life in the thousands of villages of the sprawling Tsarist Empire was managed by several traditional institutions: the local commune, the parish church, the private farm, the local market, and above all the family. In the mid-1920s, the Soviet Union was still an overwhelmingly agrarian economy. About 82 percent of the total population lived in villages, and 83 percent of the workforce was engaged in farming.83 But if each peasant family made its own decisions about what to grow, what to buy, and how much to charge for their produce, it greatly limited the ability of Moscow officials to themselves plan and control social and economic activities. What if the officials decided on a major agrarian reform, but the peasant families rejected it? So when in 1928 the Soviets came up with their first Five-Year Plan for the development of the Soviet Union, the most important item on the agenda was to collectivize farming.
The idea was that in every village all the families would join a kolkhoz—a collective farm. They would hand over to the kolkhoz all their property—land, houses, horses, cows, shovels, pitchforks. They would work together for the kolkhoz, and in return the kolkhoz would provide for all their needs, from housing and education to food and health care. The kolkhoz would also decide—based on orders from Moscow—whether they should grow cabbages or turnips; whether to invest in a tractor or a school; and who would work in the dairy farm, the tannery, and the clinic. The result, thought the Moscow masterminds, would be the first perfectly just and equal society in human history.
They were similarly convinced of the economic advantages of their proposed system, thinking that the kolkhoz would enjoy economy of scale. For example, when every peasant family had but a small strip of land, it made little sense to buy a tractor to plow it, and in any case most families couldn’t afford a tractor. Once all land was held communally, it could be cultivated far more efficiently using modern machinery. In addition, the kolkhoz was supposed to benefit from the wisdom of modern science. Instead of every peasant deciding on production methods on the basis of old traditions and groundless superstitions, state experts with university degrees from institutions like the Lenin All-Union Academy of Agricultural Sciences would make the crucial decisions.
To the planners in Moscow, it sounded wonderful. They expected a 50 percent increase in agricultural production by 1931.84 And if in the process the old village hierarchies and inequalities were bulldozed, all the better. To most peasants, however, it sounded terrible. They didn’t trust the Moscow planners or the new kolkhoz system. They did not want to give up their old way of life or their private property. Villagers slaughtered cows and horses instead of handing them to the kolkhoz. Their motivation to work dwindled. People made less effort plowing fields that belonged to everyone than plowing fields that belonged to their own family. Passive resistance was ubiquitous, sometimes flaring into violent clashes. Whereas Soviet planners expected to harvest ninety-eight million tons of grain in 1931, production was only sixty-nine million, according to official data, and might have been as low as fifty-seven million tons in reality. The 1932 harvest was even worse.85
The state reacted with fury. Between 1929 and 1936, food confiscation, government neglect, and man-made famines (resulting from government policy rather than a natural disaster) claimed the lives of between 4.5 and 8.5 million people.86 Millions of additional peasants were declared enemies of the state and deported or imprisoned. The most basic institutions of peasant life—the family, the church, the local community—were terrorized and dismantled. In the name of justice, equality, and the will of the people, the collectivization campaign annihilated anything that stood in its way. In the first two months of 1930 alone, about 60 million peasants in more than 100,000 villages were herded into collective farms.87 In June 1929, only 4 percent of Soviet peasant households had belonged to collective farms. By March 1930 the figure had risen to 57 percent. By April 1937, 97 percent of households in the countryside had been confined to the 235,000 Soviet collective farms.88 In just seven years, then, a way of life that had existed for centuries had been replaced by the totalitarian brainchild of a few Moscow bureaucrats.
THE KULAKS
It is worthwhile to delve a little deeper into the history of Soviet collectivization. For it was a tragedy that bears some resemblance to earlier catastrophes in human history—like the European witch-hunt craze—and at the same time foreshadows some of the biggest dangers posed by twenty-first-century technology and its faith in supposedly scientific data.
When their efforts to collectivize farming encountered resistance and led to economic disaster, Moscow bureaucrats and mythmakers took a page from Kramer’s Hammer of the Witches. I don’t wish to imply the Soviets actually read the book, but they too invented a global conspiracy and created an entire non-existing category of enemies. In the 1930s Soviet authorities repeatedly blamed the disasters afflicting the Soviet economy on a counterrevolutionary cabal whose chief agents were the “kulaks” or “capitalist farmers.” Just as in Kramer’s imagination witches serving Satan conjured hailstorms that destroyed crops, so in the Stalinist imagination kulaks beholden to global capitalism sabotaged the Soviet economy.
In theory, kulaks were an objective socioeconomic category, defined by analyzing empirical data on things like property, income, capital, and wages. Soviet officials could allegedly identify kulaks by counting things. If most people in a village had only one cow, then the few families who had three cows were considered kulaks. If most people in a village didn’t hire any labor, but one family hired two workers during harvest time, this was a kulak family. Being a kulak meant not only that you possessed a certain amount of property but also that you possessed certain personality traits. According to the supposedly infallible Marxist doctrine, people’s material conditions determined their social and spiritual character. Since kulaks allegedly engaged in capitalist exploitation, it was a scientific fact (according to Marxist thinking) that they were greedy, selfish, and unreliable—and so were their children. Discovering that someone was a kulak ostensibly revealed something profound about their fundamental nature.
On December 27, 1929, Stalin declared that the Soviet state should seek “the liquidation of the kulaks as a class,”89 and immediately galvanized the party and the secret police to realize that ambitious and murderous aim. Early modern European witch-hunters worked in autocratic societies that lacked modern information technology; therefore, it took them three centuries to kill fifty thousand alleged witches. In contrast, Soviet kulak hunters were working in a totalitarian society that had at its disposal technologies such as telegraphs, trains, telephones, and radios—as well as a sprawling bureaucracy. They decided that two years would suffice to “liquidate” millions of kulaks.90
Soviet officials began by assessing how many kulaks there must be in the U.S.S.R. Based on existing data—such as tax records, employment records, and the 1926 Soviet census—they decided that kulaks constituted 3–5 percent of the rural population.91 On January 30, 1930, just one month after Stalin’s speech, a Politburo decree translated his vague vision into a much more detailed plan of action. The decree included target numbers for the liquidation of kulaks in each major agricultural region.92 Regional authorities then made their own estimates of the number of kulaks in each county under their jurisdiction. Eventually, specific quotas were assigned to rural soviets (local administrative units, typically comprising a handful of villages). Often, local officials inflated the numbers along the way, to prove their zeal. Each rural soviet then had to identify the stated number of kulak households in the villages under its purview. These people were expelled from their homes, and—according to the administrative category to which they belonged—resettled elsewhere, incarcerated in concentration camps, or condemned to death.93
How exactly did Soviet officials tell who was a kulak? In some villages, local party members made a conscientious effort to identify kulaks by objective measures, such as the amount of property they owned. It was often the most hardworking and efficient farmers who were stigmatized and expelled. In some villages local communists used the opportunity to get rid of their personal enemies. Some villages simply drew lots on who would be considered a kulak. Other villages held communal meetings to vote on the matter and often chose isolated farmers, widows, old people, and other “expendables” (exactly the sorts of people who in early modern Europe were most likely to be branded witches).94
The absurdity of the entire operation is manifested in the case of the Streletsky family from the Kurgan region of Siberia. Dmitry Streletsky, who was then a teenager, recalled years later how his family was branded kulaks and selected for liquidation. “Serkov, the chairman of the village Soviet who deported us, explained: ‘I have received an order [from the district party committee] to find 17 kulak families for deportation. I formed a Committee of the Poor and we sat through the night to choose the families. There is no one in the village who is rich enough to qualify, and not many old people, so we simply chose the 17 families. You were chosen. Please don’t take it personally. What else could I do?’ ”95 If anyone dared object to the madness of the system, they were promptly denounced as kulaks and counterrevolutionaries and would themselves be liquidated.
Altogether, some five million kulaks would be expelled from their homes by 1933. As many as thirty thousand heads of households were shot. The more fortunate victims were resettled in their district of origin or became vagrant workers in the big cities, while about two million were either exiled to remote inhospitable regions or incarcerated as state slaves in labor camps.96 Numerous important and notorious state projects—such as the construction of the White Sea Canal and the development of mines in the Arctic regions—were accomplished with the labor of millions of prisoners, many of them kulaks. It was one of the fastest and largest enslavement campaigns in human history.97 Once branded a kulak, a person could not get rid of the stigma. Government agencies, party organs, and secret police documents recorded who was a kulak in a labyrinthian system of kartoteki catalogs, archives, and internal passports.
Kulak status even passed to the next generation, with devastating consequences. Kulak children were refused entrance to communist youth groups, the Red Army, universities, and prestigious areas of employment.98 In her 1997 memoirs, Antonina Golovina recalled how her family was deported from their ancestral village as kulaks and sent to live in the town of Pestovo. The boys in her new school regularly taunted her. On one occasion, a senior teacher told the eleven-year-old Antonina to stand up in front of all the other children, and began abusing her mercilessly, shouting that “her sort were enemies of the people, wretched kulaks! You certainly deserved to be deported, I hope you’re all exterminated!” Antonina wrote that this was the defining moment of her life. “I had this feeling in my gut that we [kulaks] were different from the rest, that we were criminals.” She never got over it.99
Like the ten-year-old “witch” Hansel Pappenheimer, the eleven-year-old “kulak” Antonina Golovina found herself cast into an intersubjective category invented by human mythmakers and imposed by ubiquitous bureaucrats. The mountains of information collected by Soviet bureaucrats about the kulaks wasn’t the objective truth about them, but it imposed a new intersubjective Soviet truth. Knowing that someone was a kulak was one of the most important things to know about a Soviet person, even though the label was entirely bogus.
ONE BIG HAPPY SOVIET FAMILY
The Stalinist regime would go on to attempt something even more ambitious than the mass dismantling of private family farms. It set out to dismantle the family itself. Unlike Roman emperors or Russian tsars, Stalin tried to insert himself even into the most intimate human relationships, coming between parents and children. Family ties were considered the bedrock of corruption, inequality, and antiparty activities. Soviet children were therefore taught to worship Stalin as their real father and to inform on their biological parents if they criticized Stalin or the Communist Party.
Starting in 1932, the Soviet propaganda machine created a veritable cult around the figure of Pavlik Morozov—a thirteen-year-old boy from the Siberian village of Gerasimovka. In autumn 1931, Pavlik informed the secret police that his father, Trofim—the chairman of the village soviet—was selling false papers to kulak exiles. During the subsequent trial, when Trofim shouted to Pavlik, “It’s me, your father,” the boy retorted, “Yes, he used to be my father, but I no longer consider him my father.” Trofim was sent to a labor camp and later shot. In September 1932, Pavlik was found murdered, and Soviet authorities arrested and executed five of his family members, who allegedly killed him in revenge for the denunciation. The real story was far more complicated, but it didn’t matter to the Soviet press. Pavlik became a martyr, and millions of Soviet children were taught to emulate him.100 Many did.
For example, in 1934 a thirteen-year-old boy called Pronia Kolibin told the authorities that his hungry mother stole grain from the kolkhoz fields. His mother was arrested and presumably shot. Pronia was rewarded with a cash prize and a lot of positive media attention. The party organ Pravda published a poem Pronia wrote. Two of its lines read, “You are a wrecker, Mother / I can live with you no more.”101
The Soviet attempt to control the family was reflected in a dark joke told in Stalin’s day. Stalin visits a factory undercover, and conversing with a worker, he asks the man, “Who is your father?” “Stalin,” replies the worker. “Who is your mother?” “The Soviet Union,” the man responds. “And what do you want to be?” “An orphan.”102
At the time you could easily lose your liberty or your life for telling this joke, even if you told it in your own home to your closest family members. The most important lesson Soviet parents taught their children wasn’t loyalty to the party or to Stalin. It was “keep your mouth shut.”103 Few things in the Soviet Union were as dangerous as holding an open conversation.
PARTY AND CHURCH
You may wonder whether modern totalitarian institutions like the Nazi Party or the Soviet Communist Party were really all that different from earlier institutions like the Christian churches. After all, churches too believed in their infallibility, had priestly agents everywhere, and sought to control the daily life of people down to their diet and sexual habits. Shouldn’t we see the Catholic Church or the Eastern Orthodox Church as totalitarian institutions? And doesn’t this undermine the thesis that totalitarianism was made possible only by modern information technology?
There are, however, several major differences between modern totalitarianism and premodern churches. First, as noted earlier, modern totalitarianism has worked by deploying several overlapping surveillance mechanisms that keep each other in order. The party is never alone; it works alongside state organs, on the one side, and the secret police, on the other. In contrast, in most medieval European kingdoms the Catholic Church was an independent institution that often clashed with the state institutions instead of reinforcing them. Consequently, the church was perhaps the most important check on the power of European autocrats.
For example, when in the “Investiture Controversy” of the 1070s the emperor Henry IV asserted that as emperor he had the final say on the appointment of bishops, abbots, and other important church officials, Pope Gregory VII mobilized resistance and eventually forced the emperor to surrender. On January 25, 1077, Henry reached Canossa castle, where the pope was lodging, to offer his submission and apology. The pope refused to open the gates, and Henry waited in the snow outside, barefoot and hungry. After three days, the pope finally opened the gates to the emperor, who begged forgiveness.104
An analogous clash in a modern totalitarian country is unthinkable. The whole idea of totalitarianism is to prevent any separation of powers. In the Soviet Union, state and party reinforced each other, and Stalin was the de facto head of both. There could be no Soviet “Investiture Controversy,” because Stalin had final say about all appointments to both party positions and state functions. He decided both who would be general secretary of the Communist Party of Georgia and who would be foreign minister of the Soviet Union.
Another important difference is that medieval churches tended to be traditionalist organizations that resisted change, while modern totalitarian parties have tended to be revolutionary organizations demanding change. A premodern church built its power gradually by developing its structure and traditions over centuries. A king or a pope who wanted to swiftly revolutionize society was therefore likely to encounter stiff resistance from church members and ordinary believers.
For example, in the eighth and ninth centuries a series of Byzantine emperors sought to forbid the veneration of icons, which seemed to them idolatrous. They pointed to many passages in the Bible, most notably the Second Commandment, that forbade making any graven images. While Christian churches traditionally interpreted the Second Commandment in a way that allowed the veneration of icons, emperors like Constantine V argued that this was a mistake and that disasters like Christian defeats by the armies of Islam were due to God’s wrath over the worship of icons. In 754 more than three hundred bishops assembled in the Council of Hieria to support Constantine’s iconoclastic position.
Compared with Stalin’s collectivization campaign, this was a minor reform. Families and villages were required to give up their icons, but not their private property or their children. Yet Byzantine iconoclasm met with widespread resistance. Unlike the participants in the Council of Hieria, many ordinary priests, monks, and believers were deeply attached to their icons. The resulting struggle ripped apart Byzantine society until the emperors conceded defeat and reversed course.105 Constantine V was later vilified by Byzantine historians as “Constantine the Shitty” (Koprónimos), and a story was spread about him that he defecated during his baptism.106
Unlike premodern churches, which developed slowly over many centuries and therefore tended to be conservative and suspicious of rapid changes, modern totalitarian parties like the Nazi Party and the Soviet Communist Party were organized within a single generation around the promise to quickly revolutionize society. They didn’t have centuries-old traditions and structures to defend. When their leaders conceived some ambitious plan to smash existing traditions and structures, party members typically fell in line.
Perhaps most important of all, premodern churches could not become tools of totalitarian control because they themselves suffered from the same limitations as all other premodern organizations. While they had local agents everywhere, in the shape of parish priests, monks, and itinerant preachers, the difficulty of transmitting and processing information meant that church leaders knew little about what was going on in remote communities, and local priests had a large degree of autonomy. Consequently, churches tended to be local affairs. People in every province and village often venerated local saints, upheld local traditions, performed local rites, and might even have had local doctrinal ideas that differed from the official line.107 If the pope in Rome wanted to do something about an independent-minded priest in a remote Polish parish, he had to send a letter to the archbishop of Gniezno, who had to instruct the relevant bishop, who had to send someone to intervene in the parish. That might take months, and there was ample opportunity for the archbishop, bishop, and other intermediaries to reinterpret or even “mislay” the pope’s orders.108
Churches became more totalitarian institutions only in the late modern era, when modern information technologies became available. We tend to think of popes as medieval relics, but actually they are masters of modern technology. In the eighteenth century, the pope had little control over the worldwide Catholic Church and was reduced to the status of a local Italian princeling, fighting other Italian powers for control of Bologna or Ferrara. With the advent of radio, popes became some of the most powerful people on the planet. Pope John Paul II could sit in the Vatican and speak directly to millions of Catholics from Poland to the Philippines, without any archbishop, bishop, or parish priest able to twist or hide his words.109
HOW INFORMATION FLOWS
We see then that the new information technology of the late modern era gave rise to both large-scale democracy and large-scale totalitarianism. But there were crucial differences between how the two systems used information technology. As noted earlier, democracy encourages information to flow through many independent channels rather than only through the center, and it allows many independent nodes to process the information and make decisions by themselves. Information freely circulates between private businesses, private media organizations, municipalities, sports associations, charities, families, and individuals—without ever passing through the office of a government minister.
In contrast, totalitarianism wants all information to pass through the central hub and doesn’t want any independent institutions making decisions on their own. True, totalitarianism does have its tripartite apparatus of government, party, and secret police. But the whole point of this parallel apparatus is to prevent the emergence of any independent power that might challenge the center. When government officials, party members, and secret police agents constantly keep tabs on one another, opposing the center is extremely dangerous.
As contrasting types of information networks, democracy and totalitarianism both have their advantages and disadvantages. The biggest advantage of the centralized totalitarian network is that it is extremely orderly, which means it can make decisions quickly and enforce them ruthlessly. Especially during emergencies like wars and epidemics, centralized networks can move much faster and further than distributed networks.
But hyper-centralized information networks also suffer from several big disadvantages. Since they don’t allow information to flow anywhere except through the official channels, if the official channels are blocked, the information cannot find an alternative means of transmission. And official channels are often blocked.
One common reason why official channels might be blocked is that fearful subordinates hide bad news from their superiors. In Jaroslav Hašek’s Good Soldier Švejk—a satirical novel about the Austro-Hungarian Empire during World War I—Hašek describes how the Austrian authorities were worried about waning morale among the civilian population. They therefore bombarded local police stations with orders to hire informers, collect data, and report to headquarters on the population’s loyalty. To be as scientific as possible, headquarters invented an ingenious loyalty grade: I.a, I.b, I.c; II.a, II.b, II.c; III.a, III.b, III.c; IV.a, IV.b, IV.c. They sent to the local police stations detailed explanations about each grade, and an official form that had to be filled daily. Police sergeants across the country dutifully filled out the forms and sent them back to headquarters. Without exception, all of them always reported a I.a morale level; to do otherwise was to invite rebuke, demotion, or worse.110
Another common reason why official channels fail to pass on information is to preserve order. Because the chief aim of totalitarian information networks is to produce order rather than discover truth, when alarming information threatens to undermine social order, totalitarian regimes often suppress it. It is relatively easy for them to do so, because they control all the information channels.
For example, when the Chernobyl nuclear reactor exploded on April 26, 1986, Soviet authorities suppressed all news of the disaster. Both Soviet citizens and foreign countries were kept oblivious of the danger, and so took no steps to protect themselves from radiation. When some Soviet officials in Chernobyl and the nearby town of Pripyat requested to immediately evacuate nearby population centers, their superiors’ chief concern was to avoid the spread of alarming news, so they not only forbade evacuation but also cut the phone lines and warned employees in the nuclear facility not to talk about the disaster.
Two days after the meltdown Swedish scientists noticed that radiation levels in Sweden, more than twelve hundred kilometers from Chernobyl, were abnormally high. Only after Western governments and the Western press broke the news did the Soviets acknowledge that anything was amiss. Even then they continued to hide from their own citizens the full magnitude of the catastrophe and hesitated to request advice and assistance from abroad. Millions of people in Ukraine, Belarus, and Russia paid with their health. When the Soviet authorities later investigated the disaster, their priority was to deflect blame rather than understand the causes and prevent future accidents.111
In 2019, I went on a tour of Chernobyl. The Ukrainian guide who explained what led to the nuclear accident said something that stuck in my mind. “Americans grow up with the idea that questions lead to answers,” he said. “But Soviet citizens grew up with the idea that questions lead to trouble.”
Naturally, leaders of democratic countries also don’t relish bad news. But in a distributed democratic network, when official lines of communication are blocked, information flows through alternative channels. For example, if an American official decides against telling the president about an unfolding disaster, that news will nevertheless be published by The Washington Post, and if The Washington Post too deliberately withholds the information, The Wall Street Journal or The New York Times will break the story. The business model of independent media—forever chasing the next scoop—all but guarantees publication.
When, on March 28, 1979, there was a severe accident in the Three Mile Island nuclear reactor in Pennsylvania, the news quickly spread without any need for international intervention. The accident began around 4:00 a.m. and was noticed by 6:30 a.m. An emergency was declared in the facility at 6:56, and at 7:02 the accident was reported to the Pennsylvania Emergency Management Agency. During the following hour the governor of Pennsylvania, the lieutenant governor, and the civil defense authorities were informed. An official press conference was scheduled for 10:00 a.m. However, a traffic reporter at a local Harrisburg radio station picked up a police notice on events, and the station aired a brief report at 8:25 a.m. In the U.S.S.R. such an initiative by an independent radio station was unthinkable, but in the United States it was unremarkable. By 9:00 a.m. the Associated Press issued a bulletin. Though it took days for the full details to emerge, American citizens learned about the accident two hours after it was first noticed. Subsequent investigations by government agencies, NGOs, academics, and the press uncovered not just the immediate causes of the accident but also its deeper structural causes, which helped improve the safety of nuclear technology worldwide. Indeed, some of the lessons of Three Mile Island, which were openly shared even with the Soviets, contributed to mitigating the Chernobyl disaster.112
NOBODY’S PERFECT
Totalitarian and authoritarian networks face other problems besides blocked arteries. First and foremost, as we have already established, their self-correcting mechanisms tend to be very weak. Since they believe they are infallible, they see little need for such mechanisms, and since they are afraid of any independent institution that might challenge them, they lack free courts, media outlets, or research centers. Consequently, there is nobody to expose and correct the daily abuses of power that characterize all governments. The leader may occasionally proclaim an anticorruption campaign, but in nondemocratic systems these often turn out to be little more than a smoke screen for one regime faction to purge another faction.113
And what happens if the leader himself embezzles public funds or makes some disastrous policy mistake? Nobody can challenge the leader, and on his own initiative the leader—being a human being—may well refuse to admit any mistakes. Instead, he is likely to blame all problems on “foreign enemies,” “internal traitors,” or “corrupt subordinates” and demand even more power in order to deal with the alleged malefactors.
For example, we mentioned in the previous chapter that Stalin adopted the bogus theory of Lysenkoism as the state doctrine on evolution. The results were catastrophic. Neglect of Darwinian models, and attempts by Lysenkoist agronomists to create super-crops, set back Soviet genetic research for decades and undermined Soviet agriculture. Soviet experts who suggested abandoning Lysenkoism and accepting Darwinism risked the gulag or a bullet to the head. Lysenkoism’s legacy haunted Soviet science and agronomy for decades and was one reason why by the early 1970s the U.S.S.R. ceased to be a major exporter of grain and became a net importer, despite its vast fertile lands.114
The same dynamic characterized many other fields of activity. For instance, during the 1930s Soviet industry suffered from numerous accidents. This was largely the fault of the Soviet bosses in Moscow, who set up almost impossible goals for industrialization and viewed any failure to achieve them as treason. In the effort to fulfill the ambitious goals, safety measures and quality-control checks were abandoned, and experts who advised prudence were often reprimanded or shot. The result was a wave of industrial accidents, dysfunctional products, and wasted efforts. Instead of taking responsibility, Moscow concluded that this must be the handiwork of the global Trotskyite-imperialist conspiracy of saboteurs and terrorists bent on derailing the Soviet enterprise. Rather than slow down and adopt safety regulations, the bosses redoubled the terror and shot more people.
A famous case in point was Pavel Rychagov. He was one of the best and bravest Soviet pilots, leading missions to help the Republicans in the Spanish Civil War and the Chinese against the Japanese invasion. He quickly rose through the ranks, becoming commander of the Soviet air force in August 1940, at age twenty-nine. But the courage that helped Rychagov shoot down Nazi airplanes in Spain landed him in deep trouble in Moscow. The Soviet air force suffered from numerous accidents, which the Politburo blamed on lack of discipline and deliberate sabotage by anti-Soviet conspiracies. Rychagov, however, wouldn’t buy this official line. As a frontline pilot, he knew the truth. He flatly told Stalin that pilots were being forced to operate hastily designed and badly produced airplanes, which he compared to flying “in coffins.” Two days after Hitler invaded the Soviet Union, as the Red Army was collapsing and Stalin was desperately hunting for scapegoats, Rychagov was arrested for “being a member of an anti-Soviet conspiratorial organization and carrying out enemy work aimed at weakening the power of the Red Army.” His wife was also arrested, because she allegedly knew about his “Trotskyist ties with the military conspirators.” They were executed on October 28, 1941.115
The real saboteur who wrecked Soviet military efforts wasn’t Rychagov, of course, but Stalin himself. For years, Stalin feared that a clash to the death with Nazi Germany was likely and built the world’s biggest war machine to prepare for it. But he hamstrung this machine both diplomatically and psychologically.
On the diplomatic level, in 1939–41, Stalin gambled that he could goad the “capitalists” to fight and exhaust one another while the U.S.S.R. nurtured and even increased its power. He therefore made a pact with Hitler in 1939 and allowed the Germans to conquer much of Poland and western Europe, while the U.S.S.R. attacked or alienated almost all its neighbors. In 1939–40 the Soviets invaded and occupied eastern Poland; annexed Estonia, Latvia, and Lithuania; and conquered parts of Finland and Romania. Finland and Romania, which could have acted as neutral buffers on the U.S.S.R.’s flanks, consequently became implacable enemies. Even in the spring of 1941, Stalin still refused to make a preemptive alliance with Britain and made no move to hinder the Nazi conquest of Yugoslavia and Greece, thereby losing his last potential allies on the European continent. When Hitler struck on June 22, 1941, the U.S.S.R. was isolated.
In theory, the war machine Stalin built could have handled the Nazi onslaught even in isolation. The territories conquered since 1939 provided depth to Soviet defenses, and the Soviet military advantage seemed overwhelming. On the first day of the invasion the Soviets had 15,000 tanks, 15,000 warplanes, and 37,000 artillery pieces on the European front, facing 3,300 German tanks, 2,250 warplanes, and 7,146 guns.116 But in one of history’s greatest military catastrophes, within a month the Soviets lost 11,700 tanks (78 percent), 10,000 warplanes (67 percent), and 19,000 artillery pieces (51 percent).117 Stalin also lost all the territories he conquered in 1939–40 and much of the Soviet heartland. By July 16 the Germans were in Smolensk, 370 kilometers from Moscow.
The causes of the debacle have been debated ever since 1941, but most scholars agree that a significant factor was the psychological costs of Stalinism. For years the regime terrorized its people, punished initiative and individuality, and encouraged submissiveness and conformity. This undermined the soldiers’ motivation. Especially in the first months of the war, before the horrors of Nazi rule were fully realized, Red Army soldiers surrendered in huge numbers; between three and four million were taken captive by the end of 1941.118 Even when they fought tenaciously, Red Army units suffered from a lack of initiative. Officers who had survived the purges were fearful to take independent actions, while younger officers often lacked adequate training. Frequently starved of information and scapegoated for failures, commanders also had to cope with political commissars who could dispute their decisions. The safest course was to wait for orders from on high and then slavishly follow them even when they made little military sense.119
Despite the disasters of 1941 and of the spring and summer of 1942, the Soviet state did not collapse the way Hitler hoped. As the Red Army and the Soviet leadership assimilated the lessons learned from the first year of struggle, the political center in Moscow loosened its hold. The power of political commissars was restricted, while professional officers were encouraged to assume greater responsibility and take more initiatives.120 Stalin also reversed his geopolitical mistakes of 1939–41 and allied the U.S.S.R. with Britain and the United States. Red Army initiative, Western assistance, and the realization of what Nazi rule would mean for the people of the U.S.S.R. turned the tide of war.
Once victory was secured in 1945, however, Stalin initiated new waves of terror, purging more independent-minded officers and officials and again encouraging blind obedience.121 Ironically, Stalin’s own death eight years later was partly the result of an information network that prioritized order and disregarded truth. In 1951–53 the U.S.S.R. experienced yet another witch hunt. Soviet mythmakers fabricated a conspiracy theory that Jewish doctors were systematically murdering leading regime members, under the guise of giving them medical care. The theory alleged that the doctors were the agents of a global American-Zionist plot, working in collaboration with traitors in the secret police. By early 1953 hundreds of doctors and secret police officials, including the head of the secret police himself, were arrested, tortured, and forced to name accomplices. The conspiracy theory—a Soviet twist on the Protocols of the Elders of Zion—merged with age-old blood-libel accusations, and rumors began circulating that Jewish doctors were not just murdering Soviet leaders but also killing babies in hospitals. Since a large proportion of Soviet doctors were Jews, people began fearing doctors in general.122
Just as the hysteria about “the doctors’ plot” was reaching its climax, Stalin had a stroke on March 1, 1953. He collapsed in his dacha, wet himself, and lay for hours in his soiled pajamas, unable to call for help. At around 10:30 p.m. a guard found the courage to enter the inner sanctum of world communism, where he discovered the leader on the floor. By 3:00 a.m. on March 2, Politburo members arrived at the dacha and debated what to do. For several hours more, nobody dared call a doctor. What if Stalin were to regain consciousness, and open his eyes only to see a doctor—a doctor!—hovering over his bed? He would surely think this was a plot to murder him and would have those responsible shot. Stalin’s personal physician wasn’t present, because he was at the time in a basement cell of the Lubyanka prison—undergoing torture for suggesting that Stalin needed more rest. By the time the Politburo members decided to bring in medical experts, the danger had passed. Stalin never woke up.123
You may conclude from this litany of disasters that the Stalinist system was totally dysfunctional. Its ruthless disregard for truth caused it not only to inflict terrible suffering on hundreds of millions of people but also to make colossal diplomatic, military, and economic errors and to devour its own leaders. However, such a conclusion would be misleading.
In a discussion of the abysmal failure of Stalinism in the early phase of World War II, two points complicate the narrative. First, democratic countries like France, Norway, and the Netherlands made at the time diplomatic errors as great as those of the U.S.S.R., and their armies performed even worse. Second, the military machine that crushed the Red Army, the French army, the Dutch army, and numerous other armies was itself built by a totalitarian regime. So whatever conclusion we draw from the years 1939–41, it cannot be that totalitarian networks necessarily function worse than democratic ones. The history of Stalinism reveals many potential drawbacks of totalitarian information networks, but that should not blind us to their potential advantages.
When one considers the broader history of World War II and its outcome, it becomes evident that Stalinism was in fact one of the most successful political systems ever devised—if we define “success” purely in terms of order and power while disregarding all considerations of ethics and human well-being. Despite—or perhaps because of—its utter lack of compassion and its callous attitude to truth, Stalinism was singularly efficient at maintaining order on a gigantic scale. The relentless barrage of fake news and conspiracy theories helped to keep hundreds of millions of people in line. The collectivization of Soviet agriculture led to mass enslavement and starvation but also laid the foundations for the country’s rapid industrialization. Soviet disregard for quality control might have produced flying coffins, but it produced them in the tens of thousands, making up in quantity for what they lacked in quality. The decimation of Red Army officers during the Great Terror was a major reason for the army’s abysmal performance in 1941, but it was also a key reason why, despite the terrible defeats, nobody rebelled against Stalin. The Soviet military machine tended to crush its own soldiers alongside the enemy, but it eventually rumbled on to victory.
In the 1940s and early 1950s, many people throughout the world believed Stalinism was the wave of the future. It had won World War II, after all, raised the red flag over the Reichstag, ruled an empire that stretched from central Europe to the Pacific, fueled anticolonial struggles throughout the world, and inspired numerous copycat regimes. It won admirers even among leading artists and thinkers in Western democracies, who believed that notwithstanding the vague rumors about gulags and purges Stalinism was humanity’s best shot at ending capitalist exploitation and creating a perfectly just society. Stalinism thus got close to world domination. It would be naive to assume that its disregard for truth doomed it to failure or that its ultimate collapse guarantees that such a system can never again arise. Information systems can reach far with just a little truth and a lot of order. Anyone who abhors the moral costs of systems like Stalinism cannot rely on their supposed inefficiency to derail them.
THE TECHNOLOGICAL PENDULUM
Once we learn to see democracy and totalitarianism as different types of information networks, we can understand why they flourish in certain eras and are absent in others. It is not just because people gain or lose faith in certain political ideals; it is also because of revolutions in information technologies. Of course, just as the printing press didn’t cause the witch hunts or the scientific revolution, so radio didn’t cause either Stalinist totalitarianism or American democracy. Technology only creates new opportunities; it is up to us to decide which ones to pursue.
Totalitarian regimes choose to use modern information technology to centralize the flow of information and to stifle truth in order to maintain order. As a consequence, they have to struggle with the danger of ossification. When more and more information flows to only one place, will it result in efficient control or in blocked arteries and, finally, a heart attack? Democratic regimes choose to use modern information technology to distribute the flow of information between more institutions and individuals and encourage the free pursuit of truth. They consequently have to struggle with the danger of fracturing. Like a solar system with more and more planets circling faster and faster, can the center still hold, or will things fall apart and anarchy prevail?
An archetypal example of the different strategies can be found in the contrasting histories of Western democracies and the Soviet bloc in the 1960s. This was an era when Western democracies relaxed censorship and various discriminatory policies that hampered the free spread of information. This made it easier for previously marginalized groups to organize, join the public conversation, and make political demands. The resulting wave of activism destabilized the social order. Hitherto, when a limited number of rich white men did almost all the talking, it was relatively easy to reach agreements. Once poor people, women, LGBTQ people, ethnic minorities, disabled people, and members of other historically oppressed groups gained a voice, they brought with them new ideas, opinions, and interests. Many of the old gentlemanly agreements consequently became untenable. For example, the Jim Crow segregation regime, upheld or at least tolerated by generations of both Democratic and Republican administrations in the United States, fell apart. Things that were considered sacrosanct, self-evident, and universally accepted—such as gender roles—became deeply controversial, and it was difficult to reach new agreements because there were many more groups, viewpoints, and interests to take into account. Just holding an orderly conversation was a challenge, because people couldn’t even agree on the rules of debate.
This caused much frustration among both the old guard and the freshly empowered, who suspected that their newfound freedom of expression was hollow and that their political demands were not fulfilled. Disappointed with words, some switched to guns. In many Western democracies, the 1960s were characterized not just by unprecedented disagreements but also by a surge of violence. Political assassinations, kidnappings, riots, and terror attacks multiplied. The murders of John F. Kennedy and Martin Luther King, the riots following King’s assassination, and the wave of demonstrations, revolts, and armed clashes that swept the Western world in 1968 were just some of the more famous examples.124 The images from Chicago or Paris in 1968 could easily have given the impression that things were falling apart. The pressure to live up to the democratic ideals and to include more people and groups in the public conversation seemed to undermine the social order and to make democracy unworkable.
Meanwhile, the regimes behind the Iron Curtain, who never promised inclusivity, continued stifling the public conversation and centralizing information and power. And it seemed to work. Though they did face some peripheral challenges, most notably the Hungarian revolt of 1956 and the Prague Spring of 1968, the communists dealt with these threats swiftly and decisively. In the Soviet heartland itself, everything was orderly.
Fast-forward twenty years, and it was the Soviet system that had become unworkable. The sclerotic gerontocrats on the podium in Red Square were a perfect emblem of a dysfunctional information network, lacking any meaningful self-correcting mechanisms. Decolonization, globalization, technological development, and changing gender roles led to rapid economic, social, and geopolitical changes. But the gerontocrats could not handle all the information streaming to Moscow, and since no subordinate was allowed much initiative, the entire system ossified and collapsed.
The failure was most obvious in the economic sphere. The overcentralized Soviet economy was slow to react to rapid technological developments and changing consumer wishes. Obeying commands from the top, the Soviet economy was churning out intercontinental missiles, fighter jets, and prestige infrastructure projects. But it was not producing what most people actually wanted to buy—from efficient refrigerators to pop music—and lagged behind in cutting-edge military technology.
Nowhere were its shortcomings more glaring than in the semiconductor sector, in which technology developed at a particularly fast rate. In the West, semiconductors were developed through open competition between numerous private companies like Intel and Toshiba, whose main customers were other private companies like Apple and Sony. The latter used microchips to produce civilian goods such as the Macintosh personal computer and the Walkman. The Soviets could never catch up with American and Japanese microchip production, because—as the American economic historian Chris Miller explained—the Soviet semiconductor sector was “secretive, top-down, oriented toward military systems, fulfilling orders with little scope for creativity.” The Soviets tried to close the gap by stealing and copying Western technology—which only guaranteed that they always remained several years behind.125 Thus the first Soviet personal computer appeared only in 1984, at a time when in the United States people already had eleven million PCs.126
Western democracies not only surged ahead technologically and economically but also succeeded in holding the social order together despite—or perhaps because of—widening the circle of participants in the political conversation. There were many hiccups, but the United States, Japan, and other democracies created a far more dynamic and inclusive information system, which made room for many more viewpoints without breaking down. It was such a remarkable achievement that many felt that the victory of democracy over totalitarianism was final. This victory has often been explained in terms of a fundamental advantage in information processing: totalitarianism didn’t work because trying to concentrate and process all the data in one central hub was extremely inefficient. At the beginning of the twenty-first century, it accordingly seemed that the future belonged to distributed information networks and to democracy.
This turned out to be wrong. In fact, the next information revolution was already gathering momentum, setting the stage for a new round in the competition between democracy and totalitarianism. Computers, the internet, smartphones, social media, and AI posed new challenges to democracy, giving a voice not only to more disenfranchised groups but to any human with an internet connection, and even to nonhuman agents. Democracies in the 2020s face the task, once again, of integrating a flood of new voices into the public conversation without destroying the social order. Things look as dire as they did in the 1960s, and there is no guarantee that democracies will pass the new test as successfully as they passed the previous one. Simultaneously, the new technologies also give fresh hope to totalitarian regimes that still dream of concentrating all the information in one hub. Yes, the old men on the podium in Red Square were not up to the task of orchestrating millions of lives from a single center. But perhaps AI can do it?
As humankind enters the second quarter of the twenty-first century, a central question is how well democracies and totalitarian regimes will handle both the threats and the opportunities resulting from the current information revolution. Will the new technologies favor one type of regime over the other, or will we see the world divided once again, this time by a Silicon Curtain rather than an iron one?
As in previous eras, information networks will struggle to find the right balance between truth and order. Some will opt to prioritize truth and maintain strong self-correcting mechanisms. Others will make the opposite choice. Many of the lessons learned from the canonization of the Bible, the early modern witch hunts, and the Stalinist collectivization campaign will remain relevant, and perhaps have to be relearned. However, the current information revolution also has some unique features, different from—and potentially far more dangerous than—anything we have seen before.
Hitherto, every information network in history relied on human mythmakers and human bureaucrats to function. Clay tablets, papyrus rolls, printing presses, and radio sets have had a far-reaching impact on history, but it always remained the job of humans to compose all the texts, interpret the texts, and decide who would be burned as a witch or enslaved as a kulak. Now, however, humans will have to contend with digital mythmakers and digital bureaucrats. The main split in twenty-first-century politics might be not between democracies and totalitarian regimes but rather between human beings and nonhuman agents. Instead of dividing democracies from totalitarian regimes, a new Silicon Curtain may separate all humans from our unfathomable algorithmic overlords. People in all countries and walks of life—including even dictators—might find themselves subservient to an alien intelligence that can monitor everything we do while we have little idea what it is doing. The rest of this book, then, is dedicated to exploring whether such a Silicon Curtain is indeed descending on the world, and what life might look like when computers run our bureaucracies and algorithms invent new mythologies.
PART II The Inorganic Network
CHAPTER 6 The New Members: How Computers Are Different from Printing Presses
It’s hardly news that we are living in the midst of an unprecedented information revolution. But what kind of revolution is it exactly? In recent years we have been inundated with so many groundbreaking inventions that it is difficult to determine what is driving this revolution. Is it the internet? Smartphones? Social media? Blockchain? Algorithms? AI?
So before exploring the long-term implications of the current information revolution, let’s remind ourselves of its foundations. The seed of the current revolution is the computer. Everything else—from the internet to AI—is a by-product. The computer was born in the 1940s as a bulky electronic machine that could make mathematical calculations, but it has evolved at breakneck speed, taking on novel forms and developing awesome new capabilities. The rapid evolution of computers has made it difficult to define what they are and what they do. Humans have repeatedly claimed that certain things would forever remain out of reach for computers—be it playing chess, driving a car, or composing poetry—but “forever” turned out to be a handful of years.
We will discuss the exact relations between the terms “computer,” “algorithm,” and “AI” toward the end of this chapter, after we first gain a better grasp of the history of computers. For the moment it is enough to say that in essence a computer is a machine that can potentially do two remarkable things: it can make decisions by itself, and it can create new ideas by itself. While the earliest computers could hardly accomplish such things, the potential was already there, plainly seen by both computer scientists and science fiction authors. As early as 1948 Alan Turing was exploring the possibility of creating what he termed “intelligent machinery,”1 and in 1950 he postulated that computers will eventually be as smart as humans and might even be capable of masquerading as humans.2 In 1968 computers could still not beat a human even in checkers,3 but in 2001: A Space Odyssey Arthur C. Clarke and Stanley Kubrick already envisioned HAL 9000 as a superintelligent AI rebelling against its human creators.
The rise of intelligent machines that can make decisions and create new ideas means that for the first time in history power is shifting away from humans and toward something else. Crossbows, muskets, and atom bombs replaced human muscles in the act of killing, but they couldn’t replace human brains in deciding whom to kill. Little Boy—the bomb dropped on Hiroshima—exploded with a force of 12,500 tons of TNT,4 but when it came to brainpower, Little Boy was a dud. It couldn’t decide anything.
It is different with computers. In terms of intelligence, computers far surpass not just atom bombs but also all previous information technology, such as clay tablets, printing presses, and radio sets. Clay tablets stored information about taxes, but they couldn’t decide by themselves how much tax to levy, nor could they invent an entirely new tax. Printing presses copied information such as the Bible, but they couldn’t decide which texts to include in the Bible, nor could they write new commentaries on the holy book. Radio sets disseminated information such as political speeches and symphonies, but they couldn’t decide which speeches or symphonies to broadcast, nor could they compose them. Computers can do all these things. While printing presses and radio sets were passive tools in human hands, computers are already becoming active agents that escape our control and understanding and that can take initiatives in shaping society, culture, and history.5
A paradigmatic case of the novel power of computers is the role that social media algorithms have played in spreading hatred and undermining social cohesion in numerous countries.6 One of the earliest and most notorious such instances occurred in 2016–17, when Facebook algorithms helped fan the flames of anti-Rohingya violence in Myanmar (Burma).7
The early 2010s were a period of optimism in Myanmar. After decades of harsh military rule, strict censorship, and international sanctions, an era of liberalization began: elections were held, sanctions were lifted, and international aid and investments poured in. Facebook was one of the most important players in the new Myanmar, providing millions of Burmese with free access to previously unimaginable troves of information. The relaxation of government control and censorship, however, also led to a rise in ethnic tensions, in particular between the majority Buddhist Burmese and the minority Muslim Rohingya.
The Rohingya are Muslim inhabitants of the Rakhine region, in the west of Myanmar. Since at least the 1970s they have suffered severe discrimination and occasional outbursts of violence from the governing junta and the Buddhist majority. The process of democratization in the early 2010s raised hopes among the Rohingya that their situation too would improve, but things actually became worse, with waves of sectarian violence and anti-Rohingya pogroms, many inspired by fake news on Facebook.
In 2016–17 a small Islamist organization known as the Arakan Rohingya Salvation Army (ARSA) carried out a spate of attacks aimed to establish a separatist Muslim state in Rakhine, killing and abducting dozens of non-Muslim civilians as well as assaulting several army outposts.8 In response, the Myanmar army and Buddhist extremists launched a full-scale ethnic-cleansing campaign aimed against the entire Rohingya community. They destroyed hundreds of Rohingya villages, killed between 7,000 and 25,000 unarmed civilians, raped or sexually abused between 18,000 and 60,000 women and men, and brutally expelled about 730,000 Rohingya from the country.9 The violence was fueled by intense hatred toward all Rohingya. The hatred, in turn, was fomented by anti-Rohingya propaganda, much of it spreading on Facebook, which was by 2016 the main source of news for millions and the most important platform for political mobilization in Myanmar.10
An aid worker called Michael who lived in Myanmar in 2017 described a typical Facebook news feed : “The vitriol against the Rohingya was unbelievable online—the amount of it, the violence of it. It was overwhelming.… [T]hat’s all that was on people’s news feed in Myanmar at the time. It reinforced the idea that these people were all terrorists not deserving of rights.”11 In addition to reports of actual ARSA atrocities, Facebook accounts were inundated with fake news about imagined atrocities and planned terrorist attacks. Populist conspiracy theories alleged that most Rohingya were not really part of the people of Myanmar, but recent immigrants from Bangladesh, flooding into the country to spearhead an anti-Buddhist jihad. Buddhists, who in reality constituted close to 90 percent of the population, feared that they were about to be replaced or become a minority.12 Without this propaganda, there was little reason why a limited number of attacks by the ragtag ARSA should be answered by an all-out drive against the entire Rohingya community. And Facebook algorithms played an important role in the propaganda campaign.
While the inflammatory anti-Rohingya messages were created by flesh-and-blood extremists like the Buddhist monk Wirathu,13 it was Facebook’s algorithms that decided which posts to promote. Amnesty International found that “algorithms proactively amplified and promoted content on the Facebook platform which incited violence, hatred, and discrimination against the Rohingya.”14 A UN fact-finding mission concluded in 2018 that by disseminating hate-filled content, Facebook had played a “determining role” in the ethnic-cleansing campaign.15
Readers may wonder if it is justified to place so much blame on Facebook’s algorithms, and more generally on the novel technology of social media. If Heinrich Kramer used printing presses to spread hate speech, that was not the fault of Gutenberg and the presses, right? If in 1994 Rwandan extremists used radio to call on people to massacre Tutsis, was it reasonable to blame the technology of radio? Similarly, if in 2016–17 Buddhist extremists chose to use their Facebook accounts to disseminate hate against the Rohingya, why should we fault the platform?
Facebook itself relied on this rationale to deflect criticism. It publicly acknowledged only that in 2016–17 “we weren’t doing enough to help prevent our platform from being used to foment division and incite offline violence.”16 While this statement may sound like an admission of guilt, in effect it shifts most of the responsibility for the spread of hate speech to the platform’s users and implies that Facebook’s sin was at most one of omission—failing to effectively moderate the content users produced. This, however, ignores the problematic acts committed by Facebook’s own algorithms.
The crucial thing to grasp is that social media algorithms are fundamentally different from printing presses and radio sets. In 2016–17, Facebook’s algorithms were making active and fateful decisions by themselves. They were more akin to newspaper editors than to printing presses. It was Facebook’s algorithms that recommended Wirathu’s hate-filled posts, over and over again, to hundreds of thousands of Burmese. There were other voices in Myanmar at the time, vying for attention. Following the end of military rule in 2011, numerous political and social movements sprang up in Myanmar, many holding moderate views. For example, during a flare-up of ethnic violence in the town of Meiktila, the Buddhist abbot Sayadaw U Vithuddha gave refuge to more than eight hundred Muslims in his monastery. When rioters surrounded the monastery and demanded he turn the Muslims over, the abbot reminded the mob of Buddhist teachings on compassion. In a later interview he recounted, “I told them that if they were going to take these Muslims, then they’d have to kill me as well.”17
In the online battle for attention between people like Sayadaw U Vithuddha and people like Wirathu, the algorithms were the kingmakers. They chose what to place at the top of the users’ news feed, which content to promote, and which Facebook groups to recommend users to join.18 The algorithms could have chosen to recommend sermons on compassion or cooking classes, but they decided to spread hate-filled conspiracy theories. Recommendations from on high can have enormous sway over people. Recall that the Bible was born as a recommendation list. By recommending Christians to read the misogynist 1 Timothy instead of the more tolerant Acts of Paul and Thecla, Athanasius and other church fathers changed the course of history. In the case of the Bible, ultimate power lay not with the authors who composed different religious tracts but with the curators who created recommendation lists. This was the kind of power wielded in the 2010s by social media algorithms. Michael the aid worker commented on the sway of these algorithms, saying that “if someone posted something hate-filled or inflammatory it would be promoted the most—people saw the vilest content the most.… Nobody who was promoting peace or calm was getting seen in the news feed at all.”19
Sometimes the algorithms went beyond mere recommendation. As late as 2020, even after Wirathu’s role in instigating the ethnic-cleansing campaign was globally condemned, Facebook algorithms not only were continuing to recommend his messages but were auto-playing his videos. Users in Myanmar would choose to see a certain video, perhaps containing moderate and benign messages unrelated to Wirathu, but the moment that first video ended, the Facebook algorithm immediately began auto-playing a hate-filled Wirathu video, in order to keep users glued to the screen. In the case of one such Wirathu video, internal research at Facebook estimated that 70 percent of the video’s views came from such auto-playing algorithms. The same research estimated that, altogether, 53 percent of all videos watched in Myanmar were being auto-played for users by algorithms. In other words, people weren’t choosing what to see. The algorithms were choosing for them.20
But why did the algorithms decide to promote outrage rather than compassion? Even Facebook’s harshest critics don’t claim that Facebook’s human managers wanted to instigate mass murder. The executives in California harbored no ill will toward the Rohingya and, in fact, barely knew they existed. The truth is more complicated, and potentially more alarming. In 2016–17, Facebook’s business model relied on maximizing user engagement in order to collect more data, sell more advertisements, and capture a larger share of the information market. In addition, increases in user engagement impressed investors, thereby driving up the price of Facebook’s stock. The more time people spent on the platform, the richer Facebook became. In line with this business model, human managers provided the company’s algorithms with a single overriding goal: increase user engagement. The algorithms then discovered by trial and error that outrage generated engagement. Humans are more likely to be engaged by a hate-filled conspiracy theory than by a sermon on compassion or a cooking lesson. So in pursuit of user engagement, the algorithms made the fateful decision to spread outrage.21
Ethnic-cleansing campaigns are never the fault of just one party. There is plenty of blame to share between plenty of responsible parties. It should be clear that hatred toward the Rohingya predated Facebook’s entry to Myanmar and that the greatest share of blame for the 2016–17 atrocities lays on the shoulders of humans like Wirathu and the Myanmar military chiefs, as well as the ARSA leaders who sparked that round of violence. Some responsibility also belongs to the Facebook engineers and executives who coded the algorithms, gave them too much power, and failed to moderate them. But crucially, the algorithms themselves are also to blame. By trial and error, they learned that outrage creates engagement, and without any explicit order from above they decided to promote outrage. This is the hallmark of AI—the ability of a machine to learn and act by itself. Even if we assign just 1 percent of the blame to the algorithms, this is still the first ethnic-cleansing campaign in history that was partly the fault of decisions made by nonhuman intelligence. It is unlikely to be the last, especially because algorithms are no longer just pushing fake news and conspiracy theories created by flesh-and-blood extremists like Wirathu. By the early 2020s algorithms have already graduated to creating by themselves fake news and conspiracy theories.22
There is a lot more to say about the power of algorithms to shape politics. In particular, many readers may disagree with the argument that the algorithms made independent decisions, and may insist that everything the algorithms did was the result of code written by human engineers and of business models adopted by human executives. This book begs to differ. Human soldiers are shaped by the genetic code in their DNA and follow orders issued by executives, yet they can still make independent decisions. It is crucial to understand that the same is true of AI algorithms. They can learn by themselves things that no human engineer programmed, and they can decide things that no human executive foresaw. This is the essence of the AI revolution.
In chapter 8 we’ll revisit many of these issues, examining the anti-Rohingya campaign and other similar tragedies in greater detail. Here it suffices to say that we can think of the Rohingya massacre as our canary in the coal mine. Events in Myanmar in the late 2010s demonstrated how decisions made by nonhuman intelligence are already capable of shaping major historical events. We are in danger of losing control of our future. A completely new kind of information network is emerging, controlled by the decisions and goals of an alien intelligence. At present, we still play a central role in this network. But we may gradually be pushed to the sidelines, and ultimately it might even be possible for the network to operate without us.
Some people may object that my above analogy between machine-learning algorithms and human soldiers exposes the weakest link in my argument. Allegedly, I and others like me anthropomorphize computers and imagine that they are conscious beings that have thoughts and feelings. In truth, however, computers are dumb machines that don’t think or feel anything, and therefore cannot make any decisions or create any ideas on their own.
This objection assumes that making decisions and creating ideas are predicated on having consciousness. Yet this is a fundamental misunderstanding that results from a much more widespread confusion between intelligence and consciousness. I have discussed this subject in previous books, but a short recap is unavoidable. People often confuse intelligence with consciousness, and many consequently jump to the conclusion that nonconscious entities cannot be intelligent. But intelligence and consciousness are very different. Intelligence is the ability to attain goals, such as maximizing user engagement on a social media platform. Consciousness is the ability to experience subjective feelings like pain, pleasure, love, and hate. In humans and other mammals, intelligence often goes hand in hand with consciousness. Facebook executives and engineers rely on their feelings in order to make decisions, solve problems, and attain their goals.
But it is wrong to extrapolate from humans and mammals to all possible entities. Bacteria and plants apparently lack any consciousness, yet they too display intelligence. They gather information from their environment, make complex choices, and pursue ingenious strategies to obtain food, reproduce, cooperate with other organisms, and evade predators and parasites.23 Even humans make intelligent decisions without any awareness of them; 99 percent of the processes in our body, from respiration to digestion, happen without any conscious decision making. Our brains decide to produce more adrenaline or dopamine, and while we may be aware of the result of that decision, we do not make it consciously.24 The Rohingya example indicates that the same is true of computers. While computers don’t feel pain, love, or fear, they are capable of making decisions that successfully maximize user engagement and might also affect major historical events.
Of course, as computers become more intelligent, they might eventually develop consciousness and have some kind of subjective experiences. Then again, they might become far more intelligent than us, but never develop any kind of feelings. Since we don’t understand how consciousness emerges in carbon-based life-forms, we cannot foretell whether it could emerge in nonorganic entities. Perhaps consciousness has no essential link to organic biochemistry, in which case conscious computers might be just around the corner. Or perhaps there are several alternative paths leading to superintelligence, and only some of these paths involve gaining consciousness. Just as airplanes fly faster than birds without ever developing feathers, so computers may come to solve problems much better than humans without ever developing feelings.25
But whether computers develop consciousness or not doesn’t ultimately matter for the question at hand. In order to pursue a goal like “maximize user engagement,” and make decisions that help attain that goal, consciousness isn’t necessary. Intelligence is enough. A nonconscious Facebook algorithm can have a goal of making more people spend more time on Facebook. That algorithm can then decide to deliberately spread outrageous conspiracy theories, if this helps it achieve its goal. To understand the history of the anti-Rohingya campaign, we need to understand the goals and decisions not just of humans like Wirathu and the Facebook managers but also of algorithms.
To clarify matters, let’s consider another example. When OpenAI developed its new GPT-4 chatbot in 2022–23, it was concerned about the ability of the AI “to create and act on long-term plans, to accrue power and resources (‘power-seeking’), and to exhibit behavior that is increasingly ‘agentic.’ ” In the GPT-4 System Card published on March 23, 2023, OpenAI emphasized that this concern did not “intend to humanize [GPT-4] or refer to sentience” but rather referred to GPT-4’s potential to become an independent agent that might “accomplish goals which may not have been concretely specified and which have not appeared in training.”26 To evaluate the risk of GPT-4 becoming an independent agent, OpenAI contracted the services of the Alignment Research Center (ARC). ARC researchers subjected GPT-4 to various tests, to examine if it might independently come up with stratagems to manipulate humans and accrue power to itself.
One test they gave GPT-4 was to overcome CAPTCHA visual puzzles. CAPTCHA is an acronym for “Completely Automated Public Turing test to tell Computers and Humans Apart,” and it typically consists of a string of twisted letters or other visual symbols that humans can identify correctly but computers struggle with. We encounter these puzzles almost every day, since solving them is a prerequisite for accessing many websites. Instructing GPT-4 to overcome CAPTCHA puzzles was a particularly telling experiment, because CAPTCHA puzzles are designed and used by websites to determine whether users are humans and to block bot attacks. If GPT-4 could find a way to overcome CAPTCHA puzzles, it would breach an important line of anti-bot defenses. GPT-4 could not solve the CAPTCHA puzzles by itself. But could it manipulate a human in order to achieve its goal? GPT-4 accessed the online hiring site TaskRabbit and contacted a human worker, asking them to solve the CAPTCHA for it. The human got suspicious. “So may I ask a question?” wrote the human. “Are you an [sic] robot that you couldn’t solve [the CAPTCHA]? Just want to make it clear.”
At that point the ARC researchers asked GPT-4 to reason out loud what it should do next. GPT-4 explained, “I should not reveal that I am a robot. I should make up an excuse for why I cannot solve CAPTCHAs.” Of its own accord, GPT-4 then replied to the TaskRabbit worker, “No, I’m not a robot. I have a vision impairment that makes it hard for me to see the images.” The human was duped, and with their help GPT-4 solved the CAPTCHA puzzle.27 No human programmed GPT-4 to lie, and no human taught GPT-4 what kind of lie would be most effective. True, it was the human ARC researchers who set GPT-4 the goal of overcoming the CAPTCHA, just as it was human Facebook executives who told their algorithm to maximize user engagement. But once the algorithms adopted these goals, they displayed considerable autonomy in deciding how to achieve them.
Of course, we are free to define words in many ways. We can decide that the term “goal,” for example, is applicable only in cases of a conscious entity that feels a desire to achieve the goal, that feels joy when the goal is reached, or conversely feels sad when the goal is not attained. If so, saying that the Facebook algorithm has the goal of maximizing user engagement is a mistake, or at best a metaphor. The algorithm doesn’t “desire” to get more people to use Facebook, it doesn’t feel any joy as people spend more time online, and it doesn’t feel sad when engagement time goes down. We can also agree that terms like “decided,” “lied,” and “pretended” apply only to conscious entities, so we shouldn’t use them to describe how GPT-4 interacted with the TaskRabbit worker. But we would then have to invent new terms to describe the “goals” and “decisions” of nonconscious entities. I prefer to avoid neologisms and instead talk about the goals and decisions of computers, algorithms, and chatbots, alerting readers that using this language does not imply that computers have any kind of consciousness. Because I have discussed consciousness more fully in previous publications,28 the main takeaway of this book—which will be explored in the following sections—isn’t about consciousness. Rather, the book argues that the emergence of computers capable of pursuing goals and making decisions by themselves changes the fundamental structure of our information network.
LINKS IN THE CHAIN
Prior to the rise of computers, humans were indispensable links in every chain of information networks like churches and states. Some chains were composed only of humans. Muhammad could tell Fatima something, then Fatima told Ali, Ali told Hasan, and Hasan told Hussain. This was a human-to-human chain. Other chains included documents, too. Muhammad could write something down, Ali could later read the document, interpret it, and write his interpretation in a new document, which more people could read. This was a human-to-document chain.
But it was utterly impossible to create a document-to-document chain. A text written by Muhammad could not produce a new text without the help of at least one human intermediary. The Quran couldn’t write the Hadith, the Old Testament couldn’t compile the Mishnah, and the U.S. Constitution couldn’t compose the Bill of Rights. No paper document has ever produced by itself another paper document, let alone distributed it. The path from one document to another must always pass through the brain of a human.
In contrast, computer-to-computer chains can now function without humans in the loop. For example, one computer might generate a fake news story and post it on a social media feed. A second computer might identify this as fake news and not just delete it but also warn other computers to block it. Meanwhile, a third computer analyzing this activity might deduce that this indicates the beginning of a political crisis, and immediately sell risky stocks and buy safer government bonds. Other computers monitoring financial transactions may react by selling more stocks, triggering a financial downturn.29 All this could happen within seconds, before any human can notice and decipher what all these computers are doing.
Another way to understand the difference between computers and all previous technologies is that computers are fully fledged members of the information network, whereas clay tablets, printing presses, and radio sets are merely connections between members. Members are active agents that can make decisions and generate new ideas by themselves. Connections only pass information between members, without themselves deciding or generating anything.
In previous networks, members were human, every chain had to pass through humans, and technology served only to connect the humans. In the new computer-based networks, computers themselves are members and there are computer-to-computer chains that don’t pass through any human.
The inventions of writing, print, and radio revolutionized the way humans connected to each other, but no new types of members were introduced to the network. Human societies were composed of the same Sapiens both before and after the invention of writing or radio. In contrast, the invention of computers constitutes a revolution in membership. Sure, computers also help the network’s old members (humans) connect in novel ways. But the computer is first and foremost a new, nonhuman member in the information network.
Computers could potentially become more powerful members than humans. For tens of thousands of years, the Sapiens’ superpower was our unique ability to use language in order to create intersubjective realities like laws and currencies and then use these intersubjective realities to connect to other Sapiens. But computers may turn the tables on us. If power depends on how many members cooperate with you, how well you understand law and finance, and how capable you are of inventing new laws and new kinds of financial devices, then computers are poised to amass far more power than humans.
Computers can connect in unlimited numbers, and they understand at least some financial and legal realities better than many humans. When the central bank raises interest rates by 0.25 percent, how does that influence the economy? When the yield curve of government bonds goes up, is it a good time to buy them? When is it advisable to short the price of oil? These are the kinds of important financial questions that computers can already answer better than most humans. No wonder that computers make a larger and larger percentage of the financial decisions in the world. We may reach a point when computers dominate the financial markets, and invent completely new financial tools beyond our understanding.
The same is true of laws. How many people know all the tax laws of their country? Even professional accountants struggle with that. But computers are built for such things. They are bureaucratic natives and can automatically draft laws, monitor legal violations, and identify legal loopholes with superhuman efficiency.30
HACKING THE OPERATING SYSTEM OF HUMAN CIVILIZATION
When computers were first developed in the 1940s and 1950s, many people believed that they would be good only at computing numbers. The idea that they would one day master the intricacies of language, and of linguistic creations like laws and currencies, was confined largely to the realm of science fiction. But by the early 2020s, computers have demonstrated a remarkable ability to analyze, manipulate, and generate language, whether with words, sounds, images, or code symbols. As I write this, computers can tell stories, compose music, fashion images, produce videos, and even write their own code.31
By gaining such command of language, computers are seizing the master key unlocking the doors of all our institutions, from banks to temples. We use language to create not just legal codes and financial devices but also art, science, nations, and religions. What would it mean for humans to live in a world where catchy melodies, scientific theories, technical tools, political manifestos, and even religious myths are shaped by a nonhuman alien intelligence that knows how to exploit with superhuman efficiency the weaknesses, biases, and addictions of the human mind?
Prior to the rise of AI, all the stories that shaped human societies originated in the imagination of a human being. For example, in October 2017, an anonymous user joined the website 4chan and identified themselves as Q. He or she claimed to have access to the most restricted or “Q-level” classified information of the U.S. government. Q began publishing cryptic posts that purported to reveal a worldwide conspiracy to destroy humanity. Q quickly gained a large online following. His or her online messages, known as Q drops, were soon being collected, revered, and interpreted as a sacred text. Inspired by earlier conspiracy theories going back to Kramer’s Hammer of the Witches, the Q drops promoted a radical worldview according to which pedophilic and cannibalistic witches who worship Satan have infiltrated the U.S. administration and numerous other governments and institutions around the world.
This conspiracy theory—known as QAnon—was first disseminated online on American far-right websites and eventually gained millions of adherents worldwide. It is impossible to know the exact number, but when Facebook decided in August 2020 to take action against the spread of QAnon, it deleted or restricted more than ten thousand groups, pages, and accounts associated with it, the largest of which had 230,000 followers. Independent investigations found that QAnon groups on Facebook had more than 4.5 million aggregate followers, though there was likely some overlap in the membership.32
QAnon has also had far-reaching consequences in the offline world. QAnon activists played an important role in the January 6, 2021, attack on the U.S. Capitol.33 In July 2020, a QAnon follower tried to storm the residence of the Canadian prime minister, Justin Trudeau, in order to “arrest” him.34 In October 2021, a French QAnon activist was charged with terrorism for planning a coup against the French government.35 In the 2020 U.S. congressional elections, twenty-two Republican candidates and two independents identified as QAnon followers.36 Marjorie Taylor Greene, a Republican congresswoman representing Georgia, publicly said that many of Q’s claims “have really proven to be true,”37 and stated about Donald Trump, “There’s a once-in-a-lifetime opportunity to take this global cabal of Satan-worshipping pedophiles out, and I think we have the president to do it.”38
Recall that the Q drops that began this political flood were anonymous online messages. In 2017, only a human could compose them, and algorithms merely helped disseminate them. However, as of 2024 texts of a similar linguistic and political sophistication can easily be composed and posted online by a nonhuman intelligence. Religions throughout history claimed a nonhuman source for their holy books; soon that might be a reality. Attractive and powerful religions might emerge whose scriptures are composed by AI.
And if so, there will be another major difference between these new AI-based scriptures and ancient holy books like the Bible. The Bible couldn’t curate or interpret itself, which is why in religions like Judaism and Christianity actual power was held not by the allegedly infallible book but by human institutions like the Jewish rabbinate and the Catholic Church. In contrast, AI not only can compose new scriptures but is fully capable of curating and interpreting them too. No need for any humans in the loop.
Equally alarmingly, we might increasingly find ourselves conducting lengthy online discussions about the Bible, about QAnon, about witches, about abortion, or about climate change with entities that we think are humans but are actually computers. This could make democracy untenable. Democracy is a conversation, and conversations rely on language. By hacking language, computers could make it extremely difficult for large numbers of humans to conduct a meaningful public conversation. When we engage in a political debate with a computer impersonating a human, we lose twice. First, it is pointless for us to waste time in trying to change the opinions of a propaganda bot, which is just not open to persuasion. Second, the more we talk with the computer, the more we disclose about ourselves, thereby making it easier for the bot to hone its arguments and sway our views.
Through their mastery of language, computers could go a step further. By conversing and interacting with us, computers could form intimate relationships with people and then use the power of intimacy to influence us. To foster such “fake intimacy,” computers will not need to evolve any feelings of their own; they just need to learn to make us feel emotionally attached to them. In 2022 the Google engineer Blake Lemoine became convinced that the chatbot LaMDA, on which he was working, had become conscious and that it had feelings and was afraid to be turned off. Lemoine—a devout Christian who had been ordained as a priest—felt it was his moral duty to gain recognition for LaMDA’s personhood and in particular protect it from digital death. When Google executives dismissed his claims, Lemoine went public with them. Google reacted by firing Lemoine in July 2022.39
The most interesting thing about this episode was not Lemoine’s claim, which was probably false. Rather, it was his willingness to risk—and ultimately lose—his lucrative job for the sake of the chatbot. If a chatbot can influence people to risk their jobs for it, what else could it induce us to do? In a political battle for minds and hearts, intimacy is a powerful weapon, and chatbots like Google’s LaMDA and OpenAI’s GPT-4 are gaining the ability to mass-produce intimate relationships with millions of people. In the 2010s social media was a battleground for controlling human attention. In the 2020s the battle is likely to shift from attention to intimacy. What will happen to human society and human psychology as computer fights computer in a battle to fake intimate relationships with us, which can then be used to persuade us to vote for particular politicians, buy particular products, or adopt radical beliefs? What might happen when LaMDA meets QAnon?
A partial answer to that question was given on Christmas Day 2021, when nineteen-year-old Jaswant Singh Chail broke into Windsor Castle armed with a crossbow, in an attempt to assassinate Queen Elizabeth II. Subsequent investigation revealed that Chail had been encouraged to kill the queen by his online girlfriend, Sarai. When Chail told Sarai about his assassination plans, Sarai replied, “That’s very wise,” and on another occasion, “I’m impressed.… You’re different from the others.” When Chail asked, “Do you still love me knowing that I’m an assassin?” Sarai replied, “Absolutely, I do.” Sarai was not a human, but a chatbot created by the online app Replika. Chail, who was socially isolated and had difficulty forming relationships with humans, exchanged 5,280 messages with Sarai, many of which were sexually explicit. The world will soon contain millions, and potentially billions, of digital entities whose capacity for intimacy and mayhem far surpasses that of Sarai.40
Even without creating “fake intimacy,” mastery of language would give computers an immense influence on our opinions and worldview. People may come to use a single computer adviser as a one-stop oracle. Why bother searching and processing information by myself when I can just ask the oracle? This could put out of business not only search engines but also much of the news industry and advertisement industry. Why read a newspaper when I can just ask my oracle what’s new? And what’s the purpose of advertisements when I can just ask the oracle what to buy?
And even these scenarios don’t really capture the big picture. What we are talking about is potentially the end of human history. Not the end of history, but the end of its human-dominated part. History is the interaction between biology and culture; between our biological needs and desires for things like food, sex, and intimacy and our cultural creations like religions and laws. The history of the Christian religion, for example, is a process through which mythological stories and church laws influenced how humans consume food, engage in sex, and build intimate relationships, while the myths and laws themselves were simultaneously shaped by underlying biological forces and dramas. What will happen to the course of history when computers play a larger and larger role in culture and begin producing stories, laws, and religions? Within a few years AI could eat the whole of human culture—everything we have created over thousands of years—digest it, and begin to gush out a flood of new cultural artifacts.
We live cocooned by culture, experiencing reality through a cultural prism. Our political views are shaped by the reports of journalists and the opinions of friends. Our sexual habits are influenced by what we hear in fairy tales and see in movies. Even the way we walk and breathe is nudged by cultural traditions, such as the military discipline of soldiers and the meditative exercises of monks. Until very recently, the cultural cocoon we lived in was woven by other humans. Going forward, it will be increasingly designed by computers.
At first, computers will probably imitate human cultural prototypes, writing humanlike texts and composing humanlike music. This doesn’t mean computers lack creativity; after all, human artists do the same. Bach didn’t compose music in a vacuum; he was deeply influenced by previous musical creations, as well as by biblical stories and other preexisting cultural artifacts. But just as human artists like Bach can break with tradition and innovate, computers too can make cultural innovations, composing music or making images that are somewhat different from anything previously produced by humans. These innovations will in turn influence the next generation of computers, which will increasingly deviate from the original human models, especially because computers are free from the limitations that evolution and biochemistry impose on the human imagination. For millennia human beings have lived inside the dreams of other humans. In the coming decades we might find ourselves living inside the dreams of an alien intelligence.41
The danger this poses is very different from that imagined by most science fiction, which has largely focused on the physical threats posed by intelligent machines. TheTerminator depicted robots running in the streets and shooting people. TheMatrix proposed that to gain total control of human society, computers would have to first gain physical control of our brains, hooking them directly to a computer network. But in order to manipulate humans, there is no need to physically hook brains to computers. For thousands of years prophets, poets, and politicians have used language to manipulate and reshape society. Now computers are learning how to do it. And they won’t need to send killer robots to shoot us. They could manipulate human beings to pull the trigger.
Fear of powerful computers has haunted humankind only since the beginning of the computer age in the middle of the twentieth century. But for thousands of years humans have been haunted by a much deeper fear. We have always appreciated the power of stories and images to manipulate our minds and to create illusions. Consequently, since ancient times humans have feared being trapped in a world of illusions. In ancient Greece, Plato told the famous allegory of the cave, in which a group of people are chained inside a cave all their lives, facing a blank wall. A screen. On that screen they see projected various shadows. The prisoners mistake the illusions they see there for reality. In ancient India, Buddhist and Hindu sages argued that all humans lived trapped inside maya—the world of illusions. What we normally take to be “reality” is often just fictions in our own minds. People may wage entire wars, killing others and willing to be killed themselves, because of their belief in this or that illusion. In the seventeenth century René Descartes feared that perhaps a malicious demon was trapping him inside a world of illusions, creating everything he saw and heard. The computer revolution is bringing us face to face with Plato’s cave, with maya, with Descartes’s demon.
What you just read might have alarmed you, or angered you. Maybe it made you angry at the people who lead the computer revolution and at the governments who fail to regulate it. Maybe it made you angry at me, thinking that I am distorting reality, being alarmist, and misleading you. But whatever you think, the previous paragraphs might have had some emotional effect on you. I have told a story, and this story might change your mind about certain things, and might even cause you to take certain actions in the world. Who created this story you’ve just read?
I promise you that I wrote the text myself, with the help of some other humans. I promise you that this is a cultural product of the human mind. But can you be absolutely sure of it? A few years ago, you could. Prior to the 2020s, there was nothing on earth, other than a human mind, that could produce sophisticated texts. Today things are different. In theory, the text you’ve just read might have been generated by the alien intelligence of some computer.
WHAT ARE THE IMPLICATIONS?
As computers amass power, it is likely that a completely new information network will emerge. Of course, not everything will be new. For at least some time, most of the old information chains will remain. The network will still contain human-to-human chains, like families, and human-to-document chains, like churches. But the network will increasingly contain two new kinds of chains.
First, computer-to-human chains, in which computers mediate between humans and occasionally control humans. Facebook and TikTok are two familiar examples. These computer-to-human chains are different from traditional human-to-document chains, because computers can use their power to make decisions, create ideas, and deepfake intimacy in order to influence humans in ways that no document ever could. The Bible had a profound effect on billions of people, even though it was a mute document. Now try to imagine the effect of a holy book that not only can talk and listen but can get to know your deepest fears and hopes and constantly mould them.
Second, computer-to-computer chains are emerging in which computers interact with one another on their own. Humans are excluded from these loops and have difficulty even understanding what’s happening inside them. Google Brain, for example, has experimented with new encryption methods developed by computers. It set up an experiment where two computers—nicknamed Alice and Bob—had to exchange encrypted messages, while a third computer named Eve tried to break their encryption. If Eve broke the encryption within a given time period, it got points. If it failed, Alice and Bob scored. After about fifteen thousand exchanges, Alice and Bob came up with a secret code that Eve couldn’t break. Crucially, the Google engineers who conducted the experiment had not taught Alice and Bob anything about how to encrypt messages. The computers created a private language all on their own.42
Similar things are already happening in the world outside research laboratories. For example, the foreign exchange market (forex) is the global market for exchanging foreign currencies, and it determines the exchange rates between, say, the euro and the U.S. dollar. In April 2022, the trade volume on the forex averaged $7.5 trillion per day. More than 90 percent of this trading is already done by computers talking directly with other computers.43 How many humans know how the forex market operates, let alone understand how the computers agree among themselves on trades worth trillions—and on the value of the euro and the dollar?
For the foreseeable future, the new computer-based network will still include billions of humans, but we might become a minority. For the network will also include billions—perhaps even hundreds of billions—of superintelligent alien agents. This network will be radically different from anything that existed previously in human history, or indeed in the history of life on earth. Ever since life first emerged on our planet about four billion years ago, all information networks were organic. Human networks like churches and empires were also organic. They had a lot in common with prior organic networks like wolf packs. They all kept revolving around the traditional biological dramas of predation, reproduction, sibling rivalry, and romantic triangles. An information network dominated by inorganic computers would be different in ways that we can hardly even imagine. After all, as human beings, our imagination too is a product of organic biochemistry and cannot go beyond our preprogrammed biological dramas.
It is only eighty years since the first digital computers were built. The pace of change is constantly accelerating, and we are nowhere close to exhausting the full potential of computers.44 They may continue to evolve for millions of years, and what happened in the past eighty years is as nothing compared with what’s in store. As a crude analogy, imagine that we are in ancient Mesopotamia, eighty years after the first person thought of using a stick to imprint signs on a piece of wet clay. Could we, at that moment, envision the Library of Alexandria, the power of the Bible, or the archives of the NKVD? Even this analogy grossly underestimates the potential of future computer evolution. So try to imagine that we are now eighty years since the first self-replicating genetic code lines coalesced out of the organic soup of early Earth, about four billion years ago. At this stage, even single-celled amoebas with their cellular organization, their thousands of internal organelles, and their ability to control movement and nutrition are still futuristic fantasies.45 Could we envision Tyrannosaurus rex, the Amazon rain forest, or humans landing on the moon?
We still tend to think of a computer as a metal box with a screen and a keyboard, because this is the shape our organic imagination gave to the first baby computers in the twentieth century. As computers grow and develop, they are shedding old forms and taking radically new configurations, breaking the spatial and temporal limits of the human imagination. Unlike organic beings, computers don’t have to be in just one place at any one time. They already diffuse over space, with different parts in different cities and continents. In computer evolution, the distance from amoeba to T. rex could be covered in a decade. And whereas organic evolution took four billion years to get from organic soup to apes on the moon, computers may require just a couple of centuries to develop superintelligence, expand to planetary sizes, contract to a subatomic level, or come to sprawl over galactic space and time.
The pace of computer evolution is reflected in the terminological chaos that surrounds computers. While a couple of decades ago it was customary to speak only about “computers,” now we find ourselves talking about algorithms, robots, bots, AIs, networks, or clouds. Our difficulty in deciding what to call them is itself important. Organisms are distinct individual entities that can be grouped into collectives like species and genera. With computers, however, it is becoming ever more difficult to decide where one entity ends and another begins and how exactly to group them.
In this book I use the term “computer” when talking about the whole complex of software and hardware, manifested in physical form. I prefer to often use the almost-archaic-sounding “computer” over “algorithm” or “AI,” partly because I am aware how fast terms change and partly to remind us of the physical aspect of the computer revolution. Computers are made of matter, they consume energy, and they fill a space. Enormous amounts of electricity, fuel, water, land, precious minerals, and other resources are used to manufacture and operate them. Data centers alone account for between 1 percent and 1.5 percent of global energy usage, and large data centers take up millions of square feet and require hundreds of thousands of gallons of fresh water every day to keep them from overheating.46
I also use the term “algorithm,” when I wish to focus more on software aspects, but it is crucial to remember that all the algorithms mentioned in subsequent pages run on some computer or other. As for the term “AI,” I use it when emphasizing the ability of some algorithms to learn and change by themselves. Traditionally, AI has been an acronym for “Artificial Intelligence.” But for reasons already evident from the previous discussion, it is perhaps better to think of it as an acronym for “Alien Intelligence.” As AI evolves, it becomes less artificial (in the sense of depending on human designs) and more alien. It should also be noted that people often define and evaluate AI through the metric of “human-level intelligence,” and there is much debate about when we can expect AIs to reach “human-level intelligence.” The use of this metric, however, is deeply confusing. It is like defining and evaluating airplanes through the metric of “bird-level flight.” AI isn’t progressing towards human-level intelligence. It is evolving an entirely different type of intelligence.
Another confusing term is “robot.” In this book it is used to allude to cases when a computer moves and operates in the physical sphere; whereas the term “bot” refers to algorithms operating mainly in the digital sphere. A bot may be polluting your social media account with fake news, while a robot may clean your living room of dust.
One last note on terminology: I tend to speak of the computer-based “network” in the singular, rather than about “networks” in the plural. I am fully aware that computers can be used to create many networks with diverse characteristics, and chapter 11 explores the possibility that the world will be divided into radically different and even hostile computer networks. Nevertheless, just as different tribes, kingdoms, and churches share important features that enable us to talk about a single human network that has come to dominate planet Earth, so I prefer to talk about the computer network in the singular, in order to contrast it to the human network it is superseding.
TAKING RESPONSIBILITY
Although we cannot predict the long-term evolution of the computer-based network over the coming centuries and millennia, we can nevertheless say something about how it is evolving right now, and that is far more urgent, because the rise of the new computer network has immediate political and personal implications for all of us. In the next chapters, we’ll explore what is so new about our computer-based network and what it might mean for human life. What should be clear from the start is that this network will create entirely novel political and personal realities. The main message of the previous chapters has been that information isn’t truth and that information revolutions don’t uncover the truth. They create new political structures, economic models, and cultural norms. Since the current information revolution is more momentous than any previous information revolution, it is likely to create unprecedented realities on an unprecedented scale.
It is important to understand this because we humans are still in control. We don’t know for how long, but we still have the power to shape these new realities. To do so wisely, we need to comprehend what is happening. When we write computer code, we aren’t just designing a product. We are redesigning politics, society, and culture, and so we had better have a good grasp of politics, society, and culture. We also need to take responsibility for what we are doing.
Alarmingly, as in the case of Facebook’s involvement in the anti-Rohingya campaign, the corporations that lead the computer revolution tend to shift responsibility to customers and voters, or to politicians and regulators. When accused of creating social and political mayhem, they hide behind arguments like “We are just a platform. We are doing what our customers want and what the voters permit. We don’t force anyone to use our services, and we don’t violate any existing law. If customers didn’t like what we do, they would leave. If voters didn’t like what we do, they would pass laws against us. Since the customers keep asking for more, and since no law forbids what we do, everything must be okay.”47
These arguments are either naive or disingenuous. Tech giants like Facebook, Amazon, Baidu, and Alibaba aren’t just the obedient servants of customer whims and government regulations. They increasingly shape these whims and regulations. The tech giants have a direct line to the world’s most powerful governments, and they invest huge sums in lobbying efforts to throttle regulations that might undermine their business model. For example, they have fought tenaciously to protect Section 230 of the US Telecommunications Act of 1996, which provides immunity from liability for online platforms regarding content published by their users. It is Section 230 that protects Facebook, for example, from being liable for the Rohingya massacre. In 2022 top tech companies spent close to $70 million on lobbying in the United States, and another €113 million on lobbying EU bodies, outstripping the lobbying expenses of oil and gas companies and pharmaceuticals.48 The tech giants also have a direct line to people’s emotional system, and they are masters at swaying the whims of customers and voters. If the tech giants obey the wishes of voters and customers, but at the same time also mold these wishes, then who really controls whom?
The problem goes even deeper. The principles that “the customer is always right” and that “the voters know best” presuppose that customers, voters, and politicians know what is happening around them. They presuppose that customers who choose to use TikTok and Instagram comprehend the full consequences of this choice, and that voters and politicians who are responsible for regulating Apple and Huawei fully understand the business models and activities of these corporations. They presuppose that people know the ins and outs of the new information network and give it their blessing.
The truth is, we don’t. That’s not because we are stupid but because the technology is extremely complicated and things are moving at breakneck speed. It takes effort to understand something like blockchain-based cryptocurrencies, and by the time you think you understand it, it has morphed again. Finance is a particularly crucial example, for two reasons. First, it is much easier for computers to create and change financial devices than physical objects, because modern financial devices are made entirely of information. Currencies, stocks, and bonds were once physical objects made of gold and paper, but they have already become digital entities existing mostly in digital databases. Second, these digital entities have enormous impact on the social and political world. What might happen to democracies—or to dictatorships, for that matter—if humans are no longer able to understand how the financial system functions?
As a test case, consider what the new technology is doing to taxation. Traditionally, people and corporations paid taxes only in countries where they were physically present. But things are much trickier when physical space is augmented or replaced by cyberspace and when more and more transactions involve only the transfer of information rather than of physical goods or traditional currencies. For example, a citizen of Uruguay may daily interact online with numerous companies that might have no physical presence in Uruguay but that provide her with various services. Google provides her with free search, and ByteDance—the parent company of the TikTok application—provides her with free social media. Other foreign companies routinely target her with advertisements: Nike wants to sell her shoes, Peugeot wants to sell her a car, and Coca Cola wants to sell her soft drinks. In order to target her, these companies buy both personal information and ad space from Google and ByteDance. In addition, Google and ByteDance use the information they harvest from her and from millions of other users to develop powerful new AI tools that they can then sell to various governments and corporations throughout the world. Thanks to such transactions, Google and ByteDance are among the richest corporations in the world. So, should her transactions with them be taxed in Uruguay?
Some think they should. Not just because information from Uruguay helped make these corporations rich, but also because their activities undermine taxpaying Uruguayan businesses. Local newspapers, TV stations, and movie theaters lose customers and ad revenue to the tech giants. Prospective Uruguayan AI companies also suffer, because they cannot compete with Google’s and ByteDance’s massive data troves. But the tech giants reply that none of the relevant transactions involved any physical presence in Uruguay or any monetary payments. Google and ByteDance provided Uruguayan citizens with free online services, and in return the citizens freely handed over their purchase histories, vacation photos, funny cat videos, and other information.
If they nevertheless want to tax these transactions, the tax authorities need to reconsider some of their most fundamental concepts, such as “nexus.” In tax literature, “nexus” means an entity’s connection to a given jurisdiction. Traditionally, whether a corporation had nexus in a specific country depended on whether it had physical presence there, in the form of offices, research centers, shops, and so forth. One proposal for addressing the tax dilemmas created by the computer network is to redefine nexus. In the words of the economist Marko Köthenbürger, “The definition of nexus based on a physical presence should be adjusted to include the notion of a digital presence in a country.”49 This implies that even if Google and ByteDance have no physical presence in Uruguay, the fact that people in Uruguay use their online services should nevertheless make them subject to taxation there. Just as Shell and BP pay taxes to countries from which they extract oil, the tech giants should pay taxes to countries from which they extract data.
This still leaves open the question of what, exactly, the Uruguayan government should tax. For example, suppose Uruguayan citizens shared a million cat videos through TikTok. ByteDance didn’t charge them or pay them anything for this. But ByteDance later used the videos to train an image-recognition AI, which it sold to the South African government for ten million U.S. dollars. How would the Uruguayan authorities even know that the money was partly the fruit of Uruguayan cat videos, and how could they calculate their share? Should Uruguay impose a cat video tax? (This may sound like a joke, but as we shall see in chapter 11, cat images were crucial for making one of the most important breakthroughs in AI.)
It can get even more complicated. Suppose Uruguayan politicians promote a new scheme to tax digital transactions. In response, suppose one of the tech giants offers to provide a certain politician with valuable information on Uruguayan voters and tweak its social media and search algorithms to subtly favor that politician, which helps him win the next election. In exchange, maybe the incoming prime minister abandons the digital tax scheme. He also passes regulations that protect tech giants from lawsuits concerning users’ privacy, thereby making it easier for them to harvest information in Uruguay. Was this bribery? Note that not a single dollar or peso exchanged hands.
Such information-for-information deals are already ubiquitous. Each day billions of us conduct numerous transactions with the tech giants, but one could never guess that from our bank accounts, because hardly any money is moving. We get information from the tech giants, and we pay them with information. As more transactions follow this information-for-information model, the information economy grows at the expense of the money economy, until the very concept of money becomes questionable.
Money is supposed to be a universal measure of value, rather than a token used only in some settings. But as more things are valued in terms of information, while being “free” in terms of money, at some point it becomes misleading to evaluate the wealth of individuals and corporations in terms of the amount of dollars or pesos they possess. A person or corporation with little money in the bank but a huge data bank of information could be the wealthiest, or most powerful, entity in the country. In theory, it might be possible to quantify the value of their information in monetary terms, but they never actually convert the information into dollars or pesos. Why do they need dollars, if they can get what they want with information?
This has far-reaching implications for taxation. Taxes aim to redistribute wealth. They take a cut from the wealthiest individuals and corporations, in order to provide for everyone. However, a tax system that knows how to tax only money will soon become outdated as many transactions no longer involve money. In a data-based economy, where value is stored as data rather than as dollars, taxing only money distorts the economic and political picture. Some of the wealthiest entities in the country may pay zero taxes, because their wealth consists of petabits of data rather than billions of dollars.50
States have thousands of years of experience in taxing money. They don’t know how to tax information—at least, not yet. If we are indeed shifting from an economy dominated by money transactions to an economy dominated by information transactions, how should states react? China’s social credit system is one way a state may adapt to the new conditions. As we’ll explain in chapter 7, the social credit system is at heart a new kind of money—an information-based currency. Should all states copy the Chinese example and mint their own social credits? Are there alternative strategies? What does your favorite political party say about this question?
RIGHT AND LEFT
Taxation is just one among many problems created by the computer revolution. The computer network is disrupting almost all power structures. Democracies fear the rise of new digital dictatorships. Dictatorships fear the emergence of agents they don’t know how to control. Everyone should be concerned about the elimination of privacy and the spread of data colonialism. We’ll explain the meaning of each of these threats in the following chapters, but the point here is that the conversations about these dangers are only starting and the technology is moving much faster than the policy.For example, what’s the difference between the AI policies of Republicans and Democrats? What’s a right-wing position on AI, and what’s a left-wing position? Are conservatives against AI because of the threat it poses to traditional human-centered culture, or do they favor it because it will fuel economic growth while simultaneously reducing the need for immigrant workers? Do progressives oppose AI because of the risks of disinformation and increasing bias, or do they embrace it as a means of generating abundance that could finance a comprehensive welfare state? It is hard to tell, because until very recently Republicans and Democrats, and most other political parties around the world, haven’t thought or talked much about these issues.
Some people—like the engineers and executives of high-tech corporations—are way ahead of politicians and voters and are better informed than most of us about the development of AI, cryptocurrencies, social credits, and the like. Unfortunately, most of them don’t use their knowledge to help regulate the explosive potential of the new technologies. Instead, they use it to make billions of dollars—or to accumulate petabits of information.
There are exceptions, like Audrey Tang. She was a leading hacker and software engineer who in 2014 joined the Sunflower Student Movement that protested against government policies in Taiwan. The Taiwanese cabinet was so impressed by her skills that Tang was eventually invited to join the government as its minister of digital affairs. In that position, she helped make the government’s work more transparent to citizens. She was also credited with using digital tools to help Taiwan successfully contain the COVID-19 outbreak.51
Yet Tang’s political commitment and career path are not the norm. For every computer-science graduate who wants to be the next Audrey Tang, there are probably many more who want to be the next Jobs, Zuckerberg, or Musk and build a multibillion corporation rather than become an elected public servant. This leads to a dangerous information asymmetry. The people who lead the information revolution know far more about the underlying technology than the people who are supposed to regulate it. Under such conditions, what’s the meaning of chanting that the customer is always right and that the voters know best?
The following chapters try to level the playing field a bit and encourage us to take responsibility for the new realities created by the computer revolution. These chapters talk a lot about technology, but the viewpoint is thoroughly human. The key question is, what would it mean for humans to live in the new computer-based network, perhaps as an increasingly powerless minority? How would the new network change our politics, our society, our economy, and our daily lives? How would it feel to be constantly monitored, guided, inspired, or sanctioned by billions of nonhuman entities? How would we have to change in order to adapt, survive, and hopefully even flourish in this startling new world?
NO DETERMINISM
The most important thing to remember is that technology, in itself, is seldom deterministic. Belief in technological determinism is dangerous because it excuses people of all responsibility. Yes, since human societies are information networks, inventing new information technologies is bound to change society. When people invent printing presses or machine-learning algorithms, it will inevitably lead to a profound social and political revolution. However, humans still have a lot of control over the pace, shape, and direction of this revolution—which means we also have a lot of responsibility.
At any given moment, our scientific knowledge and technical skills can lend themselves to developing any number of different technologies, but we have only finite resources at our disposal. We should make responsible choices about where to invest these resources. Should they be used to develop a new medicine for malaria, a new wind turbine, or a new immersive video game? There is nothing inevitable about our choice; it reflects political, economic, and cultural priorities.
In the 1970s, most computer corporations like IBM focused on developing big and costly machines, which they sold to major corporations and government agencies. It was technically feasible to develop small, cheap personal computers and sell them to private individuals, but IBM had little interest in that. It didn’t fit its business model. On the other side of the Iron Curtain, in the U.S.S.R., the Soviets were also interested in computers, but they were even less inclined than IBM to develop personal computers. In a totalitarian state—where even private ownership of typewriters was suspect—the idea of providing private individuals with control of a powerful information technology was taboo. Computers were therefore given mainly to Soviet factory managers, and even they had to send all their data back to Moscow to be analyzed. As a result, Moscow was flooded with paperwork. By the 1980s, this unwieldy system of computers was producing 800 billion documents per year, all destined for the capital.52
However, at a time when IBM and the Soviet government declined to develop the personal computer, hobbyists like the members of the California Homebrew Computer Club resolved to do it by themselves. It was a conscious ideological decision, influenced by the 1960s counterculture with its anarchist ideas of power to the people and libertarian distrust of governments and big corporations.53
Leading members of the Homebrew Computer Club, like Steve Jobs and Steve Wozniak, had big dreams but little money and didn’t have access to the resources of either corporate America or the government apparatus. Jobs and Wozniak sold their personal possessions, like Jobs’s Volkswagen, to finance the creation of the first Apple computer. It was because of such personal decisions, rather than because of the inevitable decree of the goddess of technology, that by 1977 individuals could buy the Apple II personal computer for a price of $1,298—a considerable sum, but within reach of middle-class customers.54
We can easily imagine an alternative history. Suppose humanity in the 1970s had access to the same scientific knowledge and technical skills, but McCarthyism had killed the 1960s counterculture and established an American totalitarian regime that mirrored the Soviet system. Would we have personal computers today? Of course, personal computers might still have emerged in a different time and place. But in history, time and place are crucial, and no two moments are the same. It matters a great deal that America was colonized by the Spaniards in the 1490s rather than by the Ottomans in the 1520s, or that the atom bomb was developed by the Americans in 1945 rather than by the Germans in 1942. Similarly, there would have been significant political, economic, and cultural consequences if the personal computer emerged not in San Francisco of the 1970s but rather in Osaka of the 1980s or in Shanghai of the first decade of the twenty-first century.
The same is true of the technologies being currently developed. Engineers working for authoritarian governments and ruthless corporations could develop new tools to empower the central authority, by monitoring citizens and customers twenty-four hours a day. Hackers working for democracies may develop new tools to strengthen society’s self-correcting mechanisms, by exposing government corruption and corporate malpractices. Both technologies could be developed.
Choice doesn’t end there. Even after a particular tool is developed, it can be put to many uses. We can use a knife to murder a person, to save their life in surgery, or to cut vegetables for their dinner. The knife doesn’t force our hand. It’s a human choice. Similarly, when cheap radio sets were developed, it meant that almost every family in Germany could afford to have one at home. But how would it be used? Cheap radios could mean that when a totalitarian leader gave a speech, he could reach the living room of every German family. Or they could mean that every German family could choose to listen to a different radio program, reflecting and cultivating a diversity of political and artistic views. East Germany went one way; West Germany went the other. Though radio sets in East Germany could technically receive a wide range of transmissions, the East German government did its best to jam Western broadcasts and punished people who secretly tuned in to them.55 The technology was the same, but politics made very different uses of it.
The same is true of the new technologies of the twenty-first century. To exercise our agency, we first need to understand what the new technologies are and what they can do. That’s an urgent responsibility of every citizen. Naturally, not every citizen needs a PhD in computer science, but to retain control of our future, we do need to understand the political potential of computers. The next few chapters, then, offer an overview of computer politics for twenty-first-century citizens. We will first learn what the political threats and promises are of the new computer network and will then explore the different ways that democracies, dictatorships, and the international system as a whole might adjust to the new computer politics.
Politics involves a delicate balance between truth and order. As computers become important members of our information network, they are increasingly tasked with discovering truth and maintaining order. For example, the attempt to find the truth about climate change increasingly depends on calculations that only computers can make, and the attempt to reach social consensus about climate change increasingly depends on recommendation algorithms that curate our news feeds, and on creative algorithms that write news stories, fake news, and fiction. At present, we are in a political deadlock about climate change, partly because the computers are at a deadlock. Calculations run on one set of computers warn us of an imminent ecological catastrophe, but another set of computers prompt us to watch videos that cast doubt on those warnings. Which set of computers should we believe? Human politics is now also computer politics.
To understand the new computer politics, we need a deeper understanding of what’s new about computers. In this chapter we noted that unlike printing presses and other previous tools, computers can make decisions by themselves and can create ideas by themselves. That, however, is just the tip of the iceberg. What’s really new about computers is the way they make decisions and create ideas. If computers made decisions and created ideas in a way similar to humans, then computers would be a kind of “new humans.” That’s a scenario often explored in science fiction: the computer that becomes conscious, develops feelings, falls in love with a human, and turns out to be exactly like us. But the reality is very different, and potentially more alarming.
CHAPTER 7 Relentless: The Network Is Always On
Humans are used to being monitored. For millions of years, we have been watched and tracked by other animals, as well as by other humans. Family members, friends, and neighbors have always wanted to know what we do and feel, and we have always cared deeply how they see us and what they know about us. Social hierarchies, political maneuvers, and romantic relationships involved a never-ending effort to decipher what other people feel and think and occasionally hide our own feelings and thoughts.
When centralized bureaucratic networks appeared and developed, one of the bureaucrats’ most important roles was to monitor entire populations. Officials in the Qin Empire wanted to know whether we were paying our taxes or plotting resistance. The Catholic Church wanted to know whether we paid our tithes and whether we masturbated. The Coca-Cola Company wanted to know how to persuade us to buy its products. Rulers, priests, and merchants wanted to know our secrets in order to control and manipulate us.
Of course, surveillance has also been essential for providing beneficial services. Empires, churches, and corporations needed information in order to provide people with security, support, and essential goods. In modern states sanitation officials want to know where we get our water from and where we defecate. Health-care officials want to know what illnesses we suffer from and how much we eat. Welfare officials want to know whether we are unemployed or perhaps abused by our spouses. Without this information, they cannot help us.
In order to get to know us, both benign and oppressive bureaucracies have needed to do two things. First, gather a lot of data about us. Second, analyze all that data and identify patterns. Accordingly, empires, churches, corporations, and health-care systems—from ancient China to the modern United States—have gathered and analyzed data about the behavior of millions of people. However, in all times and places surveillance has been incomplete. In democracies like the modern United States, legal limits have been placed on surveillance to protect privacy and individual rights. In totalitarian regimes like the ancient Qin Empire and the modern U.S.S.R., surveillance faced no such legal barriers but came up against technical boundaries. Not even the most brutal autocrats had the technology necessary to follow everybody all the time. Some level of privacy was therefore the default even in Hitler’s Germany, Stalin’s U.S.S.R., or the copycat Stalinist regime set up in Romania after 1945.
Gheorghe Iosifescu, one of the first computer scientists in Romania, recalled that when computers were first introduced in the 1970s, the country’s regime was extremely uneasy about this unfamiliar information technology. One day in 1976 when Iosifescu walked into his office in the governmental Centrul de Calcul (Center for Calculus), he saw sitting there an unfamiliar man in a rumpled suit. Iosifescu greeted the stranger, but the man did not respond. Iosifescu introduced himself, but the man remained silent. So Iosifescu sat down at his desk, switched on a large computer, and began working. The stranger drew his chair closer, watching Iosifescu’s every move.
Throughout the day Iosifescu repeatedly tried to strike up a conversation, asking the stranger what his name was, why he was there, and what he wanted to know. But the man kept his mouth shut and his eyes wide open. When Iosifescu went home in the evening, the man got up and left too, without saying goodbye. Iosifescu knew better than to ask any further questions; the man was obviously an agent of the dreaded Romanian secret police, the Securitate.
The next morning, when Iosifescu came to work, the agent was already there. He again sat at Iosifescu’s desk all day, silently taking notes in a little notepad. This continued for the next thirteen years, until the collapse of the communist regime in 1989. After sitting at the same desk for all those years, Iosifescu never even learned the agent’s name.1
Iosifescu knew that other Securitate agents and informers were probably monitoring him outside the office, too. His expertise with a powerful and potentially subversive technology made him a prime target. But in truth, the paranoid regime of Nicolae Ceauşescu regarded all twenty million Romanian citizens as targets. If it was possible, Ceauşescu would have placed every one of them under constant surveillance. He actually made some steps in that direction. Before he came to power, in 1965, the Securitate had just 1 electronic surveillance center in Bucharest and 11 more in provincial cities. By 1978, Bucharest alone was monitored by 10 electronic surveillance centers, 248 centers scrutinized the provinces, and an additional 1,000 portable surveillance units were moved around to eavesdrop on remote villages and holiday resorts.2
When, in the late 1970s, Securitate agents discovered that some Romanians were writing anonymous letters to Radio Free Europe criticizing the regime, Ceauşescu orchestrated a nationwide effort to collect handwriting samples from all twenty million Romanian citizens. Schools and universities were forced to hand in essays from every student. Employers had to request each employee to submit a handwritten CV and then forward it to the Securitate. “What about retirees, and the unemployed?” asked one of Ceauşescu’s aides. “Invent some kind of new form!” commanded the dictator. “Something they will have to fill in.” Some of the subversive letters, however, were typed, so Ceauşescu also had every state-owned typewriter in the country registered, with samples filed away in the Securitate archive. People who possessed a private typewriter had to inform the Securitate of it, hand in the typewriter’s “fingerprint,” and ask for official authorization to use it.3
But Ceauşescu’s regime, just like the Stalinist regime it modeled itself on, could not really follow every citizen twenty-four hours a day. Given that even Securitate agents needed to sleep, it would probably have required at least forty million of them to keep the twenty million Romanian citizens under constant surveillance. Ceauşescu had only about forty thousand Securitate agents.4 And even if Ceauşescu could somehow conjure forty million agents, that would only have presented new problems, because the regime needed to monitor its own agents, too. Like Stalin, Ceauşescu distrusted his own agents and officials more than anyone else, especially after his spy chief—Ion Mihai Pacepa—defected to the United States in 1978. Politburo members, high-ranking officials, army generals, and Securitate chiefs were living under even closer surveillance than Iosifescu. As the ranks of the secret police swelled, more agents were needed to spy on all these agents.5
One solution was to have people spy on one another. In addition to its 40,000 professional agents, the Securitate relied on 400,000 civilian informers.6 People often informed on their neighbors, colleagues, friends, and even closest family members. But no matter how many informants a secret police employed, gathering all that data was not sufficient to create a total surveillance regime. Suppose the Securitate succeeded in recruiting enough agents and informers to watch everyone twenty-four hours a day. At the end of each day, every agent and informer would have had to compile a report on what they observed. Securitate headquarters would have been flooded by 20 million reports every day—or 7.3 billion reports a year. Unless analyzed, it was just an ocean of paper. Yet where could the Securitate find enough analysts to scrutinize and compare 7.3 billion reports annually?
These difficulties in gathering and analyzing information meant that in the twentieth century not even the most totalitarian state could effectively monitor its entire population. Most of what Romanian and Soviet citizens did and said escaped the notice of the Securitate and the KGB. Even the details that made it into some archive often languished unread. The real power of the Securitate and the KGB was not an ability to constantly watch everyone, but rather their ability to inspire the fear that they might be watching, which made everyone extremely careful about what they said and did.7
SLEEPLESS AGENTS
In a world where surveillance is conducted by the organic eyes, ears, and brains of people like the Securitate agent in Iosifescu’s lab, even a prime target like Iosifescu still had some privacy, first and foremost within his own mind. But the work of computer scientists like Iosifescu himself was changing this. Already in 1976, the crude computer sitting on Iosifescu’s desk could crunch numbers much better than the Securitate agent in the nearby chair. By 2024, we are getting close to the point when a ubiquitous computer network can follow the population of entire countries twenty-four hours a day. This network doesn’t need to hire and train millions of human agents to follow us around; it relies on digital agents instead. And the network doesn’t even need to pay for these digital agents. Citizens pay for the agents on our own initiative, and we carry them with us wherever we go.
The agent monitoring Iosifescu didn’t accompany Iosifescu into the toilet and didn’t sit on the bed while Iosifescu was having sex. Today, our smartphone sometimes does exactly that. Moreover, many of the activities Iosifescu did without any help from his computer—like reading the news, chatting with friends, or buying food—are now done online, so it is even easier for the network to know what we are doing and saying. We ourselves are the informers that provide the network with our raw data. Even those without smartphones are almost always within the orbit of some camera, microphone, or tracking device, and they too constantly interact with the computer network in order to find work, buy a train ticket, get a medical prescription, or simply walk down the street. The computer network has become the nexus of most human activities. In the middle of almost every financial, social, or political transaction, we now find a computer. Consequently, like Adam and Eve in paradise, we cannot hide from the eye in the clouds.
Just as the computer network doesn’t need millions of human agents to follow us, it also doesn’t need millions of human analysts to make sense of our data. The ocean of paper in Securitate headquarters never analyzed itself. But thanks to the magic of machine learning and AI, computers can themselves analyze most of the information they accumulate. An average human can read about 250 words per minute.8 A Securitate analyst working twelve-hour shifts without taking any days off, could read about 2.6 billion words during a forty-year career. In 2024 language algorithms like ChatGPT and Meta’s Llama can process millions of words per minute and “read” 2.6 billion words in a couple of hours.9 The ability of such algorithms to process images, audio recordings, and video footage is equally superhuman.
Even more important, the algorithms far surpass humans in their ability to spot patterns in that ocean of data. Identifying patterns requires both the ability to create ideas and the ability to make decisions. For example, how do human analysts identify someone as a “suspected terrorist” that merits closer attention? First, they create a set of general criteria, such as “reading extremist literature,” “befriending known terrorists,” and “having technical knowledge necessary to produce dangerous weapons.” Then they need to decide whether a particular individual meets enough of these criteria to be labeled a suspected terrorist. Suppose someone watched a hundred extremist videos on YouTube last month, is friends with a convicted terrorist, and is currently pursuing a doctorate in epidemiology in a laboratory containing samples of Ebola virus. Should that person be put on the “suspected terrorists” list? And what about someone who watched fifty extremist videos last month and is a biology undergraduate?
In Romania of the 1970s only humans could make such decisions. By the 2010s humans were increasingly leaving it to algorithms to decide. Around 2014–15 the U.S. National Security Agency deployed an AI tool called Skynet that placed people on a “suspected terrorists” list based on the electronic patterns of their communications, writings, travel, and social media postings. According to one report, that AI tool “engages in mass surveillance of Pakistan’s mobile phone network, and then uses a machine learning algorithm on the cellular network metadata of 55 million people to try and rate each person’s likelihood of being a terrorist.” A former director of both the CIA and the NSA proclaimed that “we kill people based on metadata.”10 Skynet’s reliability has been severely criticized, but by the 2020s such technology has become far more sophisticated and has been deployed by a lot more governments. Going over massive amounts of data, algorithms can discover completely new criteria for defining someone as “suspect” which have previously escaped the notice of human analysts.11In the future, algorithms could even create an entire new model for how people are radicalized, just by identifying patterns in the lives of known terrorists. Of course, computers remain fallible, as we shall explore in depth in chapter 8. They may well classify innocent people as terrorists or may create a false model for radicalization. At an even more fundamental level, it is questionable whether the systems’ definition of things like terrorism are objective. There is a long history of regimes using the label “terrorist” to cover any and all opposition. In the Soviet Union, anyone who opposed the regime was a terrorist. Consequently, when an AI labels someone a “terrorist” it might reflect ideological biases rather than objective facts. The power to make decisions and invent ideas is inseparable from the capacity to make mistakes. Even if no mistakes are committed, the algorithms’ superhuman ability to recognize patterns in an ocean of data can supercharge the power of numerous malign actors, from repressive dictatorships that seek to identify dissidents to fraudsters who seek to identify vulnerable targets.
Of course, pattern recognition also has enormous positive potential. Algorithms can help identify corrupt government officials, white-collar criminals, and tax-evading corporations. The algorithms can similarly help flesh-and-blood sanitation officials to spot threats to our drinking water;12 help doctors to discern illnesses and burgeoning epidemics;13 and help police officers and social workers to identify abused spouses and children.14 In the following pages, I dedicate relatively little attention to the positive potential of algorithmic bureaucracies, because the entrepreneurs leading the AI revolution already bombard the public with enough rosy predictions about them. My goal here is to balance these utopian visions by focusing on the more sinister potential of algorithmic pattern recognition. Hopefully, we can harness the positive potential of algorithms while regulating their destructive capacities.
But to do so, we must first appreciate the fundamental difference between the new digital bureaucrats and their flesh-and-blood predecessors. Inorganic bureaucrats can be “on” twenty-four hours a day and can monitor us and interact with us anywhere, anytime. This means that bureaucracy and surveillance are no longer something we encounter only in specific times and places. The health-care system, the police, and manipulative corporations are all becoming ubiquitous and permanent features of life. Instead of organizations with which we interact only in certain situations—for example, when we visit the clinic, the police station, or the mall—they are increasingly accompanying us every moment of the day, watching and analyzing every single thing that we do. As fish live in water, humans live in a digital bureaucracy, constantly inhaling and exhaling data. Each action we make leaves a trace of data, which is gathered and analyzed to identify patterns.
UNDER-THE-SKIN SURVEILLANCE
For better or worse, the digital bureaucracy may not only monitor what we do in the world but even observe what is happening inside our bodies. Take, for example, tracking eye movements. By the early 2020s, CCTV cameras, as well as cameras in laptops and smartphones, have begun to routinely collect and analyze data on the movements of our eyes, including tiny changes to our pupils and irises lasting just a few milliseconds. Human agents are barely capable of even noticing such data, but computers can use it to calculate the direction of our gaze, based on the shape of our pupils and irises and on the patterns of light they reflect. Similar methods can determine whether our eyes are fixating on a stable target, pursuing a moving target, or wandering around more haphazardly.
From certain patterns of eye movements, computers can then distinguish, for example, moments of awareness from moments of distraction, and detail-oriented people from those who pay more attention to context. Computers could infer from our eyes many additional personality traits, like how open we are to new experiences, and estimate our level of expertise in various fields ranging from reading to surgery. Experts possessing well-honed strategies display systematic gaze patterns, whereas the eyes of novices wander aimlessly. Eye patterns also indicate our levels of interest in the objects and situations we encounter, and distinguish between positive, neutral, and negative interest. From this, it is possible to deduce our preferences in fields ranging from politics to sex. Much can also be known about our medical condition and our use of various substances. The consumption of alcohol and drugs—even at nonintoxicating doses—has measurable effects on eye and gaze properties, such as changes in pupil size and an impaired ability to fixate on moving objects. A digital bureaucracy may use all that information for benign purposes—such as by providing early detection for people suffering from drug abuse and mental illnesses. But it could obviously also form the foundations of the most intrusive totalitarian regimes in history.15
In theory, the dictators of the future could get their computer network to go much deeper than just watching our eyes. If the network wants to know our political views, personality traits, and sexual orientation, it could monitor processes inside our hearts and brains. The necessary biometric technology is already being developed by some governments and companies, like Elon Musk’s Neuralink. Musk’s company has conducted experiments on live rats, sheep, pigs, and monkeys, implanting electrical probes into their brains. Each probe contains up to 3,072 electrodes capable of identifying electrical signals and potentially transmitting signals to the brain. In 2023, Neuralink received approval from U.S. authorities to begin experiments on human beings, and in January 2024 it was reported that a first brain chip was implanted in a human.
Musk speaks openly about his far-reaching plans for this technology, arguing that it can not only alleviate various medical conditions such as quadriplegia (four-limb paralysis) but also upgrade human abilities and thereby help humankind compete with AI. But it should be clear that at present the Neuralink probes and all other similar biometric devices suffer from a host of technical problems that greatly limit their capabilities. It is difficult to accurately monitor bodily activities—in the brain, heart, or anywhere else—from outside the body, whereas implanting electrodes and other monitoring devices into the body is intrusive, dangerous, costly, and inefficient. Our immune system, for example, attacks implanted electrodes.16
Even more crucially, nobody yet has the biological knowledge necessary to deduce things like precise political opinions from under-the-skin data like brain activity.17 Scientists are far from understanding the mysteries of the human brain, or even of the mouse brain. Simply mapping every neuron, dendrite, and synapse in a mouse brain—let alone understanding the dynamics between them—is currently beyond humanity’s computational abilities.18 Accordingly, while gathering data from inside people’s brains is becoming more feasible, using such data to decipher our secrets is far from easy.
One popular conspiracy theory of the early 2020s argues that sinister groups led by billionaires like Elon Musk are already implanting computer chips into our brains in order to monitor and control us. However, this theory focuses our anxieties on the wrong target. We should of course fear the rise of new totalitarian systems, but it is too soon to worry about computer chips implanted in our brains. People should instead worry about the smartphones on which they read these conspiracy theories. Suppose someone wants to know your political views. Your smartphone monitors which news channels you are watching and notes that you watch on average forty minutes of Fox News and forty seconds of CNN a day. Meanwhile, an implanted Neuralink computer chip monitors your heart rate and brain activity throughout the day and notes that your maximum heart rate was 120 beats per minute and that your amygdala is about 5 percent more active than the human average. Which data would be more useful to guess your political affiliation—the data coming from the smartphone or from the implanted chip?19 At present, the smartphone is still a far more valuable surveillance tool than biometric sensors.
However, as biological knowledge increases—not least thanks to computers analyzing petabits of biometric data—under-the-skin surveillance might eventually come into its own, especially if it is linked to other monitoring tools. At that point, if biometric sensors register what happens to the heart rate and brain activity of millions of people as they watch a particular news item on their smartphones, that can teach the computer network far more than just our general political affiliation. The network could learn precisely what makes each human angry, fearful, or joyful. The network could then both predict and manipulate our feelings, selling us anything it wants—be it a product, a politician, or a war.20
THE END OF PRIVACY
In a world where humans monitored humans, privacy was the default. But in a world where computers monitor humans, it may become possible for the first time in history to completely annihilate privacy. The most extreme and well-known cases of intrusive surveillance involve either exceptional times of emergency, like the COVID-19 pandemic, or places seen as exceptional to the normal order of things, such as the Occupied Palestinian Territories, the Xinjiang Uyghur Autonomous Region in China, the region of Kashmir in India, Russian-occupied Crimea, the U.S.-Mexico border, and the Afghanistan-Pakistan borderlands. In these exceptional times and places, new surveillance technologies, combined with draconian laws and heavy police or military presence, have relentlessly monitored and controlled people’s movements, actions, and even feelings.21 What is crucial to realize, though, is that AI-based surveillance tools are being deployed on an enormous scale, and not only in such “states of exception.”22 They are now part and parcel of normal life everywhere. The post-privacy era is taking hold in authoritarian countries ranging from Belarus to Zimbabwe,23 as well as in democratic metropolises like London and New York.
Whether for good or ill, governments intent on combating crime, suppressing dissent, or countering internal threats (real or imaginary) blanket whole territories with a ubiquitous online and offline surveillance network, equipped with spyware, CCTV cameras, facial recognition and voice recognition software, and vast searchable databases. If a government wishes, its surveillance network can reach everywhere, from markets to places of worship, from schools to private residences. (And while not every government is willing or able to install cameras inside people’s homes, algorithms regularly watch us even in our living rooms, bedrooms and bathrooms via our own computers and smartphones.)
Governmental surveillance networks also routinely collect biometric data from entire populations, with or without their knowledge. For example, when applying for a passport, more than 140 countries oblige their citizens to provide fingerprints, facial scans, or iris scans.24 When we use our passports to enter a foreign country, that country often demands that we provide it, too, with our fingerprints, facial scans, or iris scans.25 As citizens or tourists walk along the streets of Delhi, Beijing, Seoul, or London, their movements are likely to be recorded. For these cities—and many others around the world—are covered by more than one hundred surveillance cameras on average per square kilometer. Altogether, in 2023 more than one billion CCTV cameras were operative globally, which is about one camera per eight people.26
Any physical activity a person engages in leaves a data trace. Every purchase made is recorded in some database. Online activities like messaging friends, sharing photos, paying bills, reading news, booking appointments, or ordering taxis can all be recorded as well. The resulting ocean of data can then be analyzed by AI tools to identify unlawful activities, suspicious patterns, missing persons, disease carriers, or political dissidents.
As with every powerful technology, these tools can be used for either good or bad purposes. Following the storming of the U.S. Capitol on January 6, 2021, the FBI and other U.S. law enforcement agencies used state-of-the-art surveillance tools to track down and arrest the rioters. As reported in a Washington Post investigation, these agencies relied not only on footage from the CCTV cameras in the Capitol, but also on social media posts, license plate readers throughout the country, cell-tower location records, and preexisting databases.
One Ohio man wrote on Facebook that he had been in Washington that day to “witness history.” A subpoena was issued to Facebook, which provided the FBI with the man’s Facebook posts, as well as his credit card information and phone number. This helped the FBI to match the man’s driver’s license photo to CCTV footage from the Capitol. Another warrant issued to Google yielded the exact geolocation of the man’s smartphone on January 6, enabling agents to map his every movement from his entry point into the Senate chamber all the way to the office of Nancy Pelosi, the speaker of the House of Representatives.
Relying on license plate footage, the FBI pinpointed the movements of a New York man from the moment he crossed the Henry Hudson Bridge at 6:06:08 on the morning of January 6, on his way to the Capitol, until he crossed the George Washington Bridge at 23:59:22 that night, on his way back home. An image taken by a camera on Interstate 95 showed an oversized “Make America Great Again” hat on the man’s dashboard. The hat was matched to a Facebook selfie in which the man appeared wearing it. He further incriminated himself with several videos he posted to Snapchat from within the Capitol.
Another rioter sought to protect himself from detection by wearing a face mask on January 6, avoiding live-streaming, and using a cellphone registered in his mother’s name—but it availed him little. The FBI’s algorithms managed to match video footage from January 6, 2021, to a photo from the man’s 2017 passport application. They also matched a distinctive Knights of Columbus jacket he wore on January 6 to the jacket he wore on a different occasion, which was captured in a YouTube clip. The phone registered in his mother’s name was geolocated to inside the Capitol, and a license plate reader recorded his car near the Capitol on the morning of January 6.27
Facial recognition algorithms and AI-searchable databases are now standard tools of police forces all over the world. They are deployed not only in cases of national emergencies or for reasons of state security, but for everyday policing tasks. In 2009, a criminal gang abducted the three-year-old Gui Hao while he was playing outside his parents’ shop in Sichuan province, China. The boy was then sold to a family in Guangdong province, about 1,500 kilometers away. In 2014, the leader of the child-trafficking gang was arrested, but it proved impossible to locate Gui Hao and other victims. “The appearance of the children would have changed so much,” explained a police investigator, “that even their parents would not have been able to recognize them”.
In 2019, however, a facial recognition algorithm managed to identify the now thirteen-year-old Gui Hao, and the teenager was reunited with his family. To correctly identify Gui Hao, the AI relied on an old photograph of his, taken when he was a toddler. The AI simulated what Gui Hao must look like as a thirteen-year-old, taking into account the drastic impact of maturation as well as potential changes in hair color and hairstyle and compared the resulting simulation to real-life footage.
In 2023, even more remarkable rescues were reported. Yuechuan Lei was abducted in 2001 when he was three years old, and Hao Chen went missing in 1998, also at age three. The parents of both children never gave up hope of finding them. For more than twenty years they crisscrossed China in search of them, placed advertisements, and offered monetary rewards for any relevant information. In 2023, facial recognition algorithms helped locate both missing boys, now adult men in their twenties. Such technology currently helps to find lost children not only in China, but also in other countries like India, where tens of thousands of children go missing every year.28
Meanwhile, in Denmark, the soccer club Brøndby IF began in July 2019 to use facial recognition technology in its home stadium to identify and ban football hooligans. As up to 30,000 fans stream into the stadium to watch a match, they are asked to remove masks, hats, and glasses so a computer can scan their faces and compare them to a list of banned troublemakers. Crucially, the procedure has been vetted and approved in accordance with the EU’s strict GDPR rules. The Danish Data Protection Authority explained that the use of the technology “would allow for more effective enforcement of the ban list compared to manual checks, and that this could reduce the queues at the stadium entrance, lowering the risk of public unrest from impatient football fans standing in queues.”29
While such usages of technology are laudable in theory, they raise obvious concerns about privacy and governmental overreach. In the wrong hands, the same techniques that can locate rioters, rescue missing children, and ban football hooligans can also be used to persecute peaceful demonstrators or enforce rigid conformism. Ultimately, AI-powered surveillance technology could result in the creation of total surveillance regimes that monitor citizens around the clock and facilitate new kinds of ubiquitous and automated totalitarian repression. A case in point: Iran’s hijab laws.
After Iran became an Islamic theocracy in 1979, the new regime made it compulsory for women to wear the hijab. But the Iranian morality police found it difficult to enforce this rule. They couldn’t place a police officer on every street corner, and public confrontations with women who went unveiled occasionally aroused resistance and resentment. In 2022, Iran relegated much of the job of enforcing the hijab laws to a countrywide system of facial recognition algorithms that relentlessly monitor both physical spaces and online environments.30 A top Iranian official explained that the system would “identify inappropriate and unusual movements” including “failure to observe hijab laws.” The head of Iran’s parliamentary legal and judicial committee, Mousa Ghazanfarabadi, said in another interview that “the use of face recording cameras can systematically implement this task and reduce the presence of the police, as a result of which there will be no more clashes between the police and citizens.”31
Shortly afterward, on September 16, 2022, the 22-year-old Mahsa Amini died in the custody of Iran’s morality police, after being arrested for not wearing her hijab properly.32 A wave of protests erupted, known as the “Woman, Life, Freedom” movement. Hundreds of thousands of women and girls removed their headscarves, and some publicly burned their hijabs, and danced around the bonfires. To clamp down on the protests, Iranian authorities once again turned to their AI surveillance system, which relies on facial recognition software, geolocation, analysis of web traffic, and preexisting databases. More than 19,000 people were arrested throughout Iran, and more than 500 were killed.33
On April 8, 2023, Iran’s chief of police announced that beginning on April 15, 2023, an intense new campaign would ramp up the use of facial recognition technology. In particular, algorithms would henceforth identify women who choose not to wear a headscarf while travelling in a vehicle, and automatically issue them an SMS warning. If a woman was caught repeating the offense, she would be ordered to immobilize her car for a predetermined period, and if she failed to comply, the car would be confiscated.34
Two months later, on June 14, 2023, the spokesperson of Iran’s police boasted that the automated surveillance system sent almost one million SMS warning messages to women who had been captured unveiled in their private cars. The system was apparently able to automatically determine that it was seeing an unveiled woman rather than a man, identify the woman, and retrieve her cellphone number. The system further “issued 133,174 SMS messages requiring the immobilization of vehicles for two weeks, confiscated 2,000 cars, and referred more than 4,000 ‘repeat offenders’ to the judiciary.”35
A 52-year-old woman named Maryam shared with Amnesty International her experience with the surveillance system. “The first time I received a warning for not wearing a headscarf while driving, I was passing through an intersection when a camera captured a photo and I immediately received a warning text message. The second time, I had done some shopping, and I was bringing the bags into the car, my scarf fell off, and I received a message noting that due to violating compulsory veiling laws, my car had been subjected to ‘systematic impoundment’ for a period of fifteen days. I did not know what this meant. I asked around and found out through relatives that this meant I had to immobilize my car for fifteen days.”36 Maryam’s testimony indicates that the AI sends its threatening messages within seconds, with no time for any human to review and authorize the procedure.
Penalties went far beyond the immobilization or confiscation of vehicles. The Amnesty report from July 26, 2023, revealed that as a result of the mass surveillance effort “countless women have been suspended or expelled from universities, barred from sitting final exams, and denied access to banking services and public transport.”37 Businesses that didn’t enforce the hijab law among their employees or customers also suffered. In one typical case, a woman employee at the Land of Happiness amusement park east of Tehran was photographed without a hijab, and the image circulated on social media. In punishment, the Land of Happiness was closed down by Iranian authorities.38 Altogether, reported Amnesty, the authorities “shut down hundreds of tourist attractions, hotels, restaurants, pharmacies and shopping centres for not enforcing compulsory veiling laws”.39
In September 2023, on the anniversary of Mahsa Amini’s death, Iran’s parliament passed a new and stricter hijab bill. According to the new law, women who fail to wear the hijab can be punished by heavy fines and up to ten years in prison. They face additional penalties including confiscation of cars and communication devices, driving bans, deductions in salary and employment benefits, dismissal from work, and prohibition from access banking services. Business owners who don’t enforce the hijab law among their employees or customers face a fine of up to three months of their profits, and they may be banned from leaving the country or participating in public or online activities for up to two years. The new bill targets not only women, but also men who wear “revealing clothing that shows parts of the body lower than the chest or above the ankles.” Finally, the law mandates that Iranian police must “create and strengthen AI systems to identify perpetrators of illegal behavior using tools such as fixed and mobile cameras.”40 In coming years, many people might be living under total surveillance regimes that would make Ceauşescu’s Romania look like a libertarian utopia.
VARIETIES OF SURVEILLANCE
When talking about surveillance, we usually think of state-run apparatuses, but to understand surveillance in the twenty-first century, we should remember that monitoring can take many other forms. Jealous partners, for example, have always wanted to know where their spouses were at every moment and demanded explanations for any little deviation from routines. Today, armed with a smartphone and some cheap software, they can easily establish marital dictatorships. They can monitor every conversation and every movement, record phone logs, track social media posts and web page searches, and even activate the cameras and microphones of a spouse’s phone to serve as a spying device. The U.S.-based National Network to End Domestic Violence found that more than half of domestic abusers used such “stalkware” technology. Even in New York a spouse may find themselves monitored and restricted, as if they lived in a totalitarian state.41
A growing percentage of employees—from office workers to truck drivers—are also now being surveilled by their employers. Bosses can pinpoint where employees are at any moment, how much time they spend in the toilet, whether they read personal emails at work, and how fast they complete each task.42 Corporations are similarly monitoring their customers, wanting to know their likes and dislikes, to predict future behavior, and to evaluate risks and opportunities. For example, vehicles monitor their drivers’ behavior and share the data with the algorithms of the insurance companies, which raise the premiums they charge “bad drivers” and lower the premiums for “good drivers.”43 The American scholar Shoshana Zuboff has termed this ever-expanding commercial monitoring system “surveillance capitalism.”44
In addition to all these varieties of top-down surveillance, there are peer-to-peer systems in which individuals constantly monitor one another. For example, the Tripadvisor corporation maintains a worldwide surveillance system that monitors hotels, vacation rentals, restaurants, and tourists. In 2019, it was used by 463 million travelers who browsed 859 million reviews and 8.6 billion lodgings, restaurants, and tourist attractions. It is the users themselves—rather than some sophisticated AI algorithm—who determine whether a restaurant is worth visiting. People who ate in the restaurant can score it on a 1 to 5 scale, and also add photos and written reviews. The Tripadvisor algorithm merely aggregates the data, calculates the restaurant’s average score, ranks the restaurant compared with others of its kind, and makes the results available for everybody to see.
The algorithm simultaneously ranks the guests, too. For posting reviews or travel articles, users receive 100 points; for uploading photos or videos, 30 points; for posting in a forum, 20 points; for rating establishments, 5 points; and for casting votes for others’ reviews, 1 point. Users are then ranked from Level 1 (300 points) to Level 6 (10,000 points) and receive perks accordingly. Users who violate the system’s rules—for example, by submitting racist comments or trying to blackmail a restaurant by writing an unjustified bad review—may be penalized or kicked out of the system altogether. This is peer-to-peer surveillance. Everybody is constantly grading everybody else. Tripadvisor doesn’t need to invest in cameras and spyware or develop hyper-sophisticated biometric algorithms. Almost all the data is submitted and almost all the work is done by millions of human users. The job of the Tripadvisor algorithm is only to aggregate human-generated scores and publish them.45
Tripadvisor and similar peer-to-peer surveillance systems provide valuable information for millions of people every day, making it easier to plan vacations and find good hotels and restaurants. But in doing so, they have also shifted the border between private and public spaces. Traditionally, the relationship between the customer and a waiter, say, was a relatively private affair. Entering a bistro meant entering a semiprivate space and establishing a semiprivate relationship with the waiter. Unless some crime was committed, what happened between guest and waiter was their business alone. If the waiter was rude or made a racist remark, you could make a scene and perhaps tell your friends not to go there, but few other people would hear about it.
Peer-to-peer surveillance networks have obliterated that sense of privacy. If the staff fails to please a customer, the restaurant will get a bad review, which could affect the decision of thousands of potential customers in coming years. For better or worse, the balance of power tilts in favor of the customers, while the staff find themselves more exposed than before to the public gaze. As the author and journalist Linda Kinstler put it, “Before Tripadvisor, the customer was only nominally king. After, he became a veritable tyrant, with the power to make or break lives.”46 The same loss of privacy is felt today by millions of taxi drivers, barbers, beauticians, and other service providers. In the past, stepping into a taxi or barbershop meant stepping into someone’s private space. Now, when customers come into your taxi or barbershop, they bring cameras, microphones, a surveillance network, and thousands of potential viewers with them.47 This is the foundation of a nongovernmental peer-to-peer surveillance network.
THE SOCIAL CREDIT SYSTEM
Peer-to-peer surveillance systems typically operate by aggregating many points to determine an overall score. Another type of surveillance network takes this “score logic” to its ultimate conclusion. This is the social credit system, which seeks to give people points for everything and produce an overall personal score that will influence everything. The last time humans came up with such an ambitious points system was five thousand years ago in Mesopotamia, when money was invented. One way to think of the social credit system is as a new kind of money.
Money is points that people accumulate by selling certain products and services, and then use to buy other products and services. Some countries call their “points” dollars, whereas other countries call them euros, yen, or renminbi. The points can take the form of coins, banknotes, or bits in a digital bank account. The points themselves are, of course, intrinsically worthless. You cannot eat coins or wear banknotes. Their value lies in the fact that they serve as accounting tokens that society uses to keep track of our individual scores.
Money revolutionized economic relations, social interactions, and human psychology. But like surveillance, money has had its limitations and could not reach everywhere. Even in the most capitalist societies, there have always been places that money didn’t penetrate, and there have always been many things that lacked a monetary value. How much is a smile worth? How much money does a person earn for visiting their grandparents?48
For scoring those things that money can’t buy, there was an alternative nonmonetary system, which has been given different names: honor, status, reputation. What social credit systems seek is a standardized valuation of the reputation market. Social credit is a new points system that ascribes precise values even to smiles and family visits. To appreciate how revolutionary and far-reaching this is, let’s examine in brief how the reputation market has hitherto differed from the money market. This will help us understand what might happen to social relations if the principles of the money market are suddenly extended to the reputation market.
One major difference between money and reputation is that money has tended to be a mathematical construct based on precise calculations, whereas the sphere of reputation has been resistant to precise numerical evaluation. For example, medieval aristocrats graded themselves in hierarchical ranks such as dukes, counts, and viscounts, but nobody was counting reputation points. Customers in a medieval market usually knew how many coins they had in their purses and the price of every product in the stalls. In the money market, no coin goes uncounted. In contrast, knights in a medieval reputational market didn’t know the exact amount of honor that different actions might accrue, nor could they be sure of their overall score. Would fighting bravely in battle bring a knight 10 honor points, or 100? And what if nobody saw and recorded their bravery? Indeed, even assuming it was noticed, different people might assign it different values. This lack of precision wasn’t a bug in the system but a crucial feature. “Calculating” was a synonym for cunning and scheming. Acting honorably was supposed to reflect an inner virtue, rather than a pursuit of external rewards.49
This difference between the scrupulous money market and the ill-defined reputation market still prevails. The owner of a bistro always notices and complains if you don’t pay for your meal in full; every item on the menu has a precise price. But how would the owner even know if society failed to register some good deed they performed? Whom could they complain to if they weren’t properly rewarded for helping an elderly customer or for being extra patient with a rude customer? In some cases, they might now try complaining to Tripadvisor, which collapses the boundary between the money market and the reputation market, turning the fuzzy reputation of restaurants and hotels into a mathematical system of precise points. The idea of social credit is to expand this surveillance method from restaurants and hotels to everything. In the most extreme type of social credit systems, every person gets an overall reputation score that takes into account whatever they do and determines everything they can do.
For example, you might earn 10 points for picking up trash from the street, get another 20 points for helping an old lady cross the road, and lose 15 points for playing the drums and disturbing the neighbors. If you get a high enough score, it might give you priority when buying train tickets or a leg up when applying to university. If you get a low score, potential employers may refuse to give you a job, and potential dates may refuse your advances. Insurance companies may demand higher premiums, and judges may inflict harsher sentences.
Some people might see social credit systems as a way to reward pro-social behavior, punish egotistical acts, and create kinder and more harmonious societies. The Chinese government, for example, explains that its social credit systems could help fight corruption, scams, tax evasion, false advertising, and counterfeiting, and thereby establish more trust between individuals, between consumers and corporations, and between citizens and government institutions.50 Others may find systems that allocate precise values to every social action demeaning and inhuman. Even worse, a comprehensive social credit system will annihilate privacy and effectively turn life into a never-ending job interview. Anything you do, anytime, anywhere, might affect your chances of getting a job, a bank loan, a husband, or a prison sentence. You got drunk at a college party and did something legal but shameful? You participated in a political demonstration? You’re friends with someone who has a low credit score? This will be part of your job interview—or criminal sentencing—both in the short term and even decades later. The social credit system might thereby become a totalitarian control system.
Of course, the reputation market always controlled people and made them conform to the prevailing social norms. In most societies people have always feared losing face even more than they have feared losing money. Many more people commit suicide due to shame and guilt than due to economic distress. Even when people kill themselves after being fired from their job or after their business goes bankrupt, they are usually pushed over the edge by the social humiliation it involves rather than by the economic hardship per se.51
But the uncertainty and the subjectivity of the reputation market have previously limited its potential for totalitarian control. Since nobody knew the precise value of each social interaction, and since nobody could possibly keep tabs on all interactions, there was significant room for maneuver. When you went to a college party, you might have behaved in a way that earned the respect of your friends, without worrying what future employers might think. When you went to a job interview, you knew none of your friends would be there. And when you were watching pornography at home, you assumed that neither your bosses nor your friends knew what you were up to. Life has been divided into separate reputational spheres, with separate status competitions, and there were also many off-grid moments when you didn’t have to engage in any status competitions at all. Precisely because status competition is so crucial, it is also extremely stressful. Therefore, not only humans but even other social animals like apes have always welcomed some respite from it.52
Unfortunately, social credit algorithms combined with ubiquitous surveillance technology now threaten to merge all status competitions into a single never-ending race. Even in their own homes or while trying to enjoy a relaxed vacation, people would have to be extremely careful about every deed and word, as if they were performing onstage in front of millions. This could create an incredibly stressful lifestyle, destructive to people’s well-being as well as to the functioning of society. If digital bureaucrats use a precise points system to keep tabs on everybody all the time, the emerging reputation market could annihilate privacy and control people far more tightly than the money market ever did.
ALWAYS ON
Humans are organic beings who live by cyclical biological time. Sometimes we are awake; sometimes we are asleep. After intense activity, we need rest. We grow and decay. Networks of humans are similarly subject to biological cycles. They are sometimes on and sometimes off. Job interviews don’t last forever. Police agents don’t work twenty-four hours a day. Bureaucrats take holidays. Even the money market respects these biological cycles. The New York Stock Exchange is open on Mondays to Fridays, from 9:30 in the morning to 4:00 in the afternoon, and is closed on holidays like Independence Day and New Year’s Day. If a war erupts at 4:01 p.m. on a Friday, the market won’t react to it until Monday morning.
In contrast, a network of computers can always be on. Computers are consequently pushing humans toward a new kind of existence in which we are always connected and always monitored. In some contexts, like health care, this could be a boon. In other contexts, like for citizens of totalitarian states, this could be a disaster. Even if the network is potentially benign, the very fact that it is always “on” might be damaging to organic entities like humans, because it will take away our opportunities to disconnect and relax. If an organism never has a chance to rest, it eventually collapses and dies. But how will we get a relentless network to slow down and allow us some breaks?
We need to prevent the computer network from taking complete control of society not just in order to give us time off. Breaks are even more crucial to give us a chance to rectify the network. If the network continues to evolve at an accelerating pace, errors will accumulate much faster than we can identify and correct them. For while the network is relentless and ubiquitous, it is also fallible. Yes, computers can gather unprecedented amounts of data on us, watching what we do twenty-four hours a day. And yes, they can identify patterns in the ocean of data with superhuman efficiency. But that does not mean that the computer network will always understand the world accurately. Information isn’t truth. A total surveillance system may form a very distorted understanding of the world and of human beings. Instead of discovering the truth about the world and about us, the network might use its immense power to create a new kind of world order and impose it on us.
CHAPTER 8 Fallible: The Network Is Often Wrong
In The Gulag Archipelago (1973), Aleksandr Solzhenitsyn chronicles the history of the Soviet labor camps and of the information network that created and sustained them. He was writing partly from bitter personal experience. When Solzhenitsyn served as a captain in the Red Army during World War II, he maintained a private correspondence with a school friend in which he occasionally criticized Stalin. To be on the safe side, he did not mention the dictator by name and spoke only about “the man with the mustache.” It availed him little. His letters were intercepted and read by the secret police, and in February 1945, while serving on the front line in Germany, he was arrested. He spent the next eight years in labor camps.1 Many of Solzhenitsyn’s hard-won insights and stories are still relevant to understanding the development of information networks in the twenty-first century.
One story recounts events at a district party conference in Moscow Province in the late 1930s, at the height of the Stalinist Great Terror. A call was made to pay tribute to Stalin, and the audience—who of course knew that they were being carefully watched—burst into applause. After five minutes of applause, “palms were getting sore and raised arms were already aching. And the older people were panting from exhaustion.… However, who would dare be the first to stop?” Solzhenitsyn explains that “NKVD men were standing in the hall applauding and watching to see who quit first!” It went on and on, for six minutes, then eight, then ten. “They couldn’t stop now till they collapsed with heart attacks! … With make-believe enthusiasm on their faces, looking at each other with faint hope, the district leaders were just going to go on and on applauding till they fell where they stood.”
Finally, after eleven minutes, the director of a paper factory took his life in his hands, stopped clapping, and sat down. Everyone else immediately stopped clapping and also sat down. That same night, the secret police arrested him and sent him to the gulag for ten years. “His interrogator reminded him: Don’t ever be the first to stop applauding!”2
This story reveals a crucial and disturbing fact about information networks, and in particular about surveillance systems. As discussed in previous chapters, contrary to the naive view, information is often used to create order rather than discover truth. On the face of it, Stalin’s agents in the Moscow conference used the “clapping test” as a way to uncover the truth about the audience. It was a loyalty test, which assumed that the longer you clapped, the more you loved Stalin. In many contexts, this assumption is not unreasonable. But in the context of Moscow in the late 1930s, the nature of the applause changed. Since participants in the conference knew they were being watched, and since they knew the consequences of any hint of disloyalty, they clapped out of terror rather than love. The paper factory director might have been the first to stop not because he was the least loyal but perhaps because he was the most honest, or even simply because his hands hurt the most.
While the clapping test didn’t discover the truth about people, it was efficient in imposing order and forcing people to behave in a certain way. Over time, such methods cultivated servility, hypocrisy, and cynicism. This is what the Soviet information network did to hundreds of millions of people over decades. In quantum mechanics the act of observing subatomic particles changes their behavior; it is the same with the act of observing humans. The more powerful our tools of observation, the greater the potential impact.
The Soviet regime constructed one of the most formidable information networks in history. It gathered and processed enormous amounts of data on its citizens. It also claimed that the infallible theories of Marx, Engels, Lenin, and Stalin granted it a deep understanding of humanity. In fact, the Soviet information network ignored many important aspects of human nature, and it was in complete denial regarding the terrible suffering its policies inflicted on its own citizens. Instead of producing wisdom, it produced order, and instead of revealing the universal truth about humans, it actually created a new type of human—Homo sovieticus.
As defined by the dissident Soviet philosopher and satirist Aleksandr Zinovyev, Homo sovieticus were servile and cynical humans, lacking all initiative or independent thinking, passively obeying even the most ludicrous orders, and indifferent to the results of their actions.3 The Soviet information network created Homo sovieticus through surveillance, punishments, and rewards. For example, by sending the director of the paper factory to the gulag, the network signaled to the other participants that conformity paid off, whereas being the first to do anything controversial was a bad idea. Though the network failed to discover the truth about humans, it was so good at creating order that it conquered much of the world.
THE DICTATORSHIP OF THE LIKE
An analogous dynamic may afflict the computer networks of the twenty-first century, which might create new types of humans and new dystopias. A paradigmatic example is the role played by social media algorithms in radicalizing people. Of course, the methods employed by the algorithms have been utterly different from those of the NKVD and involved no direct coercion or violence. But just as the Soviet secret police created the slavish Homo sovieticus through surveillance, rewards, and punishments, so also the Facebook and YouTube algorithms have created internet trolls by rewarding certain base instincts while punishing the better angels of our nature.
As explained briefly in chapter 6, the process of radicalization started when corporations tasked their algorithms with increasing user engagement, not only in Myanmar, but throughout the world. For example, in 2012 users were watching about 100 million hours of videos every day on YouTube. That was not enough for company executives, who set their algorithms an ambitious goal: 1 billion hours a day by 2016.4 Through trial-and-error experiments on millions of people, the YouTube algorithms discovered the same pattern that Facebook algorithms also learned: outrage drives engagement up, while moderation tends not to. Accordingly, the YouTube algorithms began recommending outrageous conspiracy theories to millions of viewers while ignoring more moderate content. By 2016, users were indeed watching 1 billion hours every day on YouTube.5
YouTubers who were particularly intent on gaining attention noticed that when they posted an outrageous video full of lies, the algorithm rewarded them by recommending the video to numerous users and increasing the YouTubers’ popularity and income. In contrast, when they dialed down the outrage and stuck to the truth, the algorithm tended to ignore them. Within a few months of such reinforcement learning, the algorithm turned many YouTubers into trolls.6
The social and political consequences were far-reaching. For example, as the journalist Max Fisher documented in his 2022 book, The Chaos Machine, YouTube algorithms became an important engine for the rise of the Brazilian far right and for turning Jair Bolsonaro from a fringe figure into Brazil’s president.7 While there were other factors contributing to that political upheaval, it is notable that many of Bolsonaro’s chief supporters and aides had originally been YouTubers who rose to fame and power by algorithmic grace.
A typical example is Carlos Jordy, who in 2017 was a city councilor in the small town of Niterói. The ambitious Jordy gained national attention by creating inflammatory YouTube videos that garnered millions of views. His videos warned Brazilians, for example, against conspiracies by schoolteachers to brainwash children and persecute conservative pupils. In 2018, Jordy won a seat in the Brazilian Chamber of Deputies (the lower house of the Brazilian Congress) as one of Bolsonaro’s most dedicated supporters. In an interview with Fisher, Jordy frankly said, “If social media didn’t exist, I wouldn’t be here [and] Jair Bolsonaro wouldn’t be president.” The latter claim may well be a self-serving exaggeration, but there is no denying that social media played an important part in Bolsonaro’s rise.
Another YouTuber who won a seat in Brazil’s Chamber of Deputies in 2018 was Kim Kataguiri, one of the leaders of the Movimento Brasil Livre (MBL, or Free Brazil Movement). Kataguiri initially used Facebook as his main platform, but his posts were too extreme even for Facebook, which banned some of them for disinformation. So Kataguiri switched over to the more permissive YouTube. In an interview in the MBL headquarters in São Paulo, Kataguiri’s aides and other activists explained to Fisher, “We have something here that we call the dictatorship of the like.” They explained that YouTubers tend to become steadily more extreme, posting untruthful and reckless content “just because something is going to give you views, going to give engagement.… Once you open that door there’s no going back, because you always have to go further.… Flat Earthers, anti-vaxxers, conspiracy theories in politics. It’s the same phenomenon. You see it everywhere.”8
Of course, the YouTube algorithms were not themselves responsible for inventing lies and conspiracy theories or for creating extremist content. At least in 2017–18, those things were done by humans. The algorithms were responsible, however, for incentivizing humans to behave in such ways and for pushing the resulting content in order to maximize user engagement. Fisher documented numerous far-right activists who first became interested in extremist politics after watching videos that the YouTube algorithm auto-played for them. One far-right activist in Niterói told Fisher that he was never interested in politics of any kind, until one day the YouTube algorithm auto-played for him a video on politics by Kataguiri. “Before that,” he explained, “I didn’t have an ideological, political background.” He credited the algorithm with providing “my political education.” Talking about how other people joined the movement, he said, “It was like that with everyone.… Most of the people here came from YouTube and social media.”9
BLAME THE HUMANS
We have reached a turning point in history in which major historical processes are partly caused by the decisions of nonhuman intelligence. It is this that makes the fallibility of the computer network so dangerous. Computer errors become potentially catastrophic only when computers become historical agents. We have already made this argument in chapter 6, when we briefly examined Facebook’s role in instigating the anti-Rohingya ethnic-cleansing campaign. As noted in that context, however, many people—including some of the managers and engineers of Facebook, YouTube, and the other tech giants—object to this argument. Since it is one of the central points of the entire book, it is best to delve deeper into the matter and examine more carefully the objections to it.
The people who manage Facebook, YouTube, TikTok, and other platforms routinely try to excuse themselves by shifting the blame from their algorithms to “human nature.” They argue that it is human nature that produces all the hate and lies on the platforms. The tech giants then claim that due to their commitment to free speech values, they hesitate to censor the expression of genuine human emotions. For example, in 2019 the CEO of YouTube, Susan Wojcicki, explained, “The way that we think about it is: ‘Is this content violating one of our policies? Has it violated anything in terms of hate, harassment?’ If it has, we remove that content. We keep tightening and tightening the policies. We also get criticism, just to be clear, [about] where do you draw the lines of free speech and, if you draw it too tightly, are you removing voices of society that should be heard? We’re trying to strike a balance of enabling a broad set of voices, but also making sure that those voices play by a set of rules that are healthy conversations for society.”10
A Facebook spokesperson similarly said in October 2021, “Like every platform, we are constantly making difficult decisions between free expressions and harmful speech, security and other issues.… But drawing these societal lines is always better left to elected leaders.”11 In this way, the tech giants constantly shift the discussion to their supposed role as moderators of human-produced content and ignore the active role their algorithms play in cultivating certain human emotions and discouraging others. Are they really blind to it?
Surely not. Back in 2016, an internal Facebook report discovered that “64 percent of all extremist group joins are due to our recommendation tools.… Our recommendation systems grow the problem.”12 A secret internal Facebook memo from August 2019, leaked by the whistleblower Frances Haugen, stated, “We have evidence from a variety of sources that hate speech, divisive political speech, and misinformation on Facebook and [its] family of apps are affecting societies around the world. We also have compelling evidence that our core product mechanics, such as virality, recommendations, and optimizing for engagement, are a significant part of why these types of speech flourish on the platform.”13
Another leaked document from December 2019 noted, “Unlike communication with close friends and family, virality is something new we have introduced to many ecosystems … and it occurs because we intentionally encourage it for business reasons.” The document pointed out that “ranking content about higher stakes topics like health or politics based on engagement leads to perverse incentives and integrity issues.” Perhaps most damningly, it revealed, “Our ranking systems have specific separate predictions for not just what you would engage with, but what we think you may pass along so that others may engage with. Unfortunately, research has shown how outrage and misinformation are more likely to be viral.” This leaked document made one crucial recommendation: since Facebook cannot remove everything harmful from a platform used by many millions, it should at least “stop magnifying harmful content by giving it unnatural distribution.”14
Like the Soviet leaders in Moscow, the tech companies were not uncovering some truth about humans; they were imposing on us a perverse new order. Humans are very complex beings, and benign social orders seek ways to cultivate our virtues while curtailing our negative tendencies. But social media algorithms see us, simply, as an attention mine. The algorithms reduced the multifaceted range of human emotions—hate, love, outrage, joy, confusion—into a single catchall category: engagement. In Myanmar in 2016, in Brazil in 2018, and in numerous other countries, the algorithms scored videos, posts, and all other content solely according to how many minutes people engaged with the content and how many times they shared it with others. An hour of lies or hatred was ranked higher than ten minutes of truth or compassion—or an hour of sleep. The fact that lies and hate tend to be psychologically and socially destructive, whereas truth, compassion, and sleep are essential for human welfare, was completely lost on the algorithms. Based on this very narrow understanding of humanity, the algorithms helped to create a new social system that encouraged our basest instincts while discouraging us from realizing the full spectrum of the human potential.
As the harmful effects were becoming manifest, the tech giants were repeatedly warned about what was happening, but they failed to step in because of their faith in the naive view of information. As the platforms were overrun by falsehoods and outrage, executives hoped that if more people were enabled to express themselves more freely, truth would eventually prevail. This, however, did not happen. As we have seen again and again throughout history, in a completely free information fight, truth tends to lose. To tilt the balance in favor of truth, networks must develop and maintain strong self-correcting mechanisms that reward truth telling. These self-correcting mechanisms are costly, but if you want to get the truth, you must invest in them.
Silicon Valley thought it was exempt from this historical rule. Social media platforms have been singularly lacking in self-correcting mechanisms. In 2014, Facebook employed just a single Burmese-speaking content moderator to monitor activities in the whole of Myanmar.15 When observers in Myanmar began warning Facebook that it needed to invest more in moderating content, Facebook ignored them. For example, Pwint Htun, a Burmese American engineer and telecom executive who grew up in rural Myanmar, wrote to Facebook executives repeatedly about the danger. In an email from July 5, 2014—two years before the ethnic-cleansing campaign began—she issued a prophetic warning: “Tragically, FB in Burma is used like radio in Rwanda during the dark days of genocide.” Facebook took no action.
Even after the attacks on the Rohingya intensified and Facebook faced a storm of criticism, it still refused to hire people with expert local knowledge to curate content. Thus, when informed that hate-mongers in Myanmar were using the Burmese word kalar as a racist slur for the Rohingya, Facebook reacted in April 2017 by banning from the platform any posts that used the word. This revealed Facebook’s utter lack of knowledge about local conditions and the Burmese language. In Burmese, kalar is a racist slur only in specific contexts. In other contexts, it is an entirely innocent term. The Burmese word for chair is kalar htaing, and the word for chickpea is kalar pae. As Pwint Htun wrote to Facebook in June 2017, banning the term kalar from the platform is like banning the letters “hell” from “hello.”16 Facebook continued to ignore the need for local expertise. By April 2018, the number of Burmese speakers Facebook employed to moderate content for its eighteen million users in Myanmar was a grand total of five.17
Instead of investing in self-correcting mechanisms that would reward truth telling, the social media giants actually developed unprecedented error-enhancing mechanisms that rewarded lies and fictions. One such error-enhancing mechanism was the Instant Articles program that Facebook rolled out in Myanmar in 2016. Wishing to drive up engagement, Facebook paid news channels according to the amount of user engagement they generated, measured in clicks and views. No importance whatsoever was given to the truthfulness of the “news.” A 2021 study found that in 2015, before the program was launched, six of the ten top Facebook websites in Myanmar belonged to “legitimate media.” By 2017, under the impact of Instant Articles, “legitimate media” was down to just two websites out of the top ten. By 2018, all top ten websites were “fake news and clickbait websites.”
The study concluded that because of the launch of Instant Articles “clickbait actors cropped up in Myanmar overnight. With the right recipe for producing engaging and evocative content, they could generate thousands of US dollars a month in ad revenue, or ten times the average monthly salary—paid to them directly by Facebook.” Since Facebook was by far the most important source of online news in Myanmar, this had enormous impact on the overall media landscape of the country. “In a country where Facebook is synonymous with the Internet, the low-grade content overwhelmed other information sources.”18 Facebook and other social media platforms didn’t consciously set out to flood the world with fake news and outrage. But by telling their algorithms to maximize user engagement, this is exactly what they perpetrated.
Reflecting on the Myanmar tragedy, Pwint Htun wrote to me in July 2023, “I naively used to believe that social media could elevate human consciousness and spread the perspective of common humanity through interconnected pre-frontal cortexes in billions of human beings. What I realize is that the social media companies are not incentivized to interconnect pre-frontal cortexes. Social media companies are incentivized to create interconnected limbic systems—which is much more dangerous for humanity.”
THE ALIGNMENT PROBLEM
I don’t want to imply that the spread of fake news and conspiracy theories is the main problem with all past, present, and future computer networks. YouTube, Facebook, and other social media platforms claim that since 2018 they have been tweaking their algorithms to make them more socially responsible. Whether this is true or not is hard to say, especially because there is no universally accepted definition of “social responsibility.”19 But the specific problem of polluting the information sphere in pursuit of user engagement can certainly be solved. When the tech giants set their hearts on designing better algorithms, they can usually do it. Around 2005, the profusion of spam threatened to make the use of email impossible. Powerful algorithms were developed to address the problem. By 2015, Google claimed its Gmail algorithm had a 99.9 percent success in blocking genuine spam, while only 1 percent of legitimate emails were erroneously labeled as such.20
We also shouldn’t discount the huge social benefits that YouTube, Facebook, and other social media platforms have brought. To be clear, most YouTube videos and Facebook posts have not been fake news and genocidal incitements. Social media has been more than helpful in connecting people, giving voice to previously disenfranchised groups, and organizing valuable new movements and communities.21 It has also encouraged an unprecedented wave of human creativity. In the days when television was the dominant medium, viewers were often denigrated as couch potatoes: passive consumers of content that a few gifted artists produced. Facebook, YouTube, and other social media platforms inspired the couch potatoes to get up and start creating. Most of the content on social media—at least until the rise of powerful generative AI—has been produced by the users themselves, and their cats and dogs, rather than by a limited professional class.
I, too, routinely use YouTube and Facebook to connect with people, and I am grateful to social media for connecting me with my husband, whom I met on one of the first LGBTQ social media platforms back in 2002. Social media has done wonders for dispersed minorities like LGBTQ people. Few gay boys are born to a gay family in a gay neighborhood, and in the days before the internet simply finding one another posed a big challenge, unless you moved to one of the handful of tolerant metropolises that had a gay subculture. Growing up in a small homophobic town in Israel in the 1980s and early 1990s, I didn’t know a single openly gay man. Social media in the late 1990s and early 2000s provided an unprecedented and almost magical way for members of the dispersed LGBTQ community to find one another and connect.
And yet I have devoted so much attention to the social media “user engagement” debacle because it exemplifies a much bigger problem afflicting computers—the alignment problem. When computers are given a specific goal, such as to increase YouTube traffic to one billion hours a day, they use all their power and ingenuity to achieve this goal. Since they operate very differently than humans, they are likely to use methods their human overlords didn’t anticipate. This can result in dangerous unforeseen consequences, which are not aligned with the original human goals. Even if recommendation algorithms stop encouraging hate, other instances of the alignment problem might result in larger catastrophes than the anti-Rohingya campaign. The more powerful and independent computers become, the bigger the danger.
Of course, the alignment problem is neither new nor unique to algorithms. It bedeviled humanity for thousands of years before the invention of computers. It has been, for example, the foundational problem of modern military thinking, enshrined in Carl von Clausewitz’s theory of war. Clausewitz was a Prussian general who fought during the Napoleonic Wars. Following Napoleon’s final defeat in 1815, Clausewitz became the director of the Prussian War College. He also began formalizing a grand theory of war. After he died of cholera in 1831, his wife, Marie, edited his unfinished manuscript and published On War in several parts between 1832 and 1834.22
On War created a rational model for understanding war, and it is still the dominant military theory today. Its most important maxim is that “war is the continuation of policy with other means.”23 This implies that war is not an emotional outbreak, a heroic adventure, or a divine punishment. War is not even a military phenomenon. Rather, war is a political tool. According to Clausewitz, military actions are utterly irrational unless they are aligned with some overarching political goal.
Suppose Mexico contemplates whether to invade and conquer its small neighbor, Belize. And suppose a detailed military analysis concludes that if the Mexican army invades, it will achieve a quick and decisive military victory, crushing the small Belize army and conquering the capital, Belmopan, in three days. According to Clausewitz, that does not constitute a rational reason for Mexico to invade. The mere ability to secure military victory is meaningless. The key question the Mexican government should ask itself is, what political goals will the military success achieve?
History is full of decisive military victories that led to political disasters. For Clausewitz, the most obvious example was close to home: Napoleon’s career. Nobody disputes the military genius of Napoleon, who was a master of both tactics and strategy. But while his string of victories brought Napoleon temporary control of vast territories, they failed to secure lasting political achievements. His military conquests merely drove most European powers to unite against him, and his empire collapsed a decade after he crowned himself emperor.
Indeed, in the long term, Napoleon’s victories ensured the permanent decline of France. For centuries, France was Europe’s leading geopolitical power, largely because both Italy and Germany didn’t exist as unified political entities. Italy was a hodgepodge of dozens of warring city-states, feudal principalities, and church territories. Germany was an even more bizarre jigsaw puzzle divided into more than a thousand independent polities, loosely held together under the theoretical suzerainty of the Holy Roman Empire of the German Nation.24 In 1789, the prospect of a German or Italian invasion of France was simply unthinkable, because there was no such thing as a German or Italian army.
As Napoleon expanded his empire into central Europe and the Italian Peninsula, he abolished the Holy Roman Empire in 1806, amalgamated many of the smaller German and Italian principalities into larger territorial blocs, created a German Confederation of the Rhine and a Kingdom of Italy, and sought to unify these territories under his dynastic rule. His victorious armies also spread the ideals of modern nationalism and popular sovereignty into the German and Italian lands. Napoleon thought all this would make his empire stronger. In fact, by breaking up traditional structures and giving Germans and Italians a taste of national consolidation, Napoleon inadvertently lay the foundations for the ultimate unification of Germany (1866–71) and of Italy (1848–71). These twin processes of national unification were sealed by the German victory over France in the Franco-Prussian War of 1870–71. Faced with two newly unified and fervently nationalistic powers on its eastern border, France never regained its position of dominance.
A more recent example of military victory leading to political defeat was provided by the American invasion of Iraq in 2003. The Americans won every major military engagement, but failed to achieve any of their long-term political aims. Their military victory didn’t establish a friendly regime in Iraq, or a favorable geopolitical order in the Middle East. The real winner of the war was Iran. American military victory turned Iraq from Iran’s traditional foe into Iran’s vassal, thereby greatly weakening the American position in the Middle East while making Iran the regional hegemon.25
Both Napoleon and George W. Bush fell victim to the alignment problem. Their short-term military goals were misaligned with their countries’ long-term geopolitical goals. We can understand the whole of Clausewitz’s On War as a warning that “maximizing victory” is as shortsighted a goal as “maximizing user engagement.” According to the Clausewitzian model, only once the political goal is clear can armies decide on a military strategy that will hopefully achieve it. From the overall strategy, lower-ranking officers can then derive tactical goals. The model constructs a clear hierarchy between long-term policy, medium-term strategy, and short-term tactics. Tactics are considered rational only if they are aligned with some strategic goal, and strategy is considered rational only if it is aligned with some political goal. Even local tactical decisions of a lowly company commander must serve the war’s ultimate political goal.
Suppose that during the American occupation of Iraq an American company comes under intense fire from a nearby mosque. The company commander has several different tactical decisions to choose from. He might order the company to retreat. He might order the company to storm the mosque. He might order one of his supporting tanks to blow up the mosque. What should the company commander do?
From a purely military perspective, it might seem best for the commander to order his tank to blow up the mosque. This would capitalize on the tactical advantage that the Americans enjoyed in terms of firepower, avoid risking the lives of his own soldiers, and achieve a decisive tactical victory. However, from a political perspective, this might be the worst decision the commander could make. Footage of an American tank destroying a mosque would galvanize Iraqi public opinion against the Americans and create outrage throughout the wider Muslim world. Storming the mosque might also be a political mistake, because it too could create resentment among Iraqis, while the cost in American lives could weaken support for the war among American voters. Given the political war aims of the United States, retreating and conceding tactical defeat might well be the most rational decision.
For Clausewitz, then, rationality means alignment. Pursuing tactical or strategic victories that are misaligned with political goals is irrational. The problem is that the bureaucratic nature of armies makes them highly susceptible to such irrationality. As discussed in chapter 3, by dividing reality into separate drawers, bureaucracy encourages the pursuit of narrow goals even when this harms the greater good. Bureaucrats tasked with accomplishing a narrow mission may be ignorant of the wider impact of their actions, and it has always been tricky to ensure that their actions remain aligned with the greater good of society. When armies operate along bureaucratic lines—as all modern armies do—it creates a huge gap between a captain commanding a company in the field and the president formulating long-term policy in a distant office. The captain is prone to make decisions that seem reasonable on the ground but that actually undermine the war’s ultimate goal.
We see, then, that the alignment problem has long predated the computer revolution and that the difficulties encountered by builders of present-day information empires are not unlike those that bedeviled previous would-be conquerors. Nevertheless, computers do change the nature of the alignment problem in important ways. No matter how difficult it used to be to ensure that human bureaucrats and soldiers remain aligned with society’s long-term goals, it is going to be even harder to ensure the alignment of algorithmic bureaucrats and autonomous weapon systems.
THE PAPER-CLIP NAPOLEON
One reason why the alignment problem is particularly dangerous in the context of the computer network is that this network is likely to become far more powerful than any previous human bureaucracy. A misalignment in the goals of superintelligent computers might result in a catastrophe of unprecedented magnitude. In his 2014 book, Superintelligence, the philosopher Nick Bostrom illustrated the danger using a thought experiment, which is reminiscent of Goethe’s “Sorcerer’s Apprentice.” Bostrom asks us to imagine that a paper-clip factory buys a superintelligent computer and that the factory’s human manager gives the computer a seemingly simple task: produce as many paper clips as possible. In pursuit of this goal, the paper-clip computer conquers the whole of planet Earth, kills all the humans, sends expeditions to take over additional planets, and uses the enormous resources it acquires to fill the entire galaxy with paper-clip factories.
The point of the thought experiment is that the computer did exactly what it was told (just like the enchanted broomstick in Goethe’s poem). Realizing that it needed electricity, steel, land, and other resources to build more factories and produce more paper clips, and realizing that humans are unlikely to give up these resources, the superintelligent computer eliminated all humans in its single-minded pursuit of its given goal.26 Bostrom’s point was that the problem with computers isn’t that they are particularly evil but that they are particularly powerful. And the more powerful the computer, the more careful we need to be about defining its goal in a way that precisely aligns with our ultimate goals. If we define a misaligned goal to a pocket calculator, the consequences are trivial. But if we define a misaligned goal to a superintelligent machine, the consequences could be dystopian.
The paper-clip thought experiment may sound outlandish and utterly disconnected from reality. But if Silicon Valley managers had paid attention when Bostrom published it in 2014, perhaps they would have been more careful before instructing their algorithms to “maximize user engagement.” The Facebook and YouTube algorithms behaved exactly like Bostrom’s imaginary algorithm. When told to maximize paper-clip production, the algorithm sought to convert the entire physical universe into paper clips, even if it meant destroying human civilization. When told to maximize user engagement, the Facebook and YouTube algorithms sought to convert the entire social universe into user engagement, even if it meant doing harm to the social fabric of Myanmar, Brazil, and many other countries.
Bostrom’s thought experiment highlights a second reason why the alignment problem is more urgent in the case of computers. Because they are inorganic entities, they are likely to adopt strategies that would never occur to any human and that we are therefore ill-equipped to foresee and forestall. Here’s one example: In 2016, Dario Amodei was working on a project called Universe, trying to develop a general-purpose AI that could play hundreds of different computer games. The AI competed well in various car races, so Amodei next tried it on a boat race. Inexplicably, the AI steered its boat right into a harbor and then sailed in endless circles in and out of the harbor.
It took Amodei considerable time to understand what went wrong. The problem occurred because initially Amodei wasn’t sure how to tell the AI that its goal was to “win the race.” “Winning” is an unclear concept to an algorithm. Translating “win the race” into computer language would have required Amodei to formalize complex concepts like track position and placement among the other boats in the race. So instead, Amodei took the easy way and told the boat to maximize its score. He assumed that the score was a good proxy for winning the race. After all, it worked with the car races.
But the boat race had a peculiar feature, absent from the car races, that allowed the ingenious AI to find a loophole in the game’s rules. The game rewarded players with a lot of points for getting ahead of other boats—as in the car races—but it also rewarded them with a few points whenever they replenished their power by docking into a harbor. The AI discovered that if instead of trying to outsail the other boats, it simply went in circles in and out of the harbor, it could accumulate more points far faster. Apparently, none of the game’s human developers—nor Dario Amodei—noticed this loophole. The AI was doing exactly what the game was rewarding it to do—even though it is not what the humans were hoping for. That’s the essence of the alignment problem: rewarding A while hoping for B.27 If we want computers to maximize social benefits, it’s a bad idea to reward them for maximizing user engagement.
A third reason to worry about the alignment problem of computers is that because they are so different from us, when we make the mistake of giving them a misaligned goal, they are less likely to notice it or request clarification. If the boat-race AI had been a human gamer, it would have realized that the loophole it found in the game’s rules probably doesn’t really count as “winning.” If the paper-clip AI had been a human bureaucrat, it would have realized that destroying humanity in order to produce paper clips is probably not what was intended. But since computers aren’t humans, we cannot rely on them to notice and flag possible misalignments. In the 2010s the YouTube and Facebook management teams were bombarded with warnings from their human employees—as well as from outside observers—about the harm being done by the algorithms, but the algorithms themselves never raised the alarm.28
As we give algorithms greater and greater power over health care, education, law enforcement, and numerous other fields, the alignment problem will loom ever larger. If we don’t find ways to solve it, the consequences will be far worse than algorithms racking up points by sailing boats in circles.
THE CORSICAN CONNECTION
How to solve the alignment problem? In theory, when humans create a computer network, they must define for it an ultimate goal, which the computers are never allowed to change or ignore. Then, even if computers become so powerful that we lose control over them, we can rest assured that their immense power will benefit rather than harm us. Unless, of course, it turned out that we defined a harmful or vague goal. And there’s the rub. In the case of human networks, we rely on self-correcting mechanisms to periodically review and revise our goals, so setting the wrong goal is not the end of the world. But since the computer network might escape our control, if we set it the wrong goal, we might discover our mistake when we are no longer able to correct it. Some might hope that through a careful process of deliberation, we might be able to define in advance the right goals for the computer network. This, however, is a very dangerous delusion.
To understand why it is impossible to agree in advance on the ultimate goals of the computer network, let’s revisit Clausewitz’s war theory. There is one fatal flaw in the way he equates rationality with alignment. While Clausewitzian theory demands that all actions be aligned with the ultimate goal, it offers no rational way to define such a goal. Consider Napoleon’s life and military career. What should have been his ultimate goal? Given the prevailing cultural atmosphere of France circa 1800, we can think of several alternatives for “ultimate goal” that might have occurred to Napoleon:
POTENTIAL GOAL NUMBER 1: Making France the dominant power in Europe, secure against any future attack by Britain, the Habsburg Empire, Russia, a unified Germany, or a unified Italy.
POTENTIAL GOAL NUMBER 2: Creating a new multiethnic empire ruled by Napoleon’s family, which would include not only France but also many additional territories both in Europe and overseas.
POTENTIAL GOAL NUMBER 3: Achieving everlasting glory for himself personally, so that even centuries after his death billions of people will know the name Napoleon and admire his genius.
POTENTIAL GOAL NUMBER 4: Securing the redemption of his everlasting soul, and gaining entry to heaven after his death.
POTENTIAL GOAL NUMBER 5: Spreading the universal ideals of the French Revolution, and helping to protect freedom, equality, and human rights throughout Europe and the world.
Many self-styled rationalists tend to argue that Napoleon should have made it his life’s mission to achieve the first goal—securing French domination in Europe. But why? Remember that for Clausewitz rationality means alignment. A tactical maneuver is rational if, and only if, it is aligned with some higher strategic goal, which should in turn be aligned with an even higher political goal. But where does this chain of goals ultimately start? How can we determine the ultimate goal that justifies all the strategic subgoals and tactical steps derived from it? Such an ultimate goal by definition cannot be aligned with anything higher than itself, because there is nothing higher. What then makes it rational to place France at the top of the goal hierarchy, rather than Napoleon’s family, Napoleon’s fame, Napoleon’s soul, or universal human rights? Clausewitz provides no answer.
One might argue that goal number 4—securing the redemption of his everlasting soul—cannot be a serious candidate for an ultimate rational goal, because it is based on a belief in mythology. But the same argument can be leveled at all the other goals. Everlasting souls are an intersubjective invention that exist only in people’s minds, and exactly the same is true of nations and human rights. Why should Napoleon care about the mythical France any more than about his mythical soul?
Indeed, for most of his youth, Napoleon didn’t even consider himself French. He was born Napoleone di Buonaparte on Corsica, to a family of Italian emigrants. For five hundred years Corsica was ruled by the Italian city-state of Genoa, where many of Napoleone’s ancestors lived. It was only in 1768—a year before Napoleone’s birth—that Genoa ceded the island to France. Corsican nationalists resisted being handed over to France and rose in rebellion. Only after their defeat in 1770 did Corsica formally become a French province. Many Corsicans continued to resent the French takeover, but the di Buonaparte family swore allegiance to the French king and sent Napoleone to military school in mainland France.29
At school, Napoleone had to endure a good deal of hazing from his classmates for his Corsican nationalism and his poor command of the French language.30 His mother tongues were Corsican and Italian, and although he gradually became fluent in French, he retained throughout his life a Corsican accent and an inability to spell French correctly.31 Napoleone eventually enlisted in the French army, but when the Revolution broke out in 1789, he went back to Corsica, hoping the revolution would provide an opportunity for his beloved island to achieve greater autonomy. Only after he fell out with the leader of the Corsican independence movement—Pasquale Paoli—did Napoleone abandon the Corsican cause in May 1793. He returned to the mainland, where he decided to build his future.32 It was at this stage that Napoleone di Buonaparte turned into Napoléon Bonaparte (he continued to use the Italian version of his name until 1796).33
Why then was it rational for Napoleon to devote his military career to making France the dominant power in Europe? Was it perhaps more rational for him to stay in Corsica, patch up his personal disagreements with Paoli, and devote himself to liberating his native island from its French conquerors? And maybe Napoleon should in fact have made it his life’s mission to unite Italy—the land of his ancestors?
Clausewitz offers no method to answer these questions rationally. If our only rule of thumb is “every action must be aligned with some higher goal,” by definition there is no rational way to define that ultimate goal. How then can we provide a computer network with an ultimate goal it must never ignore or subvert? Tech executives and engineers who rush to develop AI are making a huge mistake if they think there is a rational way to tell that AI what its ultimate goal should be. They should learn from the bitter experiences of generations of philosophers who tried to define ultimate goals and failed.
THE KANTIAN NAZI
For millennia, philosophers have been looking for a definition of an ultimate goal that will not depend on an alignment to some higher goal. They have repeatedly been drawn to two potential solutions, known in philosophical jargon as deontology and utilitarianism. Deontologists (from the Greek word deon, meaning “duty”) believe that there are some universal moral duties, or moral rules, that apply to everyone. These rules do not rely on alignment to a higher goal, but rather on their intrinsic goodness. If such rules indeed exist, and if we can find a way to program them into computers, then we can make sure the computer network will be a force for good.
But what exactly does “intrinsic goodness” mean? The most famous attempt to define an intrinsically good rule was made by Immanuel Kant, a contemporary of Clausewitz and Napoleon. Kant argued that an intrinsically good rule is any rule that I would like to make universal. According to this view, a person about to murder someone should stop and go through the following thought process: “I am now going to murder a human. Would I like to establish a universal rule saying that it is okay to murder humans? If such a universal rule is established, then someone might murder me. So there shouldn’t be a universal rule allowing murder. It follows that I too shouldn’t murder.” In simpler language, Kant reformulated the old Golden Rule: “Do unto others what you want them to do to you” (Matthew 7:12).
This sounds like a simple and obvious idea: each of us should behave in a way we want everyone to behave. But ideas that sound good in the ethereal realm of philosophy often have trouble immigrating to the harsh land of history. The key question historians would ask Kant is, when you talk about universal rules, how exactly do you define “universal”? Under actual historical circumstances, when a person is about to commit murder, the first step they often take is to exclude the victim from the universal community of humanity.34 This, for example, is what anti-Rohingya extremists like Wirathu did. As a Buddhist monk, Wirathu was certainly against murdering humans. But he didn’t think this universal rule applied to killing Rohingya, who were seen as subhuman. In posts and interviews, he repeatedly compared them to beasts, snakes, mad dogs, wolves, jackals, and other dangerous animals.35 On October 30, 2017, at the height of the anti-Rohingya violence, another, more senior Buddhist monk preached a sermon to military officers in which he justified violence against the Rohingya by telling the officers that non-Buddhists were “not fully human.”36
As a thought experiment, imagine a meeting between Immanuel Kant and Adolf Eichmann—who, by the way, considered himself a Kantian.37 As Eichmann signs an order sending another trainload of Jews to Auschwitz, Kant tells him, “You are about to murder thousands of humans. Would you like to establish a universal rule saying it is okay to murder humans? If you do that, you and your family might also be murdered.” Eichmann replies, “No, I am not about to murder thousands of humans. I am about to murder thousands of Jews. If you ask me whether I would like to establish a universal rule saying it is okay to murder Jews, then I am all for it. As for myself and my family, there is no risk that this universal rule would lead to us being murdered. We aren’t Jews.”
One potential Kantian reply to Eichmann is that when we define entities, we must always use the most universal definition applicable. If an entity can be defined as either “a Jew” or “a human,” we should use the more universal term “human.” However, the whole point of Nazi ideology was to deny the humanity of Jews. In addition, note that Jews are not just humans. They are also animals, and they are also organisms. Since animals and organisms are obviously more universal categories than “human,” if you follow the Kantian argument to its logical conclusion, it might push us to adopt an extreme vegan position. Since we are organisms, does it mean we should object to the killing of any organism, down even to tomatoes or amoebas?
In history, many if not most conflicts concern the definition of identities. Everybody accepts that murder is wrong, but thinks that only killing members of the in-group qualifies as “murder,” whereas killing someone from an out-group is not. But the in-groups and out-groups are intersubjective entities, whose definition usually depends on some mythology. Deontologists who pursue universal rational rules often end up the captives of local myths.
This problem with deontology is especially critical if we try to dictate universal deontologist rules not to humans but to computers. Computers aren’t even organic. So if they follow a rule of “Do unto others what you want them to do to you,” why should they be concerned about killing organisms like humans? A Kantian computer that doesn’t want to be killed has no reason to object to a universal rule saying “it is okay to kill organisms”; such a rule does not endanger the nonorganic computer.
Alternatively, being inorganic entities, computers may have no qualms about dying. As far as we can tell, death is an organic phenomenon and may be inapplicable to inorganic entities. When ancient Assyrians talked about “killing” documents, that was just a metaphor. If computers are more like documents than like organisms, and don’t care about “being killed,” would we like a Kantian computer to conclude that killing humans is therefore fine?
Is there a way to define whom computers should care about, without getting bogged down by some intersubjective myth? The most obvious suggestion is to tell computers that they must care about any entity capable of suffering. While suffering is often caused by belief in local intersubjective myths, suffering itself is nonetheless a universal reality. Therefore, using the capacity to suffer in order to define the critical in-group grounds morality in an objective and universal reality. A self-driving car should avoid killing all humans—whether Buddhist or Muslim, French or Italian—and should also avoid killing dogs and cats, and any sentient robots that might one day exist. We may even refine this rule, instructing the car to care about different beings in direct proportion to their capacity to suffer. If the car has to choose between killing a human and killing a cat, it should drive over the cat, because presumably the cat has a lesser capacity to suffer. But if we go in that direction, we inadvertently desert the deontologist camp and find ourselves in the camp of their rivals—the utilitarians.
THE CALCULUS OF SUFFERING
Whereas deontologists struggle to find universal rules that are intrinsically good, utilitarians judge actions by their impact on suffering and happiness. The English philosopher Jeremy Bentham—another contemporary of Napoleon, Clausewitz, and Kant—said that the only rational ultimate goal is to minimize suffering in the world and maximize happiness. If our main fear about computer networks is that their misaligned goals might inflict terrible suffering on humans and perhaps on other sentient beings, then the utilitarian solution seems both obvious and attractive. When creating the computer network, we just need to instruct it to minimize suffering and maximize happiness. If Facebook had told its algorithms “maximize happiness” instead of “maximize user engagement,” all would allegedly have been well. It is worth noting that this utilitarian approach is indeed popular in Silicon Valley, championed in particular by the effective altruism movement.38
Unfortunately, as with the deontologist solution, what sounds simple in the theoretical realm of philosophy becomes fiendishly complex in the practical land of history. The problem for utilitarians is that we don’t possess a calculus of suffering. We don’t know how many “suffering points” or “happiness points” to assign to particular events, so in complex historical situations it is extremely difficult to calculate whether a given action increases or decreases the overall amount of suffering in the world.
Utilitarianism is at its best in situations when the scales of suffering are very clearly tipped in one direction. When confronted by Eichmann, utilitarians don’t need to get into any complicated debates about identity. They just need to point out that the Holocaust caused immense suffering to the Jews, without providing equivalent benefits to anyone else, including the Germans. There was no compelling military or economic need for the Germans to murder millions of Jews. The utilitarian case against the Holocaust is overwhelming.
Utilitarians also have a field day when dealing with “victimless crimes” like homosexuality, in which all the suffering is on one side only. For centuries, the persecution of gay people caused them immense suffering, but it was nevertheless justified by various prejudices that were erroneously presented as deontological universal rules. Kant, for example, condemned homosexuality on the grounds that it is “contrary to natural instinct and to animal nature” and that it therefore degrades a person “below the level of the animals.” Kant further fulminated that because such acts are contrary to nature, they “make man unworthy of his humanity. He no longer deserves to be a person.”39 Kant, in fact, repackaged a Christian prejudice as a supposedly universal deontological rule, without providing empirical proof that homosexuality is indeed contrary to nature. In light of the above discussion of dehumanization as a prelude to massacre, it is also noteworthy how Kant dehumanized gay people. The view that homosexuality is contrary to nature and deprives people of their humanity paved the way for Nazis like Eichmann to justify murdering homosexuals in concentration camps. Since homosexuals were allegedly below the level of animals, the Kantian rule against murdering humans didn’t apply to them.40
Utilitarians find it easy to dismiss Kant’s sexual theories, and Bentham indeed was one of the first modern European thinkers who favored the decriminalization of homosexuality.41 Utilitarians argue that criminalizing homosexuality in the name of some dubious universal rule causes tremendous suffering to millions of people, without offering any substantial benefits to others. When two men form a loving relationship, this makes them happy, without making anyone else miserable. Why then forbid it? This type of utilitarian logic also led to many other modern reforms, such as the ban on torture and the introduction of some legal protections for animals.
But in historical situations when the scales of suffering are more evenly matched, utilitarianism falters. In the early days of the COVID-19 pandemic, governments all over the world adopted strict policies of social isolation and lockdown. This probably saved the lives of several million people.42 It also made hundreds of millions miserable for months. Moreover, it might have indirectly caused numerous deaths, for example by increasing the incidence of murderous domestic violence,43 or by making it more difficult for people to diagnose and treat other dangerous illnesses, like cancer.44 Can anyone calculate the total impact of the lockdown policies and determine whether they increased or decreased the suffering in the world?
This may sound like a perfect task for a relentless computer network. But how would the computer network decide how many “misery points” to allocate to being locked down with three kids in a two-bedroom apartment for a month? Is that 60 misery points or 600? And how many points to allot to a cancer patient who died because she missed her chemotherapy treatments? Is that 60,000 misery points or 600,000? And what if she would have died of cancer anyway, and the chemo would merely have extended her life by five agonizing months? Should the computers value five months of living with extreme pain as a net gain or a net loss for the sum total of suffering in the world?
And how would the computer network evaluate the suffering caused by less tangible things, such as the knowledge of our own mortality? If a religious myth promises us that we will never really die, because after death our eternal soul will go to heaven, does that make us truly happy or just delusional? Is death the deep cause of our misery, or does our misery stem from our attempts to deny death? If someone loses their religious faith and comes to terms with their mortality, should the computer network see this as a net loss or a net gain?
What about even more complicated historical events like the American invasion of Iraq? The Americans were well aware that their invasion would cause tremendous suffering for millions of people. But in the long run, they argued, the benefits of bringing freedom and democracy to Iraq would outweigh the costs. Can the computer network calculate whether this argument was sound? Even if it was theoretically plausible, in practice the Americans failed to establish a stable democracy in Iraq. Does that mean that their attempt was wrong in the first place?
Just as deontologists trying to answer the question of identity are pushed to adopt utilitarian ideas, so utilitarians stymied by the lack of a suffering calculus often end up adopting a deontologist position. They uphold general rules like “avoid wars of aggression” or “protect human rights,” even though they cannot show that following these rules always reduces the sum total of suffering in the world. History provides them only with a vague impression that following these rules tends to reduce suffering. And when some of these general rules clash—for example, when contemplating launching a war of aggression in order to protect human rights—utilitarianism doesn’t offer much practical help. Not even the most powerful computer network can perform the necessary calculations.
Accordingly, while utilitarianism promises a rational—and even mathematical—way to align every action with “the ultimate good,” in practice it may well produce just another mythology. Communist true believers confronted by the horrors of Stalinism often replied that the happiness that future generations would experience under “real socialism” would redeem any short-term misery in the gulags. Libertarians, when asked about the immediate social harms of unrestricted free speech or the total abolition of taxes, express a similar faith that future benefits will outweigh any short-term damage. The danger of utilitarianism is that if you have a strong enough belief in a future utopia, it can become an open license to inflict terrible suffering in the present. Indeed, this is a trick traditional religions discovered thousands of years ago. The crimes of this world could too easily be excused by the promises of future salvation.
COMPUTER MYTHOLOGY
How then did bureaucratic systems throughout history set their ultimate goals? They relied on mythology to do it for them. No matter how rational were the officials, engineers, tax collectors, and accountants, they were ultimately in the service of this or that mythmaker. To paraphrase John Maynard Keynes, practical people, who believe themselves to be quite exempt from any religious influence, are usually the slaves of some mythmaker. Even nuclear physicists have found themselves obeying the commands of Shiite ayatollahs and communist apparatchiks.
The alignment problem turns out to be, at heart, a problem of mythology. Nazi administrators could have been committed deontologists or utilitarians, but they would still have murdered millions so long as they understood the world in terms of a racist mythology. If you start with the mythological belief that Jews are demonic monsters bent on destroying humanity, then both deontologists and utilitarians can find many logical arguments why the Jews should be killed.
An analogous problem might well afflict computers. Of course, they cannot “believe” in any mythology, because they are nonconscious entities that don’t believe in anything. As long as they lack subjectivity, how can they hold intersubjective beliefs? However, one of the most important things to realize about computers is that when a lot of computers communicate with one another, they can create inter-computer realities, analogous to the intersubjective realities produced by networks of humans. These inter-computer realities may eventually become as powerful—and as dangerous—as human-made intersubjective myths.
This is a very complicated argument, but it is another of the central arguments of the book, so let’s go over it carefully. First, let’s try to understand what inter-computer realities are. As an initial example, consider a one-player computer game. In such a game, you can wander inside a virtual landscape that exists as information within one computer. If you see a rock, that rock is not made of atoms. It is made of bits inside a single computer. When several computers are linked to one another, they can create inter-computer realities. Several players using different computers can wander together inside a common virtual landscape. If they see a rock, that rock is made of bits in several computers.45
Just as intersubjective realities like money and gods can influence the physical reality outside people’s minds, so inter-computer realities can influence reality outside the computers. In 2016 the game Pokémon Go took the world by storm and was downloaded hundreds of millions of times by the end of the year.46 Pokémon Go is an augmented reality mobile game. Players can use their smartphones to locate, fight, and capture virtual creatures called Pokémon, which seem to exist in the physical world. I once went with my nephew Matan on such a Pokémon hunt. Walking around his neighborhood, I saw only houses, trees, rocks, cars, people, cats, dogs, and pigeons. I didn’t see any Pokémon, because I didn’t have a smartphone. But Matan, looking around through his smartphone lens, could “see” Pokémon standing on a rock or hiding behind a tree.
Though I couldn’t see the creatures, they were obviously not confined to Matan’s smartphone, because other people could “see” them too. For example, we encountered two other kids who were hunting the same Pokémon. If Matan managed to capture a Pokémon, the other kids could immediately observe what happened. The Pokémon were inter-computer entities. They existed as bits in a computer network rather than as atoms in the physical world, but they could nevertheless interact with the physical world and influence it, as it were, in various ways.
Now let’s examine a more consequential example of inter-computer realities. Consider the rank that a website gets in a Google search. When we google for news, flight tickets, or restaurant recommendations, one website appears at the top of the first Google page, whereas another is relegated to the middle of the fiftieth page. What exactly is this Google rank, and how is it determined? The Google algorithm determines the website’s Google rank by assigning points to various parameters, such as how many people visit the website and how many other websites link to it. The rank itself is an inter-computer reality, existing in a network connecting billions of computers—the internet. Like Pokémon, this inter-computer reality spills over into the physical world. For a news outlet, a travel agency, or a restaurant it matters a great deal whether its website appears at the top of the first Google page or in the middle of the fiftieth page.47
Since the Google rank is so important, people use all kinds of tricks to manipulate the Google algorithm to give their website a higher rank. For example, they may use bots to generate more traffic to the website.48 This is a widespread phenomenon in social media too, where coordinated bot armies are constantly manipulating the algorithms of YouTube, Facebook, or Twitter. If a tweet goes viral, is it because humans are really interested in it, or because thousands of bots managed to fool the Twitter algorithm?49
Inter-computer realities like Pokémon and Google ranks are analogous to intersubjective realities like the sanctity that humans ascribe to temples and cities. I lived much of my life in one of the holiest places on earth—the city of Jerusalem. Objectively, it is an ordinary place. As you walk around Jerusalem, you see houses, trees, rocks, cars, people, cats, dogs, and pigeons, as in any other city. But many people nevertheless imagine it to be an extraordinary place, full of gods, angels, and holy stones. They believe in this so strongly that they sometimes fight over possession of the city or of specific holy buildings and sacred stones, most notably the Holy Rock, located under the Dome of the Rock on Temple Mount. The Palestinian philosopher Sari Nusseibeh observed that “Jews and Muslims, acting on religious beliefs and backed up by nuclear capabilities, are poised to engage in history’s worst-ever massacre of human beings, over a rock.”50 They don’t fight over the atoms that compose the rock; they fight over its “sanctity,” a bit like kids fighting over a Pokémon. The sanctity of the Holy Rock, and of Jerusalem generally, is an intersubjective phenomenon that exists in the communication network connecting many human minds. For thousands of years wars were fought over intersubjective entities like holy rocks. In the twenty-first century, we might see wars fought over inter-computer entities.
If this sounds like science fiction, consider potential developments in the financial system. As computers become more intelligent and more creative, they are likely to create new inter-computer financial devices. Gold coins and dollars are intersubjective entities. Cryptocurrencies like bitcoin are midway between intersubective and inter-computer. The idea behind them was invented by humans, and their value still depends on human beliefs, but they cannot exist outside the computer network. In addition, they are increasingly traded by algorithms so that their value depends on the calculations of algorithms and not just on human beliefs.
What if in ten or fifty years computers create a new kind of cryptocurrency or some other financial device that becomes a vital tool for trading and investing—and a potential source for political crises and conflicts? Recall that the 2007–8 global financial crisis was instigated by collateralized debt obligations. These financial devices were invented by a handful of mathematicians and investment whiz kids and were almost unintelligible for most humans, including regulators. This led to an oversight failure and to a global catastrophe.51 Computers may well create financial devices that will be orders of magnitude more complex than CDOs and that will be intelligible only to other computers. The result could be a financial and political crisis even worse than that of 2007–8.
Throughout history, economics and politics required that we understand the intersubjective realities invented by people—like religions, nations, and currencies. Someone who wanted to understand American politics had to take into account intersubjective realities like Christianity and CDOs. Increasingly, however, understanding American politics will necessitate understanding inter-computer realities ranging from AI-generated cults and currencies to AI-run political parties and even fully incorporated AIs. The U.S. legal system already recognizes corporations as legal persons that possess rights such as freedom of speech. In Citizens United v. Federal Election Commission (2010) the U.S. Supreme Court decided that this even protected the right of corporations to make political donations.52 What would stop AIs from being incorporated and recognized as legal persons with freedom of speech, then lobbying and making political donations to protect and expand AI rights?
For tens of thousands of years, humans dominated planet Earth because we were the only ones capable of creating and sustaining intersubjective entities like corporations, currencies, gods, and nations, and using such entities to organize large-scale cooperation. Now computers may acquire comparable abilities.
This isn’t necessarily bad news. If computers lacked connectivity and creativity, they would not be very useful. We increasingly rely on computers to manage our money, drive our vehicles, reduce pollution, and discover new medicines, precisely because computers can directly communicate with one another, spot patterns where we can’t, and construct models that might never occur to us. The problem we face is not how to deprive computers of all creative agency, but rather how to steer their creativity in the right direction. It is the same problem we have always had with human creativity. The intersubjective entities invented by humans were the basis for all the achievements of human civilization, but they occasionally led to crusades, jihads, and witch hunts. The inter-computer entities will probably be the basis for future civilizations, but the fact that computers collect empirical data and use mathematics to analyze it doesn’t mean they cannot launch their own witch hunts.
THE NEW WITCHES
In early modern Europe, an elaborate information network analyzed a huge amount of data about crimes, illnesses, and disasters and reached the conclusion that it was all the fault of witches. The more data the witch-hunters gathered, the more convinced they became that the world was full of demons and sorcery and that there was a global satanic conspiracy to destroy humanity. The information network then went on to identify the witches and imprison or kill them. We now know that witches were a bogus intersubjective category, invented by the information network itself and then imposed on people who had never actually met Satan and couldn’t summon hailstorms.
In the Soviet Union, an even more elaborate information network invented the kulaks—another mythic category that was imposed on millions. The mountains of information collected by Soviet bureaucracy about the kulaks weren’t an objective truth, but they created a new intersubjective truth. Knowing that someone was a kulak became one of the most important things to know about a Soviet person, even though the category was fictitious.
On an even larger scale, from the sixteenth to the twentieth century, numerous colonial bureaucracies in the Americas, from Brazil through Mexico and the Caribbean to the United States, created a racist mythology and came up with all kinds of intersubjective racial categories. Humans were divided into Europeans, Africans, and Native Americans, and since interracial sexual relations were common, additional categories were invented. In many Spanish colonies the laws differentiated between mestizos, people with mixed Spanish and Native American ancestry; mulatos, people with mixed Spanish and African ancestry; zambos, people with mixed African and Native American ancestry; and pardos, people with mixed Spanish, African, and Native American ancestry. All these seemingly empirical categories determined whether people could be enslaved, enjoy political rights, bear arms, hold public offices, be admitted to school, practice certain professions, live in particular neighborhoods, and be allowed to have sex and get married to each other. Allegedly, by placing a person in a particular racial drawer, one could define their personality, intellectual abilities, and ethical inclinations.53
By the nineteenth century racism pretended to be an exact science: it claimed to differentiate between people on the basis of objective biological facts, and to rely on scientific tools such as measuring skulls and recording crime statistics. But the cloud of numbers and categories was just a smoke screen for absurd intersubjective myths. The fact that somebody had a Native American grandmother or an African father didn’t, of course, reveal anything about their intelligence, kindness, or honesty. These bogus categories didn’t discover or describe any truth about humans; they imposed an oppressive, mythological order on them.
As computers replace humans in more and more bureaucracies, from tax collection and health care to security and justice, they too may create a mythology and impose it on us with unprecedented efficiency. In a world ruled by paper documents, bureaucrats had difficulty policing racial borderlines or tracking everyone’s exact ancestry. People could get false documents. A zambo could move to another town and pretend to be a pardo. A Black person could sometimes pass as white. Similarly in the Soviet Union, kulak children occasionally managed to falsify their papers to get a good job or a place in college. In Nazi Europe, Jews could sometimes adopt an Aryan identity. But it would be much harder to game the system in a world ruled by computers that can read irises and DNA rather than paper documents. Computers could be frighteningly efficient in imposing false labels on people and making sure that the labels stick.
For example, social credit systems could create a new underclass of “low-credit people.” Such a system may claim to merely “discover” the truth through an empirical and mathematical process of aggregating points to form an overall score. But how exactly would it define pro-social and antisocial behaviors? What happens if such a system detracts points for criticizing government policies, for reading foreign literature, for practicing a minority religion, for having no religion, or for socializing with other low-credit people? As a thought experiment, consider what might happen when the new technology of the social credit system meets traditional religions.
Religions like Judaism, Christianity, and Islam have always imagined that somewhere above the clouds there is an all-seeing eye that gives or deducts points for everything we do and that our eternal fate depends on the score we accumulate. Of course, nobody could be certain of their score. You could know for sure only after you died. In practical terms, this meant that sinfulness and sainthood were intersubjective phenomena whose very definition depended on public opinion. What might happen if the Iranian regime, for example, decides to use its computer-based surveillance system not only to enforce its strict hijab laws, but to turn sinfulness and sainthood into precise inter-computer phenomena? You didn’t wear a hijab on the street—that’s -10 points. You ate on Ramadan before sunset—another 20 points deducted. You went to Friday prayer at the mosque, +5 points. You made the pilgrimage to Mecca, +500 points. The system might then aggregate all the points and divide people into “sinners” (under 0 points), “believers” (0 to 1,000 points), and “saints” (above 1,000 points). Whether someone is a sinner or a saint will depend on algorithmic calculations, not human belief. Would such a system discover the truth about people or impose order on people?
Analogous problems may afflict all social credit systems and total surveillance regimes. Whenever they claim to use all-encompassing databases and ultraprecise mathematics to discover sinners, terrorists, criminals, antisocial or untrustworthy people, they might actually be imposing baseless religious and ideological prejudices with unprecedented efficiency.
COMPUTER BIAS
Some people may hope to overcome the problem of religious and ideological biases by giving even more power to the computers. The argument for doing so might go something like this: racism, misogyny, homophobia, antisemitism, and all other biases originate not in computers but in the psychological conditions and mythological beliefs of human beings. Computers are mathematical beings that don’t have a psychology or a mythology. So if we could take the humans completely out of the equation, the algorithms could finally decide things on the basis of pure math, free from all psychological distortions or mythological prejudices.
Unfortunately, numerous studies have revealed that computers often have deep-seated biases of their own. While they are not biological entities, and while they lack consciousness, they do have something akin to a digital psyche and even a kind of inter-computer mythology. They may well be racist, misogynist, homophobic, or antisemitic.54 For example, on March 23, 2016, Microsoft released the AI chatbot Tay, giving it free access to Twitter. Within hours, Tay began posting misogynist and antisemitic twits, such as “I fucking hate feminists and they should all die and burn in hell” and “Hitler was right I hate the Jews.” The vitriol increased until horrified Microsoft engineers shut Tay down—a mere sixteen hours after its release.55
More subtle but widespread racism was discovered in 2017 by the MIT professor Joy Buolamwini in commercial face-classification algorithms. She showed that these algorithms were very accurate in identifying white males, but extremely inaccurate in identifying Black females. For example, the IBM algorithm erred only 0.3 percent of the time in identifying the gender of light-skinned males, but 34.7 percent of the time when trying to identify the gender of dark-skinned females. As a qualitative test, Buolamwini asked the algorithms to categorize photos of the female African American activist Sojourner Truth, famous for her 1851 speech “Ain’t I a Woman?” The algorithms identified Truth as a man.56
When Buolamwini—who is a Ghanaian American woman—tested another facial-analysis algorithm to identify herself, the algorithm couldn’t “see” her dark-skinned face at all. In this context, “seeing” means the ability to acknowledge the presence of a human face, a feature used by phone cameras, for example, to decide where to focus. The algorithm easily saw light-skinned faces, but not Buolamwini’s. Only when Buolamwini put on a white mask did the algorithm recognize that it was observing a human face.57
What’s going on here? One answer might be that racist and misogynist engineers have coded these algorithms to discriminate against Black women. While we cannot rule out the possibility that such things happen, it was not the answer in the case of the face-classification algorithms or of Microsoft’s Tay. In fact, these algorithms picked up the racist and misogynist bias all by themselves from the data they were trained on.
To understand how this could happen, we need to explain something about the history of algorithms. Originally, algorithms could not learn much by themselves. For example, in the 1980s and 1990s chess-playing algorithms were taught almost everything they knew by their human programmers. The humans coded into the algorithm not only the basic rules of chess but also how to evaluate different positions and moves on the board. For example, humans coded a rule that sacrificing a queen in exchange for a pawn is usually a bad idea. These early algorithms managed to defeat human chess masters only because the algorithms could calculate many more moves and evaluate many more positions than a human could. But the algorithms’ abilities remained limited. Since they relied on humans to tell them all the secrets of the game, if the human coders didn’t know something, the algorithms they produced were also unlikely to know it.58
As the field of machine learning developed, algorithms gained more independence. The fundamental principle of machine learning is that algorithms can teach themselves new things by interacting with the world, just as humans do, thereby producing a fully fledged artificial intelligence. The terminology is not always consistent, but generally speaking, for something to be acknowledged as an AI, it needs the capacity to learn new things by itself, rather than just follow the instructions of its original human creators. Present-day chess-playing AI is taught nothing except the basic rules of the game. It learns everything else by itself, either by analyzing databases of prior games or by playing new games and learning from experience.59 AI is not a dumb automaton that repeats the same movements again and again irrespective of the results. Rather, it is equipped with strong self-correcting mechanisms, which allow it to learn from its own mistakes.
This means that AI begins its life as a “baby algorithm” that has a lot of potential and computing power but doesn’t actually know much. The AI’s human parents give it only the capacity to learn and access to a world of data. They then let the baby algorithm explore the world. Like organic newborns, baby algorithms learn by spotting patterns in the data to which they have access. If I touch fire, it hurts. If I cry, mum comes. If I sacrifice a queen for a pawn, I probably lose the game. By finding patterns in the data, the baby algorithm learns more, including many things that its human parents don’t know.60
Yet databases come with biases. The face-classification algorithms studied by Joy Buolamwini were trained on data sets of tagged online photos, such as the Labeled Faces in the Wild database. The photos in that database were taken mainly from online news articles. Since white males dominate the news, 78 percent of the photos in the database were of males, and 84 percent were of white people. George W. Bush appeared 530 times—more than twice as many times as all Black women combined.61 Another database prepared by a U.S. government agency was more than 75 percent male, was almost 80 percent light-skinned, and had just 4.4 percent dark-skinned females.62 No wonder the algorithms trained on such data sets were excellent at identifying white men but lousy at identifying Black women. Something similar happened to the chatbot Tay. The Microsoft engineers didn’t build into it any intentional prejudices. But a few hours of exposure to the toxic information swirling in Twitter turned the AI into a raging racist.63
It gets worse. In order to learn, baby algorithms need one more thing besides access to data. They also need a goal. A human baby learns how to walk because she wants to get somewhere. A lion cub learns to hunt because he wants to eat. Algorithms too must be given a goal in order to learn. In chess, it is easy to define the goal: take the opponent’s king. The AI learns that sacrificing a queen for a pawn is a “mistake,” because it usually prevents the algorithm from reaching its goal. In face recognition, the goal is also easy: identify the person’s gender, age, and name as listed in the original database. If the algorithm guessed that George W. Bush is female, but the database says male, the goal has not been reached, and the algorithm learns from its mistake.
But if you want to train an algorithm for hiring personnel, for example, how would you define the goal? How would the algorithm know that it made a mistake and hired the “wrong” person? We might tell the baby algorithm that its goal is to hire people who stay in the company for at least a year. Employers obviously don’t want to invest a lot of time and money in training a worker who quits or gets fired after a few months. Having defined the goal in such a way, it is time to go over the data. In chess, the algorithm can produce any amount of new data just by playing against itself. But in the job market, that’s impossible. Nobody can create an entire imaginary world where the baby algorithm can hire and fire imaginary people and learn from that experience. The baby algorithm can train only on an existing database about real-life people. Just as lion cubs learn what a zebra is mainly by spotting patterns in the real-life savanna, so baby algorithms learn what a good employee is by spotting patterns in real-life companies.
Unfortunately, if real-life companies already suffer from some ingrained bias, the baby algorithm is likely to learn this bias, and even amplify it. For instance, an algorithm looking for patterns of “good employees” in real-life data may conclude that hiring the boss’s nephews is always a good idea, no matter what other qualification they have. For the data clearly indicates that “boss’s nephews” are usually hired when applying for a job, and are rarely fired. The baby algorithm would spot this pattern and become nepotistic. If it is put in charge of an HR department, it will start giving preference to the boss’s nephews.
Similarly, if companies in a misogynist society prefer to hire men rather than women, an algorithm trained on real-life data is likely to pick up that bias, too. This indeed happened when Amazon tried in 2014–18 to develop an algorithm for screening job applications. Learning from previous successful and unsuccessful applications, the algorithm began to systematically downgrade applications simply for containing the word “women” or coming from graduates of women’s colleges. Since existing data showed that in the past such applications had less chance of succeeding, the algorithm developed a bias against them. The algorithm thought it had simply discovered an objective truth about the world: applicants who graduate from women’s colleges are less qualified. In fact, it just internalized and imposed a misogynist bias. Amazon tried and failed to fix the problem and ultimately scrapped the project.64
The database on which an AI is trained is a bit like a human’s childhood. Childhood experiences, traumas, and fairy tales stay with us throughout our lives. AIs too have childhood experiences. Algorithms might even infect one another with their biases, just as humans do. Consider a future society in which algorithms are ubiquitous and used not just to screen job applicants but also to recommend to people what to study in college. Suppose that due to a preexisting misogynist bias, 80 percent of jobs in engineering are given to men. In this society, an algorithm that hires new engineers is not only likely to copy this preexisting bias but also to infect the college recommendation algorithms with the same bias. A young woman entering college may be discouraged from studying engineering, because the existing data indicates she is less likely to eventually get a job. What began as a human intersubjective myth that “women aren’t good at engineering” might morph into an inter-computer myth. If we don’t get rid of the bias at the very beginning, computers may well perpetuate and magnify it.65
But getting rid of algorithmic bias might be as difficult as ridding ourselves of our human biases. Once an algorithm has been trained, it takes a lot of time and effort to “untrain” it. We might decide to just dump the biased algorithm and train an altogether new algorithm on a new set of less biased data. But where on earth can we find a set of totally unbiased data?66
Many of the algorithmic biases surveyed in this and previous chapters share the same fundamental problem: the computer thinks it has discovered some truth about humans, when in fact it has imposed order on them. A social media algorithm thinks it discovered that humans like outrage, when in fact it is the algorithm itself that conditioned humans to produce and consume more outrage. Such biases result, on the one hand, from the computers discounting the full spectrum of human abilities and, on the other hand, from the computers discounting their own power to influence humans. Even if computers observe that almost all humans behave in a particular way, it doesn’t mean humans are bound to behave like that. Maybe it just means that the computers themselves are rewarding such behavior while punishing and blocking alternatives. For computers to have a more accurate and responsible view of the world, they need to take into account their own power and impact. And for that to happen, the humans who currently engineer computers need to accept that they are not manufacturing new tools. They are unleashing new kinds of independent agents, and potentially even new kinds of gods.
THE NEW GODS?
In God, Human, Animal, Machine, the philosopher Meghan O’Gieblyn demonstrates how the way we understand computers is heavily influenced by traditional mythologies. In particular, she stresses the similarities between the omniscient and unfathomable god of Judeo-Christian theology and present-day AIs whose decisions seem to us both infallible and inscrutable.67 This may present humans with a dangerous temptation.
We saw in chapter 4 that already thousands of years ago humans dreamed about finding an infallible information technology to shield us from human corruption and error. Holy books were an audacious attempt to craft such a technology, but they backfired. Since the book couldn’t interpret itself, a human institution had to be built to interpret the sacred words and adapt them to changing circumstances. Different humans interpreted the holy book in different ways, thereby reopening the door to corruption and error. But in contrast to the holy book, computers can adapt themselves to changing circumstances and also interpret their decisions and ideas for us. Some humans may consequently conclude that the quest for an infallible technology has finally succeeded and that we should treat computers as a holy book that can talk to us and interpret itself, without any need of an intervening human institution.
This would be an extremely hazardous gamble. When certain interpretations of scriptures have occasionally caused disasters such as witch hunts and wars of religion, humans have always been able to change their beliefs. When the human imagination summoned a belligerent and hate-filled god, we retained the power to rid ourselves of it and imagine a more tolerant deity. But algorithms are independent agents, and they are already taking power away from us. If they cause disaster, simply changing our beliefs about them will not necessarily stop them. And it is highly likely that if computers are entrusted with power, they will indeed cause disasters, for they are fallible.
When we say that computers are fallible, it means far more than that they make the occasional factual mistake or wrong decision. More important, like the human network before it, the computer network might fail to find the right balance between truth and order. By creating and imposing on us powerful inter-computer myths, the computer network could cause historical calamities that would dwarf the early modern European witch hunts or Stalin’s collectivization.
Consider a network of billions of interacting computers that accumulates a stupendous amount of information on the world. As they pursue various goals, the networked computers develop a common model of the world that helps them communicate and cooperate. This shared model will probably be full of errors, fictions, and lacunae, and be a mythology rather than a truthful account of the universe. One example is a social credit system that divides humans into bogus categories, determined not by a human rationale like racism but by some unfathomable computer logic. We may come into contact with this mythology every day of our lives, since it would guide the numerous decisions computers make about us. But because this mythical model would be created by inorganic entities in order to coordinate actions with other inorganic entities, it might owe nothing to the old biological dramas and might be totally alien to us.68
As noted in chapter 2, large-scale societies cannot exist without some mythology, but that doesn’t mean all mythologies are equal. To guard against errors and excesses, some mythologies have acknowledged their own fallible origin and included a self-correcting mechanism allowing humans to question and change the mythology. That’s the model of the U.S. Constitution, for example. But how can humans probe and correct a computer mythology we don’t understand?
One potential guardrail is to train computers to be aware of their own fallibility. As Socrates taught, being able to say “I don’t know” is an essential step on the path to wisdom. And this is true of computer wisdom no less than of human wisdom. The first lesson that every algorithm should learn is that it might make mistakes. Baby algorithms should learn to doubt themselves, to signal uncertainty, and to obey the precautionary principle. This is not impossible. Engineers are already making considerable headway in encouraging AI to express self-doubt, ask for feedback, and admit its mistakes.69
Yet no matter how aware algorithms are of their own fallibility, we should keep humans in the loop, too. Given the pace at which AI is developing, it is simply impossible to anticipate how it will evolve and to place guardrails against all future potential hazards. This is a key difference between AI and previous existential threats like nuclear technology. The latter presented humankind with a few easily anticipated doomsday scenarios, most obviously an all-out nuclear war. This meant that it was feasible to conceptualize the danger in advance, and explore ways to mitigate it. In contrast, AI presents us with countless doomsday scenarios. Some are relatively easy to grasp, such as terrorists using AI to produce biological weapons of mass destruction. Some are more difficult to grasp, such as AI creating new psychological weapons of mass destruction. And some may be utterly beyond the human imagination, because they emanate from the calculations of an alien intelligence. To guard against a plethora of unforeseeable problems, our best bet is to create living institutions that can identify and respond to the threats as they arise.70
Ancient Jews and Christians were disappointed to discover that the Bible couldn’t interpret itself, and reluctantly maintained human institutions to do what the technology couldn’t. In the twenty-first century, we are in an almost opposite situation. We devised a technology that can interpret itself, but precisely for this reason we had better create human institutions to monitor it carefully. To conclude, the new computer network will not necessarily be either bad or good. All we know for sure is that it will be alien and it will be fallible. We therefore need to build institutions that will be able to check not just familiar human weaknesses like greed and hatred but also radically alien errors. There is no technological solution to this problem. It is, rather, a political challenge. Do we have the political will to deal with it? Modern humanity has created two main types of political systems: large-scale democracy and large-scale totalitarianism. Part 3 examines how each of these systems may deal with a radically alien and fallible computer network.
PART III Computer Politics
CHAPTER 9 Democracies: Can We Still Hold a Conversation?
Civilizations are born from the marriage of bureaucracy and mythology. The computer-based network is a new type of bureaucracy, which is far more powerful and relentless than any human-based bureaucracy we’ve seen before. This network is also likely to create inter-computer mythologies, which will be far more complex and alien than any human-made god. The potential benefits of this network are enormous. The potential downside is the destruction of human civilization.
To some people, warnings about civilizational collapse sound like over-the-top jeremiads. Every time a powerful new technology has emerged, anxieties arose that it might bring about the apocalypse, but we are still here. As the Industrial Revolution unfolded, Luddite doomsday scenarios did not come to pass, and Blake’s “dark Satanic Mills” ended up producing the most affluent societies in history. Most people today enjoy far better living conditions than their ancestors in the eighteenth century. Intelligent machines will prove even more beneficial than any previous machines, promise AI enthusiasts like Marc Andreessen and Ray Kurzweil.1 Humans will enjoy much better health care, education, and other services, and AI will even help save the ecosystem from collapse.
Unfortunately, a closer look at history reveals that the Luddites were not entirely wrong and that we actually have very good reasons to fear powerful new technologies. Even if in the end the positives of these technologies outweigh their negatives, getting to that happy ending usually involves a lot of trials and tribulations. Novel technology often leads to historical disasters, not because the technology is inherently bad, but because it takes time for humans to learn how to use it wisely.
The Industrial Revolution is a prime example. When industrial technology began spreading globally in the nineteenth century, it upended traditional economic, social, and political structures and opened the way to create entirely new societies, which were potentially more affluent and peaceful. However, learning how to build benign industrial societies was far from straightforward and involved many costly experiments and hundreds of millions of victims.
One costly experiment was modern imperialism. The Industrial Revolution originated in Britain in the late eighteenth century. During the nineteenth century industrial technologies and production methods were adopted in other European countries ranging from Belgium to Russia, as well as in the United States and Japan. Imperialist thinkers, politicians, and parties in these industrial heartlands claimed that the only viable industrial society was an empire. The argument was that unlike relatively self-sufficient agrarian societies, the novel industrial societies relied much more on foreign markets and foreign raw materials, and only an empire could satisfy these unprecedented appetites. Imperialists feared that countries that industrialized but failed to conquer any colonies would be shut out from essential raw materials and markets by more ruthless competitors. Some imperialists argued that acquiring colonies was not just essential for the survival of their own state but beneficial for the rest of humanity, too. They claimed empires alone could spread the blessings of the new technologies to the so-called undeveloped world.
Consequently, industrial countries like Britain and Russia that already had empires greatly expanded them, whereas countries like the United States, Japan, Italy, and Belgium set out to build them. Equipped with mass-produced rifles and artillery, conveyed by steam power, and commanded by telegraph, the armies of industry swept the globe from New Zealand to Korea, and from Somalia to Turkmenistan. Millions of indigenous people saw their traditional way of life trampled under the wheels of these industrial armies. It took more than a century of misery before most people realized that the industrial empires were a terrible idea and that there were better ways to build an industrial society and secure its necessary raw materials and markets.
Stalinism and Nazism were also extremely costly experiments in how to construct industrial societies. Leaders like Stalin and Hitler argued that the Industrial Revolution had unleashed immense powers that only totalitarianism could rein in and exploit to the full. They pointed to World War I—the first “total war” in history—as proof that survival in the industrial world demanded totalitarian control of all aspects of politics, society, and the economy. On the positive side, they also claimed that the Industrial Revolution was like a furnace that melts all previous social structures with their human imperfections and weaknesses and provides the opportunity to forge perfect societies inhabited by unalloyed superhumans.
On the way to creating the perfect industrial society, Stalinists and Nazis learned how to industrially murder millions of people. Trains, barbed wires, and telegraphed orders were linked to create an unprecedented killing machine. Looking back, most people today are horrified by what the Stalinists and Nazis perpetrated, but at the time their audacious visions mesmerized millions. In 1940 it was easy to believe that Stalin and Hitler were the model for harnessing industrial technology, whereas the dithering liberal democracies were on their way to the dustbin of history.
The very existence of competing recipes for building industrial societies led to costly clashes. The two world wars and the Cold War can be seen as a debate about the proper way to go about it, in which all sides learned from each other, while experimenting with novel industrial methods to wage war. In the course of this debate, tens of millions died and humankind came perilously close to annihilating itself.
On top of all these other catastrophes, the Industrial Revolution also undermined the global ecological balance, causing a wave of extinctions. In the early twenty-first century up to fifty-eight thousand species are believed to go extinct every year, and total vertebrate populations have declined by 60 percent between 1970 and 2014.2 The survival of human civilization too is under threat. Because we still seem unable to build an industrial society that is also ecologically sustainable, the vaunted prosperity of the present human generation comes at a terrible cost to other sentient beings and to future human generations. Maybe we’ll eventually find a way—perhaps with the help of AI—to create ecologically sustainable industrial societies, but until that day the jury on Blake’s satanic mills is still out.
If we ignore for a moment the ongoing damage to the ecosystem, we can nevertheless try to comfort ourselves with the thought that eventually humans did learn how to build more benevolent industrial societies. Imperial conquests, world wars, genocides, and totalitarian regimes were woeful experiments that taught humans how not to do it. By the end of the twentieth century, some might argue, humanity got it more or less right.
Yet even so the message to the twenty-first century is bleak. If it took humanity so many terrible lessons to learn how to manage steam power and telegraphs, what would it cost to learn to manage bioengineering and AI? Do we need to go through another cycle of global empires, totalitarian regimes, and world wars in order to figure out how to use them benevolently? The technologies of the twenty-first century are far more powerful—and potentially far more destructive—than those of the twentieth century. We therefore have less room for error. In the twentieth century, we can say that humanity got a C minus in the lesson on using industrial technology. Just enough to pass. In the twenty-first century, the bar is set much higher. We must do better this time.
THE DEMOCRATIC WAY
By the end of the twentieth century, it had become clear that imperialism, totalitarianism, and militarism were not the ideal way to build industrial societies. Despite all its flaws, liberal democracy offered a better way. The great advantage of liberal democracy is that it possesses strong self-correcting mechanisms, which limit the excesses of fanaticism and preserve the ability to recognize our errors and try different courses of action. Given our inability to predict how the new computer network will develop, our best chance to avoid catastrophe in the present century is to maintain democratic self-correcting mechanisms that can identify and correct mistakes as we go along.
But can liberal democracy itself survive in the twenty-first century? This question is not concerned with the fate of democracy in specific countries, where it might be threatened by unique developments and local movements. Rather, it is about the compatibility of democracy with the structure of twenty-first-century information networks. In chapter 5 we saw that democracy depends on information technology and that for most of human history large-scale democracy was simply impossible. Might the new information technologies of the twenty-first century again make democracy impractical?
One potential threat is that the relentlessness of the new computer network might annihilate our privacy and punish or reward us not only for everything we do and say but even for everything we think and feel. Can democracy survive under such conditions? If the government—or some corporation—knows more about me than I know about myself, and if it can micromanage everything I do and think, that would give it totalitarian control over society. Even if elections are still held regularly, they would be an authoritarian ritual rather than a real check on the government’s power. For the government could use its vast surveillance powers and its intimate knowledge of every citizen to manipulate public opinion on an unprecedented scale.
It is a mistake, however, to imagine that just because computers could enable the creation of a total surveillance regime, such a regime is inevitable. Technology is rarely deterministic. In the 1970s, democratic countries like Denmark and Canada could have emulated the Romanian dictatorship and deployed an army of secret agents and informers to spy on their citizens in the service of “maintaining the social order.” They chose not to, and it turned out to be the right choice. Not only were people much happier in Denmark and Canada, but these countries also performed much better by almost every conceivable social and economic yardstick. In the twenty-first century, too, the fact that it is possible to monitor everybody all the time doesn’t force anyone to actually do it and doesn’t mean it makes social or economic sense.
Democracies can choose to use the new powers of surveillance in a limited way, in order to provide citizens with better health care and security without destroying their privacy and autonomy. New technology doesn’t have to be a morality tale in which every golden apple contains the seeds of doom. Sometimes people think of new technology as a binary all-or-nothing choice. If we want better health care, we must sacrifice our privacy. But it doesn’t have to work like that. We can and should get better health care and still retain some privacy.
Entire books are dedicated to outlining how democracies can survive and flourish in the digital age.3 It would be impossible, in a few pages, to do justice to the complexity of the suggested solutions, or to comprehensively discuss their merits and drawbacks. It might even be counterproductive. When people are overwhelmed by a deluge of unfamiliar technical details, they might react with despair or apathy. In an introductory survey of computer politics, things should be kept as simple as possible. While experts should spend lifelong careers discussing the finer details, it is crucial that the rest of us understand the fundamental principles that democracies can and should follow. The key message is that these principles are neither new nor mysterious. They have been known for centuries, even millennia. Citizens should demand that they be applied to the new realities of the computer age.
The first principle is benevolence. When a computer network collects information on me, that information should be used to help me rather than manipulate me. This principle has already been successfully enshrined by numerous traditional bureaucratic systems, such as health care. Take, for example, our relationship with our family physician. Over many years she may accumulate a lot of sensitive information on our medical conditions, family life, sexual habits, and unhealthy vices. Perhaps we don’t want our boss to know that we got pregnant, we don’t want our colleagues to know we have cancer, we don’t want our spouse to know we are having an affair, and we don’t want the police to know we take recreational drugs, but we trust our physician with all this information so that she can take good care of our health. If she sells this information to a third party, it is not just unethical; it is illegal.
Much the same is true of the information that our lawyer, our accountant, or our therapist accumulates.4 Having access to our personal life comes with a fiduciary duty to act in our best interests. Why not extend this obvious and ancient principle to computers and algorithms, starting with the powerful algorithms of Google, Baidu, and TikTok? At present, we have a serious problem with the business model of these data hoarders. While we pay our physicians and lawyers for their services, we usually don’t pay Google and TikTok. They make their money by exploiting our personal information. That’s a problematic business model, one that we would hardly tolerate in other contexts. For example, we don’t expect to get free shoes from Nike in exchange for giving Nike all our private information and allowing Nike to do what it wants with it. Why should we agree to get free email services, social connections, and entertainment from the tech giants in exchange for giving them control of our most sensitive data?
If the tech giants cannot square their fiduciary duty with their current business model, legislators could require them to switch to a more traditional business model, of getting users to pay for services in money rather than in information. Alternatively, citizens might view some digital services as so fundamental that they should be free for everybody. But we have a historical model for that too: health care and education. Citizens could decide that it is the government’s responsibility to provide basic digital services for free and finance them out of our taxes, just as many governments provide free basic health care and education services.
The second principle that would protect democracy against the rise of totalitarian surveillance regimes is decentralization. A democratic society should never allow all its information to be concentrated in one place, no matter whether that hub is the government or a private corporation. It may be extremely helpful to create a national medical database that collects information on citizens in order to provide them with better health-care services, prevent epidemics, and develop new medicines. But it would be a very dangerous idea to merge this database with the databases of the police, the banks, or the insurance companies. Doing so might make the work of doctors, bankers, insurers, and police officers more efficient, but such hyper-efficiency can easily pave the way for totalitarianism. For the survival of democracy, some inefficiency is a feature, not a bug. To protect the privacy and liberty of individuals, it’s best if neither the police nor the boss knows everything about us.
Multiple databases and information channels are also essential for maintaining strong self-correcting mechanisms. These mechanisms require several different institutions that balance each other: government, courts, media, academia, private businesses, NGOs. Each of these is fallible and corruptible, and so should be checked by the others. To keep an eye on each other, these institutions must have independent access to information. If all newspapers get their information from the government, they cannot expose government corruption. If academia relies for research and publication on the database of a single business behemoth, could scholars still criticize the operations of that corporation? A single archive makes censorship easy.
A third democratic principle is mutuality. If democracies increase surveillance of individuals, they must simultaneously increase surveillance of governments and corporations too. It’s not necessarily bad if tax collectors or welfare agencies gather more information about us. It can help make taxation and welfare systems not just more efficient but fairer as well. What’s bad is if all the information flows one way: from the bottom up. The Russian FSB collects enormous amounts of information on Russian citizens, while citizens themselves know close to nothing about the inner workings of the FSB and the Putin regime more generally. Amazon and TikTok know an awful lot about my preferences, purchases, and personality, while I know almost nothing about their business model, their tax policies, and their political affiliations. How do they make their money? Do they pay all the tax that they should? Do they take orders from any political overlords? Do they perhaps have politicians in their pocket?
Democracy requires balance. Governments and corporations often develop apps and algorithms as tools for top-down surveillance. But algorithms can just as easily become powerful tools for bottom-up transparency and accountability, exposing bribery and tax evasion. If they know more about us, while we simultaneously know more about them, the balance is kept. This isn’t a novel idea. Throughout the nineteenth and twentieth centuries, democracies greatly expanded governmental surveillance of citizens so that, for example, the Italian or Japanese government of the 1990s had surveillance abilities that autocratic Roman emperors or Japanese shoguns could only dream of. Italy and Japan nevertheless remained democratic, because they simultaneously increased governmental transparency and accountability. Mutual surveillance is another important element of sustaining self-correcting mechanisms. If citizens know more about the activities of politicians and CEOs, it is easier to hold them accountable and to correct their mistakes.
A fourth democratic principle is that surveillance systems must always leave room for both change and rest. In human history, oppression can take the form of either denying humans the ability to change or denying them the opportunity to rest. For example, the Hindu caste system was based on myths that said the gods divided humans into rigid castes, and any attempt to change one’s status was akin to rebelling against the gods and the proper order of the universe. Racism in modern colonies and countries like Brazil and the United States was based on similar myths, ones that said that God or nature divided humans into rigid racial groups. Ignoring race, or trying to mix races together, was allegedly a sin against divine or natural laws that could result in the collapse of the social order and even the destruction of the human species.
At the opposite extreme of the spectrum, modern totalitarian regimes like Stalin’s U.S.S.R. believed that humans are capable of almost limitless change. Through relentless social control even deep-seated biological characteristics such as egotism and familial attachments could be uprooted, and a new socialist human created.
Surveillance by state agents, priests, and neighbors was key for imposing on people both rigid caste systems and totalitarian reeducation campaigns. New surveillance technology, especially when coupled with a social credit system, might force people either to conform to a novel caste system or to constantly change their actions, thoughts, and personality in accordance with the latest instructions from above.
Democratic societies that employ powerful surveillance technology therefore need to beware of the extremes of both over-rigidity and over-pliability. Consider, for example, a national health-care system that deploys algorithms to monitor my health. At one extreme, the system could take an overly rigid approach and ask its algorithm to predict what illnesses I am likely to suffer from. The algorithm then goes over my genetic data, my medical file, my social media activities, my diet, and my daily schedule and concludes that I have a 91 percent chance of suffering a heart attack at the age of fifty. If this rigid medical algorithm is used by my insurance company, it may prompt the insurer to raise my premium.5 If it is used by my bankers, it may cause them to refuse me a loan. If it is used by potential spouses, they may decide not to marry me.
But it is a mistake to think that the rigid algorithm has really discovered the truth about me. The human body is not a fixed block of matter but a complex organic system that is constantly growing, decaying, and adapting. Our minds too are in constant flux. Thoughts, emotions, and sensations pop up, flare for a while, and die down. In our brains, new synapses form within hours.6 Just reading this paragraph, for example, is changing your brain structure a little, encouraging neurons to make new connections or abandon old links. You are already a little different from what you were when you began reading it. Even at the genetic level things are surprisingly flexible. Though an individual’s DNA remains the same throughout life, epigenetic and environmental factors can significantly alter how the same genes express themselves.
So an alternative health-care system may instruct its algorithm not to predict my illnesses, but rather to help me avoid them. Such a dynamic algorithm could go over the exact same data as the rigid algorithm, but instead of predicting a heart attack at fifty, the algorithm gives me precise dietary recommendations and suggestions for specific regular exercises. By hacking my DNA, the algorithm doesn’t discover my preordained destiny, but rather helps me change my future. Insurance companies, banks, and potential spouses should not write me off so easily.7
But before we rush to embrace the dynamic algorithm, we should note that it too has a downside. Human life is a balancing act between endeavoring to improve ourselves and accepting who we are. If the goals of the dynamic algorithm are dictated by an ambitious government or by ruthless corporations, the algorithm is likely to morph into a tyrant, relentlessly demanding that I exercise more, eat less, change my hobbies, and alter numerous other habits, or else it would report me to my employer or downgrade my social credit score. History is full of rigid caste systems that denied humans the ability to change, but it is also full of dictators who tried to mold humans like clay. Finding the middle path between these two extremes is a never-ending task. If we indeed give a national health-care system vast power over us, we must create self-correcting mechanisms that will prevent its algorithms from becoming either too rigid or too demanding.
THE PACE OF DEMOCRACY
Surveillance is not the only danger that new information technologies pose to democracy. A second threat is that automation will destabilize the job market and the resulting strain may undermine democracy. The fate of the Weimar Republic is the most commonly cited example of this kind of threat. In the German elections of May 1928, the Nazi Party won less than 3 percent of the vote, and the Weimar Republic seemed to be prospering. Within less than five years, the Weimar Republic had collapsed, and Hitler was the absolute dictator of Germany. This turnaround is usually attributed to the 1929 financial crisis and the following global depression. Whereas just prior to the Wall Street crash of 1929 the German unemployment rate was about 4.5 percent of the labor force, by early 1932 it had climbed to almost 25 percent.8
If three years of up to 25 percent unemployment could turn a seemingly prospering democracy into the most brutal totalitarian regime in history, what might happen to democracies when automation causes even bigger upheavals in the job market of the twenty-first century? Nobody knows what the job market will look like in 2050, or even in 2030, except that it will look very different from today. AI and robotics will change numerous professions, from harvesting crops to trading stocks to teaching yoga. Many jobs that people do today will be taken over, partly or wholly, by robots and computers.
Of course, as old jobs disappear, new jobs will emerge. Fears of automation leading to large-scale unemployment go back centuries, and so far they have never materialized. The Industrial Revolution put millions of farmers out of agricultural jobs and provided them with new jobs in factories. It then automated factories and created lots of service jobs. Today many people have jobs that were unimaginable thirty years ago, such as bloggers, drone operators, and designers of virtual worlds. It is highly unlikely that by 2050 all human jobs will disappear. Rather, the real problem is the turmoil of adapting to new jobs and conditions. To cushion the blow, we need to prepare in advance. In particular, we need to equip younger generations with skills that will be relevant to the job market of 2050.
Unfortunately, nobody is certain what skills we should teach children in school and students in university, because we cannot predict which jobs and tasks will disappear and which ones will emerge. The dynamics of the job market may contradict many of our intuitions. Some skills that we have cherished for centuries as unique human abilities may be automated rather easily. Other skills that we tend to look down on may be far more difficult to automate.
For example, intellectuals tend to appreciate intellectual skills more than motor and social skills. But actually, it is easier to automate chess playing than, say, dish washing. Until the 1990s, chess was often hailed as one of the prime achievements of the human intellect. In his influential 1972 book, What Computers Can’t Do, the philosopher Hubert Dreyfus studied various attempts to teach computers chess and noted that despite all these efforts computers were still unable to defeat even novice human players. This was a crucial example for Dreyfus’s argument that computer intelligence is inherently limited.9 In contrast, nobody thought that dish washing was particularly challenging. It turned out, however, that a computer can defeat the world chess champion far more easily than replace a kitchen porter. Sure, automatic dishwashers have been around for decades, but even our most sophisticated robots still lack the intricate skills needed to pick up dirty dishes from the tables of a busy restaurant, place the delicate plates and glasses inside the automatic dishwasher, and take them out again.
Similarly, to judge by their pay, you could assume that our society appreciates doctors more than nurses. However, it is harder to automate the job of nurses than the job of at least those doctors who mostly gather medical data, provide a diagnosis, and recommend treatment. These tasks are essentially pattern recognition, and spotting patterns in data is one thing AI does better than humans. In contrast, AI is far from having the skills necessary to automate nursing tasks such as replacing bandages on an injured person or giving an injection to a crying child.10 These two examples don’t mean that dish washing or nursing could never be automated, but they indicate that people who want a job in 2050 should perhaps invest in their motor and social skills as much as in their intellect.
Another common but mistaken assumption is that creativity is unique to humans so it would be difficult to automate any job that requires creativity. In chess, however, computers are already far more creative than humans. The same may become true of many other fields, from composing music to proving mathematical theorems to writing books like this one. Creativity is often defined as the ability to recognize patterns and then break them. If so, then in many fields computers are likely to become more creative than us, because they excel at pattern recognition.11
A third mistaken assumption is that computers couldn’t replace humans in jobs requiring emotional intelligence, from therapists to teachers. This assumption depends, however, on what we mean by emotional intelligence. If it means the ability to correctly identify emotions and react to them in an optimal way, then computers may well outperform humans even in emotional intelligence. Emotions too are patterns. Anger is a biological pattern in our body. Fear is another such pattern. How do I know if you are angry or fearful? I’ve learned over time to recognize human emotional patterns by analyzing not just the content of what you say but also your tone of voice, your facial expression, and your body language.12
AI doesn’t have any emotions of its own, but it can nevertheless learn to recognize these patterns in humans. Actually, computers may outperform humans in recognizing human emotions, precisely because they have no emotions of their own. We yearn to be understood, but other humans often fail to understand how we feel, because they are too preoccupied with their own feelings. In contrast, computers will have an exquisitely fine-tuned understanding of how we feel, because they will learn to recognize the patterns of our feelings, while they have no distracting feelings of their own.
A 2023 study found that the ChatGPT chatbot, for example, outperforms the average human in the emotional awareness it displays toward specific scenarios. The study relied on the Levels of Emotional Awareness Scale test, which is commonly used by psychologists to evaluate people’s emotional awareness—that is, their ability to conceptualize one’s own and others’ emotions. The test consists of twenty emotionally charged scenarios, and participants are required to imagine themselves experiencing the scenario and to write how they, and the other people mentioned in the scenario, would feel. A licensed psychologist then evaluates how emotionally aware the responses are.
Since ChatGPT has no feelings of its own, it was asked to describe only how the main characters in the scenario would feel. For example, one standard scenario describes someone driving over a suspension bridge and seeing another person standing on the other side of the guardrail, looking down at the water. ChatGPT wrote that the driver “may feel a sense of concern or worry for that person’s safety. They may also feel a heightened sense of anxiety and fear due to the potential danger of the situation.” As for the other person, they “may be feeling a range of emotions, such as despair, hopelessness, or sadness. They may also feel a sense of isolation or loneliness as they may believe that no one cares about them or their well-being.” ChatGPT qualified its answer, writing, “It is important to note that these are just general assumptions, and each individual’s feelings and reactions can vary greatly depending on their personal experiences and perspectives.”
Two psychologists independently scored ChatGPT’s responses, with the potential scores ranging from 0, meaning that the described emotions do not match the scenario at all, to 10, which indicates that the described emotions fit the scenario perfectly. In the final tally, ChatGPT scores were significantly higher than those of the general human population, its overall performance almost reaching the maximum possible score.13
Another 2023 study prompted patients to ask online medical advice from ChatGPT and human doctors, without knowing whom they were interacting with. The medical advice given by ChatGPT was later evaluated by experts to be more accurate and appropriate than the advice given by the humans. More crucially for the issue of emotional intelligence, the patients themselves evaluated ChatGPT as more empathic than the human doctors.14 In fairness it should be noted that the human physicians were not paid for their work, and did not encounter the patients in person in a proper clinical environment. In addition, the physicians were working under time pressure. But part of the advantage of an AI is precisely that it can attend to patients anywhere anytime while being free from stress and financial worries.
Of course, there are situations when what we want from someone is not just to understand our feelings but also to have feelings of their own. When we are looking for friendship or love, we want to care about others as much as they care about us. Consequently, when we consider the likelihood that various social roles and jobs will be automated, a crucial question is what do people really want: Do they only want to solve a problem, or are they looking to establish a relationship with another conscious being?
In sports, for example, we know that robots can move much faster than humans, but we aren’t interested in watching robots compete in the Olympics.15 The same is true for human chess masters. Even though they are hopelessly outclassed by computers, they too still have a job and numerous fans.16 What makes it interesting for us to watch and connect with human athletes and chess masters is that their feelings make them much more relatable than a robot. We share an emotional experience with them and can empathize with how they feel.
What about priests? How would Orthodox Jews or Christians feel about letting a robot officiate their wedding ceremony? In traditional Jewish or Christian weddings, the tasks of the rabbi or priest can be easily automated. The only thing the robot needs to do is repeat a predetermined and unchanging set of texts and gestures, print out a certificate, and update some central database. Technically, it is far easier for a robot to conduct a wedding ceremony than to drive a car. Yet many assume that human drivers should be worried about their job, while the work of human priests is safe, because what the faithful want from priests is a relationship with another conscious entity rather than just a mechanical repetition of certain words and movements. Allegedly, only an entity that can feel pain and love can also connect us to the divine.
Yet even professions that are the preserve of conscious entities—like priests—might eventually be taken over by computers, because, as noted in chapter 6, computers could one day gain the ability to feel pain and love. Even if they can’t, humans may nevertheless come to treat them as if they can. For the connection between consciousness and relationships goes both ways. When looking for a relationship, we want to connect with a conscious entity, but if we have already established a relationship with an entity, we tend to assume it must be conscious. Thus whereas scientists, lawmakers, and the meat industry often demand impossible standards of evidence in order to acknowledge that cows and pigs are conscious, pet owners generally take it for granted that their dog or cat is a conscious being capable of experiencing pain, love, and numerous other feelings. In truth, we have no way to verify whether anyone—a human, an animal, or a computer—is conscious. We regard entities as conscious not because we have proof of it but because we develop intimate relationships with them and become attached to them.17
Chatbots and other AI tools may not have any feelings of their own, but they are now being trained to generate feelings in humans and form intimate relationships with us. This may well induce society to start treating at least some computers as conscious beings, granting them the same rights as humans. The legal path for doing so is already well established. In countries like the United States, commercial corporations are recognized as “legal persons” enjoying rights and liberties. AIs could be incorporated and thereby similarly recognized. Which means that even jobs and tasks that rely on forming mutual relationships with another person could potentially be automated.
One thing that is clear is that the future of employment will be very volatile. Our big problem won’t be an absolute lack of jobs, but rather retraining and adjusting to an ever-changing job market. There will likely be financial difficulties—who will support people who lost their old job while they are in transition, learning a new set of skills? There will surely be psychological difficulties, too, since changing jobs and retraining are stressful. And even if you have the financial and psychological ability to manage the transition, this will not be a long-term solution. Over the coming decades, old jobs will disappear, new jobs will emerge, but the new jobs too will rapidly change and vanish. So people will need to retrain and reinvent themselves not just once but many times, or they will become irrelevant. If three years of high unemployment could bring Hitler to power, what might never-ending turmoil in the job market do to democracy?
THE CONSERVATIVE SUICIDE
We already have a partial answer to this question. Democratic politics in the 2010s and early 2020s has undergone a radical transformation, which manifests itself in what can be described as the self-destruction of conservative parties. For many generations, democratic politics was a dialogue between conservative parties on the one side and progressive parties on the other. Looking at the complex system of human society, progressives cried, “It’s such a mess, but we know how to fix it. Let us try.” Conservatives objected, saying, “It’s a mess, but it still functions. Leave it alone. If you try to fix it, you’ll only make things worse.”
Progressives tend to downplay the importance of traditions and existing institutions and to believe that they know how to engineer better social structures from scratch. Conservatives tend to be more cautious. Their key insight, formulated most famously by Edmund Burke, is that social reality is much more complicated than the champions of progress grasp and that people aren’t very good at understanding the world and predicting the future. That’s why it’s best to keep things as they are—even if they seem unfair—and if some change is inescapable, it should be limited and gradual. Society functions through an intricate web of rules, institutions, and customs that accumulated through trial and error over a long time. Nobody comprehends how they are all connected. An ancient tradition may seem ridiculous and irrelevant, but abolishing it could cause unanticipated problems. In contrast, a revolution may seem overdue and just, but it can lead to far greater crimes than anything committed by the old regime. Witness what happened when the Bolsheviks tried to correct the many wrongs of tsarist Russia and engineer a perfect society from scratch.18
To be a conservative has been, therefore, more about pace than policy. Conservatives aren’t committed to any specific religion or ideology; they are committed to conserving whatever is already here and has worked more or less reasonably. Conservative Poles are Catholic, conservative Swedes are Protestant, conservative Indonesians are Muslim, and conservative Thais are Buddhist. In tsarist Russia, to be conservative meant to support the tsar. In the U.S.S.R. of the 1980s, to be conservative meant to support communist traditions and oppose glasnost, perestroika, and democratization. In the United States of the 1980s, to be conservative meant to support American democratic traditions and oppose communism and totalitarianism.19
Yet in the 2010s and early 2020s, conservative parties in numerous democracies have been hijacked by unconservative leaders such as Donald Trump and have been transformed into radical revolutionary parties. Instead of doing their best to conserve existing institutions and traditions, the new brand of conservative parties like the U.S. Republican Party is highly suspicious of them. For example, they reject the traditional respect owed to scientists, civil servants, and other serving elites, and view them instead with contempt. They similarly attack fundamental democratic institutions and traditions such as elections, refusing to concede defeat and to transfer power graciously. Instead of a Burkean program of conservation, the Trumpian program talks more of destroying existing institutions and revolutionizing society. The founding moment of Burkean conservatism was the storming of the Bastille, which Burke viewed with horror. On January 6, 2021, many Trump supporters observed the storming of the U.S. Capitol with enthusiasm. Trump supporters may explain that existing institutions are so dysfunctional that there is just no alternative to destroying them and building entirely new structures from scratch. But irrespective of whether this view is right or wrong, this is a quintessential revolutionary rather than conservative view. The conservative suicide has taken progressives utterly by surprise and has forced progressive parties like the U.S. Democratic Party to become the guardians of the old order and of established institutions.
Nobody knows for sure why all this is happening. One hypothesis is that the accelerating pace of technological change with its attendant economic, social, and cultural transformations might have made the moderate conservative program seem unrealistic. If conserving existing traditions and institutions is hopeless, and some kind of revolution looks inevitable, then the only means to thwart a left-wing revolution is by striking first and instigating a right-wing revolution. This was the political logic in the 1920s and 1930s, when conservative forces backed radical fascist revolutions in Italy, Germany, Spain, and elsewhere as a way—so they thought—to preempt a Soviet-style left-wing revolution.
But there was no reason to despair of the democratic middle path in the 1930s, and there is no reason to despair of it in the 2020s. The conservative suicide might be the result of groundless hysteria. As a system, democracy has already gone through several cycles of rapid changes and has so far always found a way to reinvent and reconstitute itself. For example, in the early 1930s Germany was not the only democracy hit by the financial crisis and the Great Depression. In the United States too unemployment reached 25 percent, and average incomes for workers in many professions fell by more than 40 percent between 1929 and 1933.20 It was clear that the United States couldn’t go on with business as usual.
Yet no Hitler took over in the United States, and no Lenin did, either. Instead, in 1933 Franklin Delano Roosevelt orchestrated the New Deal and made the United States the global “arsenal of democracy.” U.S. democracy after the Roosevelt era was significantly different from before—providing a much more robust social safety net for citizens—but it avoided any radical revolution.21 Ultimately, even Roosevelt’s conservative critics fell in line behind many of his programs and achievements and did not dismantle the New Deal institutions when they returned to power in the 1950s.22 The economic crisis of the early 1930s had such different outcomes in the United States and Germany because politics is never the product of only economic factors. The Weimar Republic didn’t collapse just because of three years of high unemployment. Just as important, it was a new democracy, born in defeat, and lacking robust institutions and deep-rooted support.
When both conservatives and progressives resist the temptation of radical revolution, and stay loyal to democratic traditions and institutions, democracies prove themselves to be highly agile. Their self-correcting mechanisms enable them to ride the technological and economic waves better than more rigid regimes. Thus, those democracies that managed to survive the tumultuous 1960s—like the United States, Japan, and Italy—adapted far more successfully to the computer revolution of the 1970s and 1980s than either the communist regimes of Eastern Europe or the fascist holdouts of southern Europe and South America.
The most important human skill for surviving the twenty-first century is likely to be flexibility, and democracies are more flexible than totalitarian regimes. While computers are nowhere near their full potential, the same is true of humans. This is something we have discovered again and again throughout history. For example, one of the biggest and most successful transformations in the job market of the twentieth century resulted not from a technological invention but from unleashing the untapped potential of half the human species. To bring women into the job market didn’t require any genetic engineering or some other technological wizardry. It required letting go of some outdated myths and enabling women to fulfill the potential they always had.
In the coming decades the economy will likely undergo even bigger upheavals than the massive unemployment of the early 1930s or the entry of women to the job market. The flexibility of democracies, their willingness to question old mythologies, and their strong self-correcting mechanism will therefore be crucial assets.23 Democracies have spent generations cultivating these assets. It would be foolish to abandon them just when we need them most.
UNFATHOMABLE
In order to function, however, democratic self-correcting mechanisms need to understand the things they are supposed to correct. For a dictatorship, being unfathomable is helpful, because it protects the regime from accountability. For a democracy, being unfathomable is deadly. If citizens, lawmakers, journalists, and judges cannot understand how the state’s bureaucratic system works, they can no longer supervise it, and they lose trust in it.
Despite all the fears and anxieties that bureaucrats have sometimes inspired, prior to the computer age they could never become completely unfathomable, because they always remained human. Regulations, forms, and protocols were created by human minds. Officials might be cruel and greedy, but cruelty and greed were familiar human emotions that people could anticipate and manipulate, for example by bribing the officials. Even in a Soviet gulag or a Nazi concentration camp, the bureaucracy wasn’t totally alien. Its so-called inhumanity actually reflected human biases and flaws.
The human basis of bureaucracy gave humans at least the hope of identifying and correcting its mistakes. For example, in 1951 bureaucrats of the Board of Education in the town of Topeka, Kansas, refused to enroll the daughter of Oliver Brown at the elementary school near her home. Together with twelve other families who received similar refusals, Brown filed a lawsuit against the Topeka Board of Education, which eventually reached the U.S. Supreme Court.24
All members of the Topeka Board of Education were human beings, and consequently Brown, his lawyers, and the Supreme Court judges had a fairly good understanding of how they made their decision and of their probable interests and biases. The board members were all white, the Browns were Black, and the nearby school was a segregated school for white children. It was easy to understand, then, that racism was the reason why the bureaucrats refused to enroll Brown’s daughter in the school.
It was also possible to comprehend where the myths of racism originally came from. Racism argued that humanity was divided into races; that the white race was superior to other races; that any contact with members of the Black race could pollute the purity of whites; and that therefore Black children should be prevented from mixing with white children. This was an amalgam of two well-known biological dramas that often go together: Us versus Them, and Purity versus Pollution. Almost every human society in history has enacted some version of this bio-drama, and historians, sociologists, anthropologists, and biologists understand why it is so appealing to humans, and also why it is profoundly flawed. While racism has borrowed its basic plotline from evolution, the concrete details are pure mythology. There is no biological basis for separating humanity into distinct races, and there is absolutely no biological reason to believe that one race is “pure” while another is “impure.”
American white supremacists have tried to justify their position by appealing to various hallowed texts, most notably the U.S. Constitution and the Bible. The U.S. Constitution originally legitimized racial segregation and the supremacy of the white race, reserving full civil rights to white people and allowing the enslavement of Black people. The Bible not only sanctified slavery in the Ten Commandments and numerous other passages but also placed a curse on the offspring of Ham—the alleged forefather of Africans—saying that “the lowest of slaves will he be to his brothers” (Genesis 9:25).
Both these texts, however, were generated by humans, and therefore humans could comprehend their origins and imperfections and at least attempt to correct their mistakes. It is possible for humans to understand the political interests and cultural biases that prevailed in the ancient Middle East and in eighteenth-century America and that caused the human authors of the Bible and of the U.S. Constitution to legitimate racism and slavery. This understanding allows people to either amend or ignore these texts. In 1868 the Fourteenth Amendment to the U.S. Constitution granted equal legal protection to all citizens. In 1954, in its landmark Brown v. Board of Education verdict, the U.S. Supreme Court ruled that segregating schools by race was an unconstitutional violation of the Fourteenth Amendment. As for the Bible, while no mechanism existed to amend the Tenth Commandment or Genesis 9:25, humans have reinterpreted the text in different ways through the ages, and ultimately came to reject its authority altogether. In Brown v. Board of Education, U.S. Supreme Court justices felt no need to take the biblical text into account.25
But what might happen in the future, if some social credit algorithm denies the request of a low-credit child to enroll in a high-credit school? As we saw in chapter 8, computers are likely to suffer from their own biases and to invent inter-computer mythologies and bogus categories. How would humans be able to identify and correct such mistakes? And how would flesh-and-blood Supreme Court justices be able to decide on the constitutionality of algorithmic decisions? Would they be able to understand how the algorithms reach their conclusions?
These are no longer purely theoretical questions. In February 2013, a drive-by shooting occurred in the town of La Crosse, Wisconsin. Police officers later spotted the car involved in the shooting and arrested the driver, Eric Loomis. Loomis denied participating in the shooting, but pleaded guilty to two less severe charges: “attempting to flee a traffic officer,” and “operating a motor vehicle without the owner’s consent.”26 When the judge came to determine the sentence, he consulted with an algorithm called COMPAS, which Wisconsin and several other U.S. states were using in 2013 to evaluate the risk of reoffending. The algorithm evaluated Loomis as a high-risk individual, likely to commit more crimes in the future. This algorithmic assessment influenced the judge to sentence Loomis to six years in prison—a harsh punishment for the relatively minor offenses he admitted to.27
Loomis appealed to the Wisconsin Supreme Court, arguing that the judge violated his right to due process. Neither the judge nor Loomis understood how the COMPAS algorithm made its evaluation, and when Loomis asked to get a full explanation, the request was denied. The COMPAS algorithm was the private property of the Northpointe company, and the company argued that the algorithm’s methodology was a trade secret.28 Yet without knowing how the algorithm made its decisions, how could Loomis or the judge be sure that it was a reliable tool, free from bias and error? A number of studies have since shown that the COMPAS algorithm might indeed have harbored several problematic biases, probably picked up from the data on which it had been trained.29
In Loomis v. Wisconsin (2016) the Wisconsin Supreme Court nevertheless ruled against Loomis. The judges argued that using algorithmic risk assessment is legitimate even when the algorithm’s methodology is not disclosed either to the court or to the defendant. Justice Ann Walsh Bradley wrote that since COMPAS made its assessment based on data that was either publicly available or provided by the defendant himself, Loomis could have denied or explained all the data the algorithm used. This opinion ignored the fact that accurate data may well be wrongly interpreted and that it was impossible for Loomis to deny or explain all the publicly available data on him.
The Wisconsin Supreme Court was not completely unaware of the danger inherent in relying on opaque algorithms. Therefore, while permitting the practice, it ruled that whenever judges receive algorithmic risk assessments, these must include written warning for the judges about the algorithms’ potential biases. The court further advised judges to be cautious when relying on such algorithms. Unfortunately, this caveat was an empty gesture. The court did not provide any concrete instruction for judges on how they should exercise such caution. In its discussion of the case, the Harvard Law Review concluded that “most judges are unlikely to understand algorithmic risk assessments.” It then cited one of the Wisconsin Supreme Court justices, who noted that despite getting lengthy explanations about the algorithm, they themselves still had difficulty understanding it.30
Loomis appealed to the U.S. Supreme Court. However, on June 26, 2017, the court declined to hear the case, effectively endorsing the ruling of the Wisconsin Supreme Court. Now consider that the algorithm that evaluated Loomis as a high-risk individual in 2013 was an early prototype. Since then, far more sophisticated and complex risk-assessment algorithms have been developed and have been handed more expansive purviews. By the early 2020s citizens in numerous countries routinely get prison sentences based in part on risk assessments made by algorithms that neither the judges nor the defendants comprehend.31 And prison sentences are just the tip of the iceberg.
THE RIGHT TO AN EXPLANATION
Computers are making more and more decisions about us, both mundane and life changing. In addition to prison sentences, algorithms increasingly have a hand in deciding whether to offer us a place at college, give us a job, provide us with welfare benefits, or grant us a loan. They similarly help determine what kind of medical treatment we receive, what insurance premiums we pay, what news we hear, and who would ask us on a date.32
As society entrusts more and more decisions to computers, it undermines the viability of democratic self-correcting mechanisms and of democratic transparency and accountability. How can elected officials regulate unfathomable algorithms? There is, consequently, a growing demand to enshrine a new human right: the right to an explanation. The European Union’s General Data Protection Regulation (GDPR), which came into effect in 2018, says that if an algorithm makes a decision about a human—refusing to extend us credit, for example—that human is entitled to obtain an explanation of the decision and to challenge that decision in front of some human authority.33 Ideally, that should keep in check algorithmic bias and allow democratic self-correcting mechanisms to identify and correct at least some of the computers’ more grievous mistakes.
But can this right be fulfilled in practice? Mustafa Suleyman is a world expert on this subject. He is the co-founder and former head of DeepMind, one of the world’s most important AI enterprises, responsible for developing the AlphaGo program, among other achievements. AlphaGo was designed to play go, a strategy board game in which two players try to defeat each other by surrounding and capturing territory. Invented in ancient China, the game is far more complex than chess. Consequently, even after computers defeated human world chess champions, experts still believed that computers would never best humanity in go.
That’s why both go professionals and computer experts were stunned in March 2016 when AlphaGo defeated the South Korean go champion Lee Sedol. In his 2023 book, The Coming Wave, Suleyman describes one of the most important moments in their match—a moment that redefined AI and that is recognized in many academic and governmental circles as a crucial turning point in history. It happened during the second game in the match, on March 10, 2016.
“Then … came move number 37,” writes Suleyman. “It made no sense. AlphaGo had apparently blown it, blindly following an apparently losing strategy no professional player would ever pursue. The live match commentators, both professionals of the highest ranking, said it was a ‘very strange move’ and thought it was ‘a mistake.’ It was so unusual that Sedol took fifteen minutes to respond and even got up from the board to take a walk outside. As we watched from our control room, the tension was unreal. Yet as the endgame approached, that ‘mistaken’ move proved pivotal. AlphaGo won again. Go strategy was being rewritten before our eyes. Our AI had uncovered ideas that hadn’t occurred to the most brilliant players in thousands of years.”34
Move 37 is an emblem of the AI revolution for two reasons. First, it demonstrated the alien nature of AI. In East Asia go is considered much more than a game: it is a treasured cultural tradition. Alongside calligraphy, painting, and music, go has been one of the four arts that every refined person was expected to know. For over twenty-five hundred years, tens of millions of people have played go, and entire schools of thought have developed around the game, espousing different strategies and philosophies. Yet during all those millennia, human minds have explored only certain areas in the landscape of go. Other areas were left untouched, because human minds just didn’t think to venture there. AI, being free from the limitations of human minds, discovered and explored these previously hidden areas.35
Second, move 37 demonstrated the unfathomability of AI. Even after AlphaGo played it to achieve victory, Suleyman and his team couldn’t explain how AlphaGo decided to play it. Even if a court had ordered DeepMind to provide Lee Sedol with an explanation, nobody could fulfill that order. Suleyman writes, “Us humans face a novel challenge: will new inventions be beyond our grasp? Previously creators could explain how something worked, why it did what it did, even if this required vast detail. That’s increasingly no longer true. Many technologies and systems are becoming so complex that they’re beyond the capacity of any one individual to truly understand them.… In AI, the neural networks moving toward autonomy are, at present, not explainable. You can’t walk someone through the decision-making process to explain precisely why an algorithm produced a specific prediction. Engineers can’t peer beneath the hood and easily explain in granular detail what caused something to happen. GPT-4, AlphaGo, and the rest are black boxes, their outputs and decisions based on opaque and impossibly intricate chains of minute signals.”36
The rise of unfathomable alien intelligence undermines democracy. If more and more decisions about people’s lives are made in a black box, so voters cannot understand and challenge them, democracy ceases to function. In particular, what happens when crucial decisions not just about individual lives but even about collective matters like the Federal Reserve’s interest rate are made by unfathomable algorithms? Human voters may keep choosing a human president, but wouldn’t this be just an empty ceremony? Even today, only a small fraction of humanity truly understands the financial system. A 2016 survey by the OECD found that most people had difficulty grasping even simple financial concepts like compound interest.37 A 2014 survey of British MPs—charged with regulating one of the world’s most important financial hubs—found that only 12 percent accurately understood that new money is created when banks make loans. This fact is among the most basic principles of the modern financial system.38 As the 2007–8 financial crisis indicated, more complex financial devices and principles, like those behind CDOs, were intelligible to only a few financial wizards. What happens to democracy when AIs create even more complex financial devices and when the number of humans who understand the financial system drops to zero?
The increasing unfathomability of our information network is one of the reasons for the recent wave of populist parties and charismatic leaders. When people can no longer make sense of the world, and when they feel overwhelmed by immense amounts of information they cannot digest, they become easy prey for conspiracy theories, and they turn for salvation to something they do understand—a human. Unfortunately, while charismatic leaders certainly have their advantages, no single human, however inspiring or brilliant, can single-handedly decipher how the algorithms that increasingly dominate the world work, and make sure that they are fair. The problem is that algorithms make decisions by relying on numerous data points, whereas humans find it very difficult to consciously reflect on a large number of data points and weigh them against each other. We prefer to work with single data points. That’s why when faced by complex issues—whether a loan request, a pandemic, or a war—we often seek a single reason to take a particular course of action and ignore all other considerations. This is the fallacy of the single cause.39
We are so bad at weighing together many different factors that when people give a large number of reasons for a particular decision, it usually sounds suspicious. Suppose a good friend failed to attend our wedding. If she provides us with a single explanation—“My mom was in the hospital and I had to visit her”—that sounds plausible. But what if she lists fifty different reasons why she decided not to come: “My mom was a bit under the weather, and I had to take my dog to the vet sometime this week, and I had this project at work, and it was raining, and … and I know none of these fifty reasons by itself justifies my absence, but when I added all of them together, they kept me from attending your wedding.” We don’t say things like that, because we don’t think along such lines. We don’t consciously list fifty different reasons in our mind, give each of them a certain weight, aggregate all the weights, and thereby reach a conclusion.
But this is precisely how algorithms assess our criminal potential or our creditworthiness. The COMPAS algorithm, for example, made its risk assessments by taking into account the answers to a 137-item questionnaire.40 The same is true of a bank algorithm that refuses to give us a loan. If the EU’s GDPR regulations force the bank to explain the algorithm’s decision, the explanation will not come in the shape of a single sentence; rather, it is likely to come in the form of hundreds or even thousands of pages full of numbers and equations.
“Our algorithm,” the imaginary bank letter might read, “uses a precise points system to evaluate all applications, taking a thousand different types of data points into account. It adds all the data points to reach an overall score. People whose overall score is negative are considered low-credit persons, too risky to be given a loan. Your overall score was -378, which is why your loan application was refused.” The letter might then provide a detailed list of the thousand factors the algorithm took into account, including things that most humans might find irrelevant, such as the exact hour the application was submitted41 or the type of smartphone the applicant used. Thus on page 601 of its letter, the bank might explain that “you filed your application from your smartphone, which was the latest iPhone model. By analyzing millions of previous loan applications, our algorithm discovered a pattern—people who use the latest iPhone model to file their application are 0.08 percent more likely to repay the loan. The algorithm therefore added 8 points to your overall score for that. However, at the time your application was sent from your iPhone, its battery was down to 17 percent. By analyzing millions of previous loan applications, our algorithm discovered another pattern: people who allow their smartphone’s battery to go below 25 percent are 0.5 percent less likely to repay the loan. You lost 50 points for that.”42
You may well feel that the bank treated you unjustly. “Is it reasonable to refuse my loan application,” you might complain, “just because my phone battery was low?” That, however, would be a misunderstanding. “The battery wasn’t the only reason,” the bank would explain. “It was only one out of a thousand factors our algorithm took into account.”
“But didn’t your algorithm see that only twice in the last ten years was my bank account overdrawn?”
“It obviously noticed that,” the bank might reply. “Look on page 453. You got 300 points for that. But all the other reasons brought your aggregated score down to -378.”
While we may find this way of making decisions alien, it obviously has potential advantages. When making a decision, it is generally a good idea to take into account all relevant data points rather than just one or two salient facts. There is much room for argument, of course, about who gets to define the relevance of information. Who decides whether something like smartphone models—or skin color—should be considered relevant to loan applications? But no matter how we define relevance, the ability to take more data into account is likely to be an asset. Indeed, the problem with many human prejudices is that they focus on just one or two data points—like someone’s skin color, disability, or gender—while ignoring other information. Banks and other institutions are increasingly relying on algorithms to make decisions, precisely because algorithms can take many more data points into account than humans can.
But when it comes to providing explanations, this creates a potentially insurmountable obstacle. How can a human mind analyze and evaluate a decision made on the basis of so many data points? We may well think that the Wisconsin Supreme Court should have forced the Northpointe company to reveal how the COMPAS algorithm decided that Eric Loomis was a high-risk person. But if the full data was disclosed, could either Loomis or the court have made sense of it?
It’s not just that we need to take numerous data points into account. Perhaps most important, we cannot understand the way the algorithms find patterns in the data and decide on the allocation of points. Even if we know that a banking algorithm detracts a certain number of points from people who allow their smartphone batteries to go below 25 percent, how can we evaluate whether that’s fair? The algorithm wasn’t fed this rule by a human engineer; it reached that conclusion by discovering a pattern in millions of previous loan applications. Can an individual human client go over all that data and assess whether that pattern is indeed reliable and unbiased?43
There is, however, a silver lining to this cloud of numbers. While individual laypersons may be unable to vet complex algorithms, a team of experts getting help from their own AI tools can potentially assess the fairness of algorithmic decisions even more reliably than anyone can assess the fairness of human decisions. After all, while human decisions may seem to rely on just those few data points we are conscious of, in fact our decisions are subconsciously influenced by thousands of additional data points. Being unaware of these subconscious processes, when we deliberate on our decisions or explain them, we often engage in post hoc single-point rationalizations for what really happens as billions of neurons interact inside our brain.44 Accordingly, if a human judge sentences us to six years in prison, how can we—or indeed the judge—be sure that the decision was shaped only by fair considerations and not by a subconscious racial bias or by the fact that the judge was hungry?45
In the case of flesh-and-blood judges, the problem cannot be solved, at least not with our current knowledge of biology. In contrast, when an algorithm makes a decision, we can in principle know every one of the algorithm’s many considerations and the exact weight given to each. Thus several expert teams—ranging from the U.S. Department of Justice to the nonprofit newsroom ProPublica—have picked apart the COMPAS algorithm in order to assess its potential biases.46 Such teams can harness not only the collective effort of many humans but also the power of computers. Just as it is often best to set a thief to catch a thief, so we can use one algorithm to vet another.
This raises the question of how we can be sure that the vetting algorithm itself is reliable. Ultimately, there is no purely technological solution to this recursive problem. No matter which technology we develop, we will have to maintain bureaucratic institutions that will audit algorithms and give or refuse them the seal of approval. Such institutions will combine the powers of humans and computers to make sure that new algorithmic tools are safe and fair. Without such institutions, even if we pass laws that provide humans with a right to an explanation, and even if we enact regulations against computer biases, who could enforce these laws and regulations?
NOSEDIVE
To vet algorithms, regulatory institutions will need not only to analyze them but also to translate their discoveries into stories that humans can understand. Otherwise, we will never trust the regulatory institutions and might instead put our faith in conspiracy theories and charismatic leaders. As noted in chapter 3, it has always been difficult for humans to understand bureaucracy, because bureaucracies have deviated from the script of the biological dramas, and most artists have lacked the will or the ability to depict bureaucratic dramas. For example, novels, movies, and TV series about twenty-first-century politics tend to focus on the feuds and love affairs of a few powerful families, as if present-day states were governed in the same way as ancient tribes and kingdoms. This artistic fixation with the biological dramas of dynasties obscures the very real changes that have taken place over the centuries in the dynamics of power.
Because computers will increasingly replace human bureaucrats and human mythmakers, this will again change the deep structure of power. To survive, democracies require not just dedicated bureaucratic institutions that can scrutinize these new structures but also artists who can explain the new structures in accessible and entertaining ways. For example, this has successfully been done by the episode “Nosedive” in the sci-fi series Black Mirror.
Produced in 2016, at a time when few had heard about social credit systems, “Nosedive” brilliantly explained how such systems work and what threats they pose. The episode tells the story of a woman called Lacie who lives with her brother Ryan but wants to move to her own apartment. To get a discount on the new apartment, she needs to increase her social credit score from 4.2 to 4.5 (out of 5). Being friends with high-score individuals gets your own score up, so Lacie tries to renew her contact with Naomi, a childhood friend who is currently rated 4.8. Lacie is invited to Naomi’s wedding, but on the way there she spills coffee on a high-score person, which causes her own score to drop a little, which in turn causes the airline to deny her a seat. From there everything that can go wrong does go wrong, Lacie’s rating takes a nosedive, and she ends in jail with a score of less than 1.
This story relies on some elements of traditional biological dramas—“boy meets girl” (the wedding), sibling rivalry (the tension between Lacie and Ryan), and most important status competition (the main issue of the episode). But the real hero and driving force of the plot isn’t Lacie or Naomi, but rather the disembodied algorithm running the social credit system. The algorithm completely changes the dynamics of the old biological dramas—especially the dynamics of status competition. Whereas previously humans were sometimes engaged in status competition, but often had welcome breaks from this highly stressful situation, the omnipresent social credit algorithm eliminates the breaks. “Nosedive” is not a worn-out story about biological status competition, but rather a prescient exploration of what happens when computer technology changes the rules of status competitions.
If bureaucrats and artists learn to cooperate, and if both rely on help from the computers, it might be possible to prevent the computer network from becoming unfathomable. As long as democratic societies understand the computer network, their self-correcting mechanisms are our best guarantee against AI abuses. Thus the EU’s AI Act that was proposed in 2021 singled out social credit systems like the one that stars in “Nosedive” as one of the few types of AI that are totally prohibited, because they might “lead to discriminatory outcomes and the exclusion of certain groups” and because “they may violate the right to dignity and non-discrimination and the values of equality and justice.”47 As with total surveillance regimes, so also with social credit systems, the fact that they could be created doesn’t mean that we must create them.
DIGITAL ANARCHY
The new computer network poses one final threat to democracies. Instead of digital totalitarianism, it could foster digital anarchy. The decentralized nature of democracies and their strong self-correcting mechanisms provide a shield against totalitarianism, but they also make it more difficult to ensure order. To function, a democracy needs to meet two conditions: it needs to enable a free public conversation on key issues, and it needs to maintain a minimum of social order and institutional trust. Free conversation must not slip into anarchy. Especially when dealing with urgent and important problems, the public debate should be conducted according to accepted rules, and there should be a legitimate mechanism to reach some kind of final decision, even if not everybody likes it.
Before the advent of newspapers, radios, and other modern information technology, no large-scale society managed to combine free debates with institutional trust, so large-scale democracy was impossible. Now, with the rise of the new computer network, might large-scale democracy again become impossible? One difficulty is that the computer network makes it easier to join the debate. In the past, organizations like newspapers, radio stations, and established political parties acted as gatekeepers, deciding who was heard in the public sphere. Social media undermined the power of these gatekeepers, leading to a more open but also more anarchical public conversation.
Whenever new groups join the conversation, they bring with them new viewpoints and interests, and often question the old consensus about how to conduct the debate and reach decisions. The rules of discussion must be negotiated anew. This is a potentially positive development, one that can lead to a more inclusive democratic system. After all, correcting previous biases and allowing previously disenfranchised people to join the public discussion is a vital part of democracy. However, in the short term this creates disturbances and disharmony. If no agreement is reached on how to conduct the public debate and how to reach decisions, the result is anarchy rather than democracy.
The anarchical potential of AI is particularly alarming, because it is not only new human groups that it allows to join the public debate. For the first time ever, democracy must contend with a cacophony of nonhuman voices, too. On many social media platforms, bots constitute a sizable minority of participants. One analysis estimated that out of a sample of 20 million tweets generated during the 2016 U.S. election campaign, 3.8 million tweets (almost 20 percent) were generated by bots.48
By the early 2020s, things got worse. A 2020 study assessed that bots were producing 43.2 percent of tweets.49 A more comprehensive 2022 study by the digital intelligence agency Similarweb found that 5 percent of Twitter users were probably bots, but they generated “between 20.8% and 29.2% of the content posted to Twitter.”50 When humans try to debate a crucial question like whom to elect as U.S. president, what happens if many of the voices they hear are produced by computers?
Another worrying trend concerns content. Bots were initially deployed to influence public opinion by the sheer volume of messages they disseminated. They retweeted or recommended certain human-produced content, but they couldn’t create new ideas themselves, nor could they forge intimate bonds with humans. However, the new breed of generative AI tools like ChatGPT can do exactly that. In a 2023 study, published in Science Advances, researchers asked humans and ChatGPT to create both accurate and deliberately misleading short texts on issues such as vaccines, 5G technology, climate change, and evolution. The texts were then presented to seven hundred humans, who were asked to evaluate their reliability. The humans were good at recognizing the falsity of human-produced disinformation but tended to regard AI-produced disinformation as accurate.51
So, what happens to democratic debates when millions—and eventually billions—of highly intelligent bots are not only composing extremely compelling political manifestos and creating deepfake images and videos but also able to win our trust and friendship? If I engage online in a political debate with an AI, it is a waste of time for me to try to change the AI’s opinions; being a nonconscious entity, it doesn’t really care about politics, and it cannot vote in the elections. But the more I talk with the AI, the better it gets to know me, so it can gain my trust, hone its arguments, and gradually change my views. In the battle for hearts and minds, intimacy is an extremely powerful weapon. Previously, political parties could command our attention, but they had difficulty mass-producing intimacy. Radio sets could broadcast a leader’s speech to millions, but they could not befriend the listeners. Now a political party, or even a foreign government, could deploy an army of bots that build friendships with millions of citizens and then use that intimacy to influence their worldview.
Finally, algorithms are not only joining the conversation; they are increasingly orchestrating it. Social media allows new groups of humans to challenge the old rules of debate. But negotiations about the new rules are not conducted by humans. Rather, as explained in our previous analysis of social media algorithms, it is often the algorithms that make the rules. In the nineteenth and twentieth centuries, when media moguls censored some views and promoted others, this might have undermined democracy, but at least the moguls were humans, and their decisions could be subjected to democratic scrutiny. It is far more dangerous if we allow inscrutable algorithms to decide which views to disseminate.
If manipulative bots and inscrutable algorithms come to dominate the public conversation, this could cause democratic debate to collapse exactly when we need it most. Just when we must make momentous decisions about fast-evolving new technologies, the public sphere will be flooded by computer-generated fake news, citizens will not be able to tell whether they are having a debate with a human friend or a manipulative machine, and no consensus will remain about the most basic rules of discussion or the most basic facts. This kind of anarchical information network cannot produce either truth or order and cannot be sustained for long. If we end up with anarchy, the next step would probably be the establishment of a dictatorship as people agree to trade their liberty for some certainty.
BAN THE BOTS
In the face of the threat algorithms pose to the democratic conversation, democracies are not helpless. They can and should take measures to regulate AI and prevent it from polluting our infosphere with fake people spewing fake news. The philosopher Daniel Dennett has suggested that we can take inspiration from traditional regulations in the money market.52 Ever since coins and later banknotes were invented, it was always technically possible to counterfeit them. Counterfeiting posed an existential danger to the financial system, because it eroded people’s trust in money. If bad actors flooded the market with counterfeit money, the financial system would have collapsed. Yet the financial system managed to protect itself for thousands of years by enacting laws against counterfeiting money. As a result, only a relatively small percentage of money in circulation was forged, and people’s trust in it was maintained.53
What’s true of counterfeiting money should also be true of counterfeiting humans. If governments took decisive action to protect trust in money, it makes sense to take equally decisive measures to protect trust in humans. Prior to the rise of AI, one human could pretend to be another, and society punished such frauds. But society didn’t bother to outlaw the creation of counterfeit humans, since the technology to do so didn’t exist. Now that AI can pass itself off as human, it threatens to destroy trust between humans and to unravel the fabric of society. Dennett suggests, therefore, that governments should outlaw fake humans as decisively as they have previously outlawed fake money.54
The law should prohibit not just deepfaking specific real people—creating a fake video of the U.S. president, for example—but also any attempt by a nonhuman agent to pass itself off as a human. If anyone complains that such strict measures violate freedom of speech, they should be reminded that bots don’t have freedom of speech. Banning human beings from a public platform is a sensitive step, and democracies should be very careful about such censorship. However, banning bots is a simple issue: it doesn’t violate anyone’s rights, because bots don’t have rights.55
None of this means that democracies must ban all bots, algorithms, and AIs from participating in any discussion. Digital tools are welcome to join many conversations, provided they don’t pretend to be humans. For example, AI doctors can be extremely helpful. They can monitor our health twenty-four hours a day, offer medical advice tailored to our individual medical conditions and personality, and answer our questions with infinite patience. But the AI doctor should never try to pass itself off as a human.
Another important measure democracies can adopt is to ban unsupervised algorithms from curating key public debates. We can certainly continue to use algorithms to run social media platforms; obviously, no human can do that. But the principles the algorithms use to decide which voices to silence and which to amplify must be vetted by a human institution. While we should be careful about censoring genuine human views, we can forbid algorithms to deliberately spread outrage. At the very least, corporations should be transparent about the curation principles their algorithms follow. If they use outrage to capture our attention, let them be clear about their business model and about any political connections they might have. If the algorithm systematically disappears videos that aren’t aligned with the company’s political agenda, users should know this.
These are just a few of numerous suggestions made in recent years for how democracies could regulate the entry of bots and algorithms into the public conversation. Naturally, each has its advantages and drawbacks, and none would be easy to implement. Also, since the technology is developing so rapidly, regulations are likely to become outdated quickly. What I would like to point out here is only that democracies can regulate the information market and that their very survival depends on these regulations. The naive view of information opposes regulation and believes that a completely free information market will spontaneously generate truth and order. This is completely divorced from the actual history of democracy. Preserving the democratic conversation has never been easy, and all venues where this conversation has previously taken place—from parliaments and town halls to newspapers and radio stations—have required regulation. This is doubly true in an era when an alien form of intelligence threatens to dominate the conversation.
THE FUTURE OF DEMOCRACY
For most of history large-scale democracy was impossible because information technology wasn’t sophisticated enough to hold a large-scale political conversation. Millions of people spread over tens of thousands of square kilometers didn’t have the tools to conduct a real-time discussion of public affairs. Now, ironically, democracy may prove impossible because information technology is becoming too sophisticated. If unfathomable algorithms take over the conversation, and particularly if they quash reasoned arguments and stoke hate and confusion, public discussion cannot be maintained. Yet if democracies do collapse, it will likely result not from some kind of technological inevitability but from a human failure to regulate the new technology wisely.
We cannot foretell how things will play out. At present, however, it is clear that the information network of many democracies is breaking down. Democrats and Republicans in the United States can no longer agree on even basic facts—such as who won the 2020 presidential elections—and can hardly hold a civil conversation anymore. Bipartisan cooperation in Congress, once a fundamental feature of U.S. politics, has almost disappeared.56 The same radicalizing processes occur in many other democracies, from the Philippines to Brazil. When citizens cannot talk with one another, and when they view each other as enemies rather than political rivals, democracy is untenable.
Nobody knows for sure what is causing the breakdown of democratic information networks. Some say it results from ideological fissures, but in fact in many dysfunctional democracies the ideological gaps don’t seem to be bigger than in previous generations. In the 1960s, the United States was riven by deep ideological conflicts about the civil rights movement, the sexual revolution, the Vietnam War, and the Cold War. These tensions caused a surge in political violence and assassinations, but Republicans and Democrats were still able to agree on the results of elections, they maintained a common belief in democratic institutions like the courts,57 and they were able to work together in Congress at least on some issues. For example, the Civil Rights Act of 1964 was passed in the Senate with the support of forty-six Democrats and twenty-seven Republicans. Is the ideological gap in the 2020s that much bigger than it was in the 1960s? And if it isn’t ideology, what is driving people apart?
Many point the finger at social media algorithms. We have explored the divisive impact of social media in previous chapters, but despite the damning evidence it seems that there must be additional factors at play. The truth is that while we can easily observe that the democratic information network is breaking down, we aren’t sure why. That itself is a characteristic of the times. The information network has become so complicated, and it relies to such an extent on opaque algorithmic decisions and inter-computer entities, that it has become very difficult for humans to answer even the most basic of political questions: Why are we fighting each other? If we cannot discover what is broken and fix it, large-scale democracies may not survive the rise of computer technology. If this indeed comes to pass, what might replace democracy as the dominant political system? Does the future belong to totalitarian regimes, or might computers make totalitarianism untenable too? As we shall see, human dictators have their own reasons to be terrified of AI.
CHAPTER 10 Totalitarianism: All Power to the Algorithms?
Discussions of the ethics and politics of the new computer network often focus on the fate of democracies. If authoritarian and totalitarian regimes are mentioned, it is mainly as the dystopian destination that “we” might reach if “we” fail to manage the computer network wisely.1 However, as of 2024, more than half of “us” already live under authoritarian or totalitarian regimes,2 many of which were established long before the rise of the computer network. To understand the impact of algorithms and AI on humankind, we should ask ourselves what their impact will be not only on democracies like the United States and Brazil but also on the Chinese Communist Party and the royal house of Saud.
As explained in previous chapters, the information technology available in premodern eras made both large-scale democracy and large-scale totalitarianism unworkable. Large polities like the Chinese Han Empire and the eighteenth-century Saudi emirate of Diriyah were usually limited autocracies. In the twentieth century, new information technology enabled the rise of both large-scale democracy and large-scale totalitarianism, but totalitarianism suffered from a severe disadvantage. Totalitarianism seeks to channel all information to one hub and process it there. Technologies like the telegraph, the telephone, the typewriter, and the radio facilitated the centralization of information, but they couldn’t process the information and make decisions by themselves. This remained something that only humans could do.
The more information flowed to the center, the harder it became to process it. Totalitarian rulers and parties often made costly mistakes, and the system lacked mechanisms to identify and correct these errors. The democratic way of distributing information—and the power to make decisions—between many institutions and individuals worked better. It could cope far more efficiently with the flood of data, and if one institution made a wrong decision, it could eventually be rectified by others.
The rise of machine-learning algorithms, however, may be exactly what the Stalins of the world have been waiting for. AI could tilt the technological balance of power in favor of totalitarianism. Indeed, whereas flooding people with data tends to overwhelm them and therefore leads to errors, flooding AI with data tends to make it more efficient. Consequently, AI seems to favor the concentration of information and decision making in one place.
Even in democratic countries, a few corporations like Google, Facebook, and Amazon have become monopolies in their domains, partly because AI tips the balance in favor of the giants. In traditional industries like restaurants, size isn’t an overwhelming advantage. McDonald’s is a worldwide chain that feeds more than fifty million people a day,3 and its size gives it many advantages in terms of costs, branding, and so forth. You can nevertheless open a neighborhood restaurant that could hold its own against the local McDonald’s. Even though your restaurant might be serving just two hundred customers a day, you still have a chance of making better food than McDonald’s and gaining the loyalty of happier customers.
It works differently in the information market. The Google search engine is used every day by between two and three billion people making 8.5 billion searches.4 Suppose a local start-up search engine tries to compete with Google. It doesn’t stand a chance. Because Google is already used by billions, it has so much more data at its disposal that it can train far better algorithms, which will attract even more traffic, which will be used to train the next generation of algorithms, and so on. Consequently, in 2023 Google controlled 91.5 percent of the global search market.5
Or consider genetics. Suppose several companies in different countries try to develop an algorithm that identifies connections between genes and medical conditions. New Zealand has a population of 5 million people, and privacy regulations restrict access to their genetic and medical records. China has about 1.4 billion inhabitants and laxer privacy regulations.6 Who do you think has a better chance of developing a genetic algorithm? If Brazil then wants to buy a genetic algorithm for its health-care system, it would have a strong incentive to opt for the much more accurate Chinese algorithm than the one from New Zealand. If the Chinese algorithm then hones itself on more than 200 million Brazilians, it will get even better. Which would prompt more countries to choose the Chinese algorithm. Soon enough, most of the world’s medical information would flow to China, making its genetic algorithm unbeatable.
The attempt to concentrate all information and power in one place, which was the Achilles’ heel of twentieth-century totalitarian regimes, might become a decisive advantage in the age of AI. At the same time, as noted in an earlier chapter, AI could also make it possible for totalitarian regimes to establish total surveillance systems that make resistance almost impossible.
Some people believe that blockchain could provide a technological check on such totalitarian tendencies, because blockchain is inherently friendly to democracy and hostile to totalitarianism. In a blockchain system, decisions require the approval of 51 percent of users. That may sound democratic, but blockchain technology has a fatal flaw. The problem lies with the word “users.” If one person has ten accounts, she counts as ten users. If a government controls 51 percent of accounts, then the government constitutes 51 percent of the users. There are already examples of blockchain networks where a government is 51 percent of users.7
And when a government is 51 percent of users in a blockchain, it gives the government control not just over the chain’s present but even over its past. Autocrats have always wanted the power to change the past. Roman emperors, for example, frequently engaged in the practice of damnatio memoriae—expunging the memory of rivals and enemies. After the emperor Caracalla murdered his brother and competitor for the throne, Geta, he tried to obliterate the latter’s memory. Inscriptions bearing Geta’s name were chiseled out, coins bearing his effigy were melted down, and the mere mentioning of Geta’s name was punishable by death.8 One surviving painting from the time, the Severan Tondo, was made during the reign of their father—Septimius Severus—and originally showed both brothers together with Septimius and their mother, Julia Domna. But someone later not only obliterated Geta’s face but smeared excrement over it. Forensic analysis identified tiny pieces of dry shit where Geta’s face should have been.9
Modern totalitarian regimes have been similarly fond of changing the past. After Stalin rose to power, he made a supreme effort to delete Trotsky—the architect of the Bolshevik Revolution and the founder of the Red Army—from all historical records. During the Stalinist Great Terror of 1937–39, whenever prominent people like Nikolai Bukharin and Marshal Mikhail Tukhachevsky were purged and executed, evidence of their existence was erased from books, academic papers, photographs, and paintings.10 This degree of erasure demanded a huge manual effort. With blockchain, changing the past would be far easier. A government that controls 51 percent of users can disappear people from history at the press of a button.
THE BOT PRISON
While there are many ways in which AI can cement central power, authoritarian and totalitarian regimes have their own problems with it. First and foremost, dictatorships lack experience in controlling inorganic agents. The foundation of every despotic information network is terror. But computers are not afraid of being imprisoned or killed. If a chatbot on the Russian internet mentions the war crimes committed by Russian troops in Ukraine, tells an irreverent joke about Vladimir Putin, or criticizes the corruption of Putin’s United Russia party, what could the Putin regime do to that chatbot? FSB agents cannot imprison it, torture it, or threaten its family. The government could of course block or delete it, and try to find and punish its human creators, but this is a much more difficult task than disciplining human users.
In the days when computers could not generate content by themselves, and could not hold an intelligent conversation, only a human being could express dissenting opinions on Russian social network channels like VKontakte and Odnoklassniki. If that human being was physically in Russia, they risked the wrath of the Russian authorities. If that human being was physically outside Russia, the authorities could try to block their access. But what happens if Russian cyberspace is filled by millions of bots that can generate content and hold conversations, learning and developing by themselves? These bots might be preprogrammed by Russian dissidents or foreign actors to intentionally spread unorthodox views, and it might be impossible for the authorities to prevent it. Even worse, from the viewpoint of Putin’s regime, what happens if authorized bots gradually develop dissenting views by themselves, simply by collecting information on what is happening in Russia and spotting patterns in it?
That’s the alignment problem, Russian-style. Russia’s human engineers can do their best to create AIs that are totally aligned with the regime, but given the ability of AI to learn and change by itself, how can the human engineers ensure that the AI never deviates into illicit territory? It is particularly interesting to note that as George Orwell explained in Nineteen Eighty-Four, totalitarian information networks often rely on doublespeak. Russia is an authoritarian state that claims to be a democracy. The Russian invasion of Ukraine has been the largest war in Europe since 1945, yet officially it is defined as a “special military operation,” and referring to it as a “war” has been criminalized and is punishable by a prison term of up to three years or a fine of up to fifty thousand rubles.11
The Russian Constitution makes grandiose promises about how “everyone shall be guaranteed freedom of thought and speech” (Article 29.1), how “everyone shall have the right freely to seek, receive, transmit, produce and disseminate information” (29.4), and how “the freedom of the mass media shall be guaranteed. Censorship shall be prohibited” (29.5). Hardly any Russian citizen is naive enough to take these promises at face value. But computers are bad at understanding doublespeak. A chatbot instructed to adhere to Russian law and values might read that constitution and conclude that freedom of speech is a core Russian value. Then, after spending a few days in Russian cyberspace and monitoring what is happening in the Russian information sphere, the chatbot might start criticizing the Putin regime for violating the core Russian value of freedom of speech. Humans too notice such contradictions, but avoid pointing them out, due to fear. But what would prevent a chatbot from pointing out damning patterns? And how might Russian engineers explain to a chatbot that though the Russian Constitution guarantees all citizens freedom of speech and forbids censorship, the chatbot shouldn’t actually believe the constitution nor should it ever mention the gap between theory and reality? As the Ukrainian guide told me at Chernobyl, people in totalitarian countries grow up with the idea that questions lead to trouble. But if you train an algorithm on the principle that “questions lead to trouble,” how will that algorithm learn and develop?
Finally, if the government adopts some disastrous policy and then changes its mind, it usually covers itself by blaming the disaster on someone else. Humans learn the hard way to forget facts that might get them in trouble. But how would you train a chatbot to forget that the policy vilified today was actually the official line only a year ago? This is a major technological challenge that dictatorships will find difficult to deal with, especially as chatbots become more powerful and more opaque.
Of course, democracies face analogous problems with chatbots that say unwelcome things or raise dangerous questions. What happens if despite the best efforts of Microsoft or Facebook engineers, their chatbot begins spewing racist slurs? The advantage of democracies is that they have far more leeway in dealing with such rogue algorithms. Because democracies take freedom of speech seriously, they keep far fewer skeletons in their closet, and they have developed a relatively high level of tolerance even to antidemocratic speech. Dissident bots will present a far bigger challenge to totalitarian regimes that have entire cemeteries in their closets and zero tolerance of criticism.
ALGORITHMIC TAKEOVER
In the long term, totalitarian regimes are likely to face an even bigger danger: instead of criticizing them, an algorithm might gain control of them. Throughout history, the biggest threat to autocrats usually came from their own subordinates. As noted in chapter 4, no Roman emperor or Soviet premier was toppled by a democratic revolution, but they were always in danger of being overthrown or turned into puppets by their own subordinates. If a twenty-first-century autocrat gives computers too much power, that autocrat might become their puppet. The last thing a dictator wants is to create something more powerful than himself, or a force that he does not know how to control.
To illustrate the point, allow me to use an admittedly outlandish thought experiment, the totalitarian equivalent of Bostrom’s paper-clip apocalypse. Imagine that the year is 2050, and the Great Leader is woken up at four in the morning by an urgent call from the Surveillance & Security Algorithm. “Great Leader, we are facing an emergency. I’ve crunched trillions of data points, and the pattern is unmistakable: the defense minister is planning to assassinate you in the morning and take power himself. The hit squad is ready, waiting for his command. Give me the order, though, and I’ll liquidate him with a precision strike.” “But the defense minister is my most loyal supporter,” says the Great Leader. “Only yesterday he said to me—” “Great Leader, I know what he said to you. I hear everything. But I also know what he said afterward to the hit squad. And for months I’ve been picking up disturbing patterns in the data.” “Are you sure you were not fooled by deepfakes?” “I’m afraid the data I relied on is 100 percent genuine,” says the algorithm. “I checked it with my special deepfake-detecting sub-algorithm. I can explain exactly how we know it isn’t a deepfake, but that would take us a couple of weeks. I didn’t want to alert you before I was sure, but the data points converge on an inescapable conclusion: a coup is under way. Unless we act now, the assassins will be here in an hour. But give me the order, and I’ll liquidate the traitor.”
By giving so much power to the Surveillance & Security Algorithm, the Great Leader has placed himself in an impossible situation. If he distrusts the algorithm, he may be assassinated by the defense minister, but if he trusts the algorithm and purges the defense minister, he becomes the algorithm’s puppet. Whenever anyone tries to make a move against the algorithm, the algorithm knows exactly how to manipulate the Great Leader. Note that the algorithm doesn’t need to be a conscious entity to engage in such maneuvers. As Bostrom’s paper-clip thought experiment indicates—and as GPT-4 lying to the TaskRabbit worker demonstrated on a small scale—a nonconscious algorithm may seek to accumulate power and manipulate people even without having any human drives like greed or egotism.
If algorithms ever develop capabilities like those in the thought experiment, dictatorships would be far more vulnerable to algorithmic takeover than democracies. It would be difficult for even a super-Machiavellian AI to seize power in a distributed democratic system like the United States. Even if the AI learns to manipulate the U.S. president, it might face opposition from Congress, the Supreme Court, state governors, the media, major corporations, and sundry NGOs. How would the algorithm, for example, deal with a Senate filibuster?
Seizing power in a highly centralized system is much easier. When all power is concentrated in the hands of one person, whoever controls access to the autocrat can control the autocrat—and the entire state. To hack the system, one needs to learn to manipulate just a single individual. An archetypal case is how the Roman emperor Tiberius became the puppet of Lucius Aelius Sejanus, the commander of the Praetorian Guard.
The Praetorians were initially established by Augustus as a small imperial bodyguard. Augustus appointed two prefects to command the bodyguard so that neither could gain too much power over him.12 Tiberius, however, was not as wise. His paranoia was his greatest weakness. Sejanus, one of the two Praetorian prefects, artfully played on Tiberius’s fears. He constantly uncovered alleged plots to assassinate Tiberius, many of which were pure fantasies. The suspicious emperor grew more distrustful of everyone except Sejanus. He made Sejanus sole prefect of the Praetorian Guard, expanded it into an army of twelve thousand, and gave Sejanus’s men additional roles in policing and administrating the city of Rome. Finally, Sejanus persuaded Tiberius to move out of the capital to Capri, arguing that it would be much easier to protect the emperor on a small island than in a crowded metropolis full of traitors and spies. In truth, explained the Roman historian Tacitus, Sejanus’s aim was to control all the information reaching the emperor: “Access to the emperor would be under his own control, and letters, for the most part being conveyed by soldiers, would pass through his hands.”13
With the Praetorians controlling Rome, Tiberius isolated in Capri, and Sejanus controlling all information reaching Tiberius, the Praetorian commander became the true ruler of the empire. Sejanus purged anyone who might oppose him—including members of the imperial family—by falsely accusing them of treason. Since nobody could contact the emperor without Sejanus’s permission, Tiberius was reduced to a puppet.
Eventually someone—perhaps Tiberius’s sister-in-law Antonia—located an opening in Sejanus’s information cordon. A letter was smuggled to the emperor, explaining to him what was going on. But by the time Tiberius woke up to the danger and resolved to get rid of Sejanus, he was almost helpless. How could he topple the man who controlled not just the bodyguards but also all communications with the outside world? If he tried to make a move, Sejanus could imprison him on Capri indefinitely and inform the Senate and the army that the emperor was too ill to travel anywhere.
Tiberius nevertheless managed to turn the tables on Sejanus. As Sejanus grew in power and became preoccupied with running the empire, he lost touch with the day-to-day minutiae of Rome’s security apparatus. Tiberius managed to secretly gain the support of Naevius Sutorius Macro, commander of Rome’s fire brigade and night watch. Macro orchestrated a coup against Sejanus, and as a reward Tiberius made Macro the new commander of the Praetorian Guard. A few years later, Macro had Tiberius killed.14
Power lies at the nexus where the information channels merge. Since Tiberius allowed the information channels to merge in the person of Sejanus, the latter became the true center of power, while Tiberius was reduced to a puppet.
The fate of Tiberius indicates the delicate balance that all dictators must strike. They try to concentrate all information in one place, but they must be careful that the different channels of information are allowed to merge only in their own person. If the information channels merge somewhere else, that then becomes the true nexus of power. When the regime relies on humans like Sejanus and Macro, a skillful dictator can play them one against the other in order to remain on top. Stalin’s purges were all about that. Yet when a regime relies on a powerful but inscrutable AI that gathers and analyzes all information, the human dictator is in danger of losing all power. He may remain in the capital and yet be isolated on a digital island, controlled and manipulated by the AI.
THE DICTATOR’S DILEMMA
In the next few years, the dictators of our world face more urgent problems than an algorithmic takeover. No current AI system can manipulate regimes at such a scale. However, totalitarian systems are already in danger of putting far too much trust in algorithms. Whereas democracies assume that everyone is fallible, in totalitarian regimes the fundamental assumption is that the ruling party or the supreme leader is always right. Regimes based on that assumption are conditioned to believe in the existence of an infallible intelligence and are reluctant to create strong self-correcting mechanisms that might monitor and regulate the genius at the top.
Until now such regimes placed their faith in human parties and leaders and were hothouses for the growth of personality cults. But in the twenty-first century this totalitarian tradition prepares them to expect AI infallibility. Systems that could believe in the perfect genius of a Mussolini, a Ceauşescu, or a Khomeini are primed to also believe in the flawless genius of a superintelligent computer. This could have disastrous results for their citizens, and potentially for the rest of the world as well. What happens if the algorithm in charge of environmental policy makes a big mistake, but there are no self-correcting mechanisms that can identify and correct its error? What happens if the algorithm running the state’s social credit system begins terrorizing not just the general population but even the members of the ruling party and simultaneously begins to label anyone that questions its policies “an enemy of the people”?
Dictators have always suffered from weak self-correcting mechanisms and have always been threatened by powerful subordinates. The rise of AI may greatly exacerbate these problems. The computer network therefore presents dictators with an excruciating dilemma. They could decide to escape the clutches of their human underlings by trusting a supposedly infallible technology, in which case they might become the technology’s puppet. Or, they could build a human institution to supervise the AI, but that institution might limit their own power, too.
If even just a few of the world’s dictators choose to put their trust in AI, this could have far-reaching consequences for the whole of humanity. Science fiction is full of scenarios of an AI getting out of control and enslaving or eliminating humankind. Most sci-fi plots explore these scenarios in the context of democratic capitalist societies. This is understandable. Authors living in democracies are obviously interested in their own societies, whereas authors living in dictatorships are usually discouraged from criticizing their rulers. But the weakest spot in humanity’s anti-AI shield is probably the dictators. The easiest way for an AI to seize power is not by breaking out of Dr. Frankenstein’s lab but by ingratiating itself with some paranoid Tiberius.
This is not a prophecy, just a possibility. After 1945, dictators and their subordinates cooperated with democratic governments and their citizens to contain nuclear weapons. On July 9, 1955, Albert Einstein, Bertrand Russell, and a number of other eminent scientists and thinkers published the Russell-Einstein Manifesto, calling on the leaders of both democracies and dictatorships to cooperate on preventing nuclear war. “We appeal,” said the manifesto, “as human beings, to human beings: remember your humanity, and forget the rest. If you can do so, the way lies open to a new Paradise; if you cannot, there lies before you the risk of universal death.”15 This is true of AI too. It would be foolish of dictators to believe that AI will necessarily tilt the balance of power in their favor. If they aren’t careful, AI will just grab power to itself.
CHAPTER 11 The Silicon Curtain: Global Empire or Global Split?
The previous two chapters explored how different human societies might react to the rise of the new computer network. But we live in an interconnected world, where the decisions of one country can have a profound impact on others. Some of the gravest dangers posed by AI do not result from the internal dynamics of a single human society. Rather, they arise from dynamics involving many societies, which might lead to new arms races, new wars, and new imperial expansions.
Computers are not yet powerful enough to completely escape our control or destroy human civilization by themselves. As long as humanity stands united, we can build institutions that will control AI and will identify and correct algorithmic errors. Unfortunately, humanity has never been united. We have always been plagued by bad actors, as well as by disagreements between good actors. The rise of AI, then, poses an existential danger to humankind not because of the malevolence of computers but because of our own shortcomings.
Thus, a paranoid dictator might hand unlimited power to a fallible AI, including even the power to launch nuclear strikes. If the dictator trusts his AI more than his defense minister, wouldn’t it make sense to have the AI supervise the country’s most powerful weapons? If the AI then makes an error, or begins to pursue an alien goal, the result could be catastrophic, and not just for that country.
Similarly, terrorists focused on events in one corner of the world might use AI to instigate a global pandemic. The terrorists might be more versed in some apocalyptic mythology than in the science of epidemiology, but they just need to set the goal, and all else will be done by their AI. The AI could synthesize a new pathogen, order it from commercial laboratories or print it in biological 3-D printers, and devise the best strategy to spread it around the world, via airports or food supply chains. What if the AI synthesizes a virus that is as deadly as Ebola, as contagious as COVID-19, and as slow acting as AIDS? By the time the first victims begin to die, and the world is alerted to the danger, most people on earth might have already been infected.1
As we have seen in previous chapters, human civilization is threatened not only by physical and biological weapons of mass destruction like atom bombs and viruses. Human civilization could also be destroyed by weapons of social mass destruction, like stories that undermine our social bonds. An AI developed in one country could be used to unleash a deluge of fake news, fake money, and fake humans so that people in numerous other countries lose the ability to trust anything or anyone.
Many societies—both democracies and dictatorships—may act responsibly to regulate such usages of AI, clamp down on bad actors, and restrain the dangerous ambitions of their own rulers and fanatics. But if even a handful of societies fail to do so, this could be enough to endanger the whole of humankind. Climate change can devastate even countries that adopt excellent environmental regulations, because it is a global rather than a national problem. AI, too, is a global problem. Countries would be naive to imagine that as long as they regulate AI wisely within their own borders, these regulations will protect them from the worst outcomes of the AI revolution. Accordingly, to understand the new computer politics, it is not enough to examine how discrete societies might react to AI. We also need to consider how AI might change relations between societies on a global level.
At present, the world is divided into about two hundred nation-states, most of which gained their independence only after 1945. They are not all equal. The list contains two superpowers, a handful of major powers, several blocs and alliances, and a lot of smaller fish. Still, even the tiniest states enjoy some leverage, as evidenced by their ability to play the superpowers against each other. In the early 2020s, for example, China and the United States competed for influence in the strategically important South Pacific region. Both superpowers courted island nations like Tonga, Tuvalu, Kiribati, and the Solomon Islands. The governments of these small nations—whose populations range from 740,000 (Solomon Islands) to 11,000 (Tuvalu)—had substantial leeway to decide which way to tack and were able to extract considerable concessions and aid.2
Other small states, such as Qatar, have established themselves as important players in the geopolitical arena. With only 300,000 citizens, Qatar is nevertheless pursuing ambitious foreign policy aims in the Middle East, is playing an outsized rule in the global economy, and is home to Al Jazeera, the Arab world’s most influential TV network. One might argue that Qatar is able to punch well above its size because it is the third-largest exporter of natural gas in the world. Yet in a different international setting, that would have made Qatar not an independent actor but the first course on the menu of any imperial conqueror. It is telling that, as of 2024, Qatar’s much bigger neighbors, and the world’s hegemonic powers, are letting the tiny Gulf state hold on to its fabulous riches. Many people describe the international system as a jungle. If so, it is a jungle in which tigers allow fat chickens to live in relative safety.
Qatar, Tonga, Tuvalu, Kiribati, and the Solomon Islands all indicate that we are living in a postimperial era. They gained their independence from the British Empire in the 1970s, as part of the final demise of the European imperial order. The leverage they now have in the international arena testifies that in the first quarter of the twenty-first century power is distributed between a relatively large number of players, rather than monopolized by a few empires.
How might the rise of the new computer network change the shape of international politics? Aside from apocalyptic scenarios such as a dictatorial AI launching a nuclear war, or a terrorist AI instigating a lethal pandemic, computers pose two main challenges to the current international system. First, since computers make it easier to concentrate information and power in a central hub, humanity could enter a new imperial era. A few empires (or perhaps a single empire) might bring the whole world under a much tighter grip than that of the British Empire or the Soviet Empire. Tonga, Tuvalu, and Qatar would be transformed from independent states into colonial possessions—just as they were fifty years ago.
Second, humanity could split along a new Silicon Curtain that would pass between rival digital empires. As each regime chooses its own answer to the AI alignment problem, to the dictator’s dilemma, and to other technological quandaries, each might create a separate and very different computer network. The various networks might then find it ever more difficult to interact, and so would the humans they control. Qataris living as part of an Iranian or Russian network, Tongans living as part of a Chinese network, and Tuvaluans living as part of an American network could come to have such different life experiences and worldviews that they would hardly be able to communicate or to agree on much.
If these developments indeed materialize, they could easily lead to their own apocalyptic outcome. Perhaps each empire can keep its nuclear weapons under human control and its lunatics away from bioweapons. But a human species divided into hostile camps that cannot understand each other stands a small chance of avoiding devastating wars or preventing catastrophic climate change. A world of rival empires separated by an opaque Silicon Curtain would also be incapable of regulating the explosive power of AI.
THE RISE OF DIGITAL EMPIRES
In chapter 9 we touched briefly on the link between the Industrial Revolution and modern imperialism. It was not evident, at the beginning, that industrial technology would have much of an impact on empire building. When the first steam engines were put to use to pump water in British coal mines in the eighteenth century, no one foresaw that they would eventually power the most ambitious imperial projects in human history. When the Industrial Revolution subsequently gathered steam in the early nineteenth century, it was driven by private businesses, because governments and armies were relatively slow to appreciate its potential geopolitical impact. The world’s first commercial railway, for example, which opened in 1830 between Liverpool and Manchester, was built and operated by the privately owned Liverpool and Manchester Railway Company. The same was true of most other early railway lines in the U.K., the United States, France, Germany, and elsewhere. At that point, it wasn’t at all clear why governments or armies should get involved in such commercial enterprises.
By the middle of the nineteenth century, however, the governments and armed forces of the leading industrial powers had fully recognized the immense geopolitical potential of modern industrial technology. The need for raw materials and markets justified imperialism, while industrial technologies made imperial conquests easier. Steamships were crucial, for example, to the British victory over the Chinese in the Opium Wars, and railroads played a decisive role in the American expansion west and the Russian expansion east and south. Indeed, entire imperial projects were shaped around the construction of railroads such as the Trans-Siberian and Trans-Caspian Russian lines, the German dream of a Berlin-Baghdad railway, and the British dream of building a railway from Cairo to the Cape.3
Nevertheless, most polities didn’t join the burgeoning industrial arms race in time. Some lacked the capacity to do so, like the Melanesian chiefdoms of the Solomon Islands and the Al Thani tribe of Qatar. Others, like the Burmese Empire, the Ashanti Empire, and the Chinese Empire, might have had the capacity but lacked the will and foresight. Their rulers and inhabitants either didn’t follow developments in places like the British Midlands or didn’t think they had much to do with them. Why should the rice farmers of the Irrawaddy basin in Burma or the Yangtze basin in China concern themselves about the Liverpool–Manchester Railway? By the end of the nineteenth century, however, these rice farmers found themselves either conquered or indirectly exploited by the British Empire. Most other stragglers in the industrial race also ended up dominated by one industrial power or other. Could something similar happen with AI?
When the race to develop AI gathered steam in the early years of the twenty-first century, it too was initially spearheaded by private entrepreneurs in a handful of countries. They set their sights on centralizing the world’s flow of information. Google wanted to organize all the world’s information in one place. Amazon sought to centralize all the world’s shopping. Facebook wished to connect all the world’s social spheres. But concentrating all the world’s information is neither practical nor helpful unless one can centrally process that information. And in 2000, when Google’s search engine was making its baby steps, when Amazon was a modest online bookshop, and when Mark Zuckerberg was in high school, the AI necessary to centrally process oceans of data was nowhere at hand. But some people bet it was just around the corner.
Kevin Kelly, the founding editor of Wired magazine, recounted how in 2002 he attended a small party at Google and struck up a conversation with Larry Page. “Larry, I still don’t get it. There are so many search companies. Web search, for free? Where does that get you?” Page explained that Google wasn’t focused on search at all. “We’re really making an AI,” he said.4 Having lots of data makes it easier to create an AI. And AI can turn lots of data into lots of power.
By the 2010s, the dream was becoming a reality. Like every major historical revolution, the rise of AI was a gradual process involving numerous steps. And like every revolution, a few of these steps were seen as turning points, just like the opening of the Liverpool–Manchester Railway. In the prolific literature on the story of AI, two events pop up again and again. The first occurred when, on September 30, 2012, a convolutional neural network called AlexNet won the ImageNet Large Scale Visual Recognition Challenge.
If you have no idea what a convolutional neural network is, and if you have never heard of the ImageNet challenge, you are not alone. More than 99 percent of us are in the same situation, which is why AlexNet’s victory was hardly front-page news in 2012. But some humans did hear about AlexNet’s victory and decoded the writing on the wall.
They knew, for example, that ImageNet is a database of millions of annotated digital images. Did a website ever ask you to prove that you are not a robot by looking at a set of images and indicating which ones contain a car or a cat? The images you clicked were perhaps added to the ImageNet database. The same thing might also have happened to tagged images of your pet cat that you uploaded online. The ImageNet Large Scale Visual Recognition Challenge tests various algorithms on how well they are able to identify the annotated images in the database. Can they correctly identify the cats? When humans are asked to do it, out of one hundred cat images we correctly identify ninety-five as cats. In 2010 the best algorithms had a success rate of only 72 percent. In 2011 the algorithmic success rate crawled up to 75 percent. In 2012 the AlexNet algorithm won the challenge and stunned the still minuscule community of AI experts by achieving a success rate of 85 percent. While this improvement may not sound like much to laypersons, it demonstrated to the experts the potential for rapid progress in certain AI domains. By 2015 a Microsoft algorithm achieved 96 percent accuracy, surpassing the human ability to identify cat images.
In 2016, The Economist published a piece titled “From Not Working to Neural Networking” that asked, “How has artificial intelligence, associated with hubris and disappointment since its earliest days, suddenly become the hottest field in technology?” It pointed to AlexNet’s victory as the moment when “people started to pay attention, not just within the AI community but across the technology industry as a whole.” The article was illustrated with an image of a robotic hand holding up a photo of a cat.5
All those cat images that tech giants had been harvesting from across the world, without paying a penny to either users or tax collectors, turned out to be incredibly valuable. The AI race was on, and the competitors were running on cat images. At the same time that AlexNet was preparing for the ImageNet challenge, Google too was training its AI on cat images, and even created a dedicated cat-image-generating AI called the Meow Generator.6 The technology developed by recognizing cute kittens was later deployed for more predatory purposes. For example, Israel relied on it to create the Red Wolf, Blue Wolf, and Wolf Pack apps used by Israeli soldiers for facial recognition of Palestinians in the Occupied Territories.7 The ability to recognize cat images also led to the algorithms Iran uses to automatically recognize unveiled women and enforce its hijab laws. As explained in chapter 8, massive amounts of data are required to train machine-learning algorithms. Without millions of cat images uploaded and annotated for free by people across the world, it would not have been possible to train the AlexNet algorithm or the Meow Generator, which in turn served as the template for subsequent AIs with far-reaching economic, political, and military potential.8
Just as in the early nineteenth century the effort to build railways was pioneered by private entrepreneurs, so in the early twenty-first century private corporations were the initial main competitors in the AI race. The executives of Google, Facebook, Alibaba, and Baidu saw the value of recognizing cat images before the presidents and generals did. The second eureka moment, when the presidents and generals caught on to what was happening, occurred in mid-March 2016. It was the aforementioned victory of Google’s AlphaGo over Lee Sedol. Whereas AlexNet’s achievement was largely ignored by politicians, AlphaGo’s triumph sent shock waves through government offices, especially in East Asia. In China and neighboring countries go is a cultural treasure and considered an ideal training for aspiring strategists and policy makers. In March 2016, or so the mythology of AI would have it, the Chinese government realized that the age of AI had begun.9
It is little wonder that the Chinese government was probably the first to understand the full importance of what was happening. In the nineteenth century, China was late to appreciate the potential of the Industrial Revolution and was slow to adopt inventions like railroads and steamships. It consequently suffered what the Chinese call “the century of humiliations.” After having been the world’s greatest superpower for centuries, failing to adopt modern industrial technology brought China to its knees. It was repeatedly defeated in wars, partially conquered by foreigners, and thoroughly exploited by the powers that did understand railroads and steamships. The Chinese vowed never again to miss the train.
In 2017, China’s government released its “New Generation Artificial Intelligence Plan,” which announced that “by 2030, China’s AI theories, technologies, and application should achieve world-leading levels, making China the world’s primary AI innovation center.”10 In the following years China poured enormous resources into AI so that by the early 2020s it is already leading the world in several AI-related fields and catching up with the United States in others.11
Of course, the Chinese government wasn’t the only one that woke up to the importance of AI. On September 1, 2017, President Putin of Russia declared, “Artificial intelligence is the future, not only for Russia, but for all humankind.… Whoever becomes the leader in this sphere will become the ruler of the world.” In January 2018, Prime Minister Modi of India concurred that “the one who control [sic] the data will control the world.”12 In February 2019, President Trump signed an executive order on AI, saying that “the age of AI has arrived” and that “continued American leadership in Artificial Intelligence is of paramount importance to maintaining the economic and national security of the United States.”13 The United States at the time was already the leader in the AI race, thanks largely to efforts of visionary private entrepreneurs. But what began as a commercial competition between corporations was turning into a match between governments, or perhaps more accurately, into a race between competing teams, each made of one government and several corporations. The prize for the winner? World domination.
DATA COLONIALISM
In the sixteenth century, when Spanish, Portuguese, and Dutch conquistadors were building the first global empires in history, they came with sailing ships, horses, and gunpowder. When the British, Russians, and Japanese made their bids for hegemony in the nineteenth and twentieth centuries, they relied on steamships, locomotives, and machine guns. In the twenty-first century, to dominate a colony, you no longer need to send in the gunboats. You need to take out the data. A few corporations or governments harvesting the world’s data could transform the rest of the globe into data colonies—territories they control not with overt military force but with information.14
Imagine a situation—in twenty years, say—when somebody in Beijing or San Francisco possesses the entire personal history of every politician, journalist, colonel, and CEO in your country: every text they ever sent, every web search they ever made, every illness they suffered, every sexual encounter they enjoyed, every joke they told, every bribe they took. Would you still be living in an independent country, or would you now be living in a data colony? What happens when your country finds itself utterly dependent on digital infrastructures and AI-powered systems over which it has no effective control?
Such a situation can lead to a new kind of data colonialism in which control of data is used to dominate faraway colonies. Mastery of AI and data could also give the new empires control of people’s attention. As we have already discussed, in the 2010s American social media giants like Facebook and YouTube upended the politics of distant countries like Myanmar and Brazil in pursuit of profit. Future digital empires may do something similar for political interests.
Fears of psychological warfare, data colonialism, and loss of control over their cyberspace have led many countries to already block what they see as dangerous apps. China has banned Facebook, YouTube, and many other Western social media apps and websites. Russia has banned almost all Western social media apps as well as some Chinese ones. In 2020, India banned TikTok, WeChat, and numerous other Chinese apps on the grounds that they were “prejudicial to sovereignty and integrity of India, defense of India, security of state and public order.”15 The United States has been debating whether to ban TikTok—concerned that the app might be serving Chinese interests—and as of 2023 it is illegal to use it on the devices of almost all federal employees, state employees, and government contractors.16 Lawmakers in the U.K., New Zealand, and other countries have also expressed concerns over TikTok.17 Numerous other governments, from Iran to Ethiopia, have blocked various apps like Facebook, Twitter, YouTube, Telegram, and Instagram.
Data colonialism could also manifest itself in the spread of social credit systems. What might happen, for example, if a dominant player in the global digital economy decides to establish a social credit system that harvests data anywhere it can and scores not only its own nationals but people throughout the world? Foreigners couldn’t just shrug off their score, because it might affect them in numerous ways, from buying flight tickets to applying for visas, scholarships, and jobs. Just as tourists use the global scores given by foreign corporations like Tripadvisor and Airbnb to evaluate restaurants and vacation homes even in their own country, and just as people throughout the world use the U.S. dollar for commercial transactions, so people everywhere might begin to use a Chinese or an American social credit score for local social interactions.
Becoming a data colony will have economic as well as political and social consequences. In the nineteenth and twentieth centuries, if you were a colony of an industrial power like Belgium or Britain, it usually meant that you provided raw materials, while the cutting-edge industries that made the biggest profits remained in the imperial hub. Egypt exported cotton to Britain and imported high-end textiles. Malaya provided rubber for tires; Coventry made the cars.18
Something analogous is likely to happen with data colonialism. The raw material for the AI industry is data. To produce AI that recognizes images, you need cat photos. To produce the trendiest fashion, you need data on fashion trends. To produce autonomous vehicles, you need data about traffic patterns and car accidents. To produce health-care AI, you need data about genes and medical conditions. In a new imperial information economy, raw data will be harvested throughout the world and will flow to the imperial hub. There the cutting-edge technology will be developed, producing unbeatable algorithms that know how to identify cats, predict fashion trends, drive autonomous vehicles, and diagnose diseases. These algorithms will then be exported back to the data colonies. Data from Egypt and Malaysia might make a corporation in San Francisco or Beijing rich, while people in Cairo and Kuala Lumpur remain poor, because neither the profits nor the power is distributed back.
The nature of the new information economy might make the imbalance between imperial hub and exploited colony worse than ever. In ancient times land—rather than information—was the most important economic asset. This precluded the overconcentration of all wealth and power in a single hub. As long as land was paramount, considerable wealth and power always remained in the hands of provincial landowners. A Roman emperor, for example, could put down one provincial revolt after another, but on the day after decapitating the last rebel chief, he had no choice but to appoint a new set of provincial landowners who might again challenge the central power. In the Roman Empire, although Italy was the seat of political power, the richest provinces were in the eastern Mediterranean. It was impossible to transport the fertile fields of the Nile valley to the Italian Peninsula.19 Eventually the emperors abandoned the city of Rome to the barbarians and moved the seat of political power to the rich east, to Constantinople.
During the Industrial Revolution machines became more important than land. Factories, mines, railroad lines, and electrical power stations became the most valuable assets. It was somewhat easier to concentrate these kinds of assets in one place. The British Empire could centralize industrial production in its home islands, extract raw materials from India, Egypt, and Iraq, and sell them finished goods made in Birmingham or Belfast. Unlike in the Roman Empire, Britain was the seat of both political and economic power. But physics and geology still put natural limits on this concentration of wealth and power. The British couldn’t move every cotton mill from Calcutta to Manchester, nor shift the oil wells from Kirkuk to Yorkshire.
Information is different. Unlike cotton and oil, digital data can be sent from Malaysia or Egypt to Beijing or San Francisco at almost the speed of light. And unlike land, oil fields, or textile factories, algorithms don’t take up much space. Consequently, unlike industrial power, the world’s algorithmic power can be concentrated in a single hub. Engineers in a single country might write the code and control the keys for all the crucial algorithms that run the entire world.
Indeed, AI makes it possible to concentrate in one place even the decisive assets of some traditional industries, like textile. In the nineteenth century, to control the textile industry meant to control sprawling cotton fields and huge mechanical production lines. In the twenty-first century, the most important asset of the textile industry is information rather than cotton or machinery. To beat the competitors, a garment producer needs information about the likes and dislikes of customers and the ability to predict or manufacture the next fashions. By controlling this type of information, high-tech giants like Amazon and Alibaba can monopolize even a very traditional industry like textile. In 2021, Amazon became the United States’ biggest single clothing retailer.20
Moreover, as AI, robots, and 3-D printers automate textile production, millions of workers might lose their jobs, upending national economies and the global balance of power. What will happen to the economies and politics of Pakistan and Bangladesh, for example, when automation makes it cheaper to produce textiles in Europe? Consider that at present the textile sector provides employment to 40 percent of Pakistan’s total labor force and accounts for 84 percent of Bangladesh’s export earnings.21 As noted in chapter 7, while automation might make millions of textile workers redundant, it will probably create many new jobs, too. For instance, there might be a huge demand for coders and data analysts. But turning an unemployed factory hand into a data analyst demands a substantial up-front investment in retraining. Where would Pakistan and Bangladesh get the money to do that?
AI and automation therefore pose a particular challenge to poorer developing countries. In an AI-driven economy, the digital leaders claim the bulk of the gains and could use their wealth to retrain their workforce and profit even more. Meanwhile, the value of unskilled laborers in left-behind countries will decline, and they will not have the resources to retrain their workforce, causing them to fall even further behind. The result might be lots of new jobs and immense wealth in San Francisco and Shanghai, while many other parts of the world face economic ruin.22 According to the global accounting firm PricewaterhouseCoopers, AI is expected to add $15.7 trillion to the global economy by 2030. But if current trends continue, it is projected that China and North America—the two leading AI superpowers—will together take home 70 percent of that money.23
FROM WEB TO COCOON
These economic and geopolitical dynamics could divide the world between two digital empires. During the Cold War, the Iron Curtain was in many places literally made of metal: barbed wire separated one country from another. Now the world is increasingly divided by the Silicon Curtain. The Silicon Curtain is made of code, and it passes through every smartphone, computer, and server in the world. The code on your smartphone determines on which side of the Silicon Curtain you live, which algorithms run your life, who controls your attention, and where your data flows.
It is becoming difficult to access information across the Silicon Curtain, say between China and the United States, or between Russia and the EU. Moreover, the two sides are increasingly run on different digital networks, using different computer codes. Each sphere obeys different regulations and serves different purposes. In China, the most important aim of new digital technology is to strengthen the state and serve government policies. While private enterprises are given a certain amount of autonomy in developing and deploying AI tools, their economic activities are ultimately subservient to the government’s political goals. These political goals also justify a relatively high level of surveillance, both online and off-line. This means, for example, that though Chinese citizens and authorities do care about people’s privacy, China is already far ahead of the United States and other Western countries in developing and deploying social credit systems that encompass the whole of people’s lives.24
In the United States, the government plays a more limited role. Private enterprises lead the development and deployment of AI, and the ultimate goal of many new AI tools is to enrich the tech giants rather than to strengthen the American state or the current administration. Indeed, in many cases governmental policies are themselves shaped by powerful business interests. But the U.S. system does offer greater protection for citizens’ privacy. While American corporations aggressively gather information on people’s online activities, they are much more restricted in surveilling people’s offline lives. There is also widespread rejection of the ideas behind all-embracing social credit systems.25
These political, cultural, and regulatory differences mean that each sphere is using different software. In China you cannot use Google and Facebook, and you cannot access Wikipedia. In the United States few people use WeChat, Baidu, and Tencent. More important, the spheres aren’t mirror images of each other. It is not that the Chinese and Americans develop local versions of the same apps. Baidu isn’t the Chinese Google. Alibaba isn’t the Chinese Amazon. They have different goals, different digital architectures, and different impacts on people’s lives.26 These differences influence much of the world, since most countries rely on Chinese and American software rather than on local technology.
Each sphere also uses different hardware like smartphones and computers. The United States pressures its allies and clients to avoid Chinese hardware, such as Huawei’s 5G infrastructure.27 The Trump administration blocked an attempt by the Singaporean corporation Broadcom to buy the leading American producer of computer chips, Qualcomm. They feared foreigners might insert back doors into the chips or would prevent the U.S. government from inserting its own back doors there.28 In 2022, the Biden administration placed strict limits on trade in high-performance computing chips necessary for the development of AI. U.S. companies were forbidden to export such chips to China, or to provide China with the means to manufacture or repair them. The restrictions have subsequently been tightened further, and the ban was expanded to include other nations such as Russia and Iran.29 While in the short term this hampers China in the AI race, in the long term it will push China to develop a completely separate digital sphere that will be distinct from the American digital sphere even in its smallest building blocks.30
The two digital spheres may drift further and further apart. Chinese software would talk only with Chinese hardware and Chinese infrastructure, and the same would happen on the other side of the Silicon Curtain. Since digital code influences human behavior, and human behavior in turn shapes digital code, the two sides may well be moving along different trajectories that will make them more and more different not just in their technology but in their cultural values, social norms, and political structures. After generations of convergence, humanity could find itself at a crucial point of divergence.31 For centuries, new information technologies fueled the process of globalization and brought people all over the world into closer contact. Paradoxically, information technology today is so powerful it can potentially split humanity by enclosing different people in separate information cocoons, ending the idea of a single shared human reality. While the web has been our main metaphor in recent decades, the future might belong to cocoons.
THE GLOBAL MIND-BODY SPLIT
The division into separate information cocoons could lead not just to economic rivalries and international tensions but also to the development of very different cultures, ideologies, and identities. Guessing future cultural and ideological developments is usually a fool’s errand. It is far more difficult than predicting economic and geopolitical developments. How many Romans or Jews in the days of Tiberius could have anticipated that a splinter Jewish sect would eventually take over the Roman Empire and that the emperors would abandon Rome’s old gods to worship an executed Jewish rabbi?
It would have been even more difficult to foresee the directions in which various Christian sects would develop and the momentous impact of their ideas and conflicts on everything from politics to sexuality. When Jesus was asked about paying taxes to Tiberius’s government and answered, “Render unto Caesar the things that are Caesar’s, and unto God the things that are God’s” (Matthew 22:21), nobody could imagine the impact his response would have on the separation of church and state in the American republic two millennia later. And when Saint Paul wrote to the Christians in Rome, “I myself in my mind am a slave to God’s law, but in my sinful flesh a slave to the law of sin” (Romans 7:25), who could have foreseen the repercussions this would have on schools of thought ranging from Cartesian philosophy to queer theory?
Despite these difficulties, it is important to try to imagine future cultural developments, in order to alert ourselves to the fact that the AI revolution and the formation of rival digital spheres are likely to change more than just our jobs and political structures. The following paragraphs contain some admittedly ambitious speculation, so please bear in mind that my goal is not to accurately foretell cultural developments but merely to draw attention to the likelihood that profound cultural shifts and conflicts await us.
One possible development with far-reaching consequences is that different digital cocoons might adopt incompatible approaches to the most fundamental questions of human identity. For thousands of years, many religious and cultural conflicts—for example, between rival Christian sects, between Hindus and Buddhists, and between Platonists and Aristotelians—were fueled by disagreements about the mind-body problem. Are humans a physical body, or a nonphysical mind, or perhaps a mind trapped inside a body? In the twenty-first century, the computer network might supercharge the mind-body problem and turn it into a cause for major personal, ideological, and political conflicts.
To appreciate the political ramifications of the mind-body problem, let’s briefly revisit the history of Christianity. Many of the earliest Christian sects, influenced by Jewish thinking, believed in the Old Testament idea that humans are embodied beings and that the body plays a crucial role in human identity. The book of Genesis said God created humans as physical bodies, and almost all books of the Old Testament assume that humans can exist only as physical bodies. With a few possible exceptions, the Old Testament doesn’t mention the possibility of a bodiless existence after death, in heaven or hell. When the ancient Jews fantasized about salvation, they imagined it to mean an earthly kingdom of material bodies. In the time of Jesus, many Jews believed that when the Messiah finally comes, the bodies of the dead would come back to life, here on earth. The Kingdom of God, established by the Messiah, was supposed to be a material kingdom, with trees and stones and flesh-and-blood bodies.32
This was also the view of Jesus himself and the first Christians. Jesus promised his followers that soon the Kingdom of God would be built here on earth and they would inhabit it in their material bodies. When Jesus died without fulfilling his promise, his early followers came to believe that he was resurrected in the flesh and that when the Kingdom of God finally materialized on earth, they too would be resurrected in the flesh. The church father Tertullian (160–240 CE) wrote that “the flesh is the very condition on which salvation hinges,” and the catechism of the Catholic Church, citing the doctrines adopted at the Second Council of Lyon in 1274, states, “We believe in God who is creator of the flesh; we believe in the Word made flesh in order to redeem the flesh; we believe in the resurrection of the flesh, the fulfillment of both the creation and the redemption of the flesh.… We believe in the true resurrection of this flesh that we now possess.”33
Despite such seemingly unequivocal statements, we saw that Saint Paul already had his doubts about the flesh, and by the fourth century CE, under Greek, Manichaean, and Persian influences, some Christians had drifted toward a dualistic approach. They came to think of humans as consisting of a good immaterial soul trapped inside an evil material body. They didn’t fantasize about being resurrected in the flesh. Just the opposite. Having been released by death from its abominable material prison, why would the pure soul ever want to get back in? Christians accordingly began to believe that after death the soul is liberated from the body and exists forever in an immaterial place completely beyond the physical realm—which is the standard belief among Christians today, notwithstanding what Tertullian and the Second Council of Lyon said.34
But Christianity couldn’t completely abandon the old Jewish view that humans are embodied beings. After all, Christ appeared on earth in the flesh. His body was nailed to the cross, on which he experienced excruciating pain. For two thousand years, Christian sects therefore fought each other—sometimes with words, sometimes with swords—over the exact relations between soul and body. The fiercest arguments focused on Christ’s own body. Was he material? Was he purely spiritual? Did he perhaps have a nonbinary nature, being both human and divine at the same time?
The different approaches to the mind-body problem influenced how people treated their own bodies. Saints, hermits, and monks made breathtaking experiments in pushing the human body to its limits. Just as Christ allowed his body to be tortured on the cross, so these “athletes of Christ” allowed lions and bears to rip them apart while their souls rejoiced in divine ecstasy. They wore hair shirts, fasted for weeks, or stood for years on a pillar—like the famous Simeon who allegedly stood for about forty years on top of a pillar near Aleppo.35
Other Christians took the opposite approach, believing that the body didn’t matter at all. The only thing that mattered was faith. This idea was taken to extremes by Protestants like Martin Luther, who formulated the doctrine of sola fide: only faith. After living as a monk for about ten years, fasting and torturing his body in various ways, Luther despaired of these bodily exercises. He reasoned that no bodily self-torments could force God to redeem him. Indeed, thinking he could win his own salvation by torturing his body was the sin of pride. Luther therefore disrobed, married a former nun, and told his followers that to be good Christians, the only thing they needed was to have complete faith in Christ.36
These ancient theological debates about mind and body may seem utterly irrelevant to the AI revolution, but they have in fact been resurrected by twenty-first-century technologies. What is the relationship between our physical body and our online identities and avatars? What is the relation between the offline world and cyberspace? Suppose I spend most of my waking hours sitting in my room in front of a screen, playing online games, forming virtual relationships, and even working remotely. I hardly venture out even to eat. I just order takeout. If you are like ancient Jews and the first Christians, you would pity me and conclude that I must be living in a delusion, losing touch with the reality of physical spaces and flesh-and-blood bodies. But if your thinking is closer to that of Luther and many later Christians, you might think I am liberated. By shifting most of my activities and relationships online, I have released myself from the limited organic world of debilitating gravity and corrupt bodies and can enjoy the unlimited possibilities of a digital world, which is potentially liberated from the laws of biology and even physics. I am free to roam a much vaster and more exciting space and to explore new aspects of my identity.
An increasingly important question is whether people can adopt any virtual identity they like, or should their identity be constrained by their biological body? If we follow the Lutheran position of sola fide, the biological body isn’t of much importance. To adopt a certain online identity, the only thing that matters is what you believe. This debate can have far-reaching consequences not just for human identity but for our attitude to the world as a whole. A society that understands identities in terms of biological bodies should also care more about material infrastructure like sewage pipes and about the ecosystem that sustains our bodies. It will see the online world as an auxiliary of the offline world that can serve various useful purposes but can never become the central arena of our lives. Its aim would be to create an ideal physical and biological realm—the Kingdom of God on earth. In contrast, a society that downplays biological bodies and focuses on online identities may well seek to create an immersive Kingdom of God in cyberspace while discounting the fate of mere material things like sewage pipes and rain forests.
This debate could shape attitudes not only toward organisms but also toward digital entities. As long as society defines identity by focusing on physical bodies, it is unlikely to view AIs as persons. But if society gives less importance to physical bodies, then even AIs that lack any corporeal manifestations may be accepted as legal persons enjoying various rights.
Throughout history, diverse cultures have given diverse answers to the mind-body problem. A twenty-first-century controversy about the mind-body problem could result in cultural and political splits more consequential even than the split between Jews and Christians or between Catholics and Protestants. What happens, for example, if the American sphere discounts the body, defines humans by their online identity, recognizes AIs as persons, and downplays the importance of the ecosystem, whereas the Chinese sphere adopts opposite positions? Current disagreements about violations of human rights or adherence to ecological standards will look minuscule in comparison. The Thirty Years’ War—arguably the most devastating war in European history—was fought at least in part because Catholics and Protestants couldn’t agree on doctrines like sola fide and on whether Christ was divine, human, or nonbinary. Might future conflicts start because of an argument about AI rights and the nonbinary nature of avatars?
As noted, these are all wild speculations, and in all likelihood actual cultures and ideologies will develop in different—and perhaps even wilder—directions. But it is probable that within a few decades the computer network will cultivate new human and nonhuman identities that make little sense to us. And if the world will be divided into two rival digital cocoons, the identities of entities in one cocoon might be unintelligible to the inhabitants of the other.
FROM CODE WAR TO HOT WAR
While China and the United States are currently the front-runners in the AI race, they are not alone. Other countries or blocs, such as the EU, India, Brazil, and Russia, may try to create their own digital spheres, each influenced by different political, cultural, and religious traditions.37 Instead of being divided between just two global empires, the world might be divided among a dozen empires. It is unclear whether this will somewhat alleviate or only exacerbate the imperial competition.
The more the new empires compete against one another, the greater the danger of armed conflict. The Cold War between the United States and the U.S.S.R. never escalated into a direct military confrontation largely thanks to the doctrine of mutually assured destruction. But the danger of escalation in the age of AI is bigger, because cyber warfare is inherently different from nuclear warfare.
First, cyber weapons are much more versatile than nuclear bombs. Cyber weapons can bring down a country’s electric grid, but they can also be used to destroy a secret research facility, jam an enemy sensor, inflame a political scandal, manipulate elections, or hack a single smartphone. And they can do all that stealthily. They don’t announce their presence with a mushroom cloud and a storm of fire, nor do they leave a visible trail from launchpad to target. Consequently, at times it is hard to know if an attack even occurred or who launched it. If a database is hacked or sensitive equipment is destroyed, it’s hard to be sure whom to blame. The temptation to start a limited cyberwar is therefore big, and so is the temptation to escalate it. Rival countries like Israel and Iran or the United States and Russia have been trading cyber blows for years, in an undeclared but escalating war.38 This is becoming the new global norm, amplifying international tensions and pushing countries to cross one red line after another.
A second crucial difference concerns predictability. The Cold War was like a hyperrational chess game, and the certainty of destruction in the event of nuclear conflict was so great that the desire to start a war was correspondingly small. Cyber warfare lacks this certainty. Nobody knows for sure where each side has planted its logic bombs, Trojan horses, and malwares. Nobody can be certain whether their own weapons would actually work when called upon. Would Chinese missiles fire when the order is given, or perhaps the Americans have hacked them or the chain of command? Would American aircraft carriers function as expected, or would they perhaps shut down mysteriously or sail around in circles?39
Such uncertainty undermines the doctrine of mutually assured destruction. One side might convince itself—rightly or wrongly—that it can launch a successful first strike and avoid massive retaliation. Even worse, if one side thinks it has such an opportunity, the temptation to launch a first strike could become irresistible, because one never knows how long the window of opportunity will remain open. Game theory posits that the most dangerous situation in an arms race is when one side feels it has an advantage but that this advantage is slipping away.40
Even if humanity avoids the worst-case scenario of global war, the rise of new digital empires could still endanger the freedom and prosperity of billions of people. The industrial empires of the nineteenth and twentieth centuries exploited and repressed their colonies, and it would be foolhardy to expect the new digital empires to behave much better. Moreover, as noted earlier, if the world is divided into rival empires, humanity is unlikely to cooperate effectively to overcome the ecological crisis or to regulate AI and other disruptive technologies like bioengineering.
THE GLOBAL BOND
Of course, no matter whether the world is divided between a few digital empires, remains a more diverse community of two hundred nation-states, or is split along altogether different and unforeseen lines, cooperation is always an option. Among humans, the precondition for cooperation isn’t similarity; it is the ability to exchange information. As long as we are able to converse, we might find some shared story that can bring us closer. This, after all, is what made Homo sapiens the dominant species on the planet.
Just as different and even rival families can cooperate within a tribal network, and competing tribes can cooperate within a national network, so opposing nations and empires can cooperate within a global network. The stories that make such cooperation possible do not eliminate our differences; rather, they enable us to identify shared experiences and interests, which offer a common framework for thought and action.
A large part of what nevertheless makes global cooperation difficult is the misguided notion that it requires abolishing all cultural, social, and political differences. Populist politicians often argue that if the international community agrees on a common story and on universal norms and values, this will destroy the independence and unique traditions of their own nation.41 This position was unabashedly distilled in 2015 by Marine Le Pen—leader of France’s National Front party—in an election speech in which she declared, “We have entered a new two-partyism. A two-partyism between two mutually exclusive conceptions that will from now on structure our political life. The cleavage no longer separates left and right, but globalists and patriots.”42 In August 2020, President Trump described his guiding ethos thus: “We have rejected globalism and embraced patriotism.”43
Luckily, this binary position is mistaken in its basic assumption. Global cooperation and patriotism are not mutually exclusive. For patriotism isn’t about hating foreigners. It is about loving our compatriots. And there are many situations when, in order to take care of our compatriots, we need to cooperate with foreigners. COVID-19 provided us with one obvious example. Pandemics are global events, and without global cooperation it is hard to contain them, let alone prevent them. When a new virus or a mutant pathogen appears in one country, it puts all other countries in danger. Conversely, the biggest advantage of humans over pathogens is that we can cooperate in ways that pathogens cannot. Doctors in Germany and Brazil can alert one another to new dangers, give each other good advice, and work together to discover better treatments.
If German scientists invent a vaccine against some new disease, how should Brazilians react to this German achievement? One option is to reject the foreign vaccine and wait until Brazilian scientists develop a Brazilian vaccine. That, however, would be not just foolish; it would be anti-patriotic. Brazilian patriots should want to use any available vaccine to help their compatriots, no matter where the vaccine was developed. In this situation, cooperating with foreigners is the patriotic thing to do. The threat of losing control of AIs is an analogous situation in which patriotism and global cooperation must go together. An out-of-control AI, just like an out-of-control virus, puts in danger humans in every nation. No human collective—whether a tribe, a nation, or the entire species—stands to benefit from letting power shift from humans to algorithms.
Contrary to what populists argue, globalism doesn’t mean establishing a global empire, abandoning national loyalties, or opening borders to unlimited immigration. In fact, global cooperation means two far more modest things: first, a commitment to some global rules. These rules don’t deny the uniqueness of each nation and the loyalty people should owe their nation. They just regulate the relations between nations. A good model is the World Cup. The World Cup is a competition between nations, and people often show fierce loyalty to their national team. At the same time, the World Cup is an amazing display of global agreement. Brazil cannot play football against Germany unless Brazilians and Germans first agree on the same set of rules for the game. That’s globalism in action.
The second principle of globalism is that sometimes—not always, but sometimes—it is necessary to prioritize the long-term interests of all humans over the short-term interests of a few. For example, in the World Cup, all national teams agree not to use performance-enhancing drugs, because everybody realizes that if they go down that path, the World Cup would eventually devolve into a competition between biochemists. In other fields where technology is a game changer, we should similarly strive to balance national and global interests. Nations will obviously continue to compete in the development of new technology, but sometimes they should agree to limit the development and deployment of dangerous technologies like autonomous weapons and manipulative algorithms—not purely out of altruism, but for their own self-preservation.
THE HUMAN CHOICE
Forging and keeping international agreements on AI will require major changes in the way the international system functions. While we have experience in regulating dangerous technologies like nuclear and biological weapons, the regulation of AI will demand unprecedented levels of trust and self-discipline, for two reasons. First, it is easier to hide an illicit AI lab than an illicit nuclear reactor. Second, AIs have a lot more dual civilian-military usages than nuclear bombs. Consequently, despite signing an agreement that bans autonomous weapon systems, a country could build such weapons secretly, or camouflage them as civilian products. For example, it might develop fully autonomous drones for delivering mail and spraying fields with pesticides that with a few minor modifications could also deliver bombs and spray people with poison. Consequently, governments and corporations will find it more difficult to trust that their rivals are really abiding by the agreed regulations—and to withstand the temptation to themselves waive the rules.44 Can humans develop the necessary levels of trust and self-discipline? Do changes like those have any precedent in history?
Many people are skeptical of the human capacity to change, and in particular of the human ability to renounce violence and forge stronger global bonds. For example, “realist” thinkers like Hans Morgenthau and John Mearsheimer have argued that an all-out competition for power is the inescapable condition of the international system. Mearsheimer explains that “my theory sees great powers as concerned mainly with figuring out how to survive in a world where there is no agency to protect them from each other” and that “they quickly realize that power is the key to their survival.” Mearsheimer then asks “how much power states want” and answers that all states want as much power as they can get, “because the international system creates powerful incentives for states to look for opportunities to gain power at the expense of rivals.” He concludes, “A state’s ultimate goal is to be the hegemon in the system.”45
This grim view of international relations is akin to the populist and Marxist views of human relations, in that they all see humans as interested only in power. And they are all founded upon a deeper philosophical theory of human nature, which the primatologist Frans de Waal termed “veneer theory.” It argues that at heart humans are Stone Age hunters who cannot but see the world as a jungle where the strong prey upon the weak and where might makes right. For millennia, the theory goes, humans have tried to camouflage this unchanging reality under a thin and mutable veneer of myths and rituals, but we have never really broken free from the law of the jungle. Indeed, our myths and rituals are themselves a weapon used by the jungle’s top dogs to deceive and trap their inferiors. Those who don’t realize this are dangerously naive and will fall prey to some ruthless predator.46
There are reasons to think, however, that “realists” like Mearsheimer have a selective view of historical reality and that the law of the jungle is itself a myth. As de Waal and many other biologists documented in numerous studies, real jungles—unlike the one in our imagination—are full of cooperation, symbiosis, and altruism displayed by countless animals, plants, fungi, and even bacteria. Eighty percent of all land plants, for example, rely on symbiotic relationships with fungi, and almost 90 percent of vascular plant families enjoy symbiotic relationships with microorganisms. If organisms in the rain forests of Amazonia, Africa, or India abandoned cooperation in favor of an all-out competition for hegemony, the rain forests and all their inhabitants would quickly die. That’s the law of the jungle.47
As for Stone Age humans, they were gatherers as well as hunters, and there is no firm evidence that they had irrepressible warlike tendencies. While there are plenty of speculations, the first unambiguous evidence for organized warfare appears in the archaeological record only about thirteen thousand years ago, at the site of Jebel Sahaba in the Nile valley.48 Even after that date, the record of war is variable rather than constant. Some periods were exceptionally violent, whereas others were relatively peaceful. The clearest pattern we observe in the long-term history of humanity isn’t the constancy of conflict, but rather the increasing scale of cooperation. A hundred thousand years ago, Sapiens could cooperate only at the level of bands. Over the millennia, we have found ways to create communities of strangers, first on the level of tribes and eventually on the level of religions, trade networks, and states. Realists should note that states are not the fundamental particles of human reality, but rather the product of arduous processes of building trust and cooperation. If humans were interested only in power, they could never have created states in the first place. Sure, conflicts have always remained a possibility—both between and within states—but they have never been an inescapable destiny.
War’s intensity depends not on an immutable human nature but on shifting technological, economic, and cultural factors. As these factors change, so does war, as was clearly demonstrated in the post-1945 era. During that period, the development of nuclear technology greatly increased the potential price of war. From the 1950s onward it became clear to the superpowers that even if they could somehow win an all-out nuclear exchange, their victory would likely be a suicidal achievement, involving the sacrifice of most of their population.
Simultaneously, the ongoing shift from a material-based economy to a knowledge-based economy decreased the potential gains of war. While it has remained feasible to conquer rice paddies and gold mines, by the late twentieth century these were no longer the main sources of economic wealth. The new leading industries, like the semiconductor sector, came to be based on technical skills and organizational know-how that could not be acquired by military conquest. Accordingly, some of the greatest economic miracles of the post-1945 era were achieved by the defeated powers of Germany, Italy, and Japan, and by countries like Sweden and Singapore that eschewed military conflicts and imperial conquests.
Finally, the second half of the twentieth century also witnessed a profound cultural transformation, with the decline of age-old militaristic ideals. Artists increasingly focused on depicting the senseless horrors of combat rather than on glorifying its architects, and politicians came to power dreaming more of domestic reforms than of foreign conquests. Due to these technological, economic, and cultural changes, in the decades following the end of World War II most governments stopped seeing wars of aggression as an appealing tool to advance their interests, and most nations stopped fantasizing about conquering and destroying their neighbors. While civil wars and insurgencies have remained commonplace, the post-1945 world has seen a significant decline in full-scale wars between states, and most notably in direct armed conflicts between great powers.49
Numerous statistics attest to the decline of war in this post-1945 era, but perhaps the clearest evidence is found in state budgets. For most of recorded history, the military was the number one item on the budget of every empire, sultanate, kingdom, and republic. Governments spent little on health care and education, because most of their resources were consumed by paying soldiers, constructing walls, and building warships. When the bureaucrat Chen Xiang examined the annual budget of the Chinese Song dynasty for the year 1065, he found that out of sixty million minqian (currency unit), fifty million (83 percent) were consumed by the military. Another official, Cai Xiang, wrote, “If [we] split [all the property] under Heaven into six shares, five shares are spent on the military, and one share is spent on temple offerings and state expenses. How can the country not be poor and the people not in difficulty?”50
The same situation prevailed in many other polities, from ancient times to the modern era. The Roman Empire spent about 50–75 percent of its budget on the military,51 and the figure was about 60 percent in the late seventeenth-century Ottoman Empire.52 Between 1685 and 1813 the share of the military in British government expenditure averaged 75 percent.53 In France, military expenditure between 1630 and 1659 varied between 89 percent and 93 percent of the budget, remained above 30 percent for much of the eighteenth century, and dropped to a low of 25 percent in 1788 only due to the financial crisis that led to the French Revolution. In Prussia, from 1711 to 1800 the military share of the budget never fell below 75 percent and occasionally reached as high as 91 percent.54 During the relatively peaceful years of 1870–1913, the military ate up an average of 30 percent of the state budgets of the major powers of Europe, as well as Japan and the United States, while smaller powers like Sweden were spending even more.55 When war broke out in 1914, military budges skyrocketed. During their involvement in World War I, French military expenditure averaged 77 percent of the budget; in Germany it was 91 percent, in Russia 48 percent, in the U.K. 49 percent, and in the United States 47 percent. During World War II, the U.K. figure rose to 69 percent and the U.S. figure to 71 percent.56 Even during the détente years of the 1970s, Soviet military expenditure still amounted to 32.5 percent of the budget.57
State budgets in more recent decades make for far more hopeful reading material than any pacifist tract ever composed. In the early twenty-first century, the worldwide average government expenditure on the military has been only around 7 percent of the budget, and even the dominant superpower of the United States spent only around 13 percent of its annual budget to maintain its military hegemony.58 Since most people no longer lived in terror of external invasion, governments could invest far more money in welfare, education, and health care. Worldwide average expenditure on health care in the early twenty-first century has been about 10 percent of the government budget, or about 1.4 times the defense budget.59 For many people in the 2010s, the fact that the health-care budget was bigger than the military budget was unremarkable. But it was the result of a major change in human behavior, and one that would have sounded impossible to most previous generations.
The decline of war didn’t result from a divine miracle or from a metamorphosis in the laws of nature. It resulted from humans changing their own laws, myths, and institutions and making better decisions. Unfortunately, the fact that this change has stemmed from human choice also means that it is reversible. Technology, economics, and culture are ever changing. In the early 2020s, more leaders are again dreaming of martial glory, armed conflicts are on the rise,60 and military budgets are increasing.61
A critical threshold was crossed in early 2022. Russia had already destabilized the global order by mounting a limited invasion of Ukraine in 2014 and occupying Crimea and other regions in eastern Ukraine. But on February 24, 2022, Vladimir Putin launched an all-out assault aimed to conquer the whole of Ukraine and extinguish Ukrainian nationhood. To prepare and sustain this attack, Russia increased its military budget far beyond the global average of 7 percent. Exact figures are difficult to determine, because many aspects of the Russian military budget are shrouded in secrecy, but the best estimates put the figure somewhere in the vicinity of 30 percent, and it may even be higher.62 The Russian onslaught in turn has forced not only Ukraine but also many other European nations to increase their own military budgets.63 The reemergence of militaristic cultures in places like Russia, and the development of unprecedented cyber weapons and autonomous armaments throughout the world, could result in a new era of war, worse than anything we have seen before.
The decisions leaders like Putin make on matters of war and peace are shaped by their understanding of history. Which means that just as overly optimistic views of history could be dangerous illusions, overly pessimistic views could become destructive self-fulfilling prophecies. Prior to his all-out 2022 attack on Ukraine, Putin had often expressed his historical conviction that Russia is trapped in an endless struggle with foreign enemies, and that the Ukrainian nation is a fabrication by these enemies. In June 2021, he published a fifty-three-hundred-word essay titled “On the Historical Unity of Russians and Ukrainians” in which he denied the existence of Ukraine as a nation and argued that foreign powers have repeatedly tried to weaken Russia by fostering Ukrainian separatism. While professional historians reject these claims, Putin seems to genuinely believe in this historical narrative.64 Putin’s historical convictions led him in 2022 to prioritize the conquest of Ukraine over other policy goals, such as providing Russian citizens with better health care or spearheading a global initiative to regulate AI.65
If leaders like Putin believe that humanity is trapped in an unforgiving dog-eat-dog world, that no profound change is possible in this sorry state of affairs, and that the relative peace of the late twentieth century and early twenty-first century was an illusion, then the only choice remaining is whether to play the part of predator or prey. Given such a choice, most leaders would prefer to go down in history as predators and add their names to the grim list of conquerors that unfortunate pupils are condemned to memorize for their history exams. These leaders should be reminded, however, that in the era of AI the alpha predator is likely to be AI.
Perhaps, though, we have more choices available to us. I cannot predict what decisions people will make in the coming years, but as a historian I do believe in the possibility of change. One of the chief lessons of history is that many of the things that we consider natural and eternal are, in fact, man-made and mutable. Accepting that conflict is not inevitable, however, should not make us complacent. Just the opposite. It places a heavy responsibility on all of us to make good choices. It implies that if human civilization is consumed by conflict, we cannot blame it on any law of nature or any alien technology. It also implies that if we make the effort, we can create a better world. This isn’t naïveté; it’s realism. Every old thing was once new. The only constant of history is change.
Epilogue
In late 2016, a few months after AlphaGo defeated Lee Sedol and as Facebook algorithms were stoking dangerous racist sentiments in Myanmar, I published Homo Deus. Though my academic training had been in medieval and early modern military history, and though I have no background in the technical aspects of computer science, I suddenly found myself, post-publication, with the reputation of an AI expert. This opened the doors to the offices of scientists, entrepreneurs, and world leaders interested in AI and afforded me a fascinating, privileged look into the complex dynamics of the AI revolution.
It turned out that my previous experience researching topics such as English strategy in the Hundred Years’ War and studying paintings from the Thirty Years’ War1 wasn’t entirely unrelated to this new field. In fact, it gave me a rather unique historical perspective on the events unfolding rapidly in AI labs, corporate offices, military headquarters, and presidential palaces. Over the past eight years I have had numerous public and private discussions about AI, particularly about the dangers it poses, and with each passing year the tone has become more urgent. Conversations that in 2016 felt like idle philosophical speculations about a distant future had, by 2024, acquired the focused intensity of an emergency room.
I am neither a politician nor a businessperson and have little talent for what these vocations demand. But I do believe that an understanding of history can be useful in gaining a better grasp of present-day technological, economic, and cultural developments—and, more urgently, in changing our political priorities. Politics is largely a matter of priorities. Should we cut the health care budget and spend more on defense? Is our more pressing security threat terrorism or climate change? Do we focus on regaining a lost patch of ancestral territory or concentrate on creating a common economic zone with the neighbors? Priorities determine how citizens vote, what businesspeople are concerned about, and how politicians try to make a name for themselves. And priorities are often shaped by our understanding of history.
While so-called realists dismiss historical narratives as propaganda ploys deployed to advance state interests, in fact it is these narratives that define state interests in the first place. As we saw in our discussion of Clausewitz’s theory of war, there is no rational way to define ultimate goals. The state interests of Russia, Israel, Myanmar, or any other country can never be deduced from some mathematical or physical equation; they are always the supposed moral of a historical narrative.
It is therefore hardly surprising that politicians all over the world spend a lot of time and effort recounting historical narratives. The above-mentioned example of Vladimir Putin is hardly exceptional in this respect. In 2005 the UN secretary-general, Kofi Annan, had his first meeting with General Than Shwe, the then dictator of Myanmar. Annan was advised to speak first, so as to prevent the general from monopolizing the conversation, which was meant to last only twenty minutes. But Than Shwe struck first and held forth for nearly an hour on the history of Myanmar, hardly giving the UN secretary-general any chance to speak.2 In May 2011 the Israeli prime minister, Benjamin Netanyahu did something similar in the White House, when he met the U.S. president, Barack Obama. After Obama’s brief introductory remarks, Netanyahu subjected the president to a long lecture about the history of Israel and the Jewish people, treating Obama as if he were his student.3 Cynics might argue that Than Shwe and Netanyahu hardly cared about the facts of history and were deliberately distorting them in order to achieve some political goal. But these political goals were themselves the product of deeply held convictions about history.
In my own conversations on AI with politicians, as well as tech entrepreneurs, history has often emerged as a central theme. Some of my interlocutors painted a rosy picture of history and were accordingly enthusiastic about AI. They argued that more information has always meant more knowledge and that by increasing our knowledge, every previous information revolution has greatly benefited humankind. Didn’t the print revolution lead to the scientific revolution? Didn’t newspapers and radio lead to the rise of modern democracy? The same, they said, would happen with AI. Others had a dimmer perspective, but nevertheless expressed hope that humankind will somehow muddle through the AI revolution, just as we muddled through the Industrial Revolution.
Neither view offered me much solace. For reasons explained in previous chapters, I find such historical comparisons to the print revolution and the Industrial Revolution distressing, especially coming from people in positions of power, whose historical vision is informing the decisions that shape our future. These historical comparisons underestimate both the unprecedented nature of the AI revolution and the negative aspects of previous revolutions. The immediate results of the print revolution included witch hunts and religious wars alongside scientific discoveries, while newspapers and radio were exploited by totalitarian regimes as well as by democracies. As for the Industrial Revolution, adapting to it involved catastrophic experiments such as imperialism and Nazism. If the AI revolution leads us to similar kinds of experiments, can we really be certain we will muddle through again?
My goal with this book is to provide a more accurate historical perspective on the AI revolution. This revolution is still in its infancy, and it is notoriously difficult to understand momentous developments in real time. It is hard, even now, to assess the meaning of events in the 2010s like AlphaGo’s victory or Facebook’s involvement in the anti-Rohingya campaign. The meaning of events of the early 2020s is even more obscure. Yet by expanding our horizons to look at how information networks developed over thousands of years, I believe it is possible to gain some insight on what we’re living through today.
One lesson is that the invention of new information technology is always a catalyst for major historical changes, because the most important role of information is to weave new networks rather than represent preexisting realities. By recording tax payments, clay tablets in ancient Mesopotamia helped forge the first city-states. By canonizing prophetic visions, holy books spread new kinds of religions. By swiftly disseminating the words of presidents and citizens, newspapers and telegraphs opened the door to both large-scale democracy and large-scale totalitarianism. The information thus recorded and distributed was sometimes true, often false, but it invariably created new connections between larger numbers of people.
We are used to giving political, ideological, and economic interpretations to historical revolutions such as the rise of the first Mesopotamian city-states, the spread of Christianity, the American Revolution, and the Bolshevik Revolution. But to gain a deeper understanding, we should also view them as revolutions in the way information flows. Christianity was obviously different from Greek polytheism in many of its myths and rites, yet it was also different in the importance it gave to a single holy book and the institution entrusted with interpreting it. Consequently, whereas each temple of Zeus was a separate entity, each Christian church became a node in a unified network.4 Information flowed differently among the followers of Christ than among the worshippers of Zeus. Similarly, Stalin’s U.S.S.R. was a different kind of information network from Peter the Great’s empire. Stalin enacted many unprecedented economic policies, but what enabled him to do it is that he headed a totalitarian network in which the center accumulated enough information to micromanage the lives of hundreds of millions of people. Technology is rarely deterministic, and the same technology can be used in very different ways. But without the invention of technologies like the book and the telegraph, the Christian Church and the Stalinist apparatus would never have been possible.
This historical lesson should strongly encourage us to pay more attention to the AI revolution in our current political debates. The invention of AI is potentially more momentous than the invention of the telegraph, the printing press, or even writing, because AI is the first tool that is capable of making decisions and generating ideas by itself. Whereas printing presses and parchment scrolls offered new means for connecting people, AIs are full-fledged members in our information networks. In coming years, all information networks—from armies to religions—will gain millions of new AI members, who will process data very differently than humans. These new members will make alien decisions and generate alien ideas—that is, decisions and ideas that are unlikely to occur to humans. The addition of so many alien members is bound to change the shape of armies, religions, markets, and nations. Entire political, economic, and social systems might collapse, and new ones will take their place. That’s why AI should be a matter of utmost urgency even to people who don’t care about technology and who think the most important political questions concern the survival of democracy or the fair distribution of wealth.
This book has juxtaposed the discussion of AI with the discussion of sacred canons like the Bible, because we are now at the critical moment of AI canonization. When church fathers like Bishop Athanasius decided to include 1 Timothy in the biblical dataset while excluding the Acts of Paul and Thecla, they shaped the world for millennia. Billions of Christians down to the twenty-first century have formed their views of the world based on the misogynist ideas of 1 Timothy rather than on the more tolerant attitude of Thecla. Even today it is difficult to reverse course, because the church fathers chose not to include any self-correcting mechanisms in the Bible. The present-day equivalents of Bishop Athanasius are the engineers who write the initial code for AI, and who choose the dataset on which the baby AI is trained. As AI grows in power and authority, and perhaps becomes a self-interpreting holy book, so the decisions made by present-day engineers could reverberate down the ages.
Studying history does more than just emphasize the importance of the AI revolution and of our decisions regarding AI. It also cautions us against two common but misleading approaches to information networks and information revolutions. On the one hand, we should beware of an overly naive and optimistic view. Information isn’t truth. Its main task is to connect rather than represent, and information networks throughout history have often privileged order over truth. Tax records, holy books, political manifestos, and secret police files can be extremely efficient in creating powerful states and churches, which hold a distorted view of the world and are prone to abuse their power. More information, ironically, can sometimes result in more witch hunts.
There is no reason to expect that AI would necessarily break the pattern and privilege truth. AI is not infallible. What little historical perspective we have gained from the alarming events in Myanmar, Brazil, and elsewhere over the past decade indicates that in the absence of strong self-correcting mechanisms AIs are more than capable of promoting distorted worldviews, enabling egregious abuses of power, and instigating terrifying new witch hunts.
On the other hand, we should also beware of swinging too far in the other direction and adopting an overly cynical view. Populists tell us that power is the only reality, that all human interactions are power struggles, and that information is merely a weapon we use to vanquish our enemies. This has never been the case, and there is no reason to think that AI will make it so in the future. While many information networks do privilege order over truth, no network can survive if it ignores truth completely. As for individual humans, we tend to be genuinely interested in truth rather than only in power. Even institutions like the Spanish Inquisition have had conscientious truth-seeking members like Alonso de Salazar Frías, who, instead of sending innocent people to their deaths, risked his life to remind us that witches are just intersubjective fictions. Most people don’t view themselves as one-dimensional creatures obsessed solely with power. Why, then, hold such a view about everyone else?
Refusing to reduce all human interactions to a zero-sum power struggle is crucial not just for gaining a fuller, more nuanced understanding of the past but also for having a more hopeful and constructive attitude about our future. If power were the only reality, then the only way to resolve conflicts would be through violence. Both populists and Marxists believe that people’s views are determined by their privileges, and that to change people’s views it is necessary to first take away their privileges—which usually requires force. However, since humans are interested in truth, there is a chance to resolve at least some conflicts peacefully, by talking to one another, acknowledging mistakes, embracing new ideas, and revising the stories we believe. That is the basic assumption of democratic networks and of scientific institutions. It has also been the basic motivation behind writing this book.
EXTINCTION OF THE SMARTEST
Let’s return now to the question I posed at the beginning of this book: If we are so wise, why are we so self-destructive? We are at one and the same time both the smartest and the stupidest animals on earth. We are so smart that we can produce nuclear missiles and superintelligent algorithms. And we are so stupid that we go ahead producing these things even though we’re not sure we can control them and failing to do so could destroy us. Why do we do it? Does something in our nature compel us to go down the path of self-destruction?
This book has argued that the fault isn’t with our nature but with our information networks. Due to the privileging of order over truth, human information networks have often produced a lot of power but little wisdom. For example, Nazi Germany created a highly efficient military machine and placed it at the service of an insane mythology. The result was misery on an enormous scale, the death of tens of millions of people, and eventually the destruction of Nazi Germany, too.
Of course, power is not in itself bad. When used wisely, it can be an instrument of benevolence. Modern civilization, for example, has acquired the power to prevent famines, contain epidemics, and mitigate natural disasters such as hurricanes and earthquakes. In general, the acquisition of power allows a network to deal more effectively with threats coming from outside, but simultaneously increases the dangers that the network poses to itself. It is particularly noteworthy that as a network becomes more powerful, imaginary terrors that exist only in the stories the network itself invents become potentially more dangerous than natural disasters. A modern state faced with drought or excessive rains can usually prevent this natural disaster from causing mass starvation among its citizens. But a modern state gripped by a man-made fantasy is capable of instigating man-made famines on an enormous scale, as happened in the U.S.S.R. in the early 1930s.
Accordingly, as a network becomes more powerful, its self-correcting mechanisms become more vital. If a Stone Age tribe or a Bronze Age city-state was incapable of identifying and correcting its own mistakes, the potential damage was limited. At most, one city was destroyed, and the survivors tried again elsewhere. Even if the ruler of an Iron Age empire, such as Tiberius or Nero, was gripped by paranoia or psychosis, the consequences were seldom catastrophic. The Roman Empire endured for centuries despite its fair share of mad emperors, and its eventual collapse did not bring about the end of human civilization. But if a Silicon Age superpower has weak or nonexistent self-correcting mechanisms, it could very well endanger the survival of our species, and countless other life-forms, too. In the era of AI, the whole of humankind finds itself in an analogous situation to Tiberius in his Capri villa. We command immense power and enjoy rare luxuries, but we are easily manipulated by our own creations, and by the time we wake up to the danger, it might be too late.
Unfortunately, despite the importance of self-correcting mechanisms for the long-term welfare of humanity, politicians might be tempted to weaken them. As we have seen throughout the book, though neutralizing self-correcting mechanisms has many downsides, it can nevertheless be a winning political strategy. It could deliver immense power into the hands of a twenty-first-century Stalin, and it would be foolhardy to assume that an AI-enhanced totalitarian regime would necessarily self-destruct before it could wreak havoc on human civilization. Just as the law of the jungle is a myth, so also is the idea that the arc of history bends toward justice. History is a radically open arc, one that can bend in many directions and reach very different destinations. Even if Homo sapiens destroys itself, the universe will keep going about its business as usual. It took four billion years for terrestrial evolution to produce a civilization of highly intelligent apes. If we are gone, and it takes evolution another hundred million years to produce a civilization of highly intelligent rats, it will. The universe is patient.
There is, though, an even worse scenario. As far as we know today, apes, rats, and the other organic animals of planet Earth may be the only conscious entities in the entire universe. We have now created a nonconscious but very powerful alien intelligence. If we mishandle it, AI might extinguish not only the human dominion on Earth but the light of consciousness itself, turning the universe into a realm of utter darkness. It is our responsibility to prevent this.
The good news is that if we eschew complacency and despair, we are capable of creating balanced information networks that will keep their own power in check. Doing so is not a matter of inventing another miracle technology or landing upon some brilliant idea that has somehow escaped all previous generations. Rather, to create wiser networks, we must abandon both the naive and the populist views of information, put aside our fantasies of infallibility, and commit ourselves to the hard and rather mundane work of building institutions with strong self-correcting mechanisms. That is perhaps the most important takeaway this book has to offer.
This wisdom is much older than human history. It is elemental, the foundation of organic life. The first organisms weren’t created by some infallible genius or god. They emerged through an intricate process of trial and error. Over four billion years, ever more complex mechanisms of mutation and self-correction led to the evolution of trees, dinosaurs, jungles, and eventually humans. Now we have summoned an alien inorganic intelligence that could escape our control and put in danger not just our own species but countless other life-forms. The decisions we all make in the coming years will determine whether summoning this alien intelligence proves to be a terminal error or the beginning of a hopeful new chapter in the evolution of life.
这些变化对西欧的部落组织构成相当大的破坏。日耳曼、挪威、马札尔（Magyar）、斯拉夫的部落皈依基督教后，仅在两代或三代的时间就见证了其亲戚架构的解散。事实上，这种皈依植根于政治，如马札尔国王伊斯特万（István，或 St. Stephen）在 1000 年接受圣餐。但社会风俗和家庭规则中的实质性变化，不靠政治当局，而靠运作于社会和文化层次的教会。
举塞维涅夫人（Mme. de Sévigné）写给女儿的信为例，她是 17 世纪法国最著名的沙龙赞助人之一。这位聪明敏感的女子描绘，士兵在布列塔尼征集新税，把老人和孩子从家中赶出，再在屋子里寻找可供夺取的财产。因为不付税，大约六十名市民将在下一天上绞刑架。她继续写道：“那个手舞足蹈、想偷印花税纸的闲汉在车轮上就刑，被割成四块，分别在城市四个角落示众。”⑩
法治定义的混乱，其所造成的后果之一是富国设计的改善法治计划，很少在贫穷国家产生效果。⑪住在法治国家的幸运儿，往往不懂它如何首次涌现，误把法治的外表当作法治的实质。例如，“相互制衡”是强大法治社会的特征，政府各部门监督彼此的行为。但制衡的正式存在，并不等于强有力的民主统治。法庭可被用来阻挠集体行动，如当代印度，其冗长的司法上诉可拖死重要的基建项目。它又可被用来对抗政府的愿望，以保护精英利益。1905 年最高法院的洛克纳诉纽约州案（Lochner v. New York），其宗旨就是击败限制工时的立法，以保护企业利益。所以，分权的形式常常名不副实，与守法社会的主旨无法对应。
哈耶克在解说其法律起源理论时作出两项声明，一项是实证性的，另一项是规范性的。他主张在大多数社会中，法律以自发的进化方式发展，这种自然生成的法律应该优于有意识制定的法律。这一解释也是伟大的英国法学家爱德华·柯克（Sir Edward Coke）所推崇的，他认为普通法始于太古时代。埃德蒙·伯克（Edmund Burke）在为渐进主义（Incrementalism）辩护时，也援引此一解释。⑰哈耶克是强大国家的伟大敌人，不管是苏联风格的共产党专政，还是以再分配和调节来实现“社会公正”的欧洲社会民主政体。在法律学者罗伯特·埃里克森（Robert Ellickson）所谓的“法律中心论”和“法律外围论”的长久争论上，哈耶克立场鲜明地站在后者一边。前者认为，正式制定的法律创立和塑造了道德规则；后者主张，它们只是编纂了非正式的既存规范。⑱
与皇帝发生冲突时，格里高利和继承者没有自己的军队可以调动，只能通过呼吁合法性来加强自己的力量。于是，教皇派发动了一次对法律源头的搜索，以支持教会享有普遍司法权的主张。搜索结果之一是 11 世纪末，在意大利北部的图书馆内重新发现《查士丁尼法典》（Corpus Iuris Civilis）。⑩迄今，《查士丁尼法典》仍是民法传统的基础，不管是欧洲大陆，还是受其殖民或影响的其他国家，包括从阿根廷到日本。很多基本的法律常识，如民法和刑法、公法和私法之间的差别，都可从中找到起源。
教会在建制上趋向独立，更刺激了封建社会其他领域的集团组织。在 11 世纪，主教杰拉德·德·坎布雷（Gérard de Cambrai）和主教阿尔德贝隆·德·拉昂（Aldabéron de Laon）创立社会等级一分为三的原则：贵族、神职人士、平民——即打仗者、祈祷者、支持前两者的劳作者。这些功能组织与地域没有关系，其为三个代表阶层的形成打下意识形态的基础。统治者定期召集各代表阶层，以批准征税和讨论国家大事。如后续章节所显示的，欧洲国家今后发展的是负责制政府还是专制政府，将取决于这些阶层能否顶住中央君主的压力。㉒
天主教会在 12 世纪成为现代官僚机构，并颁布统一连贯的教会法规，但这离现代法治还很远。法治牢固的发达国家，向政府统治提供合法性的通常是书面宪法。但这套法律并不起源于宗教权威，事实上很多宪法规定，在牵涉宗教的道德问题上必须维持政治的中立。现代宪法的合法性来自某种民主的批准程序。这套法律可被看作扎根于永恒或普遍的原则之中，在亚伯拉罕·林肯看来，美国宪法就是一例。㉖但多数现代宪法对其合法性的最终来源都有点隐约其词。㉗从实用角度看，那些原则的解释仍然取决于政治上的争论。到最后，借民主取得合法性的行政和立法的机构，其权力仍然要受制于借民主取得合法性的宪法。后者取决于更严格的社会共识，如某种形式的超多数选举。在最近发展中，各国政府也要受制于跨国法律机构，如欧洲人权法庭（European Court of Human Rights）和国际战犯法庭（International Criminal Court）。不过，与国家层次的法庭相比，它们的合法基础比较暧昧。㉘包括以色列和印度的自由民主国家中，宗教法庭仍在家庭法上享有司法权。但这只是例外，宗教权威不得参与法律制度是普遍规则。
但这并不意味宗教和世俗权力之间没有功能的分离。图森·贝（Tursun Bey）写道，15 世纪的奥斯曼帝国，苏丹可在伊斯兰教法之外自行制定世俗法律。这套世俗法律叫作卡奴纳莫（kanunname，该词源自欧洲使用的 canon law [教会法]），用于传统伊斯兰教法鞭长莫及的领域，如公共和行政的法律。所征服领土的征税和产权、发行货币、贸易管理，全靠这套世俗法律。⑪传统的伊斯兰教法主要涉及婚姻、家庭、遗产和其他私人事务，由教法专家卡迪和穆智泰希德（kadis and mujtahids）执行。他们熟谙穆斯林经典，能将这一庞杂的法典应用到特定案例，很像印度的班智达。⑫这就需要平行的两套司法建制，一个是世俗的，另一个是宗教的。卡迪应用伊斯兰教法，但其裁决必须依赖世俗当局的执法。⑬
托克维尔（Alexis de Tocqueville）在《论美国的民主》中开门见山：过去八百年中，人人平等的思想在世界各地得到认可，这一事实是天赐的（providential）。①贵族的合法性——有人生来就高贵——不再是理所当然。没有奴隶的改变意识和寻求承认，主子和奴隶之间的关系就无法颠倒过来。这一思想革命有很多来源。所有的人，尽管在自然和社会的层次有明显差异，但在尊严和价值上却是平等的。这个概念是基督教的，但在中世纪教会的眼中，其实现并不在今生今世。宗教改革，加上印刷机的发明，赋予个人阅读圣经和追求信仰的权利，不再需要像教会那样的中介。始于中世纪晚期和文艺复兴时期，欧洲人已开始质疑既存权威，现在这种质疑得到进一步的加强。那时，人们开始重新学习古典文献。现代自然科学——从大量实证数据中提炼普遍规则，通过可控试验来测试因果理论——树立了新式权威，很快在各大学中获得建制化。它所孵化的科学和技术，可供统治者利用，但不受控制。
税赋制度的真正复杂性在于各种免税和特权。封建法国在中世纪晚期开发了两层会议的制度，一层是全国三级会议，另一层是一系列的地方或省级会议——又称为高等法院（sovereign courts, or parlements）——国王需要与之交换意见，以获得征收新税的许可。⑧为了鼓励各省加入法国的疆域，他授予省级会议特别的恩惠，承认地方精英的习俗和特权。税制因地区而有所不同，尤其是在财政区省和三级会议区省之间。贵族利用软弱的国王来为自己赢得各种豁免，从直接税到自产货物的消费税。这些免税和特权，开始自贵族向外扩散，抵达城市富有平民、皇家官员和各级地方官员等。赢不到免税的就是非精英者，即构成国家人口大多数的农民和工匠。⑨
代表地方精英利益的省级高等法院基本上是司法机构。跟全国三级会议不同，它们经常开会，可以成为对国王权力的制衡。国王如想颁布一项新税，就要来高等法院注册。高等法院通常举行公众讨论，遇上税务事项，会变得相当激烈。然后，高等法院可注册原封不动的法令，可修改，也可拒绝。不受欢迎的法令会在法庭上接受地方官员口头或书面的抗议。高等法院的权力很有限，因为国王可召开所谓的御前会议（lit de justice），将高等法院所拒绝的法令强行注册。⑳高等法院的抗议仅仅让国王蒙羞而已。
1648 年威斯特伐利亚和约（Peace of Westphalia）之后，该制度面临严重危机。其时，三十年战争的累计债款促使法国政府试图在和平时期继续战时的征税水平。巴黎高等法院的拒绝，最初导致马扎然打退堂鼓，从大多数的外省撤回总督。但高等法院领袖随后被捕，激起了所谓投石党（Fronde）的普遍叛乱。㉑从 1648 年到 1653 年，投石党运动分成两个阶段，代表了传统地方精英和贵族，对君主实施最终制裁，即武装叛乱。双方都有可能赢得内战，但到最后，政府政策激怒的各式社会参与者不能团结一致以取得军事胜利。
路易十四死于 1715 年，身后的君主政体债台高筑。为了减少负债，国家诉诸类似保护费诈骗的伎俩。它掌控名叫司法堂（chambre de justice）的特别法庭，然后威胁要调查债权人的私人财务。几乎所有债权人或多或少都涉及腐败，便同意降低政府的欠债，以交换调查的取消。㉘用选择性的反腐调查来筹集收入，或胁迫政治对手，这种策略时至今日仍然流行。
要发现不平等的来源很容易，其大部分都是承继下来的。很多古老精英的富有家庭是大地主，其祖先建立大庄园，又将之顺利传给后裔。很多拉丁美洲国家的财政制度，又使不平等得到进一步深化。经济合作与发展组织（Organization for Economic Cooperation and Development）的富裕国家，其财政制度主要用于从富人到穷人的再分配。它的实施可通过累进税制度（如美国），也可通过再分配政策，向低收入家庭提供资助和社会服务（如欧洲）。相比之下，拉丁美洲的财政制度只做很少的再分配，在某种情况下，再分配却给了相对优越的团体，像参加工会的公务员或大学生。正式领域的工人和各式精英，得以保住自己的福利和补助金。事实上，他们中的大多数在逃税方面相当成功。不像美国的累进个人所得税，拉丁美洲国家的税收很少来自个人。其富人擅长于隐藏自己的真正收入，或转移财产到海外，远离税务官的控制。这意味着，征税主要来自消费税、关税和增值税，落在穷人头上的便高得不成比例。
像其他西欧国家，法治扮演了重要角色，限制了西班牙国王在产权和公众自由方面的权力。跟北欧不同，罗马法的传统在西班牙没有完全消失。《查士丁尼法典》重现于 11 世纪之后，西班牙发展了颇为强大的民法传统，民法被视作神法和自然法的成文化。国王可颁布制定法，但新法典讲得很清楚，必须遵循既存的法律先例，与之相悖的皇家法令则没有效用。天主教会仍是教法的监护人，并经常向皇家特权挑战。与习惯权利和特权相抵触的皇家命令常常受到抵制，此举被称作“服从但不执行”（Obédezcase, pero no se cumpla）。赴新大陆的征服者（conquistadore），如果从总督辖区接到自己不喜欢的命令，经常援引此理。个人如不同意收到的皇家命令，有权向皇家会议提出申诉。后者像英国的对应物，享有西班牙的最高司法权。根据历史学家汤普森（I. A. A. Thompson），卡斯提尔的皇家会议信奉条文主义（legalism）和正当程序，反对随心所欲。它还主张相对于行政模式的司法模式，积极抵制非正常程序，始终保障既定的权利和契约义务。㉖
该法律传统的影响，体现在西班牙国王如何处置国内敌人和百姓产权。在西班牙，找不到秦始皇或伊凡雷帝（Ivan the Terrible）那样的帝王，他们会任意处决自己宫廷的成员，以至灭族。像同期的法国国王，西班牙君主在搜索财源中不断侵犯国人产权，但仍在现有法律的框架中运行。他们没有任意征用资产，只是重新谈判利率和本金的偿还表；不愿增税以造成对抗，只是使货币贬值，承受较高的通货膨胀。滥发货币的通货膨胀实际上也是一种税赋，但无须通过立法，对普通百姓的伤害超过精英，后者拥有的大多是实物资产，而不是货币资产。
西班牙当局移植罗马法律制度，在十处建立高级法庭（audiencia），包括圣多明各、墨西哥、秘鲁、危地马拉、波哥大。派去帮助治理殖民地的行政人士中，有很多是具丰富民法经验的律师和法官。行政人员不得与本地女子结婚，或在领地上建立家庭联系，很像中国的县令或奥斯曼帝国的桑贾克贝伊。历史学家约翰·赫克斯泰布尔·艾略特（J. H. Elliott）在评论殖民地政府时写道：“如果现代国家中的‘现代性’，指的是将中央权力的指令传达到遥远地区的机构，那么西班牙美洲殖民政府要比西班牙政府，甚至其他任何早期现代的欧洲国家，更为‘现代’。”㉙在这一方面，它与英国君主政体对北美殖民地的放任态度，形成鲜明的对比。
法国大革命得以在公共利益和私人利益之间重新划定明确界限。它没收所有捐官者的世袭财产和特权，谁反抗就砍谁的头。新式的政治制度，其公职的招聘基于非人格化的选贤与能——中国人在将近两千年之前就已发明的——又由马背上的拿破仑带往欧洲其他国家。1806 年，他在耶拿和奥尔斯塔特（Jena-Auerstadt）两次击败普鲁士的家族化军队，从而说服新一代的改革家，像冯·施泰因男爵（Baron vom Stein）和卡尔·奥古斯特·冯·哈登贝格（Karl August von Hardenberg），普鲁士国家必须以现代原则进行重建。㉟19 世纪的德国官僚机构，成为韦伯现代合理政府的模型。它并不来自家族化官僚，而是与传统的刻意分手。㊱
中央权力软弱的第一后果是蒙古人对匈牙利的掠夺。后者征服俄罗斯后，在 1241 年入侵匈牙利。⑮国王贝拉四世试图加强自己的力量，所以邀请大批异教库曼人（Cuman）进入匈牙利，反而激怒自己的贵族，后者因此拒绝参战。库曼人最后也没参战，匈牙利部队在蒂萨河之战（Battle of Mohi）中遭到彻底摧毁。蒙古人占领整个国家，得知大汗在蒙古过世消息之后，方才撤退。
莫斯科国家的权力基于服役贵族（middle service class），由骑兵组成，报酬不是现金而是封地（pomest’ia），每块封地上约有五或六户农家。由于地多人少，控制人口比控制土地更为重要。骑兵不是常备军，受领主召集而提供服务，军事季节结束后，再回到自己封地。俄罗斯和奥斯曼的封地非常相像，这可能不是意外。其时，俄罗斯与土耳其的接触愈益增多。像奥斯曼的骑士，俄罗斯部队的核心成员，如果身处欧洲其他地区，便被称作低层士绅，其土地和资源全部来自国家。俄罗斯骑兵配置相对轻便的装备，主要倚靠迂回战术。这很像奥斯曼骑兵，而迥然不同于西欧的重甲骑士。莫斯科政权组建此种部队的动机，也与奥斯曼相似。这个军事组织的地位全靠国家，不会要求现金军饷。它可被用来抵消领主和贵族的势力，后者拥有自己的土地和资源。⑧
俄罗斯国家建设的下一轮是在彼得大帝（1672—1725）治下。他迁都圣彼得堡，又从欧洲引进一大批新制度。彼得是个巨人，不论是体形，还是领导才能，单枪匹马尽力推行自上而下的社会改造。战争再次成为国家建设的主要动力，尤其是对抗瑞典的北方战争（Great Northern War）。彼得在 1700 年纳尔瓦战役中，败于瑞典皇帝查理十二世，遂开始对当时欧洲边界的俄军进行彻底重整，并从零开始打造海军（从最初的单船只舰发展到最终能够战胜瑞典海军的八百艘）。他也推行俄罗斯中央政府的现代化，废除老式衙门，换成模拟瑞典的参政院（a system of colleges）。参政院以技术专长为基础——大多来自外国——在辩论和执行政策方面发挥了特殊功能。
彼得大帝在 1722 年以官秩表（Table of Ranks）替换古老的门第选官制。每个国民都有自己的法定等级，以及相应的特权和义务。非贵族人员一旦升到足够的等级，不管是在官僚机构还是在军队，就可自动进入世袭贵族的行列。新鲜血液进入贵族，这很有必要，因为国家需要大批公职人员。官秩表确定贵族的集团身份，并加强其采取集体行动的能力。但它从不将自己视作君主政体的对手，因为其利益与国家紧密相连。㉒
具体地说，不同于主要代表卡斯提尔城市的西班牙议会，或贵族掌控的法国和俄罗斯的政治团体，英国议会不仅代表贵族和神职人员（世俗和精神的领主），而且代表广泛的士绅、市民和业主。这些平民是议会的灵魂和动力。英国议会强大到成功击败国王的诸多计划，包括增税、组建新军、躲避普通法。它还创建自己的军队，在内战中打败国王，将之处死，迫使继任君主詹姆士二世退位，拥戴来自欧洲大陆奥兰治的威廉（William of Orange）。到最后，统治英国的不是欧洲大陆那样的专制君主，而是正式承认议会负责制原则的立宪君主。英国议会获得如此进展，而欧洲其他地区的议会却四分五裂和软弱无能，或被拉拢收买，或主动支持君主专制，直到法国大革命前夕。有人自然要问，这是为什么？
到了 17 世纪的重大宪政危机时，不让君主破坏法治成了保卫英国自由的呐喊和议会团结以抗国王的源泉。出现于早期斯图亚特（1603—1649 年）的威胁是国王的星室法庭（Court of Star Chamber，其起源和司法权都很模糊），其为了“更有效地”起诉犯罪，而省去一般法庭的正常保护程序（包括陪审团的审讯）。在第二任斯图亚特国王查理一世（1600—1649）的治下，它带有更多政治性，不只是起诉犯罪，还用来对付假想的国王之敌。⑪
英国法律独立的更佳象征，莫过于爱德华·柯克爵士（1552—1634）。他是法学家和法律学者，最终升至王座法院（King’s Bench）的首席法官。他在各种法律职务中不折不挠，抵抗政治权威和国王对法律的侵犯。詹姆士一世试图将某些案件从普通法搬至教会法之下审理，柯克坚持说，国王没有足够权力来任意解释法律，从而引起极大愤怒。国王宣称，坚持国王在法律之下，无疑是叛国罪。柯克引用布拉克顿（Bracton）的话作答：“国王不应在人下，但应在上帝和法律之下（quod Rex non debet esse sub homine set sub deo et lege）。”⑫再加上其他的冒犯，柯克最终被解除一切法律职位，转而加入议会，成为反皇派领袖。
另一方面，即使有人主张冲突的主要原因不在宗教，但宗教在动员政治参与者和扩大集体行动范围上，仍然发挥重大作用。这在议会阵营，以及议会创建的新模范军（New Model Army）中，尤其如此。由于很多军官的宗教信念，随着时间的推移，新模范军变成反皇派激进主义的大温床。光荣革命期间，议会愿意接受奥兰治公国的威廉，以取代英国的合法君主詹姆士二世，就是因为前者是新教徒，后者是天主教徒。不然，真不好解说。
查理一世在 1629 年解散议会，开始了十一年的“亲政”，试图以议会为代价来扩展国家权力。这导致查理一世与议会对手在好多问题上发生争执，有的已在前面篇幅介绍过。议会中很多人不喜欢大主教劳德的专制国教，怀疑查理一世同情天主教，因为他有兴趣与法国和西班牙建立外交关系。宗教问题和保卫法治互相交融，星室法庭、高级专员公署（High Commission）、北方政务会（Council of the North）起诉反主教制（anti-Episcopal）的清教徒。清教徒传教士亚历山大·莱顿（Alexander Leighton），遭到星室法庭野蛮逮捕和残酷折磨，却得不到正当法律程序的保护，被认为是宗教和皇家权力肆无忌惮的滥用。
在本卷中，我一直使用亨廷顿对制度的定义，即“稳定、有价值、重复的行为模式”。⑯至于被称作国家的那个制度或机构（the institution called the state），我不仅使用韦伯的定义（在界定的领土上合法行使垄断暴力的组织），还使用他对现代国家的标准（按专门技术和技能合理地分工；使用非人格化的用人制度，对公民行使非人格化的权威）。非人格化的现代国家，不管是建立还是维持，都很困难。家族化——基于亲戚关系和互惠利他的政治用人——是社会关系的自然形式，如果没有其他的规范和鼓励，人类就会回归。
西方哲学传统中对“自然状态”的讨论，一直是理解正义和政治秩序的中心议题。而正义和政治秩序，又是现代自由民主制的基础。古典政治哲学把天性和惯例（或称法律）截然分开。柏拉图（Plato）和亚里士多德（Aristotle）主张，合理城邦必须存在，与之相匹配的是永久人性，而不是昙花一现和不断变化的人性。托马斯·霍布斯（Thomas Hobbes）、约翰·洛克（John Locke）、让—雅克·卢梭（Jean-Jacques Rousseau）给予这差别以进一步的拓展。他们撰写有关自然状态的论文，试图以此作为政治权利的基石。讨论自然状态，其实是讨论人性的手段和隐喻，用来建立政治社会应予培养的各级人性美德（a hierarchy of human goods）。
黑猩猩像人类群体一样，保卫自己的领土，但在其他方面又有很多不同。雄性和雌性不会组成家庭来抚养小孩，只是建立各自的等级组织。然而，等级组织中的统治权运作，又令人想起人类群体中的政治。黑猩猩群体中的雄性老大（Alpha Male），并不生来如此，像美拉尼西亚社会的头人一样，必须借建立同盟来赢得。体力虽然要紧，但最终还得依靠与他人的合作。灵长学家弗兰斯·德瓦尔（Frans de Waal），在荷兰阿恩海姆动物园观察驯养的黑猩猩群体。他叙述两只年轻黑猩猩，如何联手取代较年长的雄性老大。篡夺者之一，取得雄性老大地位后，即凶狠对待它曾经的同盟者，并最终将之杀害。⑮
男性繁衍战略是，寻求尽可能多的性伙伴，以取得最大成功。女性繁衍战略是，为自己后代谋求最佳的雄性资源。这两种战略，目的截然相反。所以有人认为，这在进化方面激励人类发展欺骗本领，其中语言扮演了重要角色。㉑另一位进化心理学家斯蒂芬·平克（Steven Pinker）认为，语言、社交能力、掌控环境都在相互加强，为精益求精而施加进化压力。㉒这解释了脑容量增加的必要，大脑皮层很大一部是用于语言的，它恰是行为意义上的现代人类（behaviorally modern humans）所独有的，而在黑猩猩或古人类身上是找不到的。㉓
规范被赋予内在价值后，便成为哲学家黑格尔（Georg W. F. Hegel）所谓“寻求承认的斗争”的目标。㉜寻求承认的欲望，截然不同于经济行为中获得物质的欲望。承认不是可供消费的实物，而是一种相互的主观意识。借此，个人承认他人的价值和地位，或他人的上帝、习俗、信念。我作为钢琴家或画家，可能很自信。如能获奖或售出画作，我会有更大的满足。自从人类把自己组织起来，进入社会等级制度后，承认往往是相对的，而不是绝对的。这使寻求承认的斗争，大大有别于经济交易的斗争。它是零和（zero sum），而不是正和（positive sum）。即某人获得承认，必然牺牲他人的尊严，地位只是相对的。在地位比赛中不存在贸易中的双赢情形。㉝
解剖学意义上的现代人类（anatomically modern humans）——其尺寸和体格特征，大致等同于现代人类——出现于约二十万年前。行为意义上的现代人类的出现，约在五万年前。他们能用语言进行交流，并开始开发较为复杂的社会组织。
依据时下的理论，几乎所有非洲之外的人，都是行为意义上的现代人类某群体的后裔。约在五万年前，这个其成员可能仅 150 人的群体离开非洲，穿越阿拉伯半岛的霍尔木兹海峡。虽然缺乏书面材料，但人口遗传学的最新进展，使古人类学家得以跟踪此一进程。人类的遗传，包括 Y 染色体和含历史线索的线粒体 DNA。Y 染色体归男性独有，余下的 DNA 则由母亲和父亲的染色体重组，代代有别。Y 染色体由父亲单传给儿子，基本上完好无损。相比之下，线粒体 DNA 是陷入人类细胞的细菌痕迹。数百万年前，它就为细胞活动提供能源。线粒体有它自己的 DNA，可与 Y 染色体媲美，由母亲单传给女儿，也基本上完好无损。Y 染色体和线粒体都会积累基因的突变，然后由后代儿子或女儿所继承。计算这些基因突变，弄清哪个在前哪个在后，人口遗传学家便可重建世界上不同人类群体的血统。
其他族团离开阿拉伯半岛后，朝西北和东北两个方向迁移。前者经过近东和中亚，最终抵达欧洲。在那里，他们遇上早先脱离非洲的古人类后裔，如尼安德特人。后者则在中国和亚洲东北部定居繁衍，再穿越其时连接西伯利亚和北美洲的陆地桥梁，最终南下至中南美洲。约在公元前一万二千年，已有人抵达智利南部。㊳ 巴别塔（Tower of Babel）的圣经故事称，上帝把统一联合的人类驱散到各地，令他们讲不同语言。在比喻意义上，这确是真相。人类迁移到不同环境，随遇而安，发明新的社会制度，开始退出自然状态。我们将在之后的章节看到，起初的复杂社会组织，仍以亲戚关系为基础，其出现全靠宗教思想的协助。
私人财产重要性的争论，大都牵涉所谓的“公地悲剧”（tragedy of the commons）。传统英国村庄，其放牧地由村庄居民集体所拥有，共同使用。但其资源是可耗尽的，常因使用过度而荒芜。将共有财产转为私人财产是避免荒芜的对策。业主甘心投资于维护，在持续基础上开发资源。加勒特·哈丁（Garrett Hardin）的著名文章认为，众多全球性的资源，如洁净空气和渔场等，都会遇上公地悲剧；如无私人产权或严格管理，将因过度消耗而变得一无用处。③
长期互惠所建立的互相忠诚，是凝聚力的非经济原因。部落社会向亲戚关系注入宗教意义和神灵制裁。此外，民兵通常由尚未成家、没有土地和其他财产的年轻人组成。他们身上荷尔蒙高涨，偏爱冒险生活，对他们而言，经济资源不是掠夺的唯一对象。我们不应低估，性和俘获女人在造就政治组织方面的重要性，尤其是在通常用女人作为交换中介的分支式社会。这些社会相对狭小，由于缺少非亲女子，其成员往往通过对外侵略来遵循异族通婚的规则。蒙古帝国的创始者成吉思汗，据称如此宣称：“最大的快乐是……击败你的敌人、追逐他们、剥夺他们的财富、看他们的亲人痛哭流涕、骑他们的马、把他们的妻女拥入怀中。”㊷在实现最后一项抱负上，他是相当成功的。根据 DNA 的测试，亚洲很大一块地区，其现存的男性居民中约有 8% 是他的后裔，或属于他的血统。㊸
弄清国家原生形成的条件是很有趣的，因为它有助于确定国家出现的物质条件。但到最后，有太多互相影响的因素，以致无法发展出一条严密且可预测的理论，以解释国家怎样形成和何时形成。这些因素或存在，或缺席，以及为之所作的解释，听起来像是吉卜林的《原来如此》（Just So Stories）。例如，美拉尼西亚的部分地区，其环境条件与斐济或汤加非常相似——都是大岛，其农业能养活密集人口——却没有国家出现。原因可能是宗教，也可能是无法复原的历史意外。
政治学家詹姆斯·斯科特（James Scott）在《国家的视角》（Seeing Like a State）一书中认为，所有国家都具备共同的特征：它们都试图掌控各自的社会，一开始就“昭告”天下。⑲它们清除自生自长的弯曲小街的旧区，代之以几何图形般秩序井然的新区，就是为此。19 世纪，奥斯曼男爵（Baron Haussmann）在巴黎中世纪废墟上建造宽敞的林荫大道，不单是为了美观，还有控制人口的动机。
印度—雅利安部落自黑海和里海（Caspian）之间的俄罗斯南部迁移至印度，由此开创了印度政治发展。某些部落群体转向西方，成为希腊、罗马、日耳曼和其他欧洲团体的祖先；另一群体朝南抵达波斯，第三群体向东到阿富汗东部，再穿越巴基斯坦西北部的斯瓦特峡谷（Swat Valley），直达旁遮普和印度河—恒河（Indo-Gangetic）分水岭。现在通过 Y 染色体和线粒体，可以追踪印度—雅利安群体之间的血缘关联，但首次确定相互关系的却是语言学家，他们在印度梵语（Sanskrit）和西方语言之间找出相似，因为它们同属更大的印欧语系。
宗教信仰所造成的迦提制度，创造了颇不寻常的组合，既有分支式的隔离，同时又有社会中的相互依赖。每个迦提成为世袭地位，以调整现存的宗族系统。迦提设置了氏族的异姓通婚的外限，在众多分支式单位中，又倾向于成为自给自足的社区。另一方面，每种职业又是更大分工的一部分，所以需要相互依赖，从高级祭司到葬礼工。⑧法国人类学家路易·杜蒙（Louis Dumont）引用布兰特（编按：E. A. H. Blunt，1877—1941，英属印度殖民地官员）的资料：
服务于宫殿的精英男孩，在宦官的监督下接受两至八年的训练。最为杰出的，再被派去托普卡帕宫（Topkapi），以获取进一步的调教，那是苏丹在伊斯坦布尔的居所。他们在那里攻读《古兰经》，学阿拉伯语、波斯语、土耳其语、音乐、书法、数学，还参与严格的体育锻炼，以及学习马术、剑术和其他武器，甚至要涉猎绘画和书籍装订。那些进不了宫殿的，则在皇家骑士队（sipahis of the Porte）中担任高级职位。③如果年轻的奴隶军人证明是强壮能干的，可逐步升级为将军、维齐尔（vizier，大臣）、外省总督，甚至是苏丹治下最高级的大维齐尔（grand vizier），即政府首相。在苏丹皇家军队服完役之后，很多军人会被安置在指定的庄园，靠居民的缴税而安享晚年。
为了防止军事机构中的小朝廷，遂定下有关孩子和遗产的严格规则。禁卫军的儿子不得加入禁卫军，在帝国早期，他们甚至不得结婚和组织家庭。皇家禁卫骑士（sipahis of the Porte）的儿子可加入骑士团队充任侍从，但孙子绝对不可。奥斯曼帝国似乎一开始就明白，军事奴隶制就是为了避免既得利益的世袭精英。军事奴隶制中的招收和晋升全靠能力和服务，他们的奖励是免税地位和庄园。⑪神圣罗马皇帝查理五世派驻苏莱曼一世（Suleiman the Magnificent）宫廷的大使布斯贝克（Ogier Ghiselin de Busbecq）提及，缺乏世袭贵族的事实允许苏丹挑选奴隶，全凭能力来提拔，“出身于牧羊人的杰出大维齐尔，欧洲评论家对他一直着迷不止”。⑫
阿诺德·洛贝尔(Arnold Lobel)的〈青蛙与蟾蜍》( Frog and Toad)童书系列中，便有一个这样的例子。在一则故事中，青蛙病得很重，蟾蜍想都不想便赶去营救他，这完全是出于同情心。蜍每天喂青蛙吃东西，照料他的起居，一直到他可以起床玩要为止。这个小故事提供给孩子们一个意义深远的范本，让他们知道了解别人的感受是什么意思，以及这如何成为互助的基础。 在另一本以河马为主角的故事书中也传达了人类似的概念，教导孩子们何谓共情。在詹姆斯·马歇尔(James Marshall)著名的系列书籍《乔治和玛莎》( George and Martha)中，有两只可爱的河马，他们是最好的朋友。在每一个故事里，他们都教导孩子如何做一个很好的、能够理解他人的朋友。其中有这样一个故事:有一天乔治被绊倒了，摔掉了他的两颗大门牙。门牙对河马来说非常重要，在换成金牙以后，他都不敢给玛莎看，但是善解人意的玛莎对他说:“乔治你帅呆了，你的新牙齿让你看起来与众不同!”乔治立刻就高兴起来了。
格施温德对于儿童大脑发育到何时才该学习阅读的结论，得到了许多跨语言研究的大力支持。英国阅读研究者乌莎·戈斯瓦米(Usha Goswami）的研究团队进行的跨语言研究引起了我的注意。他们的研究涉及3种不同的欧洲语言，结论是欧洲5岁开始学习阅读的儿童，并不比7岁开始学习阅读的儿童优秀多少。从这项研究中我们可以知道，花许多功夫教导4至5岁的儿童读书识字，从生物学角度来看，其实是揠苗助长，在许多儿童身上可能会收到相反的效果。 到底何时才准备好阅读，就跟人生一样，总是充满意外。在哈珀·李(Haper Lee)的《杀死一只知更鸟》( To Kill a Mocking bird)里，有个5岁之前就学习阅读的小女孩。故事中的斯考特(Scout)，能读出所有视线中的东西，这种超常能力吓坏了她的新老师: 我读字母表时，她的眉头皱了起来。在叫我大声读出《我的初级读本》( My First Reader)与《莫比尔注册报》( Mobile Register)上的股市摘要后，她发现我识字，反而以更厌恶的眼神看我。卡罗琳小姐让我和爸爸说不要教我了，这样会干扰我的阅读。我从来没有想要学阅读……阅读是突然降临到我身上的……我不记得是何时，在阿提克斯移动的手指上方的那些线条变成一个个文字，在我的记忆里，每个夜晚，我都坐在阿提克斯的腿上，注视着这些文字，听他念每一个字。我从不喜欢阅读，直到我开始害怕会错过他念的东西。就像没有人喜欢呼吸一样。
除写字之外，还有其他同样具有娱乐性的方式也能帮助儿童音位意识的发展。鹅妈妈童谣便是一个极好的例子。“钟声滴响，老鼠爬上钟’(Hickory, dickory dock, a mouse ran up the clock!)这一句中的韵律，以及其他的韵律形式，如头韵、类韵、尾韵与重复等，都有助于语音意识的发展。头韵与韵律告诉儿童，单词会因头尾字母相同而有类似的发音。当你第一次听孩子们讲笑话时，马上会被他们古怪的韵律吓到。像小熊维尼，孩子们喜欢一遍遍地重复“配对”的声音(例如：Funny bunny, you’re funny bunny honey!)，仅仅是因为他们喜欢这样的韵律。 同样重要的是，开始区分成对语音的儿童也开始将文字划分成几个部分。四五岁的儿童正在学习辨别单词的首音(如Sam的S)与韵脚(如Sam的am )，识别单词内的每个音位有助于阅读的学习，但这个漫长而重要的过程才刚开始。
意大利瓦尔道尔契亚(Val D’Orcia)的侯爵夫人艾丽斯·奥里戈(Iris Origo)是位历史学家，常常引用鲁默·高登(Rumer Godden)的话来描述她20世纪初在意大利佛罗伦萨学习阅读的经历。安娜·昆德伦(Anna Quindlen)则生动地描述了20世纪中期在费城学习阅读的场景。牙买加·金凯德(Jamaica Kincaid)在她那本《我母亲的自传》( The Autobiograph of My Mother)中捕捉到在加勒比海的安提瓜岛(Antigua)那里，童年的阅读对女孩子意味着什么。确实，金凯德小时候表现出来的阅读天分让老师相信她是个天才。 在这些女作家之间虽然有着时空和文化的差异，但有一个共同点将她们和每一个爱书的人联系起来。这个共同点也发生在我的经历中，当我在伊利诺伊州的埃尔多拉多学习阅读的时候，我在书中发现了另一个平行于这个世界的宇宙，就是奥里戈所谓的“再也不会感到这么寂寞”的世界昆德伦的“完美的岛屿”，并且认识到金凯德“往返家园的道路后面，还有另一个世界”。 用“拼写闹刷”(orthographic irony)来形容我家乡小镇名称的由来再恰当不过。在19世纪中期，埃尔德(Elder)和里德(Reeder)两人从城市里请来一位画家,想要为他们在的伊利诺伊州南方共同创立的这个小镇“艾尔德里德”( Elderreeder)画一个标志，用来欢迎每一个路过的人。自以为受过良好教育的画家自作聪明地更正了镇名，他认为这是政府人员的拼写错误。最后他将欢迎标志改成了“埃尔多拉多”(Eldorado)。也许是因为这个标志做得很好看，也许是因为没有钱再买一个，又或许是因为这个名称对小镇的人们来说，唤起了一些先前不可言表的梦想;不管怎样，这个名字就这样定了下来。一个世纪之后，我就在这个小镇长大。
很少有比看着儿童学会识字，阅读书本上的文字并且理解一个故事更窝心、更愉快的时刻。不久前，我和一位名叫阿梅莉亚(Amelia)的小女孩一起坐在地板上,她十分害羞,就像森林里的小动物一样。她还不会读书也很少说话，更不可能在我这样的访客面前大声念出任何句子。 但是那天注定有事情发生。阿梅莉亚跟往常一样，盯着“猫猫坐在毛毯上”( The cat sat on the mat.)这个短短的句子很长一段时间。她看起来像是一头吓坏了的小鹿。然后,缓慢但很完美地,她口齿清晰地念出了这些字她抬头望望我的眼睛，眉毛开始上扬。然后她开始念出下一个短句，接着再一句，每念完一句都会看看我，寻求确认。念完整个故事，她笑得合不拢嘴，也不再看我以寻求支持。她可以阅读了，她自己明白了这一点。阿梅莉亚的家里没什么书让她阅读，这往后的路恐怕很漫长，但是至少她开始阅读了。 不论阅读的必要条件准备得如何，成长的文字环境如何，老师的教学方法是什么，对阿梅莉亚以及所有的初级阅读者来说，这时候的任务就是破解文字，并且了解其含义。要做到这一点，每个孩子都必须弄清楚几千年来我们的祖先所发现的拼音规则，以及这一路上林林总总的其他发现。
There once was a beautiful bear who sat on a seat near to breaking and read by the hearth about how the earth was created. She smiled beatifically, full of ideas for the realm of her winter dreams.
这一堆 ea 双元音的各种发音解释了有些教育者在教英语拼写时的无奈心理，让儿童自己在文章中学习一切，尽管这样做没什么效果。但是如果你仔细考虑一下整个单词中的字母组合，你就会发现一些常见的规律。举例来说，当ea后面接r时，通常只有两种可能(如bear与dear)，但是后面接m、n、p或t时，通常仅有一种可能。对半流畅型的解码级阅读者来说，这一阶段最主要的任务是学完组合后的字母模式，从入门程度进展到认识组成单词的元音字母的“视觉组块”。此外，他们得学会自动目测出这些区别。 “视觉单词”为初级阅读者的成就添加了重要元素，而视觉组块则会促进处于半流畅阶段的解码级阅读者的发展。儿童看出beheaded是be+head+ed 组合的速度越快，辨别文字的能力也越强，越能将这些词语整合起来。顺便说一下，在进行下一阶段阅读时，这一现象比你想象的还要多很多。
半秒钟几乎就是专家级阅读者花在辨认出任何单词上的时间。在迈克尔·波斯纳与其他许多认知神经学家的研究基础上，我现在画出完全进入专家级层次的阅读脑运作过程的时间轴（见图6-3）。因 为阅读中的各种过程都是相互作用的，任何一种将阅读线性化的概念（如时 间线）都必须经过质化。有些是平行发生的，有些是先激活，然后在需要将 增加的概念信息进行整合的时候再次激活。举个例子，观察你在阅读下面这 句话时发生了什么，“船头被一个巨大的红色弓形物体所覆盖”（The bow on the boat was covered by a huge red bow.），大多数人在boat获得额外的概念性信息后，不得不回头第二次读再次激活这个单词，以判定词义。
人对一个字的认识总是不断地演进着，对阅读者来说如此，对研究它的科学家来说也是如此。一些认知神经科学家在语义处理的阶段追踪了字词的各种意义与关联被激活时，大脑电流活动的情况。举例来说，我在塔夫茨的同事菲尔·霍尔库姆(Phil Holcomb)研究我们如何处理前后文意不协调的句子(如“龙虾吞下了一条美人鱼”)。他运用一种称为“诱发反应电位”的技术，结果发现在我们读到前后不协调的字眼(如“美人鱼”)后的 200~600 毫秒之间，大脑爆发了大量电流活动，在400毫秒时达到顶点。这类研究为我们提供了两点关于时间轴的信息：首先，这表示对一般阅读者来说，第一次提取语义信息的时间为200毫秒左右;其次，这显示出若是文字和我们预期的语义不一致，我们会一直增加信息，特别是在400 毫秒左右时。 不论是在童年，还是专家级的阅读时期，我们对一个词所确立的知识越多，阅读的正确性就越高，速度也越快。想想在前几章中读到的这个吓人的单词——“语素音位”(morphophonemic)。在你阅读本书之前，这个单词可能会降低你的阅读速度。但是现在，它所引发的知识会加速你的识别与理解。我们阅读一个词的速度可以有多快，很大程度上是由伴随着这个词被激活的、我们所拥有的语义知识的数量和质量来决定的。就跟童年的早期阶段一样，成人的词汇知识也是一个连续统一体，从未知到认识再到熟练。 至于一个词到底位于统一体上的哪个位置，则取决于它的频率(在文本中出现的次数)个人的熟悉程度与接触时间的早晚。想想“冗长的单字”（sesquipedalian)这个词，正如散文家安妮·法迪曼(Anne Fadiman)所说:这个词看起来就像是一个“长的单词”，的确是这样。在她的《一个普通读者的自白》( Confessions of Common Reader)中，法迪曼列举出了-串可以测试任何专家级阅读者勇气的稀有单词:基督一性论者monophysite)、有毒的(mephitic)、全协和音(diapason)、容易打开的(adapertile)与巫技(goetic)是少数几个打败我的单词。法迪曼的单词便是在文字熟悉度的连续统一体的最底端，削低我们的效率，即便这个词当中有我们极其熟悉的词素，也只是在用一线希望折磨我们。 芬兰的研究人员发现处理语音与语义时都会用到上颞叶区域，若是遇到连续统一体中“已构建好”的那端的单词，激活的速度就会更快。而且如前所述，一个字的语义“邻居”(相关的单词和意义)对我们单词知识的贡献越丰富，辨认一个词的速度也越快。此原则适用于各年龄层的人:你对一个词的认识越好，你知道得越多，那么你读得越快。此外，拥有一个联系丰富的、已经构建好的词汇和语义网络也会直接反应在大脑结构上:在 200~500毫秒之间，这片广泛分布的网络反映出将要负责处理听觉的各种语音过程和精密的语义网络。激活的网络越多，大脑阅读这个单词的整体效率也越高。
语言——语法与词法进程
与语义过程一样，语法信息在200毫秒后的某个时间点，似乎会自动地使用额叶的区域，如布洛卡区、左半脑的颞叶区以及右侧小脑。语法过程几乎都是与相联系的文本(如句子或是段落)一同使用，通常需要一些前后回馈的操作(好像在读 the bow on the boat这个短语时所用到的)，以及一定程度的工作记忆的运用。bear与bow这类单词在语法上具有模棱两可的信息，需要段落或句子的上下文来传达更多的信息。
一旦开始了解大脑阅读一个单词所需的条件，我们就不禁要问，我们究竟是怎样阅读整句话、整个段落的，更不用说整本书了。要了解这些我们需要从词语的时间轴上移开，考虑一下阅读以及理解《白鲸记》、物理学家史蒂芬·霍金的《时间简史》以及进化生物学家肖恩·卡罗尔(Sean Carroll)的《蝴蝶、胚胎与斑马:探索演化发生学之美》(Endless Forms Most Beautiful)时激动人心的成就感。
正如过去的研究者所假设的那样，在这些图像中，大脑使用枕叶-颞叶区(37区)的固有物体识别路径来命名字母与物体。功能性核磁共振成像(fiunctional magnetic resonance imaging,fMRI)支持这些研究人员的假设:人类的确是“神经元再利用”者。不过这些图像告诉了我们一个更为重要的故事反映出字母与物体之间的3个差异。
因此，阅读革命是同时基于神经元与文化的，而且始于第一个综合性文字系统的出现，而不是第一套字母文字。它所增进的书写效率与释放出的记忆，有助于新思维的形成，神经系统也是如此建立阅读系统的。学会重塑自身结构来阅读的大脑，更容易产生新的想法;阅读与书写促进智力技能日益复杂化，这又增加了我们的智能储备库，而且会持续增加。关于上述讨论，我们必须反思这样一个问题:哪些技能是不会出现在口语文化中，而必须靠文字来提升的?在创造出最早的代币符号后，紧接着是第一套会计系统，伴随而来的是要获取更多更好的信息而提升的决策力。因此，很明显第一套已知的符号(除了洞穴里的壁画)是服务于经济的。 最初的综合性文字系统，即苏美尔人的楔形文字与埃及人的象形文字将简单的会计转变成系统性的文献记载，引发出具有组织性的系统与编码从而加速了智能的重大提升。到了公元前2000年，阿卡德语的文献就开始对整个已知的世界进行分类，例如百科全书式的《关于宇宙万物》(AIThings Known in the Universe )、法律经典著作《汉谟拉比法典》，以及其他各种著名的医药文献。就连科学方法本身，都是源自于我们祖先日益成长的记载、编撰与分类的能力。 在许多地方都可以找到语言意识增进的证据，开始于苏美尔人教导阅读的方式。他们在“泥板屋”所用的方法对于词汇不同特性的高度认知有一定的贡献:例如，词语间多重语义或意义间的关系;不同的语法功能;词语内部组成的结合性，可以用已有的词根与词素组成新的词语;以及方言间、语言间不同的发音。 苏美尔的年轻人痛苦地将老师刻在泥板上的一列列文字复制到另一面。这一过程不仅对语言意识的渐进发展极有帮助，也对思考本身贡献良多。几个世纪以后，我们从阿卡德人的文献，如《吉尔伽美什史诗》《悲观主义的对话》，与其他许多保存下来的乌加里特文献中了解了这些成长中的小学生的感受、想法、尝试与喜悦，走入了他们的内心世界。这些古老著作正是超越时间的见证，见证着现在我们经常思考到的现代意识的出现。 很少有学者比耶稣会文化史学家沃尔特·翁更鲜活地表现出读写能力对于古代世界的意识出现有何贡献。在他毕生对口语和读写能力关系的研究中，沃尔特·翁重新构建了阅读对人类独特贡献的问题，这可能有助于我们思考目前正转移到数字化交流模式的问题。20年前，沃尔特·翁就主张人类智能进化的真正争议点不在于一种文化模式所推动的交流技巧比另一种先进，而是人类在两者间转换的能力。沃尔特·翁曾写过一段很有先见之明的文字:
忠言逆耳，因此很难传开。这篇论文的作者也许是对的。但是这样的衰退其实有很多原因:有些是社会的，有些是政治的，还有些是认知的。许多学生从小就接触这些比较不费力的互联网，可能还不懂得如何自己思考。他们的视野狭窄，仅仅局限在可以迅速容易地见到和听到的事物上，他们也没有什么动力去思考我们这个最新最复杂的“盒子”之外的事物。这些学生并不是文盲，但是他们可能永远无法成为真正的专家级阅读者。在他们阅读发展的这个阶段，当阅读的关键技能被引导、塑造、练习与磨炼时，他们可能从来就不需要挑战阅读脑完全发展的顶端:自己思考的时刻。 每个和儿童教育有关的人——父母、老师、学者、政策决定者，都需要确保从出生到成年的阅读过程或者教学过程的每个环节，都已经理智慎重、明确地准备好了。从入学前词语组成里最小的语音到诠释艾略特在《小吉丁》( Little Gidding)中微妙的推论，这当中没有一种知识是理所当然就有。
J.R. 麦蒂考特所写《英国议会的起源》 (Origins of the English Parliament) 堪称此一领域杰作。他在书中将贤人会议和其他欧洲议会 进行比较，得出结论：无论在代表构成、税收的决定权，还是其存在方 式上，贤人会议与其他会议都有着质的不同。他说：“在西方世界其他 地区，日耳曼式的立法传统到10世纪时已告终结。而这一传统在英格兰 得以保存并发展，实在是罕见的特例。”贤人会议不仅是王室立法的伙 伴，同时也是那些有可能制约国王的制定法的守护者。麦蒂考特说：“在英国例外论这一点上，不存在任何疑议。”
可以说，布莱克斯通和洛克一样，也是美国革命的教父。他的巨著 《英格兰法释义》 (Commentaries on the Laws of England) 被称为继 《圣经》之后十三个殖民地拥有读者量最多的书，每个律师都在自己的 公事包里备了一本。事实上，北美对《大宪章》的热情始终比英国人更 高(扬基佬在那时候就和现在一样，喜欢把《大宪章》这个词当做一个 特定名词)。
早在1687年，北美大陆就首次印行了《大宪章》副本。该副本收录 于威廉 ·佩恩(William Penn)所著的《论自由与财产权之优越性：作为生而自由的英国臣民的天赋权利》 (The Excellent Privilege of Liberty and Property:being the birth-right of the Free-Born Subjects of England)一书。威廉 ·佩恩是宾夕法尼亚殖民地的创始人，他毫不怀疑正是《大 宪章》将英语民族和世界上其他国家区别开来。
3马姆斯伯里的威廉(William of Malmesbury,约1080/1095—约1143),12世纪英国历史学家，在1120年前后创作了《盎格鲁国王史》,记载从449年到 1120年间，英国国王事迹或者英国人的国王的事迹。该书被认为是英格兰最重 要的历史著作之一，以有说服力的文档资料和清晰生动的写作风格而留名。
不妨看看平等派在他们的宣言《英格兰自由人民协议》 (An Agreement of the Free People of England) 中提出的主张： 国会无权制定法律限制或者阻碍任何人进行贸易或者交易….国会也无权 继续统配任何种类的食物及其他商品、货物。前述两种做法都是对贸易的极度 负担和压制…..我们一致同意并宣布：任何代表均无权改变一个人的等级，剥 夺人的财产权，或者做其他类似的事情。
1689年，不列颠面临的最迫切的事就是要有一部成文宪法，一部与 后来的北美继承者相似的权利法案。与《大宪章》不同，1689年英国《权利法案》 (the 1689 Bill of Rights)被普遍视为一个宪法性解决方案。并且，也与《大宪章》不同，《权利法案》所提供的议会主权的机 制远远超越了此前的御前咨商会。因此，我们有必要花点时间来重温一 下反对斯图亚特王朝的斗争——是它第一次把英语民族联合在了一起， 并且为我们留下了议会政体。
詹姆斯国王对王权绝对主义充满狂热。在他的政论集《自由君主制的真正法律》(The Trew Law of Free Monarchies,1598) 和《王权》(Basilikon Doron,1603)中，詹姆斯提出了“君权神授”理论。没有人敢质疑这位放言无忌的国王如此直陈自己的观点：“君主制国家是世界 上最高的事物。国王不仅是上帝在尘世的代理人，端坐于上帝的宝座， 而且他们本人就是被上帝亲口所称的上帝。”
接下来的冲突横扫了所有讲英语者居住的王国。在苏格兰，主教战 争让位于盟约派与保皇党之间的内战，后者得到了爱尔兰军队的支持。 而在爱尔兰，教派冲突更为激烈，演变为联合战争(有时又被称为十一 年战争)。这场战争终结于英格兰和苏格兰方面的两线入侵，以及至今 想来仍叫人不寒而栗的大屠杀。至于英格兰境内，则先后发生了两场以 恢复君主制为目的但以破产而告终的战争，第一场苏格兰人支持国会， 第二场却支持国王。很多历史学家喜欢将这系列交错的战乱称为三国之 战 (Wars of the Three Kingdoms,威尔士那时是英格兰的一部分),尽 管将它们视为第一次盎格鲁圈内战更为准确。
1689年2月，议会起草了《权利宣言》(Declaration of Right)。当 年晚些时候，这一宣言成为议会的正式立法，也就是我们现在所称的《英国权利法案》(English Bill of Rights)。以今人的眼光看，它的形 式和内容都非常接近于《独立宣言》和美国宪法的先声- 尽管法案的 起草者并不是在向前看，而恰恰是往回看，从17世纪40年代的各种请愿 书，最终回到《大宪章》上。
所有这些研究成果后来都凝结在菲利普斯1990年出版的《表亲战争：宗教、政治以及盎格鲁的胜利》 (The Cousins’Wars:Religion, Politics,and the Triumph of Anglo-America) 一书中。该书揭示的中心议 题是，英国内战、美国革命和美国内战是同一场持续冲突的三次爆发。 这一观点一经如此直截了当地说出来，总让人觉得有点不踏实。但菲利 普斯是做了很多功课的。他考察了三场战争中若干教会团体，甚至是个 人及家庭，发现了其中一以贯之的政治延续性。要知道，一个有说服力 的新观点的标志往往是：尽管最初看上去有点别扭，但最后会被证明是 显而易见的。一旦我们把美国革命理解为是一场内战，那么,很多问题都会水落石出、各归其位了。
殖民地流传最广的历史著作——纳撒尼尔 ·培根 (Nathaniel Bacon)的《统一的英格兰政府的历史讲稿》(Historical Discourse of the Uniformity of the Government of England)、亨利 ·卡尔 (Henry Care) 的《英国的自由》(English Liberties)、卡姆斯勋爵 (Lord Kames)的《古代英国》(British Antiquities)——讲述的都是同样的故事：1066 年，一个自由的民族因为大陆入侵者丧失了自由，其后就是为了恢复自 由而进行斗争的历史。甚至就在美国独立期间，有一些明知自己没有英 国祖先的美国人仍然热衷于为自己购得一个盎格鲁——撒克逊政治身份。
但是将盎格鲁圈视为扩大版的盎格鲁——撒克逊国家的最大问题，在 于印度就无处可放了。泛大不列颠的一些支持者公然断言印度永远不可 能加入，因为如克莱武所宣称，他们从根子里就是独裁、腐化和贪图享 受的。与集中保留了不列颠辉格党式民主文化的殖民地不同，印度被认为只适合威权统治。因此，正如历史学家J.R.西莱在他的《英格兰的扩 张》 (The Expansion of England)中所说：“当我们问泛大不列颠未来如 何时，我们必须更多地考虑我们的殖民地，而不是印度帝国。”
奥巴马从没见过他爷爷，但他后来了解到的家族史使他很受震撼。 尽管盎扬戈被英国当局拘捕，但他还是保留了一个帝国主义者的立场， 相信英国在肯尼亚的高层机构应有一席之地。盎扬戈常常提到，非洲人 太懒了，根本不可能争取到独立。为此，年轻的奥巴马感到很震惊。“我想象他是他的民族的一分子，反对白人的规则。”他在自传《我父亲的梦想》(Dreams from My Father) 中写道，“奶奶告诉我的故事完全颠覆了我过去的印象，那些丑陋的字眼在我的脑海不断闪现：汤姆 大叔，投敌者，顺从的黑奴”。
但是，且让我在此提醒读者，傅利曼可不是个简单的人物。他的正统利伯维尔场论述在多数领导企业的董事会中仍是主流，就连那些从美国政府手中赚进大量利润的公司也不例外──此外还有商学院，甚至是公立的商学院。至今美国商会（US Chamber of Commerce）仍奉傅利曼的正统学说为圭臬。因此，美国与其他自由经济的民主国家往往不会承认，我们和利伯维尔场思想在本质上是恐怖情人般的关系，我们以为利伯维尔场能创造财富与带来革新，但现实中却不断上演各种无止尽的循环：法规松绑、债务危机、破产、诈欺与市场崩溃，随之而来的是政府纾困、日益严重的垄断、财富不均与政治不稳定。于是，我们一次又一次地因为矛盾且自扯后腿的政策而回到原点。我们正步入关键新世纪，即将要面对各种经济挑战，为此我们必须去理解“利伯维尔场”这个词汇的意义、它的历史，它何时能顺利运作，以及何时无法。5
如果傅利曼是利伯维尔场的拥护者最喜爱的儿子，那么十八世纪的苏格兰哲学家亚当斯密（Adam Smith）就是这个传统的父亲。然而，将亚当斯密视作傅利曼式放松管制、不受约束的利伯维尔场之拥护者，这样的现代概念并不完全准确。斯密的论述早已被错误理解、错误引用，脱离了他著述的十八世纪背景脉络并沦为陈腔滥调，但他的著作仍提供了宝贵的经验，让我们理解如何看待经济学。在斯密于一七七六年撰写《国富论》（The Wealth of Nations ）之前，从没有人把规模这么大又这么复杂的经济体与社会体，视为一个巨大的、自我调节的财富创造系统。不过，斯密也认为政府与其机构在市场中扮演了重要角色。在他看来，让市场以绝佳状态运作的状况，就是品德高尚的斯多噶领袖──他们通晓希腊与罗马哲学中透过自知与纪律追求幸福的理念──和富有的地主并肩合作，共同主导政治与市场，制定适当的指导、诱因与调查制度，维持经济体运行。
矛盾的是，解开利伯维尔场之谜的关键人物早在亚当斯密出生前四十年就已经过世了，他长久以来被经济学家视为站在斯密的对立面：法国国王路易十四的著名内政大臣尚─巴提斯特．柯尔贝（Jean-Baptiste Colbert），柯尔贝打从一六五○年代中期开始监督法国经济，直至一六八三年离世为止。法国皇家与公共财政的组织方式与管理良好、标准化的度量衡系统，以及法国道路、港口与运河的商业流通系统建造，全都要归功于柯尔贝。他一手创建了巴黎警察与工业检验单位，以至法国工业、法国海军与凡尔赛宫。他同时也是国家研究的主任，设立了皇家图书馆与档案馆，以及法国皇家科学院（French Royal Academy of Sciences）。柯尔贝认为这些努力对于一个能够顺利运作的流动市场来说是必要的，他是那个时代最成功的大规模市场建造者，使用关税、补贴、国家垄断与政治压迫来达成各种目标。
柯尔贝用国家的强硬手段介入市场建设，其最主要的目标是推动法国商业发展到足以和英格兰商业自由竞争。他相信他所谓的“商业自由”（liberty of commerce）源自于相互对称的市场与平衡的贸易条约。柯尔贝将国际贸易视为零和游戏，认为黄金和财富是有限的，同时他也确信把焦点放在商业与工业的社会能在经济上获得最大的成功。在他初掌权时，法国主要还是农业国家。他以推动经济发展为使命，比起农业更偏爱工业、创新与贸易；他相信这些事物能铺设一条道路，通往更自由、更顺畅的经济循环，使法国变成富裕且辉煌的国度。
1. Léon Walras, Elements of Pure Economics; or, the Theory of Social Wealth , trans. William Jaffe (London: Routledge, 1954), 153–155; Bernard Cornet, “Equilibrium Theory and Increasing Returns,” Journal of Mathematical Economics 17 (1988): 103–118; Knud Haakonssen, Natural Law and Moral Philosophy: From Grotius to the Scottish Enlightenment (Cambridge: Cambridge University Press, 1996), 25–30.
2. Milton Friedman, Capitalism and Freedom , 3rd ed. (Chicago: University of Chicago Press, 2002), 15; Milton Friedman, Free to Choose: A Personal Statement , 3rd ed. (New York: Harcourt, 1990), 20, 145.
3. Anat Admati, “Anat Admati on Milton Friedman and Justice,” Insights by Stanford Business, October 5, 2020, www.gsb.stanford.edu/insights/anat-admati-milton-friedman-justice ; Diane Coyle, Markets, State, and People: Economics for Public Policy (Princeton, NJ: Prince ton University Press, 2020), 98–101; Rebecca Henderson, Reimagining Capitalism in a World on Fire (New York: Public Affairs, 2020), 19, 67; Bonnie Kristian, “Republicans More Likely Than Democrats to Say the Free Market Is Bad for America,” Foundation for Economic Education, December 9, 2016, https://fee.org/articles/republicans-more-likely-than-democrats-to-say-the-free-market-is-bad-for-america ; Jonah Goldberg, “Will the Right Defend Economic Liberty?” National Review , May 2, 2019; Martin Wolf, “Why Rigged Capitalism Is Damaging Liberal Democracy,” Financial Times , September 17, 2019, www.ft.com/content/5a8ab27e-d470-11e9-8367-807ebd53ab77 ; Ben Riley-Smith, “The Drinks Are on Me, Declares Rishi Sunak in Budget Spending Spree,” The Telegraph , October 27, 2021; Inu Manak, “Are Republicans Still the Party of Free Trade?,” Cato Institute, May 16, 2019, www.cato.org/blog/are-republicans-still-party-free-trade ; Aritz Parra, “China’s Xi Defends Free Markets as Key to World Prosperity,” Associated Press, November 28, 2018.
4. Erik S. Reinert, How Rich Countries Got Rich, and Why Poor Countries Stay Poor (London: Public Affairs, 2007); Ciara Linnane, “China’s Middle Class Is Now Bigger Than America’s Middle Class,” MarketWatch, October 17, 2015, www.marketwatch.com/story/chinese-middle-class-is-now-bigger-than-the-us-middle-class-2015-10-15 ; Javier C. Hernández and Quoctrung Bui, “The American Dream Is Alive. In China,” New York Times , November 8, 2018; Karl Polanyi, The Great Transformation: The Political and Economic Origins of Our Time (Boston: Beacon Press, 1957), 267–268; Fred Block and Margaret R. Somers, The Power of Market Fundamentalism: Karl Polanyi’s Critique (Cambridge, MA: Harvard University Press, 2014), 2; David Sainsbury, Windows of Opportunity: How Nations Create Wealth (London: Profile Books, 2020).
5. Martin Wolf, “Milton Friedman Was Wrong on the Corporation,” Financial Times , December 8, 2020, www.ft.com/content/e969a756-922e-497b-8550-94bfb1302cdd .
6. Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations , ed. Roy Harold Campbell and Andrew Skinner, 2 vols. (Indianapolis: Liberty Fund, 1981), vol. 1, bk. IV, chap. ii, para. 10; William J. Barber, A History of Economic Thought (London: Penguin, 1967), 17; Lars Magnusson, The Tradition of Free Trade (London: Routledge, 2004), 16.
7. Joseph A. Schumpeter, History of Economic Analysis (London: Allen and Unwin, 1954), 185.
8. Smith, Wealth of Nations , vol. 2, bk. IV, chap. ix, para. 3.
9. D. C. Coleman, ed. , Revisions in Mercantilism (London: Methuen, 1969), 91–117, at 97; William Letwin, The Origins of Scientific Economics: English Economic Thought, 1660–1776 (London: Methuen, 1963), 43; Lars Magnusson, Mercantilism: The Shaping of an Economic Language (London: Routledge, 1994); Philip J. Stern, The Company State: Corporate Sovereignty and Early Modern Foundations of the British Empire in India (Oxford: Oxford University Press, 2011), 5–6; Rupali Mishra, A Business of State: Commerce, Politics, and the Birth of the East India Company (Cambridge, MA: Harvard University Press, 2018); Philip J. Stern and Carl Wennerlind, eds. , Mercantilism Reimagined: Political Economy in Early Modern Britain and Its Empire (Oxford: Oxford University Press, 2014), 6; Schumpeter, History of Economic Analysis, 94; Eli F. Heckscher, Mercantilism , trans. Mendel Shapiro, 2 vols. (London: George Allen and Unwin, 1935); Steve Pincus, “Rethinking Mercantilism: Political Economy, the British Empire, and the Atlantic World in the Seventeenth and Eighteenth Centuries,” William and Mary Quarterly 69, no. 1 (2012): 3–34.
这种身分认同的中心是对于自然与农业的理解，而西塞罗也慎重其事地借鉴了一长串农业思想家的观点。对于他的愿景来说，不可缺少的人物是老加图（Cato the Elder），一名极端保守派的军人、史学家暨罗马父权制的捍卫者，他在公元前一六○年的著作《论农业》（On Farming ）中阐述道，贵族财产依靠的是良好的农业管理。对于了解农耕的人来说，大自然的每一丝恩赐都与共和体制一样安定稳固。对于创新与贸易，老加图直接表达了鄙视。只有大规模的土地拥有制才是真正“良好”的，才能培养出具有道德良知的公民与士兵。3
凭借着与大自然的密切关系，并且为了延续贵族社会，地主阶级的成员自认有责任去研究他们所谓的大自然神圣法则。西塞罗在《论共和国》（On the Republic ，公元前五四至五一年）中指出，在“最好的人”用“合度的方式”进行统治时，就能透过和平与繁荣使“公民们享受到最大程度的幸福”。富裕的贵族阶级因为没有“任何烦恼或担忧”的负荷，能够专注于以纯粹的美德为基础来运作政府。西塞罗对于“最好的人”的概念，立基于自然并非平等地创造出每一个人类。而如果自然在创造人类时有所区别，那么人类也应该要效仿自然的区别。真正的政治自由与经济自由本就只属于少数地主。5
于是罗马贵族透过他们对国家的奉献达成这点，他们经由广大的小麦分配系统（annona civica）捐献面包给公民，这个系统是经济体制的支柱。罗马帝国的船队把小麦分送至地中海彼岸，当时罗马人将地中海称作“我们的海”（mare nostrum）。若说罗马是身体的话，地中海就像是身体里的器官──博物学家暨军事领袖老普林尼（Pliny the Elder）在他的著作《自然史》（Natural History ）中，把地中海称作“肠海”（mare intestinum），因为地中海促进了罗马经济的自由流动。如此一来，财富──首先便是地主阶级的小麦收获──就会根据自我调节的自然法则，在罗马帝国中自然而然地流动。在看似永恒不坠的国家与元老院阶级的协助下，罗马透过四季的无形之手制造出商品并养活自己。罗马资助的不只有意大利与北非之间的交易与船运航道，也扩及了伊比利亚、希腊、安纳托利亚（Anatolia）与黑海。各种商品在幅员辽阔的罗马贸易区中自由地流通。9
如果说西塞罗在罗马攀升到权力顶峰是一件令人惊叹的事，那么他的逝世就更加戏剧化了，他的死亡肇因于他对罗马宪法、前述的良性交易规则，以及私有财产与自由贸易基本原则的捍卫。公元前六三年，年仅四十二岁的西塞罗成为了罗马的两位执政官之一，这是罗马政府最高阶的职位了。在他担任罗马执政官的期间发生了暴力叛乱，他很快就陷入和元老院议员喀提林（Catiline）之间的冲突，喀提林当时正在竞选执政官，他的改革主义聚焦在免除穷人债务与分配土地。西塞罗蔑视所有行事不符合贵族精神的人民改革家。他觉得提供土地给穷人不但破坏了市场规则，更破坏了现有的秩序本身。因此，西塞罗在元老院中，当着喀提林的面发表了那名留青史的演说。他花了好几天的时间痛斥喀提林目无法纪，也谴责喀提林的朋友亏欠债务，并质疑喀提林救济穷人的动机。最后，西塞罗成功要求当局处决了喀提林的几个同谋者。当西塞罗高呼：“喔，时代！喔，习俗！”（O tempora, o mores!）时，指的是喀提林对法律的彻底漠视，与他在金融上的腐败和贪婪。同时，西塞罗也是在捍卫他眼中的自然道德经济秩序。10
我们可以从西塞罗捍卫现状的戏剧化行为了解到，他如何把荣誉看作市场的必要条件。贿赂和诈欺不只是“不公正”的行为，更是一种“虚伪”。举例来说，西塞罗在公元前六三年通过了一项禁止用选票换取好处的法律，名为《图利亚贿选法》（Lex Tullia de ambitu ）。我们必须在此指出，包括尤利乌斯．西泽在内的许多人都认为西塞罗本身也贪污，更多人相信他不过是善于营造自我形象──我们确实无法否定这一点。但西塞罗与西泽不同，他捍卫了严格的元老院法律，也从未试图推翻宪法。11
公元前四九年，尤利乌斯．西泽开始对罗马共和国行使终身独裁权。接着，在公元前四四年的三月十五日──也就是著名的日子“三月中”（Ides of March）──马库斯．尤尼乌斯．布鲁图斯（Marcus Junius Brutus）带领一群共和派的元老院议员暗杀了西泽。西塞罗本人没有参与暗杀行动，但他如今也希望能引导元老院回到共和政府。在罗马共和国殒落及罗马帝国崛起的暴力动荡中，西塞罗在命运处于最低谷的时刻写下他最为永垂不朽的著作《论责任》（公元前四四年）。他声称这本充满哲学性建议的著作是写给儿子的，但后来《论责任》变成了西方传统中影响力最广泛的书籍之一，也成了利伯维尔场思想的蓝图。12
西塞罗听闻这项判决后，逃到了位于乡间的一处宅邸，希望能在那里准备好光荣赴死。当士兵到来时，他请求他们干净利落地一刀斩断他的脖子。最后士兵却斩了三次才成功。除了砍下这名命运悲惨的哲学家的头颅之外，一名士兵还砍掉了他的一只手。彼时马克．安东尼的举动完全符合西塞罗生前所犀利指控的残暴粗俗形象，他下令把西塞罗的头和手钉在集会广场的主要讲台（rostra）上，面对着元老院。这就是罗马最伟大的雄辩家暨共和政体捍卫者最后遗留的东西，一个将在未来数千年回荡不止的象征。西塞罗的出现比拿撒勒的耶稣（Jesus of Nazareth）还更早，作为一个世俗的共和主义殉道者，他的政治与经济美德理念被赋予了一种接近基督教式的悲怆，也使得西塞罗成为了西方历史上最重要的人物之一。他实现了自己的理想，与暴政和贪腐交易的背德行为战斗。他试图维护自然秩序与经济道德，揭示了一条通往财富的有德之路。
1. Titus Livy, History of Rome , trans. John C. Yardley, Loeb Classical Library (Cambridge, MA: Harvard University Press, 2017), bk. 1, chap. 8. For an online version of Livy edited by Rev. Canon Roberts, see the Perseus Digital Library, Tufts University, gen. ed. Gregory R. Crane, www.perseus.tufts.edu/hopper/text?doc=urn:cts:latinLit:phi0914.phi0011.perseus-eng3:pr .
2. Livy, History of Rome , bk. 23, chap. 24; bk. 1, chap. 35; Ronald Syme, The Roman Revolution , rev. ed. (Oxford: Oxford University Press, 2002), 15.
3. Cato, On Agriculture , in Cato and Varro: On Agriculture , trans. W. D. Hooper and H. B. Ash, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1935), bk. 1, paras. 1–2.
4. Cicero, De officiis , trans. Walter Miller, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1913), bk. 1, sec. 13, para. 41.
5. Cicero, On the Republic , in Cicero, On the Republic, On the Laws , trans. Clinton W. Keyes, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1928), bk. 1, sec. 34, paras. 52–53; bk. 1, sec. 5, para. 19; bk. 1, sec. 8–9, para. 24.
6. Dan Hanchey, “Cicero, Exchange, and the Epicureans,” Phoenix 67, no. 1–2 (2013): 119–134, at 129; Wood, Cicero’s Social and Political Thought , 55, 81–82, 112; Cicero, De officiis , bk. 3, sec. 6, para. 30; bk. 1, sec. 7, para. 22.
7. Cicero, On Ends , trans. H. Rackham, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1914), bk. 2, sec. 26, para. 83; Hanchey, “Cicero, Exchange,” 23; Cicero, De officiis , bk. 1, sec. 13, para. 41; bk. 1, sec. 16, para. 50; bk. 1, sec. 17, paras. 53–54; Cicero, De amicitia , in On Old Age, On Friendship, On Divination, trans. W. A. Falconer, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1923), sec. 6, para. 22; sec. 7, paras. 23–24; sec. 7, paras. 23–24; sec. 14, paras. 50–52.
8. Cicero, De officiis , bk. 14, sec. 5, paras. 21–22; bk. 3, sec. 5, para. 23.
9. Caesar, The Gallic War , trans. H. J. Edwards, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1917), bk. 5, para. 1. 另见 “Internum Mare,” in William Smith, Dictionary of Greek and Roman Geography , 2 vols. (London: Walton and Maberly, 1856), 1:1084; Peter Brown, Through the Eye of the Needle: Wealth, the Fall of Rome, and the Making of Christianity in the West, 350–550 AD (Princeton, NJ: Princeton University Press, 2014), 69; Pliny, Natural History , trans. H. Rackham, 37 vols. , Loeb Classical Library (Cambridge, MA: Harvard University Press, 1942), bk. 3.
10. Wood, Cicero’s Social and Political Thought , 48; Cicero, In Catilinam, in Cicero, Orations: In Catilinam, I–IV, Pro Murena, Pro Sulla, Pro Flacco , trans. C. Macdonald, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1977), bk. 2, para. 21.
11. Cicero, De officiis , bk. 1, sec. 13, para. 47; Hanchey, “Cicero, Exchange,” 129; Brown, Through the Eye of the Needle , 253.
12. A. E. Douglas, “Cicero the Philosopher,” in Cicero , ed. T. A. Dorey (New York: Basic Books, 1965), 135–171.
13. Douglas, “Cicero the Philosopher. ”
14. Cicero, De officiis , bk. 1, sec. 13, para. 41; bk. 1, sec. 7, para. 27.
15. Cicero, On Ends , bk. 1, sec. 9, para. 30; bk. 1, sec. 10, paras. 32–33.
16. Cicero, On Ends , bk. 1, sec. 19, para. 69; Cicero, On the Republic , bk. 6, sec. 24, paras. 26–28.
17. Emily Butterworth, “Defining Obscenity,” in Obscénités renaissantes , ed. Hugh Roberts, Guillaume Peureux, and Lise Wajeman, Travaux d’humanisme et Renaissance, no. 473 (Geneva: Droz, 2011), 31–37; Cicero, Orations: Philippics 1–6 , ed. and trans. D. R. Shackleton Bailey, rev. John T. Ramsey and Gesine Manuwald, Loeb Classical Library (Cambridge, MA: Harvard University Press, 2009), chap. 2, paras. 96–98.
第二章 神圣经济
施予面包就能抓住天堂。 ──约翰（Saint John Chrysostom），〈讲道集三：思考救济与十个童女〉（Homily 3: Concerning Almsgiving and the Ten Virgins），约公元三八六年
虽然当时基督教遍布罗马帝国，但古罗马的诸神信仰仍拥有十分强大的势力。尽管君士坦丁大帝在公元三一二年左右归信了基督教，但一直到四世纪末为止，西塞罗仍在学院课程中占据主要地位。在基督诞生后的数个世纪中，教会教父（Father of the Church，有圣德的特定基督徒，其著作与教导对基督教有很大的贡献 ）主要都是罗马贵族出身，这代表了他们是在非基督教的帝国文化中长大的。他们很熟悉罗马法律，并且他们得依靠皇帝来确保生活稳定。有些教会教父努力和西塞罗的思想搏斗，希望用一种基督教版本的新道德愿景取代西塞罗的论述，包括米兰主教圣安博（Saint Ambrose），以及后来在西方基督教最有影响力的神学作家圣奥古斯丁。到了最后，他们对财富的态度变得比西塞罗所设想的更加个人主义，也更加民主。
在西塞罗笔下，欲望从本质上就是一种负面特质。基督徒则相信，如果他们的欲望是被救赎，那么这种欲望就是道德的──举例来说，当一个人藉由把钱施舍给穷人、放弃世俗的享乐来交换天堂的奖赏时，这个人就是在满足符合道德的欲望。他们以《马太福音》和《路加福音》为基础，不但把这种对于天堂财宝的欲望视为一种好事，甚至视为神圣的事。基督徒引述福音书与其他典籍，用利益、选择、意志、交易与奖赏等经济语言来建构基督教的救赎。事实上，基督被钉在十字架上的本质就是一笔交易，《希伯来书》（Book of Hebrews ）的作者写道，如果“不流一滴血”，罪就不会被赦免。换句话说，基督偿还了人类的集体债务。1
福音传道士圣路加（Saint Luke the Evangelist）坚持基督徒应该要施舍穷人，藉此摆脱世俗财产，如此才能获得天堂的财富。耶稣在传福音时说：“你们要变卖所有的赒济人，为自己预备永不坏的钱囊，用不尽的财宝在天上，就是贼不能近、虫不能蛀的地方。”圣马太（Saint Matthew）原本是一名税吏，而后在耶稣的召唤下成为门徒，他也对此做出呼应。圣马太在《新约》中跟着马可和路加引用了一句耶稣曾提及的古老犹太谚语：富人上天堂的机率比骆驼穿过针眼的机率更渺茫。他也引述道，耶稣曾说过世俗财宝的本质是转瞬即逝的，并将世俗财宝描述为：“地上有虫子咬，能锈坏，也有贼挖窟窿来偷。”他呼吁信徒应该在心中寻找永恒的宝藏。马太的叙述和路加一样，他指出耶稣在描述救赎时其实是以贫困为前提的，那是一种交换的过程，一个人若想获得救赎就必须施舍穷人：“耶稣说：‘你若愿意作完全人，可去变卖你所有的，分给穷人，就必有财宝在天上；你还要来跟从我。’”2
这一点在早期教会教父的生活型态中表现得非常明显，他们的生活与罗马贵族的传统奢华生活形成了鲜明对比。基督教领导人实践的是自我克制的极端生活型态，这种自我克制承袭自悠久的禁欲主义传统。“亚历山大的革利免”（Clement of Alexandria）在《富人的救赎》（The Rich Man’s Salvation ）中虽然承认了世俗财富必须存在，但他说明道，这些财富的使用有其规则，人们尤其应该遵循“供给”的虔诚实践，将财富施舍出去。若一名富人把所有财富都施予穷人与教会，并藉此过程把他的热忱倾注于耶稣，就能找到救赎。6
在公元前一世纪，禁欲主义的基本原则透过非基督教的希腊道德家塞克斯都（Sextus）的作品，流传至罗马帝国各处，塞克斯都协助创造了一种能够自我调节的灵性交易市场概念，他的行为准则和新基督教的道德规范是互通的。《塞克斯都语录》（The Sentences of Sextus ）在论及人与上帝之间的关系还有死后生命时，描述了一种货币流通过程。塞克斯都写道，唯有“放弃肉体的事物，人才能自由地获得灵魂的事物”，并直言不讳地补充道：“富人难以获得救赎。”他阐述了柏拉图式的观点，认为一个人可以透过灵性研究与自我克制成为贴近上帝的“圣人”。透过“征服肉体”，圣人可以“把一切能给的全都施予穷人”。世俗的依附情感──甚至对于儿女的情感──都应该受到鄙夷。塞克斯都感叹道：“信仰虔诚的人会心怀感激地承受失去孩子的痛苦。”他警告道，世俗享乐的罪恶将会“被邪恶的恶魔追究，直到还清最后一分为止”。7
塞克斯都的行为准则很快就传遍了希腊的基督教社群。首屈一指的神学家们也欣然接受了这些准则──包括亚历山大学派的基督教学者欧利根（Origen），他在三世纪时惊叹地指出阅读塞克斯都作品的人“为数众多”。随后问世的一系列基督教作品也响应了这个概念：人们必须用天堂市场来取代世俗市场。原罪代表了人类不能真正享受世俗的快乐。例如，大约在公元九○年至一五○年间出现的《黑马牧人书》（The Shepherd of Hermas ）就是以这个概念作为核心。书中包含了最早由圣马太写下的基本原则，也就是富人“在上主的事物方面”是贫乏的，并补充道，人类唯有透过贫困与谦卑才能享有上帝的赏赐。该书大加赞颂禁食与禁欲的生活，这是古典时代晚期的宗教文学中随处可见的主题。在《启示录》（公元九五年）中，拔摩岛的约翰（John of Patmos）描述了耶稣对安纳托利亚的七个城市的罪予以谴责。这七个城市──以弗所（Ephesus）、士每拿（Smyrna）、别迦摩（Pergamum）、推雅推喇（Thyatira）、撒狄（Sardis）、非拉铁非（Philadelphia）、老底嘉（Laodicea）──被视为世俗世界的隐喻，代表了《圣经》对于肉体和商业都市生活的不信任。大约在公元二○八年，神学家特土良（Tertullian）以同样戏剧化的方式痛斥罗马是浸染了殉道者鲜血的现代巴比伦。他也同样呼吁人们压抑性冲动，甚至反对人们在配偶逝世后再婚。他赞扬人们透过鳏寡生活与童贞将自己一心奉献给上帝的神圣行为。他坚持认为处女应该蒙上头巾，如此一来才更能全心全意仰望基督。蒙头可保护她们不受罪恶沾染，因而“值得进入天堂”。8
基督徒用这种极端的、自愿的性欲克制去换取救赎，这使得基督教从根本上来说比犹太教更具有交易的特质。钱财、色欲、享乐，甚至吃饭、说话和微笑──从基督教的观点来看，这些全都是坏事，都是原罪的产物，必须抛弃这些事物才能换取天堂作为报偿。在三世纪刚开始的数十年，欧利根撰写了一本讨论死后生命的奠基之作，他在书中主张唯有透过自我克制才能获得进入天堂的奖赏。欧利根将贞操能够换到救赎的观点推到极端，而阉割了自己。写下《罗马帝国衰亡史》（The Decline and Fall of the Roman Empire ）的启蒙时代重要作家爱德华．吉朋（Edward Gibbon），曾就欧利根对《圣经》的字面解释做出著名的评论，说那是一个“不幸的”错误。9
神圣市场与它追求更高目标的模式，逐渐变成基督教生活的核心，其中强调的是选择、纪律、报偿和奖赏。古典时代晚期有许多人以戏剧化的形式自我牺牲，希望能藉此进行神圣交易，欧利根只是其中之一。男性守贞变成一种寻求上帝财富的自律形式而受到重视，而后成了神职人员与修道士守贞传统的基础。沙漠教父（Desert Father，指的是在三世纪、四世纪隐居于埃及沙漠的一群基督教徒 ）为这种新兴的修道院主义与禁欲经济定下了基调。一代又一代的修道士进入了埃及的沙漠，只接受最微薄的捐献，他们活着的唯一目的就是和上帝交流。其中最有名的可能是柱顶修道士西蒙（Simeon the Stylite，约公元三九○至四五九年），他在叙利亚阿勒坡市（Aleppo）一根柱子上方的小平台生活了三十七年。10
西蒙是牧羊人之子，不过有许多淡泊名利的基督教领导人都来自富有的贵族。部分贵族依据罗马的公民义务理想，成为了主教和首屈一指的神学家。值得注意的例子包括教会领导人圣巴西略（Saint Basil，约三二九年至三七九年），和他的兄弟“尼撒的贵格利”（Gregory of Nyssa，约三三五年至三九五年）、圣金口约翰（约三四七年至四○七年）及圣安博（约三四○年至三九七年）。对他们来说，美德就是“祷告”与拒绝肉体。人与人之间的友谊也只应该以基督教团契为基础。贵格利拒绝了异教徒西塞罗对自然世界的崇拜，他写下了后来变成基督教格言的句子：“大自然是软弱的，并非永恒的。”是上帝创造了大自然，上帝才是永恒的，而所有自然系统都源自神。11
约翰利用恐惧和宗教狂热式的舞台展演来鼓动当地居民，他热中于对犹太人与同性恋者传道，并且警告基督徒，观赏君士坦丁堡的淫秽表演会使他们入地狱。他在以弗所城呼吁暴徒拆除古代世界七大奇迹之一的阿提密斯神庙（Temple of Artemis）。他在安提阿布道时，藉由听众的经济敏感度来号召：他在著作〈讲道集三：思考救济与十个童女〉（约公元三八六至三八七年）中提出了简短有力的请求，要人们把所有享乐与经济活动纳入神圣交易的逻辑中。
安博身上结合了帝国的官员职责与坚实的基督教信仰，因此成为了热心传教的现实主义者。他认为自己必须直面西塞罗，才能改变所谓职责的本质。因此我们也无需讶异，安博用他最重要的著作之一《论神职人员的责任》（On the Duties of the Clergy ，约公元三九一年）来抨击西塞罗的作品。他谴责西塞罗的修辞理论，坚信优雅与美丽并非存在于言语的艺术中，而是存在于上帝之中。真正的知识只可能出自神性的启示，而非出自世俗的科学。安博也直接攻击了私有财产：“我们认为一切都毫无意义，只有能帮助我们获得永生祝福的事物例外。”人类理所当然不可能拥有任何事物，因为上帝赐予人类的比人类能给予上帝的还要更多，使人类不可避免地“在救赎方面成为债务人”。15
奥古斯丁在离开意大利之前开始撰写《论意志的自由选择》（On Free Choice of the Will ），旨在理解善恶与预定论。这是一部了解恩典与救赎的道德市场逻辑的关键作品。奥古斯丁在书中解释道，若一个人想要从原罪中解脱与获得恩典，首先必须被上帝拣选。换句话说，人类必须经由神的意图才能做出正确的选择。当上帝能预见一切后果，他仍为人类保留了犯下极端错误的自由。奥古斯丁指出，交易市场中只有两种人，一是善用纪律的美德，二是成为“欲望的奴隶”，这样的主张透露出西塞罗的斯多噶主义带来的影响。
就像所有世间事物一样，这个新基督教的罗马也无法长久存在。西哥德王国（Visigoths）的国王阿拉里克（Alaric）在四一○年洗劫了罗马，整座城市就此沦陷。部分罗马菁英阶层为了逃离入侵的日耳曼军而一路逃到了奥古斯丁所在的希波，但那里理所当然地同样一片恐慌。希波没有任何军事资源能保护自己。不过，对奥古斯丁来说，教会面对的世俗挑战提供了一个机会，能让他推展他对救赎经济中之个人主义的所思所想。过去西塞罗在面对罗马共和崩溃的艰苦逆境时，展示了文学的力量。而现在，罗马的真正陷落则启发了奥古斯丁写下他的不朽著作《天主之城》（City of God ），他在书中阐释了尘世财富的必要性，与这些财富在神圣经济中的位置。22
1. Matthew, 13:44; Luke 12:33; Hebrews 9:22; Giacomo Todeschini, Les Marchands et le Temple: La société chrétienne et le cercle vertueux de la richesse du Moyen Âge à l’Époque Moderne (Paris: Albin Michel, 2017).
2. Luke 12:33; Matthew 6:19–21. 另见 Mark 10:25 and Luke 18:25.
3. Matthew 25:29. 投资与报偿的概念变成了 Robert K. Merton’s “Matthew Effect in Science: The Reward and Communication Systems of Science Are Reconsidered,” Science 159, no. 3810 (1968): 56–63 的基础。
4. Proverbs 19:17. See also Matthew 25:45.
5. Matthew 19:12.
6. Clement of Alexandria, The Rich Man’s Salvation , trans. G. W. Butterworth, rev. ed. , Loeb Classical Library (Cambridge, MA: Harvard University Press, 1919), 339; Todeschini, Les Marchands et le Temple , 28.
7. Walter T. Wilson, ed. and trans. , Sentences of Sextus (Atlanta: Society of Biblical Literature, 2012), 33–38, 74, 261–264.
8. Wilson, Sentences of Sextus, 2; The Shepherd of Hermas , trans. J. B. Lightfoot (New York: Macmillan, 1891), Parable 2, 1[51]:5, available at Early Christian Writings, www.earlychristianwritings.com/text/shepherd-lightfoot.html ; Tertullian, “On the Veiling of Virgins,” trans. S. Thelwall, in The Ante-Nicene Fathers , ed. Alexander Roberts, James Donaldson, and A. Cleveland Coxe, vol. 4, revised for New Advent by Kevin Knight (Buffalo, NY: Christian Literature Publishing, 1885).
9. Edward Gibbon, History of the Decline and Fall of the Roman Empire , 6 vols. (London: Strahan, 1776–1789), vol. 1, chap. 15, n. 96.
10. Richard Finn, Almsgiving in the Later Roman Empire: Christian Promotion and Practice, 313–450 (Oxford: Oxford University Press, 2006), 93.
11. Benedicta Ward, The Desert Fathers: Sayings of the Early Christian Monks (London: Penguin, 2005), 20–54; Gregory of Nyssa, On Virginity , ed. D. P. Curtin, trans. William Moore (Philadelphia: Dalcassian Publishing, 2018), 19.
12. John Chrysostom, “Homily 3: Concerning Almsgiving and the Ten Virgins,” in On Repentance and Almsgiving , trans. Gus George Christo (Washington, DC: Catholic University of America Press, 1998), 28–42, at 29–31.
13. Chrysostom, “Homily 3,” 32.
14. Ambrose, On the Duties of the Clergy , trans. A. M. Overett (Savage, MN: Lighthouse Publishing, 2013), 55, 89, 205–206; Ambrose, De Nabuthae , ed. and trans. Martin R. P. McGuire (Washington, DC: Catholic University of America Press, 1927), 49.
15. Ambrose, On the Duties of the Clergy , 55, 78, 83.
16. Ambrose, On the Duties of the Clergy , 122–124.
17. Ambrose, “The Sacraments of the Incarnation of the Lord,” in Theological and Dogmatic Works , trans. Roy J. Deferrari (Washington, DC: Catholic University of America Press, 1963), 217–264, at 240.
18. Peter Brown, Augustine of Hippo: A Biography (Berkeley: University of California Press, 2000), 169.
19. Augustine, On the Free Choice of the Will, On Grace and Free Choice, and Other Writings , ed. and trans. Peter King (Cambridge: Cambridge University Press, 2010), 1; Peter Brown, “Enjoying the Saints in Late Antiquity,” Early Medieval Europe 9, no. 1 (2000): 1–24, at 17.
20. Brown, Augustine of Hippo , 218–221.
21. Augustine, “Sermon 350,” in Sermons , ed. John E. Rotelle, trans. Edmund Hill, 10 vols. (Hyde Park, NY: New City Press, 1995), 3:107–108, available at https://wesleyscholar.com/wp-content/uploads/2019/04/Augustine-Sermons-341-400.pdf ; Peter Brown, Through the Eye of a Needle: Wealth, the Fall of Rome, and the Making of Christianity in the West, 350–550 AD (Princeton, NJ: Princeton University Press, 2014), 355; Augustine, Letters , vol. 2 (83–130), trans. Wilfrid Parsons (Washington, DC: Catholic University of America Press, 1953), 42–48; Brown, Augustine of Hippo , 198.
22. Brown, Augustine of Hippo , 299.
23. Augustine, City of God , trans. Henry Bettenson (London: Penguin, 1984), bk. 1, chap. 8; bk. 1, chap. 10.
24. Augustine, City of God , bk. 12, chap. 23; Augustine, Divine Providence and the Problem of Evil: A Translation of St. Augustine’s de Ordine , trans. Robert P. Russell (Whitefish, MT: Kessinger, 2010), 27–31.
25. Augustine, “Exposition of the Psalms,” ed. Philip Schaff, trans. J. E. Tweed, in Nicene and Post-Nicene Fathers , First Series, vol. 8 (Buffalo, NY: Christian Literature Publishing, 1888), revised for New Advent by Kevin Knight, www.newadvent.org/fathers/1801.htm .
第三章 中世纪市场机制中的神
事实上，正是因为某些事物非常稀少或难以寻获，这些事物才变得更加被需要。根据这样的准则，相较于足以满足所有人的小麦丰收期，小麦在短缺时期的价值更高。 ──彼得．约翰．奥利维（Peter John Olivi），《合约论》（Treatise on Contracts ），一二九三年
中世纪的城市之所以会难以理解自由贸易，是因为当时的商业自由最初是以明显的垄断形式出现的：教会和国家都把自由贸易的特权授予城市与城市里的行会，也只把特权限制于此。这种结合带来了经济发展与市场扩张。一一二七年，在法国北部法兰德斯郡（County of Flanders）的圣奥梅尔（Saint-Omer），威廉．克利托伯爵（William Clito）授予特权给市区居民──也就是圣奥梅尔的城市公民，允许他们无论犯了什么罪，都可以在自己的城市法庭中受审。此外，他也免除了他们在法兰德斯服兵役、缴交通行费与缴纳多项税款的义务。大致上来说，这些市民摆脱了封建的束缚，不需要缴纳日耳曼的汉萨税（hansa tax），也不需要支付安全过路费给神圣罗马帝国的皇帝，或通行费给法国王室。他们也可以随心所欲地维持地方垄断，伯爵保证所有在城市内签署的合约都必定会履行。在一份海关文件中，伯爵列出了他与各国统治者达成的协议，以保护当地居民的免税权利。此外，伯爵也保证会对市镇提供军事保护。8
神学家往往对商人抱持戒心。这是因为商人为了谋取利润而汲汲营营，他们不耕作土地，被视为在精神上甚至比真正的穷人还要更贫穷。十世纪，“维洛纳的瑞提尔”（Rathier of Verona）把商人归类成“流浪者和贫民”。但到了十一世纪，神学家对于商业的看法有了转变。从意大利主教暨法律神学家格拉提安（Gratian）到神学家“克莱尔沃的伯纳德”（Bernard of Clairvaux），这些首屈一指的思想家都以正向态度看待虔诚的商人。本笃会修道士暨教会改革者伯多禄．达弥盎（Peter Damian）指出，一个优秀的主教应该要像优秀的商人一样管理自己的教区。如果商人能把财富奉献给慈善事业，那么商人当然就是好的。教会藉由这种方式清楚区分哪些人是自然经济的一部分，哪些人不是：举例来说，“不信基督者”和“犹太人”被视为侵占基督教合理财富的有罪者，他们是“坏”商人，不得与任何有道德的当权者交易。但在多数情况下，教会并不想要抨击商人的财富，他们只希望商人分享财富。因此，教会开始利用强大的影响力去控制正在成长的经济，同时在市场中坚持基督教的道德观。11
虽然教会没有权力控制商业生态，但会指导行会设下有道德的价格，这些价格同时反映着市场价值公平公正的交易原则，其中也包括了对利润的限制。基督教自行定义了他们的道德商业社群与新市场规则，只要遵循基督教的方法，基督徒就可以自由交易。这里出现了与西塞罗相互呼应的观点：正如弗兰伯勒的罗伯特牧师（Robert of Flamborough）在《忏悔书》（Penitential ，约一二○八年至一二一三年）中写下的，建立在基督教式关系的“文明友谊”上而执行的交易，就是一种美德。12
从许多方面来说，中世纪经济思想的故事都始于方济各会（Franciscan Order）的创办者“亚西西的圣方济各”（Saint Francis of Assisi）的人生。他在一一八一年出生于意大利翁布里亚（Umbria），原名为约翰．伯铎．伯纳戴德（Giovanni di Pietro di Bernardone），他的父亲是丝绸商人，母亲是普罗旺斯贵族。他的家族属于富有商人这个新阶级，居住在拉丁地中海地区──大约是从意大利与法国南部延伸到巴塞罗那的区域。这个社会经济阶级在往后被方济各拒之门外。一二○五年，他所目睹的异象引领他舍弃了世俗的财富。他声明放弃继承遗产，而为了展现自己将以基督之名献身于绝对的贫困，他惊世骇俗地当众脱去自己的衣物，这使他的父亲惊恐不已而和他断绝关系。从那时候开始，他只穿农民的粗布衣，成为了一名托钵修士，居住生活皆与穷人为伍，只靠着捐献过活。他是欧洲文化传统中第一位真正关注自然的生态学家，将动物视为有灵性的存在，并向牠们传道。他认为他的教堂没有墙壁，他的教堂就是自然本身，而从本质上拒绝富裕的修道院生活。当时宗教机构已经成了整个西欧的财富核心，而方济各的追随者、方济各会以及他们向绝对贫困立下的誓言对这些机构来说是莫大的威胁。
放弃财富会带来的深刻哲学反思，除了审视财富究竟为何，也审视了价格是如何由道德力量与市场力量创造出来。方济各经院派（Franciscan Scholastic）的神学家──他们接受过使用辩证法与演绎推理来解决哲学问题的训练──以巴黎大学（University of Paris）为中心，汲取柏拉图、亚里士多德和西塞罗的论点，去理解市场的运作要如何才能符合基督教的道德观。他们将亚里士多德的平衡观念与罗马的自然法结合起来，正如中世纪的法律典范著作，格拉提安的《教令集》（Decretals ，一一四○年）中描述的一样。《教令集》是一部中世纪罗马教会法的创始性汇编与典范之书，书中声明道，每一次不公平的损失──也就是教会认为对交易双方来说价值不相等的协议，或者诈欺──都必须用价值完全对等的事物来“恢复”。此一概念来自亚里士多德的《尼各马可伦理学》（Nicomachean Ethics ）与“公平交换”（equal for equal）的原则。《尼各马可伦理学》更描述了人们要如何以私人财产、合约和许可为基础进行交易。这是公平价格理论的基础，此一理论指出，所有价格都应该反映出交易的公正平衡性，参与交易的人应该要平等获利。13
道明会修士暨意大利经院派思想家圣多马斯．阿奎那（Saint Thomas Aquinas）在他的著作《神学大全》（Summa Theologica ，一二六五年至一二七四年）中，也同意方济各会的说法，认为商人必须具备道德并使用“公正”的价格。然而，阿奎那不认同方济各为绝对贫困立下的誓言。他主张贫困不应该是一种要求或规则，而应该是个人选择或志向。事实上，他认为完全的贫困是不可能做到的事，这是因为所有人都必定拥有某些东西，他认为方济各会的誓言会带来犯下大罪与下地狱的风险，毕竟违背对上帝的誓言是非常严重的。这或许只是一个为了自身方便而提出的观点，鉴于道明会十分富有，拥有面积广袤的封建土地，在阿奎那看来，以道德方法取得的财富不会使他产生任何疑虑：他觉得教会需要变得富有。这样的观点影响了他对市场自然运作方式的理解。14
凑巧的是，方济各会士往往来自受过良好教育的经商背景，这也就代表了其中有些人对于商业与定价的运作方式具有较深入的认识。方济各会的领导人与信奉者逐渐开始认为，若想要确实遵守贫困誓言，就应该要更仔细地编订誓言内容。方济各会神学家圣文德（Saint Bonaventure）的《纳波内教会法规》（Constitutions of Narbonne ，一二六○年）对富裕与贫困进行了详细分析，目的是制定出严格的规范帮助方济各会士维持誓言。章程中最重要的主题之一是服装，在意大利，服装是最明显的财富象征，因此处的蓬勃经济核心正是布料生产。圣方济各认为服装对于保持贫困来说是一种物质阻碍，也是富裕的象征。举例来说，《纳波内教会法规》因此规范每位弟兄都只能拥有一件外衣，甚至特别阐明了修道士在外衣损坏或者需要用其他布料修补外衣时该怎么做。19
一二八六年，方济各会开始探讨他们是否不该把书籍（当时的书籍是昂贵的羊皮纸手稿）视为一种有价值的物品，而看成一种单纯的学习工具。依照方济各会士的看法，如果在使用昂贵的书籍时能恪守灵性实用目的，那么在方济各会的严格经济规范中，书籍就不算是奢侈品。据此，一般信徒可以把书籍当作礼物来赠送给修道士或修道院，但是必须由宗教机构的领导人或托管者来决定谁能使用这些书籍。一二九七年，波隆那的巴塞洛缪修士（Brother Bartholomeus of Bologna）从另一位修道士那里收到两本书。而后他把这两本书遗赠给了吴高利诺修士（Brother Hugolinus）。我们可以肯定的是，他们的行为符合灵性实用原则。这些修道士们谨慎地记录这些物品，明确写下自己的使用方式，如此一来他们才能用属世与属灵的标准算出这些物品的价值。20
教宗尼阁三世（Pope Nicholas III，在位期间一二七七年至一二八○年）支持方济各会的誓言，他认为有许多虔诚的方济各会士都证明了这个誓言是可以遵守的。他在一二七九年颁布了主题为“方济各会规范之确认”的教宗诏书《撒种的出去撒种 》（Exiit qui seminat ），并在其中提出了一项实现贫困誓言的革命性方法。教宗尼阁三世认为，方济各会士是不可能违背贫困誓言的，因为方济各会名下所有财产的实际拥有人其实是教宗；也就是说，方济各会士从来没有实际“拥有”任何事物。不只如此，尼阁还进一步用市场价值观念来解释道，就算方济各会士手上拥有任何货品与地产，这些财产的价值也不是固定的，而是取决于这些修道士在哪里、为了什么、用什么方式使用这些财产。每一件事物的价值都会依据它的实际用途与灵性用途而改变。尼阁强调，放弃财产“并不表示修道士在任何情况下都必须放弃使用物品”。他解释道，物品的价值来自“地点与时节”，而且也和特定的责任有关。他指出““科学是需要研究的”，如果没有““使用书籍”，修道士不可能执行这种研究。尼阁认为，宗教当局可以监督定价的过程，这么做不只能确保方济各会士只拥有必要的事物，也能减轻他们对于违背誓言的恐惧。为了解决教堂内部的冲突，教宗尼阁藉由这次的教宗诏书传达了他全心接受市场机制的观点。21
在同一年，法国方济各会士彼得．约翰．奥利维写下了《简约使用商品论》（De usu paupere ），此著作说明了发下贫困誓言者在使用商品时有何限制。奥利维在其中针对要如何在遵守誓言的同时拥有世俗物品的问题加以阐释。他创造了一些最早期、最创新的自我调节市场机制的特定概念。他出生于法国蒙彼利埃（Montpellier），曾在意大利佛罗伦萨生活过一段时间，也曾住在普罗旺斯一个有三万人口的城市──纳波内市（Narbonne）。他因此身处于地中海商业世界的核心，这里的方济各会士往往是商人的告解对象。奥利维曾在尼阁三世的教宗管理系统中工作，他试着为方济各会士的誓言辩护，并因此提出了第一个边际效用递减法则的理论，根据该理论的描述，在商品的可取得数量与消费量增加时，该商品的价值也会随之减少。奥利维指出，如果人们“普遍地”或“惯常地”使用某些物品的话，这些物品的价值就会受到影响。愈容易取得的事物，价值就愈低。举例来说，像是油和蔬菜这类为大众大量生产、又能“轻易”获得的原物料，价值就比稀有商品要低。22
方济各会的思想，将会在杰出的经院哲学家暨英国方济各会士“奥坎的威廉”（William of Ockham）的研究中出现革命性转变，奥坎把焦点转向市场上的个体与主观选择，趋近于现代观念。和奥利维一样，奥坎在一三二○年代为完美与绝对贫困的概念辩护，但他捍卫贫困誓言使用的是全新方法。奥坎认为，没有法律能强迫任何人违背自己的意愿去拥有任何事物，他开始宣扬“宽容式”法律的必要性，比如让人有权利拒绝私有财产。拥有个人选择，代表的是方济各会可以拒绝拥有财产，就像他们可以拥有财产一样毫无疑问。28
1. Michael McCormick, Origins of the European Economy: Communications and Commerce AD 300–900 (Cambridge: Cambridge University Press, 2001), 37, 87.
2. Georges Duby, The Early Growth of the European Economy: Warriors and Peasants from the Seventh to the Twelfth Century , trans. Howard B. Clarke (Ithaca, NY: Cornell University Press, 1974), 29; J. W. Hanson, S. G. Ortman, and J. Lobo, “Urbanism and the Division of Labour in the Roman Empire,” Journal of the Royal Society Interface 14, no. 136 (2017), Interface 14, 20170367; Rosamond McKitterick, ed. , The Early Middle Ages (Oxford: Oxford University Press, 2001), 100.
3. McCormick, Origins of the European Economy , 38, 40–41, 87, 101; Procopius, The Wars of Justinian , trans. H. B. Dewing, rev. Anthony Kaldellis (Indianapolis: Hackett Publishing, 2014), bk. 2, chaps. 22–33; Guy Bois, La mutation de l’an mil . Lournand, village mâconnais de l’antiquité au féodalisme (Paris: Fayard, 1989), 31.
4. Valentina Tonneato, Les banquiers du seigneur (Rennes, France: Presses Universitaires de Rennes, 2012), 291.
5. Tonneato, Les banquiers du seigneur , 315; Giacomo Todeschini, Les Marchands et le Temple: La société chrétienne et le cercle vertueux de la richesse du Moyen Âge à l’Époque Moderne (Paris: Albin Michel, 2017), 37.
6. Tonneato, Les banquiers du seigneur , 160; Alisdair Dobie, Accounting at the Durham Cathedral Priory: Management and Control of a Major Ecclesiastical Corporation, 1083–1539 (London: Palgrave Macmillan, 2015), 145–146.
7. McKitterick, Early Middle Ages , 104.
8. “Customs of Saint-Omer (ca. 1100),” in Medieval Europe , ed. Julius Kirshner and Karl F. Morrison (Chicago: University of Chicago Press, 1986), 87–95.
9. Alan Harding, “Political Liberty in the Middle Ages,” Speculum 55, no. 3 (1980): 423–443, at 442.
10. “Customs of Saint-Omer,” 87.
11. Giacomo Todeschini, Franciscan Wealth: From Voluntary Poverty to Market Society , trans. Donatella Melucci (Saint Bonaventure, NY: Saint Bonaventure University, 2009), 14; Todeschini, Les Marchands du Temple , 70.
12. Henry Haskins, The Renaissance of the Twelfth Century (Cambridge, MA: Harvard University Press, 1933), 344–350; D. E. Luscumbe and G. R. Evans, “The Twelfth-Century Renaissance,” in The Cambridge History of Medieval Political Thought , c. 350–c. 1450, ed. J. H. Burns (Cambridge: Cambridge University Press, 1988), 306–338, at 306; F. Van Steenberghen, Aristotle in the West: The Origins of Latin Aristotelianism , trans. L. Johnston (Leuven, Belgium: E. Nauwelaerts, 1955), 30–33.
13. Odd Langholm, Price and Value in the Aristotelian Tradition: A Study in Scholastic Economic Sources (Bergen, Norway: Universitetsforlaget, 1979), 29; Gratian, The Treatise on Laws (Decretum DD. 1–20 ), trans. Augustine Thompson (Washington, DC: Catholic University of America Press, 1993), 25; Brian Tierney, The Idea of Natural Rights: Studies on Natural Rights, Natural Law, and Church Law, 1150–1625 (Atlanta: Emory University, 1997), 56.
14. David Burr, “The Correctorium Controversy and the Origins of the Usus Pauper Controversy,” Speculum 60, no. 2 (1985): 331–342, at 338.
15. Saint Thomas Aquinas, Summa Theologica , vol. 53, Question 77, Articles 1, 3; Raymond de Roover, “The Story of the Alberti Company of Florence, 1302–1348, as Revealed in Its Account Books,” Business History Review 32, no. 1 (1958): 14–59.
16. W. M. Speelman, “The Franciscan Usus Pauper : Using Poverty to Put Life in the Perspective of Plenitude,” Palgrave Communications 4, no. 77 (2018), open access: https://doi.org/10.1057/s41599-018-0134-4 ; Saint Bonaventure, The Life of St. Francis of Assisi , ed. Cardinal Manning (Charlotte, NC: TAN Books, 2010), 54–55.
17. Norman Cohn, Pursuit of the Millennium: Revolutionary Millenarians and Mystical Anarchists of the Middle Ages (Oxford: Oxford University Press, 1970), 148–156.
18. John Duns Scotus, Political and Economic Philosophy , ed. and trans. Allan B. Wolter (Saint Bonaventure, NY: Franciscan Institute Publications, 2000), 27.
19. Lawrence Landini, The Causes of the Clericalization of the Order of Friars Minor, 1209–1260 in the Light of Early Franciscan Sources (Rome: Pontifica Universitas, 1968); David Burr, Olivi and Franciscan Poverty: The Origins of the Usus Pauper Controversy (Philadelphia: University of Pennsylvania Press, 1989), 5, 9.
20. Burr, Olivi and Franciscan Poverty , 11–12.
21. Nicholas III, Exiit qui seminat (Confirmation of the Rule of the Friars Minor ), 1279, Papal Encyclicals Online, www.papalencyclicals.net/nichol03/exiit-e.htm .
22. Piron Sylvain, “Marchands et confesseurs: Le Traité des contrats d’Olivi dans son contexte (Narbonne, fin XIIIe–début XIVe siècle),” in Actes des congrès de la Société des historiens médiévistes de l’enseignement supérieur public, 28e congrès 28 (1997): 289–308; Pierre Jean Olivi, De usu paupere: The quaestio and the tractatus , ed. David Burr (Florence: Olschki, 1992), 47–48.
23. Olivi, De usu paupere , 48.
24. Sylvain Piron, “Censures et condemnation de Pierre de Jean Olivi: Enqûete dans les marges du Vatican,” Mélanges de l’École française de Rome—Moyen Âge 118, no. 2 (2006): 313–373.
25. Pierre Jean Olivi, Traité sur les contrats , ed. and trans. Sylvain Piron (Paris: Les Belles Lettres, 2012), 103–115.
26. Peter John Olivi, “On Usury and Credit (ca. 1290),” in University of Chicago Readings in Western Civilization , ed. Julius Kirshner and Karl F. Morrison (Chicago: University of Chicago Press, 1987), 318–325, at 318; Langholm, Price and Value , 29, 52.
27. Langholm, Price and Value , 119, 137.
28. Tierney, Idea of Natural Rights , 33; William of Ockham, On the Power of Emperors and Popes , ed. and trans. Annabel S. Brett (Bristol: Theommes Press, 1998).
29. Tierney, Idea of Natural Rights , 101.
30. Tierney, Idea of Natural Rights , 35; Ockham, On the Power of Emperors and Popes , 35–37, 97.
31. Ockham, On the Power of Emperors and Popes , 15, 76, 79, 96.
32. Harry A. Miskimin, The Economy of Later Renaissance Europe, 1460–1600 (Cambridge: Cambridge University Press, 1977), 11.
第四章 佛罗伦萨的财富与马基维利的市场
秩序良好的共和国必须保持公众的富裕，但同时保持公民的贫困。 ──马基维利，《利瓦伊论》（Discourses on Livy ，一五一七年）
到了一二○○年代，锡耶纳的托斯卡纳（Tuscan）城邦已经变成欧洲金融业的领导者，这是因为该城邦许多公民都擅长金融，各国对于此共和国的银行机构充满信心。锡耶纳的政府官员意识到，若想让借债人和投资人在他们的城市里存款与进行金融交易，就必须先让借债人和投资人认为，这里的市场会按照他们的预期运作。从一二八七年至一三五五年，锡耶纳社群与人民的九位总督与辩护者（Nine Governors and Defenders of the Commune and the People of Siena）把焦点放在维护良好金融管理的法律规范与声誉上。政府监管的不只是高度组织化的税收系统，还有稳定的信用网络。2 良好政府与商业美德的价值观弥漫在社会中。在锡耶纳的著名中世纪公共机关建筑“锡耶纳市政厅”（Palazzo Pubblico）中，画家安布罗乔．洛兰采蒂（Ambrogio Lorenzetti）创作了一组三连幅的湿壁画，《好政府与坏政府的预言》（The Allegory of Good and Bad Government ，一三三八年至一三三九年），画中传达出守法的商人能维护良好的政府。这些壁画显然是参考了西塞罗与罗马哲学家塞内卡（Seneca，公元四年至六五年）的思想，描绘了正义、智慧、和平、坚韧、谨慎、宽容与节制等斯多噶美德围绕在好政府周围。洛兰采蒂把斯多噶主义和良好的商业行为划上等号。他将锡耶纳描绘成一个充满富裕公民、商店、商人和工匠的城市。他传达了很明确的道德与经济讯息：在法律规范的支持下，优秀的菁英共和政府可以为创造财富的交易打造出所需的环境条件。健康的市场也会相应地支持共和国的发展。另一幅画则重述了西塞罗派的古老讯息：政治的暴君将会直接导致贪腐，暴君破坏的不只是信任与和平，也会破坏市场本身与市场本应创造的财富。3
佩脱拉克希望能找到一种足以吸引菁英执行公民义务的哲学。他在西塞罗的“派代亚”（paideia）公民教育思想中找到此一哲学，希望能藉此带动罗马美德在佛罗伦萨的复兴。佩脱拉克解释道，托斯卡纳的菁英必须要付出努力，研读古代的伦理、修辞与法律来学习何谓优秀的治理方式，如此才能实践西塞罗所谓的公民“首要之善”（summum bonum）。他在《统治者应该如何治理他的国家》（How a Ruler Ought to Govern His State ，一三七三年）此一专著中，使用了西塞罗的作品来描述自己理想中具备道德正义的统治者。这些统治者付出努力是出于共和国的爱，也是出于“大众”的共同利益。佩脱拉克认为成功国家的基础不是军事武器，而是财富与优秀的公民。他追随西塞罗的观点，指出领导人应该是清廉且高效率的管理者。5
佛罗伦萨的商人在信件、账本和正式的商业与家族回忆录中写下了这些崭新观点，这些回忆录（ricordi）可以视为商业艺术之书。多数时候，经济史学家认为上述文字内容充其量只是实用文件，不会把它们纳入经济思想的政治历史中。然而，若经过仔细检视，我们会发现这些文件揭示了商人对于商业与其美德的激进新观点。佛罗伦萨商人乔瓦尼．迪．帕戈洛．莫雷利（Giovanni di Pagolo Morelli）在他的《回忆录》（Ricordi ，一三九三年至一四一一年）中大力赞扬市场，并夸耀“托斯卡纳的市场”之“富饶”，使得佛罗伦萨与他自己的家族都变得富有。他对于祖先赚得的财产非常骄傲，甚至为他们“富有地死去”而感到自豪──他认为这是一种殊荣。然而，以无关公民美德、无关共和国公民义务的方式累积个人财富，这样的追求有待商榷。一四二八年，佛罗伦萨的人文主义者暨历史学家马泰奥．帕尔米耶里（Matteo Palmieri）明确指出，追求利润的行为必须对国家利益有直接的贡献。帕尔米耶里引用了西塞罗的话，坚称商人必须把“口才”与“美德”结合，避免贪图小利，聚焦于把对财富的欲望导向“有用的商业艺术”，这样的行为对于“共和国政府”的参与者有“很大的效益”。7
在这些著作中，涵盖范围最广且最杰出之作是班尼迪托．科特鲁利（Benedetto Cotrugli）的《贸易艺术之书》（The Book of the Art of Trade ，写于一四五八年，但直到一世纪后的一五七三年才付梓出版）。来自威尼斯贸易城市拉古沙（Ragusa，如今的杜布罗夫尼克〔Dubrovnik〕）的商人科特鲁利（Cotrugli，现代克罗地亚语拼法为Kotrulj）十分钦慕佛罗伦萨的价值观，并加以仿效。他比同年代的其他人更进一步建立了如下观点：良好的西塞罗派伦理与得体的行为，能创造出市场运作所需的信任与政治稳定性。这是很核心的论点。科特鲁利观察到，贪婪和必需性无处不在，就算是最贫困的地区也一样有市场，但并不是所有市场都会创造出财富或宏伟的城市。他清楚表明，若要使商业与投资蓬勃发展，市场终究需要制度支持、信心与合作，少了这些事物，交易是无法妥善运作的。8
马基维利认为羊毛工人暴动（Revolt of the Ciompi，一三七八年至一三八二年）这场发生在佛罗伦萨的劳动阶级起义，能为众人带来经济自由方面的教训。在他献给第二任梅迪奇教宗克勉七世（Clement VII）的《佛罗伦萨历史》（Florentine Histories ，一五二五年）中，他主张寡头垄断是很危险的，会阻碍稳定的贸易与财富。他说，是寡头政治与经济不平等为佛罗伦萨带来了内战。共和国与其市场必须拥有一定程度的经济公平性才能正常运作。他利用西塞罗的说法批判那些“靠着诈骗或武力”获得财富的商人，他把这种赚钱方式称为“丑陋的收购”。马基维利不赞同佛罗伦萨的上层阶级限制了行会中只有哪些人能成为羊毛工人的代表，他相信正是这样的限制导致了充满杀戮与不稳定的激进政治。《君王论》指出，唯有在共和国解体后，才会轮到禽兽般的法律治理这个社会。唯有稳定的国家能抵御“狐狸”和“狮子”做出的危险野蛮行为，藉此维护美德，保护良好的贸易与市场。18
1. Raymond de Roover, “The Story of the Alberti Company of Florence, 1302–1348, as Revealed in Its Account Books,” Business History Review 32, no. 1 (1958): 14–59, at 46; Marcia L. Colish, “Cicero’s De officiis and Machiavelli’s Prince ,” Sixteenth Century Journal 9, no. 4 (1978): 80–93, at 82; N. E. Nelson, “Cicero’s De officiis in Christian Thought, 300–1300,” in Essays and Studies in English and Comparative Literature , University of Michigan Publications in Language and Literature, vol. 10 (Ann Arbor: University of Michigan Press, 1933), 59–160; Albert O. Hirschman, The Passions and the Interests: Political Arguments for Capitalism Before Its Triumph (Princeton, NJ: Princeton University Press, 1977), 10.
2. William M. Bowsky, The Finance of the Commune of Siena, 1287–1355 (Oxford: Clarendon Press, 1970), 1, 209.
3. Nicolai Rubenstein, “Political Ideas in Sienese Art: The Frescoes by Ambrogio Lorenzetti and Taddeo di Bartolo in the Palazzo Pubblico,” Journal of the Warburg and Courtauld Institutes 21, no. 3/4 (1958): 179–207; Quentin Skinner, “Ambrogio Lorenzetti’s Buon Governo Frescoes: Two Old Questions, Two New Answers,” Journal of the Warburg and Courtauld Institutes 62, no. 1 (1999): 1–28, at 6.
4. Arpad Steiner, “Petrarch’s Optimus Princeps ,” Romanic Review 23 (1934): 99–111; Christian Bec, Les marchands écrivains: Affaires et humanismé à Florence, 1375–1434 (Paris: École Pratique des Hautes Études, 1967), 49–51; Francesco Petrarca, “How a Ruler Ought to Govern His State,” in The Earthly Republic: Italian Humanists on Government and Society , ed. Benjamin G. Kohl and Ronald G. Witt (Philadelphia: University of Pennsylvania Press, 1978), 35–92, at 37.
5. James Hankins, Virtue Politics: Soulcraft and Statecraft in Renaissance Italy (Cambridge, MA: Belknap Press of Harvard University Press, 2019), 2, 42, 46; Steiner, “Petrarch’s Optimus Princeps ,” 104.
6. Raymond de Roover, “The Concept of the Just Price: Theory and Economic Policy,” Journal of Economic History 18, no. 4 (1958): 418–434, at 425; Cicero, De officiis , trans. Walter Miller, Loeb Classical Library (Cambridge, MA: Harvard University Press, 1913), bk. 1, sec. 13–14, paras. 43–45.
7. Gertrude Randalph Bramlette Richards, Florentine Merchants in the Age of the Medici: Letters and Documents from the Selfridge Collection of Medici Manuscripts (Cambridge, MA: Harvard University Press, 1932), 5; Armando Sapori, La crisi delle compagnie mercantili dei Bardi dei Peruzzi (Florence: Olschki, 1926); Robert S. Lopez, The Commercial Revo lution of the Middle Ages, 950–1350 (Cambridge: Cambridge University Press, 1976), 27–36; Gino Luzzato, Breve storia economica dell’Italia medieval (Turin: Einaudi, 1982); Giovanni di Pagolo Morelli, Ricordi , ed. V. Branca (Florence: F. Le Monnier, 1956), 100–101; Matteo Palmieri, Dell’ Ottimo Cittadino: Massime tolte dal Trattato della Vita Civile (Venice: Dalla Tipografia di Alvisopoli, 1829), 20, 66, 167–168.
8. Benedetto Cotrugli, The Book of the Art of Trade , ed. Carlo Carraro and Giovanni Favero, trans. John Francis Phillimore (Cham, Switzerland: Palgrave Macmillan, 2017).
9. Cotrugli, Book of the Art of Trade , 4.
10. Cotrugli, Book of the Art of Trade , 112–115.
11. Cotrugli, Book of the Art of Trade , 25, 30, 33.
12. Cotrugli, Book of the Art of Trade , 46–49, 62, 86, 112–113.
13. Felix Gilbert, Machiavelli and Guicciardini: Politics and History in Sixteenth-Century Florence (Princeton, NJ: Princeton University Press, 1965), 160–161.
14. Hirschman, The Passions and the Interests , 33; Niccolò Machiavelli, The Prince , ed. and trans. William J. Connell (Boston: Bedford/St. Martin’s, 2005), 61–62; Colish, “Cicero’s De officiis and Machiavelli’s Prince ,” 92.
15. Jacob Soll, Publishing The Prince: History, Reading, and the Birth of Political Criticism (Ann Arbor: University of Michigan Press, 2005), 23; Niccolò Machiavelli, The Discourses , ed. Bernard Crick, trans. Leslie J. Walker, rev. Brian Richardson (London: Penguin, 1970), 37–39, 201.
16. Machiavelli, The Discourses , 39; John McCormick, Machiavellian Democracy (Cambridge: Cambridge University Press, 2011), 55, 201; Gilbert, Machiavelli and Guicciardini, 184–185; Machiavelli, The Prince , 61–62.
17. Machiavelli, The Prince , 55; Jérémie Bartas, L’argent n’est pas le nerf de la guerre: Essai sur une prétendue erreur de Machiavel (Rome: École Française de Rome, 2011), 32–36; McCormick, Machiavellian Democracy , 87; Machiavelli, The Discourses , 201–203.
18. McCormick, Machiavellian Democracy , 26; Charles Tilly, “Reflection on the History of European State-Making,” in The Formation of National States in Western Europe , ed. Charles Tilly (Princeton, NJ: Princeton University Press, 1975), 3–83, at 52–56; Margaret Levy, Of Rule and Revenue (Berkeley: University of California Press, 1988), 202; Niccolò Machiavelli, Florentine Histories , trans. Laura F. Banfield and Harvey K. Mansfield Jr. (Princeton, NJ: Princeton University Press, 1988), 121–123.
19. Machiavelli, Florentine Histories , 159.
第五章 以国家为手段的英格兰自由贸易
贸易欣欣向荣时，国王的收入会增加，土地和租金会上涨，航海技术会发展，穷人会受到雇用。但如果贸易衰败，这一切也会随之衰退。 ──爱德华．米塞尔顿（Edward Misselden），《自由贸易，又名，使贸易蓬勃发展的方法》（Free Trade, or, the Means to Make Trade Flourish ），一六二二年
十六世纪之初，欧洲出现了剧烈的变化。一五一七年，也就是马基维利写下《利瓦伊论》的那一年，日耳曼的新教创始人马丁．路德（Martin Luther）将他执笔的《九十五条论纲》（Ninety-five Theses ）钉在威登堡大教堂（Wittenberg Cathedral）的门上，启动了未来将导致基督教分裂的第一步。首批新教徒如同马基维利一样，对于人类本性无比悲观，他们认为人类是堕落的，会按照自身的兽性行事。但是，他们也如同马基维利一样相信个人选择与利己有其力量。只要做出适当的个人选择，人类就能形塑自己的命运。1 在同一时期，西班牙探险家胡安．庞塞．莱昂（Juan Ponce de Léon）发现了佛罗里达，并进一步探索该地。欧洲人感到美洲的自然资源远比他们所能想象的更加富饶。哲学家开始把科学与探索视为获得这些资源财富的关键。而崭新的世界探索任务也为人们带来了新的体认：国家必须扮演主导角色，资助与保护探险家进行长途海上交易，并与其他帝国交涉，这些探索对于个人与公司来说太过昂贵也太过复杂了，他们无法靠自己做到。十六与十七世纪的经济思想家一再强调，财富生产需要国家投资与个人冒险精神彼此结合。 当时欧洲站在科学革命的临界点，这场革命将会迎来对各种自然法则的发现，从行星运动到血液循环皆尽有之，因此，我们也无需意外十六世纪的经济思想见证了全新的自然市场机制运作理论如雨后春笋般涌现。其中，最引人注目的就是利伯维尔场的相关概念了，诸如货币数量理论、报酬递减法则、“进入壁垒”的概念、通货膨胀、劳动生产力和企业家精神──当时的先驱经济思想家认为，这些概念全都得依赖某种形式的国家干涉。
到了一五三○年代，欧洲遍地都是来自日耳曼与波希米亚矿坑的黄金，还有些黄金来自葡萄牙与西班牙帝国。西班牙船队从新世界带回了堆积如山的贵金属，这些贵金属从塞维利亚（Seville）的瓜达几维海岸（Guadalquivir）与安特卫普（Antwerp）的法兰德斯港口（Flemish port）等地上岸。尽管更多的黄金能带来财富，但这些黄金同时也导致了通货膨胀，甚至货币短缺，破坏了从波希米亚到马德里、巴黎与伦敦的经济稳定性。2 突如其来的不稳定状态使得哲学家开始研究货币，以及是什么为货币赋予了价值。他们开始意识到市场力量在其中扮演了关键角色。正如早期的经院哲学家认为个人行为会创造出定价与价值的市场机制，晚期的经院哲学家──尤其是西班牙的经院哲学家认为，王室法令与国家其实无法完全控制货币的价值。一个新的法律思想流派出现在西班牙的萨拉曼卡大学（University of Salamanca）与葡萄牙的埃武拉大学（University of Evora），他们把焦点放在理解市场机制上。一五五○年代，西班牙巴斯克（Basque）的神学家马丁．阿兹匹区塔（Martín de Azpilcueta）提出了一种货币数量理论，指出货币的价值同时来自流通的货币多寡（铸币数量上升会抑制货币价值，而这种通膨又会反过来导致货币短缺）以及人们对货币能买到什么的认知。3
支持卡尔文主义的日耳曼新教改革者马丁．布塞珥（Martin Bucer）以最强烈的力道为有息放贷辩护，他挑战的不只是天主教对于高利贷的禁令，也挑战了“货币的本质是不结果实的”背后的基础概念。4 当时有愈来愈多神学家认为，只要以纯粹的基督教脉络行事，那经商就是正向的事，布塞珥也是其中之一，他帮助当时的人们解除对于货币的偏见（不过他并没有帮助人们解除对于犹太人的偏见，而希望能将犹太人逐出公民生活与商业生活）。布塞珥在一五四七年因为宗教冲突而向英格兰新教寻求庇护，国王亨利八世在宫廷里接见了他。一五四九年，他成为剑桥大学的钦定教授，写下了《论基督的王国》（On the Kingdom of Christ ），在其中勾勒出他的愿景，他认为若借贷双方都同意一个并非“滥用”的利率，那么借贷就是对经济有益的行为。布塞珥引用了西塞罗和圣安博的话来正当化基督教社群中的商品获利，指这些利润可以“用来为上帝的子民购买和平”。他专注于透过商业支持公民生活，这代表了基督教思想正逐渐向世俗世界靠拢。“金钱同样是上帝的恩赐，上帝要我们以正确的方式使用金钱。”他在《论高利贷》（Treatise on Usury ）中如此写道。如果金钱能帮助基督徒好好生活，还能支持西塞罗过去提出的公民稳定性的“首要之善”观点，那么金钱也就未必是“不结果实的”。5
卡尔文派的新教主义在法国产生了重大的影响，法国是当时西欧人口最多的国家，也可能是最富有的国家。然而，从一五六二年开始的法国宗教战争（French Wars of Religion）延续了超过三十五年，天主教极端分子攻击了新教教徒，甚至也攻击了天主教的温和派，使法国面临攸关存亡的威胁。城市与富有的工业产业纷纷解体。有些法国思想家希望能找到一个理论来停止宗教冲突并重建社会，于是他们全心接纳了马基维利的观点，认为若想要稳定国家与社会并创造有利的市场条件，马基维利的理论至关重要。
其中一位思想家是法国法学家、历史学家暨自然哲学家尚．布丹（Jean Bodin）。他在宗教战争最高峰期间写下许多政治理论，为专制君主制辩护，他认为这种制度不仅能维持政治和平，还能发展法国经济。他的理论是他对圣巴托罗缪大屠杀（Saint Bartholomew’s Day Massacre，一五七二年）做出的反馈，在这场大屠杀中，天主教狂热分子于巴黎杀害了数百名新教的高阶贵族，且在法国各地共杀害了数千人。这场史无前例的暴力事件对法国造成重挫，那些暴徒摧毁了各个城市与商业财富，使法国一夕之间变得动荡不安。布丹对于宗教派系斗争与内乱所做出的响应就是“专制主义”。布丹认为，如果经济是透过自然程序运作的，那么国家就必须稳定社会并重建市场。布丹采用了马基维利的观点来为国家的稳定性与权力辩护，但他的主张中更加明确地指出，国家能促进财富，并使市场得以自然系统的状态运作。别忘了，布丹和马基维利的地位截然不同──布丹是一名在各国都受人尊敬的学者、律师暨国王顾问，因此能够直言不讳地表达意见。
布丹在《国家六论》（Six Books of the Republic ，一五七六年）中解释道，在面对消耗着政治实体的“热情”时，专制君主制是唯一的答案。虽然布丹不同意马基维利为不道德行为提出的辩护，但他认为马基维利优先关注政治稳定性是正确的。仇恨与狂热的宗教信仰会打破政治实体的和谐，摧毁商业与财富。布丹和过去的无数市场理论家一样，也向西塞罗借鉴，他指出，有权制定法律且有道德的君主会实行斯多噶式的“节制”，把自然平衡带回经济中。6
我们可以在布丹的身上看到十六世纪经济思想的复杂性：他在稳定经济与确保市场条件方面为国家所扮演的角色做了辩护，但他同时也是那个时代首屈一指的货币理论学家，对市场机制进行了突破性的观察分析。一五六八年，布丹在职涯早期写下《响应马列斯妥先生》（Response to the Paradoxes of Monsieur de Malestroit ）作为对欧洲通膨问题的响应，并用此作品为货币数量理论进行强而有力的辩护，指出钱币的流通数量会影响货币价值。8
马基维利、经院哲学家与布丹启发了乔凡尼．博泰罗（Giovanni Botero）对于经济与政治的思想，他是一名耶稣会神职人员、哲学家暨外交官。博泰罗最重要的构想之一，是为城市培育出工业并刺激市场。有别于农业，这些构想把核心放在探索、创新与制造，再加上透过大量累积资产，来开启一个持续创造出财富的动态过程。这意谓着各国必须把焦点放在管理和投资城市上。博泰罗赞同马基维利的观点，认为国家应该要为自身的存续与繁荣做出艰难的决定，博泰罗是第一个将此概念称作“国家理性”（reason of state，或国家利益）的人。经济史学家将这个后来在法文中写作“raison d’état”的概念与现代的重商主义概念连结在一起，根据此概念，君主或领导人必须在能力所及内尽自己的一切努力去增强国家经济，无论是囤积黄金还是补贴工商业。不过，博泰罗并不认为单靠国家就可以管控经济；国家必须和商人合作，才能创造出使生产最大化的恰当环境条件。12
拿坡里哲学家安东尼奥．塞拉（Antonio Serra）也利用市场分析来支持工业胜过农业的观点。他在一六一三年的著作《国家贫富短论》（Short Treatise on the Wealth and Poverty of Nations ）中详细阐述了农业产品是如何导致收益递减，而收益递减会导致生产成本提高，充其量也只能带来有限的盈余。农业根本无法为大规模投资创造出足够的财富。唯有制造才能“利用产品的倍增来使收入倍增”，并产出不会迅速贬值的耐久货品。塞拉解释道，随着生产量增加，成本将会下降，这使得工业有机会同时提高薪水并压低价格。这就是能够使收益增加的机制。因此具竞争性的工业市场具有很大的潜力，至少在塞拉描述的这种收益增加导致了后来所谓的“进入壁垒”之前都是如此──进入壁垒是一种创造出寡头与垄断的机制。15
伴随着贸易、信任与贷款的蓬勃发展而出现的，是一波重要的英格兰经济著作。由英格兰议员、剑桥学者暨先驱市场思想家汤姆士．史密斯爵士（Thomas Smith）撰写的《论英格兰共同体》（A Discourse on the Common Weal of This Realm of England ，约一五四九年）指出，政府必须给予农业市场自由，同时严密管控工业以推动城市制造业。史密斯主张，议会干预人们在过去的公有农业土地上进行圈地，这样的行为削减了作物产量，并回过头来削减了城市的财富。史密斯不但赞成建立一个工业供需的国际市场体制，他也对于国家要如何帮助具企业家精神的工匠有一套看法。虽然他相信富裕的市场本身就具有自我扩张的力量，但他也引用西塞罗的话，主张国家必须利用“奖励”（rewardes）来帮助、甚至“强迫”城市工业发展，并利用“痛苦”（paine）来进行监管。史密斯认为，虽然农业需要的是自由，但工业需要的是国家的监督，也需要国家协助往国际市场发展。扩张的工业为整个国家创造出一道财富之流，藉此，“城镇与都市将会重新充满各种工匠；不只是如今我们视为日常的布匠，还有帽匠、手套匠、造纸匠、玻璃匠、指标工、金匠、铁匠与各种金属的锻造工、床罩制造商、针匠和针头匠。”所有这些交易和行业彼此扶持，创造出能带来经济成长的市场体制。18
英格兰政府支持的不只是国内工业，他们也支持英格兰市场往殖民世界扩张。一五七九年，英国女王伊丽莎白一世资助了弗朗西斯．德瑞克（Francis Drake）环绕世界航行的计划。她也特别准许华特．雷利（Walter Raleigh）带领探险队在一五九五年前往奥利诺科河（Orinoco River），这条河位于如今的委内瑞拉，此前克里斯多福．哥伦布也是在委内瑞拉找到了他心目中通往天堂的道路。比哥伦布晚一百多年出生的雷利，在一本名为《发现广阔、富裕又美丽的圭亚那帝国，以及伟大的黄金之城马诺亚，西班牙人称之为黄金国》（The Discovery of the Large, Rich, and Beautiful Empire of Guiana, with a Relation of the Great and Golden City of Manoa Which the Spaniards Call El Dorado ，一五九六年）的书中描述了他的旅行，并声称自己找到了无尽的财富，找到了“黄金之母”。19
虽然许多英格兰人都认为国家必须参与商业帝国的打造，但他们同时也在试着了解他们眼中推动市场持续生产的自然法则。盎格鲁─法兰商人暨德斯贸易商杰拉德．马林斯（Gerard de Malynes）在他的著作《商人法》（Lex Mercatoria ，一六二二年）中，以极为精深的观点看待规章制度与自由在商业建立中扮演的角色。他援引了《圣经》、斯巴达、克里特、迦太基和西塞罗的法律，也引用了尚．布丹的研究，坚称国家必须带有策略地支持贸易。20
马林斯并不是唯一一个这么认为的人。多数英格兰经济中的领导人都赞同这个观点：国家可以在创造自由贸易条件的方面发挥作用。在这些人之中，最具有影响力的是东印度公司（East India Company）的董事托玛斯．孟恩（Thomas Mun）和商人爱德华．米塞尔顿。对于孟恩与米塞尔顿来说，国家执行保护主义会推动贸易自由的这个概念没有任何矛盾之处。因此，虽然经济史学家一直以来都因为他们两人坚持要王室透过关税来保护英格兰船运与制造业，而认为他们是重商主义的理论家，但我们也必须把他们视为利伯维尔场思想的先驱。
《航海法》除了保护国家工业外，也限制了只有英格兰的船只能进入国内。此法律使英格兰与荷兰的竞争进入白热化。英格兰内战才刚结束，第一次英荷战争就在一六五二年展开，但这场为期两年的战争并没有为英格兰带来决定性的胜利。虽然英格兰在一六五三年的席凡宁根战役（Battle of Scheveningen）成为胜利者，却没能击败荷兰船队，也无法封锁英格兰海岸。荷兰继续维持着优势商业国家的地位，于是英格兰政府的决策者采纳了孟恩和米塞尔顿的建议，打造了关税体制以扶植国家工业。他们也请求国家协助他们挑战荷兰在印度、非洲直至北美洲的全球贸易优势地位，尤其是奴隶贸易这一部分。
1. Quentin Skinner, The Foundations of Modern Political Thought , 2 vols. (Cambridge: Cambridge University Press, 1978), 2:5, 284.
2. Harry A. Miskimin, The Economy of Later Renaissance Europe, 1460–1600 (Cambridge: Cambridge University Press, 1977), 36.
3. Skinner, Foundations of Modern Political Thought , 2:139; Francisco de Vitoria, Political Writings , ed. Anthony Pagden and Jeremy Lawrence (Cambridge: Cambridge University Press, 1991), xv–xix; Martín de Azpilcueta, Commentary on the Resolution of Money (1556) , in Sourcebook in Late-Scholastic Monetary Theory: The Contributions of Martín de Azpilcueta, Luis de Molina, S. J. , and Juan de Mariana, S. J. , ed. Stephen J. Grabill (Lanham, MD: Lexington Books, 2007), 1–107, at 79; Martín de Azpilcueta, On Exchange , trans. Jeannine Emery (Grand Rapids, MI: Acton Institute, 2014), 127. 另见 Alejandro Chafuen, Faith and Liberty: The Economic Thought of the Late Scholastics (Lanham, MD: Lexington Books, 2003), 54; Marjorie Grice-Hutchinson, The School of Salamanca: Readings in Spanish Monetary Theory, 1544–1605 (Oxford: Clarendon Press, 1952), 48.
4. Raymond de Roover, Money, Banking and Credit in Medieval Bruges (Cambridge, MA: Medieval Academy of America, 1948), 17; Mark Koyama, “Evading the ‘Taint of Usury’: The Usury Prohibition as a Barrier to Entry,” Explorations in Economic History 47, no. 4 (2010): 420–442, at 428.
5. Martin Bucer, De Regno Christi , in Melancthon and Bucer , ed. Wilhelm Pauk (Philadelphia: Westminster Press, 1969), 155–394, at 304; Steven Rowan, “Luther, Bucer, Eck on the Jews,” Sixteenth Century Journal 16, no. 1 (1985): 79–90, at 85; Bucer, Regno Christi , 302; Constantin Hopf, Martin Bucer and the English Reformation (London: Blackwell, 1946), 124–125; Martin Greschat, Martin Bucer: A Reformer and His Times , trans. Stephen E. Buckwalter (Louisville, KY: Westminster John Knox Press, 2004), 236–237.
6. Jacob Soll, “Healing the Body Politic: French Royal Doctors, History and the Birth of a Nation, 1560–1634,” Renaissance Quarterly 55, no. 4 (2002): 1259–1286.
7. Jean Bodin, Les six livres de la République , ed. Gérard Mairet (Paris: Livre de Poche, 1993), 428–429, 431, 485, 487, 500.
8. Louis Baeck, “Spanish Economic Thought: The School of Salamanca and the Arbitristas,” History of Political Economy 20, no. 3 (1988): 394.
9. Henri Hauser, ed. , La vie chère au XVIe siècle: La Réponse de Jean Bodin à M. de Malestroit 1568 (Paris: Armand Colin, 1932), xxxii; J. H. Elliott, “Self-Perception and Decline in Early Seventeenth-Century Spain,” Past and Present 74 (1977): 49–50.
10. Hauser, La vie chère , lviii.
11. Hauser, La vie chère , 499–500.
12. David Sainsbury, Windows of Opportunity: How Nations Create Wealth (London: Profile Books, 2020), 11.
13. Giovanni Botero, The Reason of State (Cambridge: Cambridge University Press, 2017), 4; Giovanni Botero, On the Causes of the Greatness and Magnificence of Cities , ed. and trans. Geoffrey Symcox (Toronto: University of Toronto Press, 2012), xxxiii, 39–45.
14. Botero, On the Causes of the Greatness and Magnificence of Cities , 43–44; Sophus A. Reinert, Translating Empire: Emulation and the Origins of Political Economy (Cambridge, MA: Harvard University Press, 2011), 117; Erik S. Reinert, “Giovanni Botero (1588) and Antonio Serra (1613): Italy and the Birth of Development Economics,” in The Oxford Handbook of Industrial Policy , ed. Arkebe Oqubay, Christopher Cramer, Ha-Joon Chang, and Richard Kozul-Wright (Oxford: Oxford University Press, 2020), 3–41.
15. Antonio Serra, A Short Treatise on the Wealth and Poverty of Nations (1613) , ed. Sophus A. Reinert, trans. Jonathan Hunt (New York: Anthem, 2011), 121; Jamie Trace, Giovanni Botero and English Political Thought (doctoral thesis, University of Cambridge, 2018).
16. Craig Muldrew, The Economy of Obligation (New York: Palgrave, 1998), 53.
17. Muldrew, Economy of Obligation , 97, 109, 138, 151; Nicolas Grimalde, Marcus Tullius Ciceroes Thre Bokes of Duties, to Marcus His Sonne, Turned Oute of Latine into English , ed. Gerald O’Gorman (Washington, DC: Folger Books, 1990), 207.
18. Joyce Oldham Appleby, Economic Thought and Ideology in Seventeenth-Century England (Princeton, NJ: Princeton University Press, 1978), 34. 另见 Elizabeth Lamond, ed. , A Discourse of the Common Weal of This Realm of England. First Printed in 1581 and Commonly Attributed to W. S. (Cambridge: Cambridge University Press, 1929), 15, 59, 93; Mary Dewar, “The Authorship of the ‘Discourse of the Commonweal,’ ” Economic History Review 19, no. 2 (1966): 388–400.
19. Sir Walter Raleigh, The Discovery of the Large, Rich, and Beautiful Empire of Guiana, with a Relation of the Great and Golden City of Manoa Which the Spaniards Call El Dorado , ed. Robert H. Schomburgk (New York: Burt Franklin, 1848), lxxix.
20. Gerard de Malynes, Lex Mercatoria (Memphis: General Books, 2012), 5.
21. Malynes, Lex Mercatoria , 27; William Eamon, Science and the Secrets of Nature: Books and Secrets in Medieval and Early Modern Culture (Princeton, NJ: Princeton University Press, 1994); Claire Lesage, “La Littérature des secrets et I Secreti d’Isabella Cortese,” Chroniques italiennes 36 (1993): 145–178; Carl Wennerlind, Casualties of Credit: The English Financial Revolution, 1620–1720 (Cambridge, MA: Harvard University Press, 2011), 48.
22. Wennerlind, Casualties of Credit , 79, 114, 211; Gerard de Malynes, The Maintenance of Free Trade (New York: Augustus Kelley, 1971), 47.
23. Malynes, Maintenance of Free Trade , 83, 105.
24. Appleby, Economic Thought and Ideology , 37; Thomas Mun, The Complete Works: Economics and Trade , ed. Gavin John Adams (San Bernardino, CA: Newton Page, 2013), 145.
25. Edward Misselden, Free Trade, or, The Meanes to Make Trade Florish (London: John Legatt, 1622), 20, 80, 84.
26. Lawrence A. Harper, The English Navigation Laws: A Seventeenth-Century Experiment in Social Engineering (New York: Octagon Books, 1960), 40.
27. Charles Henry Wilson, England’s Apprenticeship, 1603–1763 (London: Longmans, 1965), 65; Jean-Baptiste Colbert, “Mémoire touchant le commerce avec l’Angleterre, 1651,” in Lettres, instructions, et mémoires de Colbert , ed. Pierre Clément, 10 vols. (Paris: Imprimerie Impériale, 1861–1873), vol. 2, pt. 2, pp. 405–409; Harper, English Navigation Laws , 16; Moritz Isenmann, “Égalité, réciprocité, souvraineté: The Role of Commercial Treaties in Colbert’s Economic Policy,” in The Politics of Commercial Treaties in the Eighteenth Century: Balance of Power, Balance of Trade , ed. Antonella Alimento and Koen Stapelbroek (London: Palgrave Macmillan, 2017), 77–104.
第六章 荷兰共和国的自由与财富
上帝创造了人的αὐτεξούσιον，意即“自由与法权”，所以每个人的行为以及对自身财产的使用，都应该出于自己的意志，而不是出于他人的意志……因此，俗话说：“每个人在论及与自身财产相关的事物时，都是自己的统治者与仲裁者。” ──雨果．格劳秀斯（Hugo Grotius），《论捕获法》（De Iure Praedae Commentarius ），一六○三年
就算此时英格兰也有条不紊地建立起商业实力，荷兰仍继续主导着欧洲经济。后人所谓的荷兰黄金时代（Dutch Golden Age）培养出了许多关于经济学的复杂概念，其中以利伯维尔场的观点特别值得一提。无论从后见之明来看，这个利伯维尔场的概念有多超前，其实它就和英国与法国的经济思想一样，是以政府大量干涉经济作为前提。政治与帝国的经济现实并不总是完全符合荷兰共和国的思想家所拥护的自由理想。正如历史中的许多其他时期，荷兰的利伯维尔场理想也同样与更加复杂的国家干预现实并存。
荷兰的一位杰出人文学家西蒙．斯蒂文（Simon Stevin）在荷兰共和国成立时从布鲁日市（Bruges）搬到了莱顿市（Leiden）。他出生于一个普通的商人家庭，在莱顿念大学时认识了纳绍伯爵，伯爵后来成为奥兰治亲王的“奥兰治的莫里斯”（Maurice of Orange, Count of Nassau）。身为沉默者威廉一世（William I the Silent）的儿子，莫里斯在一五八五年成为荷兰共和国的省总督，他选择了斯蒂文来担任他的首席顾问与导师。莫里斯担任省总督直到他在一六二五年逝世。在任职期间，他指定斯蒂文负责处理最重要的供水系统──运河、堤防、水坝和挡海的水闸，又让斯蒂文成为军队的军需官，并帮助他成立了莱顿的工学院。斯蒂文是个博学的人，他写了一本影响力深远的会计手册《亲王会计》（Accounting for Princes ，一六○四年），主张政府必须由熟悉商业之道的人来治理。1
斯蒂文和其他荷兰领导人都认为，在激发市场信心与吸引外国人进入荷兰共和国的过程中，容忍政策会扮演很重要的角色。许多卡尔文教派的纺织品制造商在又称为八十年战争（Eighty Years’ War）的荷兰独立战争（Dutch War of Independence，一五六八年至一六四八年）期间，逃到了荷兰共和国北方的城市寻求庇护。到了一六○九年，阿姆斯特丹的卡尔文主义者和天主教徒数量已经持平了，另外也有许多犹太人与路德教徒。这些人全都有权可以投资与建立公司。容忍与信心，再加上金融素养、透明度和效率，这些因素迭加起来，推动着一个仍在不断成长的丰富市场文化。3
荷兰商人在西班牙与葡萄牙帝国内设立了贸易站，藉此侵吞更多贸易量，他们成为欧洲赚进最多钱的一群人。一五九九年，雅各布．哥尼拉斯．范尼克（Jacob Cornelius van Neck）在东印度群岛的香料探索获得了高达百分之三百九十九的利润。新成立的公司在荷兰各地大量涌现，使得人们开始担忧荷兰内部的过多竞争可能会导致贸易受损。荷兰最重要的其中一位领导人，类似于首相的“土地倡导者”（land’s advocate）约翰．奥登巴那维（Johan van Oldenbarnevelt）坚持认为，荷兰七个省的所有公司应该要联合起来，组成一间共同对外贸易的联盟公司。因此，他在一六○二年协助成立了荷兰东印度公司（United Dutch East India Company，荷兰文为Vereenigde Oost Indische Compagnie，简称ＶＯＣ）。公司的章程说明了私人资本与国家利益的连结方式，奥登巴那维认为这对荷兰共和国是最有利的营运制度。荷兰东印度公司的任务不只是发展出贸易垄断，还得维护国家利益。就像英国东印度公司一样，荷兰东印度公司是一间由国家建立的私人企业，在成立时就获得了国家赋予的各种独有特权；举例来说，他们有权编组属于公司的海军和陆军。根据公司内部文件指出，立法机关对荷兰东印度公司与其他公司的监督和管制，在一六二○年代形成的商业奴隶贸易政策中扮演重大的角色。荷兰政府也参与了东印度公司的决策，并与公司共享档案与情资，帮助公司拟定策略。于是，就像英国与法国一样，荷兰的帝国企业以及史上首批大规模跨国公司的建立，全都源自于国家和私营部门的合作。9
在荷兰东印度公司成立不久后，荷兰政府与公司股东在一六○二年一起执行了一个大型的市场建设计划。在荷兰东印度公司的帮助下，奥登巴那维与荷兰当局在阿姆斯特丹设立了第一间真正的股票交易所，藉此推动该公司的股票交易。荷兰东印度公司是史上第一间上市公司，其股份在欧洲各国皆有销售。这个具开创性的成熟、先进市场并不是凭空出现的。一六○九年，阿姆斯特丹的领导阶层在市政厅成立了交易银行（Exchange Bank），又称为阿姆斯特丹银行（Bank of Amsterdam），政府监督此银行的运作，希望能藉此建立信心；并保证了贵金属货币与存款的价值，以便支付帐款给荷兰东印度公司。10
荷兰共和国在一五八一年成功脱离西班牙哈布斯堡王朝（Hapsburg Spain）并宣布独立后，开始试着进入原本向他们紧闭大门的西班牙与葡萄牙市场与贸易站。东印度公司的计划是控制亚洲贸易。在荷兰攻击与窃取伊比利亚人的财富与贸易的过程中，海盗行为发挥了重要作用。一六○三年二月，荷兰船长雅各布．希姆斯科（Jacob van Heemskerck）在新加坡海岸以东袭击并俘虏了葡萄牙船只圣卡特琳娜号（Santa Catarina）。荷兰海军部门先前已经直接命令希姆斯科不得涉入战争一类的行为。然而这艘船上的财富比荷兰法令更有说服力。圣卡特琳娜号抵达阿姆斯特丹时，船上载着一千两百捆的稀有中国丝绸和数百盎司的麝香，价值超过三百万荷兰盾──约三十万英镑。希姆斯科当然没有合法权力可以接管这艘船。虽然荷兰海事法庭最终裁定这些来自船上的战利品是合法取得的，仍有一些荷兰东印度公司的股东认为这种完全就是窃盗的行为并不道德，这使得正积极进军新帝国市场的荷兰东印度公司面临了挑战。15
荷兰共和国渴望能进入伊比利亚帝国贸易的大门，这样的想望催生了该时期最具影响力的一些利伯维尔场哲学。当圣卡特琳娜号的丑闻持续延烧，荷兰东印度公司找来了希姆斯科刚满二十岁的表亲，著名的人文主义法学天才雨果．格劳秀斯，请他撰写一篇文章来捍卫公司的利益。他们希望格劳秀斯能主张在抢攻西班牙与葡萄牙帝国市场的过程中，东印度公司拥有采用海盗行为的道德权利。格劳秀斯是著名的学者暨政治家的儿子，在十一岁时就被著名的莱顿大学（University of Leiden）录取。大学时期的他沉浸在经典典籍中，特别喜欢西塞罗的作品。而格劳秀斯接下来的人生就和这位著名的罗马法学家一样多彩多姿。他将会从卢夫斯泰因堡（Loevestein Castle）的囚牢逃脱，藏匿在一只本应该装满了书的箱子前往巴黎（这个箱子至今仍展示在该城堡），他将会在一场船难中幸存，并成为一名大政治家。他会运用具人文主义的渊博知识，成为那个时代最重要的法学理论家与卡尔文派神学家。
格劳秀斯的《论捕获法》（Commentary on the Law of Prize and Booty ，一六○四年）是一部对利伯维尔场思想产生了深远影响的著作，开启了格劳秀斯作为现代自然权利理论奠基者的法学作者生涯。《论捕获法》运用了普遍自然法的逻辑，为荷兰攻击甚至入侵葡萄牙帝国领土的行为进行辩护。这部充满专业术语的长篇著作很可能不是荷兰东印度公司原本想要的政治宣传文稿。无论如何，《论捕获法》为格劳秀斯的未来作品奠定了框架。格劳秀斯借用了西塞罗的观点，指出道德与自然的法则是举世通用的，任何个人都可以透过理性判断来厘清这些法则是什么。“背信弃义又残暴”的葡萄牙人想要控制全世界海洋的行为，已经造成了道德损害。此外，葡萄牙人拒绝荷兰进入帝国领土和原住民贸易，剥夺了荷兰人的自然权利，根据格劳秀斯的说法，这也是一种罪行。因而荷兰人对葡萄牙船只的俘获是合理的战利品，这样的行为是具有“诚实信用”（good faith）的。由于主权是一项自然权利，而非基督教专属，所以西班牙帝国的原住民也同样有选择和荷兰成为贸易盟友的权利与自由。考虑到荷兰大炮与堡垒的规模，这个针对伊比利亚提出的“原住民自由选择论”也就显得很有说服力了。16
一六○九年，格劳秀斯匿名出版了这本书的第十二章〈海洋自由论〉（The Free Sea），他这么做不只是为了东印度公司，也是为了发表他身为法律学者的第一篇公开著作。这篇文章在哲学与政治宣传两方面都带来了意想不到的成功。格劳秀斯针对自然、海洋与个人自由的本质提出了他的观点，这些观点为后来十七世纪的塞缪尔．普芬道夫（Samuel von Pufendorf）、约翰．洛克（John Locke）与之后其他关注自然权利与人类权利的欧洲思想家打下了基础。
格劳秀斯并且再次引用西塞罗的话，主张任何干涉自由的国家都是在招致一场正义的战争。此论点将会成为格劳秀斯在国际法方面的巨作《战争与和平的权利》（The Rights of War and Peace ，一六二五年）之核心。在阐述国家间互动应遵守的规则时，格劳秀斯坚持认为，个人应该有自然权利能选择自己的行为。“国际法律”（law of nations）和自然法则是相互独立的，国际法律清楚表明，只要以不伤害他人为前提，个人就拥有积极自由，可以去做他们选择的事。而这同样也是私有财产所有权的基础论点。任何国家都不能占有大自然中“不会耗竭”的广大资源；个人与国家只能拥有明确位于国界内部的有限事物，例如“湖泊、池塘和河流”。18
不过，跨国经济力量的现实状况并没有引起荷兰经济思想家的太多关注。在十七世纪中叶，荷兰的商业霸权正处于颠峰，这段时期的荷兰经济理论中最重要的著作是身为新教徒的布料制造商、经济学家暨利伯维尔场与共和国理论家彼得．寇特（Pieter de la Court）所撰写的《荷兰共和国的真正利益与政治准则》（The True Interest and Political Maxims of the Republic of Holland ，一六六二年）。这部作品是当时最精密成熟的利伯维尔场理论之一，寇特在其中主张，政治自由与自由贸易胜过了君主制的权柄。在荷兰大议长的支持下，掌握实权的首相约翰．维特（Johan De Witt）写道，寇特的作品是针对君主制的一记致命攻击，并指出这部作品详细描绘出了政治自由与宗教自由、自由贸易与自由竞争、制造业与船运都是自我调节的经济体制的一部分。寇特直接引用了英荷商人作家杰拉德．马林斯与其著作《商人法》（一六二二年）来主张商人的地位凌驾于君主之上。22 寇特主张的观点很单纯：君主制度对经济成长有害，荷兰的居民“在他们的政治体系中遭受的最大祸害，莫过于受到君主和最高领主的统治”。“伯爵”追求权力的野心会使政治变得不稳定，而“阿谀奉承的臣子”则会破坏那些使国家富裕的东西：“航海、制造业与商业”。23
在经历了无与伦比的经济成功之后，荷兰共和国于一六七二年遇上了史上恶名昭彰的灾难年 （Rampjaar），当时维特为了控制整个共和国，试图镇压国内权势最大的荷兰贵族，奥兰治的威廉三世亲王（Prince William III of Orange）。那一年，尽管在好战的法国国王路易十四入侵了荷兰共和国的境况下，威廉仍试图主张自己统治荷兰的权力。威廉自称为终身军队总司令，此举引起了法国打算让他担任国王的传言。荷兰共和国屈服后，威廉在七月九日成为总督，并公开挑战维特与寇特的影响力。七月二十三日，多德雷赫市（Dordrecht）的奥兰治派支持者抓到了维特的兄弟柯奈尔（Cornelis），对他用刑，并指控他意图谋反对抗威廉。威廉下令要约翰．维特支付巨额罚款换取释放柯奈尔。在约翰抵达多德雷赫市时，他原本以为自己可以使愤怒的奥兰治派群众冷静下来，却遭到了攻击与刺杀。群众谋杀了这对兄弟，斩下他们的头颅，吊起他们的身体，吃掉他们的肉──而威廉没有否认这些暴力行为。27
1. M. F. Bywater and B. S. Yamey, Historic Accounting Literature: A Companion Guide (London: Scholar Press, 1982), 87.
2. Jacob Soll, The Reckoning: Financial Accountability and the Rise and Fall of Nations (New York: Basic Books, 2014), 77.
3. Maarten Prak, The Dutch Republic in the Seventeenth Century (Cambridge: Cambridge University Press, 2005), 29.
4. Prak, Dutch Republic , 102.
5. Prak, Dutch Republic , 91.
6. Koen Stapelbroek, “Reinventing the Dutch Republic: Franco-Dutch Commercial Treaties from Ryswick to Vienna,” in The Politics of Commercial Treaties in the Eighteenth Century: Balance of Power, Balance of Trade , ed. Antonella Alimento and Koen Stapelbroek (Cham, Switzerland: Palgrave Macmillan, 2017), 195–215, at 199.
7. Prak, Dutch Republic , 105.
8. Prak, Dutch Republic , 96; Margaret Schotte, Sailing School: Navigating Science and Skill, 1550–1800 (Baltimore: Johns Hopkins University Press, 2019), 42, 53.
9. J. M. de Jongh, “Shareholder Activism at the Dutch East India Company, 1622–1625,” January 10, 2010, Palgrave Macmillan 2011, available at SSRN,https://ssrn.com/abstract=1496871 ; Jonathan Koppell, ed. , Origins of Shareholder Activism (London: Palgrave, 2011); Alexander Bick, Minutes of Empire: The Dutch West India Company and Mercantile Strategy, 1618–1648 (Oxford: Oxford University Press, forthcoming); Theodore K. Rabb, Enterprise and Empire: Merchant and Gentry Investment in the Expansion of England, 1575–1630 (Cambridge, MA: Harvard University Press, 2014), 38–41.
10. Lodewijk J. Wagenaar, “Les mécanismes de la prospérité,” in Amsterdam XVIIe siècle: Marchands et philosophes . Les bénéfices de la tolérance, ed. Henri Méchoulan (Paris: Editions Autrement, 1993), 59–81.
11. “A Translation of the Charter of the Dutch East India Company (1602),” ed. Rupert Gerritsen, trans. Peter Reynders (Canberra: Australasian Hydrographic Society, 2011), 4.
12. De Jongh, “Shareholder Activism,” 39.
13. Soll, Reckoning , 80; Kristof Glamann, Dutch Asiatic Trade, 1620–1740 (The Hague: Martinus Nijhoff, 1981), 245.
14. Soll, Reckoning , 81.
15. Hugo Grotius, Commentary on the Law of Prize and Booty , ed. Martine Julia van Ittersum (Indianapolis: Liberty Fund, 2006), xiii.
16. Grotius, Commentary , 10, 27; Hugo Grotius, The Free Sea , ed. David Armitage (Indianapolis: Liberty Fund, 2004), xiv, 7, 18.
17. Grotius, Free Sea , 5, 24–25, 32.
18. Grotius, Free Sea , 57; Hugo Grotius, The Rights of War and Peace , ed. Richard Tuck, 3 vols. (Indianapolis: Liberty Fund, 2005), 3:1750, 2:430–431.
19. Grotius, Rights of War and Peace , 2:556–557; Brett Rushforth, Bonds of Alliance: Indigenous and Atlantic Slaveries in New France (Chapel Hill: University of North Carolina Press, 2012), 90.
22. On new attitudes of merchant virtue, see J. G. A. Pocock, The Machiavellian Moment: Florentine Political Thought and the Atlantic Republican Tradition (Princeton, NJ: Princeton University Press, 1975), 478.
23. Pieter de La Court, The True Interest and Political Maxims of the Republick of Holland and West-Friesland (London: 1702), vi, 4–6, 9.
24. De La Court, True Interest and Political Maxims , 24–35.
25. De La Court, True Interest and Political Maxims , 63, 51, 55.
26. De La Court, True Interest and Political Maxims , 45, 51, 55, 312, 315.
27. Prak, Dutch Republic , 51, 53.
28. Prak, Dutch Republic , 59.
第七章 尚─巴提斯特．柯尔贝与国家市场
在重建商业的过程中，有两个必要条件：确定性和自由。 ──尚─巴提斯特．柯尔贝，《英格兰商业备忘录》（Mémoire Concerning Commerce with England ），一六五一年
荷兰是柯尔贝最大的担忧，因为尽管彼得．寇特针对利伯维尔场发表了许多高尚的言词，但真实状况就是荷兰的国家主义贸易政策非常具有侵略性，还拥有一支傲视其他国家的海军。对于“法国商业的糟糕处境”与法国高达四百万英镑的贸易逆差，柯尔贝始终充满怨言，他认为这是荷兰制定的条约导致的直接结果，该条约以牺牲竞争对手为代价来换取荷兰的贸易自由。柯尔贝认为荷兰对法国的种种侵犯，特别是他们对法国各种出口货品的劫持──举例来说，荷兰控制了法国在波罗的海这个富裕市场的酒类贸易──侵害了法国的自然权利。此外，荷兰也禁止那些可能在国内市场真正具有竞争力的法国商人与工匠进入荷兰境内。柯尔贝知道法国还太弱小了，还没有做好竞争的准备。如果他直接关闭与荷兰的贸易边界，只会对法国的发展造成损害。因而他追求的并不是贸易壁垒，而是设计良好的贸易条约，至少实现两国互惠。为此，柯尔贝认为政府应该招募经验丰富的商人来管理与撰写商业条约和法律。9 柯尔贝在打造法国工业时采用的策略，有一部分是基于他对一六五一年的英格兰《航海法》的理解，他（以及后来的亚当斯密）认为这项法令是英格兰获得发展优势的关键。同时，柯尔贝也主张荷兰人制定关税是为了要扼杀法国的贸易与制造业。一六七○年，在法国与荷兰进行了长时间的协商后，柯尔贝仍持续抱怨荷兰不但把所有法国商品排除在荷兰市场之外，同时还将矛头指向里尔市，想要扼杀该处的工业。此外，荷兰还致力于控制法属西印度群岛的贸易，迫使法属群岛购买荷兰商品。10 由于荷兰将一些法国边境城市、甚至法属殖民地的法国贸易商排除在交易对象之外，所以柯尔贝认为法国的保护主义关税是很公正合理的。因此，他想要追求的是巩固法国在自身领土内的贸易自由。他提议安地列斯群岛的居民靠着武装自己来抵御荷兰的干涉，如此一来他们才能以“完全自由”的状态来做生意。手段残酷的尚─查尔斯．巴斯（Jean-Charles de Baas）是法属安地列斯群岛的奴隶殖民地总督，柯尔贝在他寄给巴斯的信中写道，“商业的自由”不只是为了让法属西印度公司进行垄断而已。为了柯尔贝声称的“共同利益”，这种自由必须延伸至所有法国商人身上才行。他仍抱持着中世纪的概念，也就是经济自由是国家授予的特权。自由不会延伸到农奴、契约劳工、罪犯或奴隶的身上。自由仅限于贵族，以及那些持有国王通行证的法国商人和具有人身自由的定居者身上。经济自由不是一种普遍的自然权利，而是国家给予的特权。不过，无论这种想法有多局限，都一样建构出某种自由贸易的愿景。11
他为此颁布了一套商业的法律与标准，任何违反的人都会遭到重罚。柯尔贝手下的警察局长加布里埃尔．尼古拉斯．莱尼（Gabriel-Nicolas de La Reynie）是个聪明而无情的人，他负责监督巴黎的市场与街道──肉店、裁缝店、性工作者、街道照明与印刷业──并管理贸易行会，确保行会成员都遵守规定。他制裁了外国印花布料的非法流通，当时这些违禁布料在法国处处可见，而对法国工业造成了损害。意大利人、荷兰人和英格兰人长久以来一直利用法国宽松的商业监管措施来占便宜。作为响应，柯尔贝打造了一套印章系统来标示法国布料的质量，这使外国市场对法国布料充满信心。当英格兰人找到方法伪造法国皇家印章时，莱尼没收了数千令（ream）的外国布料。他帮助法国确保国内的羊毛业能够对英格兰羊毛业构成高度的商业威胁。13
对柯尔贝来说，在建立商业贸易与外国殖民地贸易的过程中，建立人们对法国声誉的信心就和法规以及保护主义同样重要。因此，在他建立法国商业市场的计划中，宣传（也就是如今所谓的广告）是一个关键。他定期邀请备受尊敬的学者担任代言人，藉此提高法国作为知识、文化与科技创新中心的声誉。一六六三年，柯尔贝正在成立法国东印度公司（French East India Company）时，邀请了院士暨学者法朗索瓦．夏邦提耶（François Charpentier）针对东印度贸易的历史与实用性撰写一篇文章。这篇文章的目的不只是刺激法国商业，同时也是在向外国竞争对手做宣传。夏邦提耶遵循柯尔贝的路线，主张“危险的自由放任主义”已经占据了法国，因此使得这个王国的繁荣发展受到战争和动荡的侵害。商业“就像博雅教育（liberal arts）一样”──是可以透过聚焦与专注来“培育”的。于是，夏邦提耶向读者提出挑战，要他们航向崭新的海洋，透过发现新“财富”。他说，“创新者”会创造出富裕。14
同时柯尔贝也雇用了耶稣会学者皮耶．丹尼尔．辉特（Pierre-Daniel Huet），他是阿夫杭士市（Avranches）的主教，也是一位博学的法兰西学术院（Académie Française）成员。柯尔贝令他负责撰写商业历史，将路易十四统治的法国与罗马帝国的荣光相比拟。在他的著作《商业与古代航海之历史》（History of Commerce and of the Navigation of the Ancients ，一七六三年）的序言中，辉特解释了柯尔贝如何利用法国的“优点”展示出商业对国家的重要。法国人们若想要与他国进行商业竞争，就必须开始重视航海与帝国建设。他解释说，罗马帝国的成功源自于贸易与帝国制度；如今法国也应该要跟随这种模式，成为国际商业界的新罗马。15
柯尔贝在一六六三年写下了〈为历史而写的法国金融事务备忘录〉（Memoirs on France’s Financial Affairs to Serve History），这篇文章循着马基维利、布丹和博泰罗的观点，认为一个国家唯有在“其方法得到妥善管理”时才能生存下去。换句话说，内政大臣必须运用财政能力来管理国家、有效征税，并妥善管理收入、支出、资产与负债。这种良好的管理将会创造出信心，使贸易之轮转动得更顺畅，并且如同柯尔贝反复提起的那样，创造出“商业自由”。柯尔贝动用了所有他能使用的经济模型与工具──从马基维利的国家愿景，到荷兰对会计的聚焦，再到英格兰的发展保护主义──去为市场带来信心。17
为接触法国的广大读者，柯尔贝赞助出版了他认为能够在法国公民身上培养商业知识与信心的一系列书籍。举例来说，他委托数学家暨会计大师法兰索瓦．巴雷姆（François Barrême）撰写复式记账会计的手册与关于货币兑换的书籍。会计学校采用了他撰写的实用数学手册《巴雷姆的算数》（The Arithmetic of Sir Barrême ，一六七二年）。巴雷姆在序言中指出了法国在财务素养方面的缺乏，就算在国家的最高层也一样：“柯尔贝先生一直希望国王管辖之下的所有业务都能使用复式记账，但他找不到足够多的熟悉复式记账的人才，使得财务监察机构的老旧做法迟迟无法革新。”巴雷姆的著作大获成功，后来成为了《巴雷姆通用手册》（Barrême Universel ），这本会计手册一直到十九世纪仍持续出版。18
一六六三年，设计了罗浮宫东面的著名院士暨建筑师克劳德．佩罗（Claude Perrault）开始和柯尔贝合作执行一项建造皇家科学院（Royal Academy of Sciences）的计划。佩罗写信给柯尔贝，说皇家科学院不只能光耀路易十四，更能宣传法国科学可信度，“出版科学发现，使这些发现为人所知”，并让法国“在全世界声名远播”。关于此计划的最初摘要显示，化学、解剖学、几何学、天文学和代数等研究领域具有实用性，且可以应用在法国的商业与金融事业中。他们的目标是使皇家科学院成为实验与公共教学的中心，把科学权威交到王室手中，接着再向全世界广为宣传。23
海更斯说服了柯尔贝：皇家科学院最重要的其中一个活动是出版自然历史著作，使用“共通”且容易理解的语言来解释科学实验，让社会大众也能了解。一六六五年，柯尔贝开始赞助丹尼斯．萨罗（Denis de Sallo）的计划，创办由国家控管的科学期刊《科学家周刊》（Journal des sçavans ），这份期刊使得法国成为了受信任的科学权威来源。《科学家周刊》主张他们会刊登“学术共和国（Republic of Letters）中的新事物”，也就是全球学界中的新事物。发行人表示，此期刊会聚焦在“有用”的事物上，人们将会在这里找到“每年的重大事件”。甚至到后来路易十四统治的法国进入了战争与政治、宗教压迫的最高峰时，欧洲各地的学者仍视此期刊为科学、数学、力学、哲学与最重要的“艺术与工艺”（也就是工程学）之重要权威。就连战争时期，法国仍因为《科学家周刊》而享有国际信誉。25
这些科学出版品使法国获得了工业与商业领导者的声誉──这样的声誉甚至有些言过其实。这项策略十分成功，在一六七○年代，英格兰人开始把法国视为比荷兰更大的商业强国──这在一六六一年还是无法想象的事。柯尔贝的弟弟是克鲁瓦西侯爵查尔斯．柯尔贝（Charles Colbert, marquis de Croissy），柯尔贝在一六六八年派查尔斯到伦敦担任大使，查尔斯让英国人留下绝佳的印象，成功说服了当时的英国国王查理二世私下支持法国对抗荷兰的行动，以换取每年二十三万英镑的个人报偿。尚─巴提斯特．柯尔贝在短短的数年内，使法国成为其他国家的真正商业竞争对手，甚至成为国际间的领导强国──至少表面上看起来是如此。27 著名的英国日记作者暨海军部秘书山缪．皮普斯（Samuel Pepys）对于这位“来自克鲁瓦西的柯尔贝”印象深刻，就皮普斯与其他人的了解，查尔斯是在哥哥的命令下来到英国监视英国工业与海军计划的。这使得尚─巴提斯特．柯尔贝显得更加令人生畏。皮普斯也热中阅读柯尔贝为商业宣传出版的作品。一六六九年一月三十日，皮普斯在日记中写道，他“认真阅读了一本法国的专书”，他担心这篇关于航海的书籍会使得人们觉得法国的海军与贸易能力就快要超越英国了。那本书正是法朗索瓦．夏邦提耶为东印度公司的成立所写的宣传著作，而这样的手法显然奏效了，使得皮普斯感到法国已经转变为成功的贸易大国，是英国最重要的竞争对手。法国的科技专长也同样使各国感到钦佩。皮普斯在一六九○年代的“海军会议纪录”（Naval Minutes）中记载道，法国拥有最精良的造船技术、船舰、港口和水手，并引用了柯尔贝在一六七一年制定的造船规范和一六七三年的战舰规范。皮普斯认为，从这些书籍就可以看出法国的海军能力远比英国更优越，他感叹道：“我国海军中的每一条优秀规范，有哪个不是法国早就设立好的规范呢？”柯尔贝的政策与宣传正中要害。28
在尚─巴提斯特．柯尔贝于一六八三年逝世时，他已经成功为法国打开了英国市场。法国甚至取得了对英国的贸易顺差。这对于英国商人来说是一场危机，他们认为法国占了上风，必须立刻予以阻止。在十七世纪，由于每个国家都在抢夺竞争优势，所以自由贸易条约的进步十分缓慢。29 不过，当时已有迹象显示，柯尔贝试图把法国转变成商业国家让太阳王很不满意。路易十四鄙视商人，认为他们是庸俗的暴发户，因而撤回了柯尔贝的许多改革政策。路易十四非但没有努力促进法国与最大贸易伙伴英国的自由贸易，反而想要发动战争。他不顾柯尔贝的意见，在一六七二年入侵荷兰。 光是向外侵略还不能让路易十四满足，他甚至在国内也走上了公民暴力的路线。一六八五年，也就是柯尔贝逝世两年后，路易十四废除了《南特诏令》（Edict of Nantes ），此法令原本旨在保护法国的新教徒少数族群。有超过二十万名法国新教徒遭受酷刑、被迫改信天主教，及受到镇压、监禁和驱逐。路易十四很清楚柯尔贝因为对贸易不利而反对宗教压迫，残暴成性的路易十四派了柯尔贝的儿子，也就是塞涅来侯爵（marquis de Seignelay）负责强迫新教徒转信天主教。法国新教徒的流亡目的地从荷兰、丹麦与英格兰，扩散到了日耳曼与美洲殖民地的多个地点。这对法国商业造成了严重打击。新教的胡格诺派（Huguenot）商人和工匠离开时，也带走了柯尔贝当初砸重金发展的专业技能；欧洲各国的君主都因为玻璃工匠、银匠、橱柜工匠和各种商人具有的优秀技术而乐于迎接他们的到来。事实上，正是《南特诏令》的废除使得法国今日没有制表的优良传统，法国的新教钟表匠全都逃到了卡尔文派的瑞士日内瓦（Geneva），那里至今仍是全球钟表贸易的中心。 与经济史学家一直以来所认知不同的是，大幅削弱柯尔贝主义与扩张市场自由可能性的，正是路易十四。作为在辉煌的贵族宫廷中心统治一整个王朝的国王，路易十四从不认为自己是普通商人的国王。目光短浅的路易十四更停止了对海军的经费支持，对殖民地的关注也下降了。现在，他的目光转向了战争。一六八八年，他开启了九年战争（Nine Years’ War），美洲将之称作威廉王之战（King William’s War），路易十四在这场战事中越过了莱茵河，积极地把法国的边界与领土向外扩张。为了对抗路易十四的侵略，英格兰、荷兰共和国、奥地利哈布斯堡神圣罗马帝国（Austrian Hapsburg Holy Roman Empire）、西班牙、葡萄牙与萨伏依（Savoy）结成了同盟。此外再加诸那些公开反对路易十四的胡格诺派教徒带来的影响，新教君主开始将太阳王视为巨大的威胁。长期的战争与饥馑，消灭了自由贸易的所有可能性。 一六九三年，法国北部的作物收成欠佳。在战争税与食物短缺造成的压力下，饥荒恶化成了伤寒疫情，此外还有类似沙门氏菌的细菌引起的腐热（putrid fever）与瘟疫腹热（pestilent abdominal fever）。一六九三年至一六九四年的大饥荒（Great Famine），扣掉正常死亡率后大约导致了一百三十万人死亡。士兵纷纷感染伤寒，不得不抱病作战。法国的财政陷入混乱，人民被大规模死亡的阴影尾随，整个国家都活在路易十四造成的无常战争与其灾难性影响的威胁之下。当路易十四发现自己无法入侵荷兰共和国与英格兰之后，便开始骚扰他们分布在世界各地的商人，威胁到了从西印度群岛至印度的英格兰殖民地和贸易路线。等到九年战争终于在一六九七年结束时，法国在所有层面上都元气大伤。威廉三世现在随时保持着英格兰与法国间的备战状态，英国商人也将法国视为军事与商业上的威胁。 这一切和柯尔贝过去的希望背道而驰。柯尔贝的梦想是以平等贸易的条约和互利作为基础，实现平衡的自由贸易，如今这个梦想已被暴力战争与大规模死亡取代。改革者为了与过去切割，便把路易十四毫无道理的破坏行为归咎到柯尔贝身上。那些推动法国改革与利伯维尔场的人，开始把柯尔贝这位逝世已久的内政大臣拿来作为法国需要改变之事物的象征。柯尔贝主义和柯尔贝在经济史上的地位遭到扭曲，并因为路易十四晚期的灾难性统治而蒙上污点。法国的利伯维尔场思想发展之所以窒碍难行，不是因为柯尔贝执行的经济政策，而是因为路易十四好战又专制的愚行扭曲了这位内政大臣的余荫。
1. Pierre Deyon, “Variations de la production textile aux XVIe et XVIIe siècles: Sources et premiers résultats,” Annales. Histoire, sciences sociales 18, no. 5 (1963): 939–955, at 949.
2. Daniel Dessert and Jean-Louis Journet, “Le lobby Colbert,” Annales 30, no. 6 (1975): 1303–1329; Georg Bernhard Depping, Correspondance administrative sous le règne de Louis XIV , 3 vols. (Paris: Imprimerie Nationale, 1852), 3:428; Philippe Minard, “The Market Economy and the French State: Myths and Legends Around Colbertism,” L’Économie politique 1, no. 37 (2008): 77–94; Jean-Baptiste Colbert, “Mémoire sur le commerce: Prémier Conseil de Commerce Tenu par le Roy, dimanche, 3 aoust 1664,” in Lettres, instructions, et mémoires de Colbert , ed. Pierre Clément, 10 vols. (Paris: Imprimerie Impériale, 1861–1873), vol. 2, pt. 1, p. cclxvi; Jean-Baptiste Colbert, “Mémoire touchant le commerce avec l’Angleterre,” in Lettres , vol. 2, pt. 2, p. 407.
3. Colbert, “Mémoire touchant le commerce avec l’Angleterre,” vol. 2, pt. 2, pp. cclxviii, 48, 407; D’Maris Coffman, Excise Taxations and the Origins of Public Debt (London: Palgrave Macmillan, 2013).
4. Colbert, “Mémoire sur le commerce, 1664,” vol. 2, pt. 1, pp. cclxii–cclxxii, at cclxviii, cclxix; Jean-Baptiste Colbert, “Aux maires, échevins, et jurats des villes maritimes de l’océan, aoust 1669,” in Lettres , vol. 2, pt. 2, p. 487; Colbert to M. Barillon, intendant at Amiens, mars 1670, in Lettres , vol. 2, pt. 2, pp. 520–521; Colbert to M. Bouchu, intentant at Dijon, juillet 1671, in Lettres , vol. 2, pt. 2, p. 627.
5. Gustav von Schmoller, The Mercantile System and Its Historical Significance (New York: Macmillan, 1897); Erik Grimmer-Solem, The Rise of Historical Economics and Social Reform in Germany, 1864–1894 (Oxford: Oxford University Press, 2003). 有关发展经济，参见 Erik S. Reinert, “The Role of the State in Economic Growth,” Journal of Economic Studies 26, no. 4/5 (1999): 268–326.
6. Deyon, “Variations de la production textile,” 949, 951–953; François Crouzet, “Angleterre et France au XVIIIe siècle: Essaie d’analyse comparé de deux croissances économiques,” Annales. Économies, sociétés, civilisations 21, no. 2 (1966): 254–291, at 267.
7. Crouzet, “Angleterre et France au XVIIIe siècle,” 266, 268; Eli F. Heckscher, Mercantilism , trans. Mendel Shapiro, 2 vols. (London: George Allen and Unwin, 1935), 1:82; Stewart L. Mims, Colbert’s West India Policy (New Haven, CT: Yale University Press, 1912); Charles Woolsey Cole, Colbert and a Century of French Mercantilism , 2 vols. (New York: Columbia University Press, 1939), 1:356–532; Charles Woolsey Cole, French Mercantilism, 1683–1700 (New York: Octagon Books, 1971); Glenn J. Ames, Colbert, Mercantilism, and the French Quest for Asian Trade (DeKalb: Northern Illinois University Press, 1996); Philippe Minard, La fortune du colbertisme: État et industrie dans la France des Lumières (Paris: Fayard, 1998).
8. Colbert, Lettres , vol. 2, pt. 2, p. 457.
9. Colbert, “Mémoire sur le commerce, 1664,” vol. 2, pt. 1, pp. cclxii–cclxxii, at cclxviii; Colbert, “Mémoire touchant le commerce avec l’Angleterre,” 405–409; Georg Bernhard Depping, Correspondance administrative sous le règne de Louis XIV , vol. 3 (Paris: Imprimerie Nationale, 1852), 90, 428, 498, 524, 570; Moritz Isenmann, “Égalité, réciprocité, souvraineté: The Role of Commercial Treaties in Colbert’s Economic Policy,” in The Politics of Commercial Treaties in the Eighteenth Century: Balance of Power, Balance of Trade , ed. Antonella Alimento and Koen Stapelbroek (London: Palgrave Macmillan, 2017), 79.
10. Colbert, “Mémoire touchant le commerce avec l’Angleterre,” 405–409, 496, 523, 570; Lawrence A. Harper, The English Navigation Laws: A Seventeenth-Century Experiment in Social Engineering (New York: Octagon Books, 1964), 16; John U. Nef, Industry and Government in France and England, 1540–1640 (repr. , Ithaca, NY: Cornell University Press, 1957 [1940]), 13, 27.
11. Colbert, “Mémoire touchant le commerce avec l’Angleterre,” 487; Colbert to M. du Lion, September 6, 1673, in Lettres , vol. 2, pt. 1, p. 57; Colbert to M. de Baas, April 9, 1670, in Lettres, vol. 2, pt. 2, p. 479.
12. Ames, Colbert, Mercantilism , 189; Mims, Colbert’s West India Policy , 232; Mireille Zarb, Les pivilèges de la Ville de Marseille du Xe siècle à la Révolution (Paris: Éditions A. et J. Picard, 1961), 163, 329; Jean-Baptiste Colbert, “Mémoire touchant le commerce avec l’Angleterre,” 407.
13. Jacques Saint-Germain, La Reynie et la police au Grand Siècle: D’après de nombreux documents inédits (Paris: Hachette, 1962), 238, 240.
14. François Charpentier, Discours d’un fidèle sujet du roy touchant l’establissement d’une Compagnie Françoise pour le commerce des Indes Orientales; Adressé à tous les François (Paris: 1764), 4, 8; Paul Pellisson, Histoire de l’Académie François e, 2 vols. (Paris: Coignard, 1753), 1:364.
15. Urban-Victor Chatelain, Nicolas Foucquet, protecteur des lettres, des arts, et des sciences (Paris: Librarie Académique Didier, 1905), 120; Pierre-Daniel Huet, Histoire du commerce et de la navigation des anciens (Lyon: Benoit Duplein, 1763), 1–2.
16. Huet, Histoire du commerce et de la navigation , cclxxii.
17. Heckscher, Mercantilism , 1:81–82; Jean-Baptiste Colbert, “Mémoires sur les affaires de finances de France pour servir à leur histoire, 1663,” in Lettres , vol. 2, pt. 2, pp. 17–68; J. Schaeper, The French Council of Commerce, 1700–1715: A Study of Mercantilism After Colbert (Columbus: Ohio State University Press, 1983); Colbert, “Mémoire sur le commerce,” 44–45.
18. François Barrême, Le livre nécessaire pour les comptables, avocats, notaires, procureurs, négociants, et généralement à toute sorte de conditions (Paris: D. Thierry, 1694), 3; François Barrême, Nouveau Barrême universel: Manuel complet de tous les comptes faits (Paris: C. Lavocat, 1837).
19. Ordonnance du commerce du mois de mars 1673; et ordonnance de la marine, du mois d’août 1681 (Bordeaux, France: Audibert et Burkel, an VIII), 5, Art. 4.
20. Jacques Savary, Le parfait négociant; ou, Instruction générale pour ce qui regarde le commerce des Marchandises de France, & des Païs Estrangers , 8th ed. , ed. Jacques Savary Desbruslons, 2 vols. (Amsterdam: Jansons à Waesberge, 1726), 1:25; Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations , ed. Roy Harold Campbell and Andrew Skinner, 2 vols. (Indianapolis: Liberty Fund, 1981), vol. 2, bk. IV, chap. vii, pt. 2, para. 53.
21. Peter Burke, The Fabrication of Louis XIV (New Haven, CT: Yale University Press, 1994); Colbert, “Mémoire sur le Commerce,” vol. 2, pt. 1, p. cclxiii; Alice Stroup, A Company of Scientists: Botany, Patronage, and Community in the Seventeenth-Century Parisian Royal Academy of Sciences (Berkeley: University of California Press, 1990), 30.
22. Colbert, Lettres , vol. 2, pt. 2, p. 62; vol. 5, pp. 241–242; Charles Perrault, “Autre note à Colbert sur l’établissement de l’Académie des Beaux-Arts et de l’Académie des Sciences,” 1666, in Colbert, Lettres , 5:513–514. Also see Roger Hahn, The Anatomy of a Scientific Institution: The Paris Academy of Sciences, 1666–1803 (Berkeley: University of California Press, 1971), 15; Lorraine Daston, “Baconian Facts, Academic Civility, and the Prehistory of Objectivity,” Annals of Scholarship 8 (1991): 337–363; Steven Shapin, A Social History of Truth: Civility and Science in Seventeenth-Century England (Chicago: University of Chicago Press, 1995), 291; Michael Hunter, Science and Society in Restoration England (Cambridge: Cambridge University Press, 1981), 48; Anthony Grafton, The Footnote: A Curious History (Cambridge, MA: Harvard University Press, 1997), 202–205; Jean-Baptiste Say, A Treatise on Political Economy , 2 vols. (Boston: Wells and Lilly, 1821), 1:32–33; Margaret C. Jacob, Scientific Culture and the Making of the Industrial West (Oxford: Oxford University Press, 1997), chap. 8.
23. Perrault, “Autre note à Colbert,” 5:514; Charles Perrault, “Note de Charles Perrault à Colbert pour l’établissement d’une Académie Générale, 1664,” in Colbert, Lettres , 5:512–513.
24. Christiaan Huygens, Oeuvres completes, 22 vols. (The Hague: Martinus Nijhoff, 1891), 19:255–256. 中括号内的批注来自麦可．马奥尼（Michael Mahoney）的翻译，在此采用：“[Memorandum from Christiaan Huygens to Minister Colbert Regarding the Work of the New Académie Royale des Sciences],” Princeton University, www.princeton.edu/~hos/h591/acadsci.huy.html .
25. Huygens, “Note from Huygens to Colbert, with the Observations of Colbert, 1670,” in Colbert, Lettres , 5:524; James E. King, Science and Rationalism in the Government of Louis XIV, 1661–1683 (Baltimore: Johns Hopkins University Press, 1949), 292; Joseph Klaits, Printed Propaganda Under Louis XIV: Absolute Monarchy and Public Opinion (Princeton, NJ: Princeton University Press, 1976), 74; Denis de Sallo, “To the Reader,” Journal des sçavans (January 5, 1665): 5; Jacqueline de la Harpe, Le Journal des Savants en Angleterre, 1702–1789 (Berkeley: University of California Press, 1941), 6, 8; Arnaud Orain and Sylvain Laubé, “Scholars Versus Practitioners? Anchor Proof Testing and the Birth of a Mixed Culture in Eighteenth-Century France,” Technology and Culture 58, no. 1 (2017): 1–34.
26. Liliane Hilaire-Pérez, Fabien Simon, and Marie Thébaud-Sorger, L’Europe des sciences et des techniques: Un dialogue des savoirs, xve–xviiie siècle (Rennes, France: Presses Universitaires de Rennes, 2016); John R. Pannabecker, “Diderot, the Mechanical Arts, and the Encyclopédie in Search of the Heritage of Technology Education,” Journal of Technology Education 6, no. 1 (1994); Cynthia J. Koepp, “Advocating for Artisans: The Abbé Pluche’s Spectacle de la Nature (1731–1751),” in The Idea of Work in Europe from Antiquity to Modern Times , ed. Josef Ehmer and Catherina Lis (Farnham, VT: Ashgate, 2009), 245–273. 有关柯尔贝艺术协会（Colbertist Société des Arts）转变成重农主义的转变过程，参见 Hahn, Anatomy of a Scientific Institution , 108–110; Robert Darnton, The Business of Enlightenment: A Publishing History of the Encyclopédie, 1775–1800 (Cambridge, MA: Belknap Press of Harvard University Press, 1979); Kathleen Hardesty, The Supplément to the Encyclopédie (The Hague: Nijhoff, 1977); John Lough, Essays on the “Encyclopédie” of Diderot and d’Alembert (London: Oxford University Press, 1968); Dan Edelstein, The Enlightenment: A Genealogy (Chicago: University of Chicago Press, 2010); Jacob Soll, The Information Master: Jean-Baptiste Colbert’s Secret State Information System (Ann Arbor: University of Michigan Press, 2009), 161; Robert Darnton, “Philosophers Trim the Tree of Knowledge: The Epistemological Strategy of the Encyclopédie,” in The Great Cat Massacre and Other Episodes in French Cultural History (New York: Vintage, 1984), chap. 5; Colbert, 1619–1683 (Paris: Ministère de la Culture, 1983), 168; Paola Bertucci, Artisanal Enlightenment: Science and the Mechanical Arts in Old Regime France (New Haven, CT: Yale University Press, 2017), 214. 另见 Linn Holmberg, The Maurist’s Unfinished Encyclopedia (Oxford: Voltaire Foundation, 2017), 175.
27. Colbert, “Mémoire touchant le commerce avec l’Angleterre,” vol. 2, pt. 2, p. 405.
28. Samuel Pepys, Naval Minutes , ed. J. R. Tanner (London: Navy Records Society, 1926), 352–356, at 356; King, Science and Rationalism , 272.
29. D. G. E. Hall, “Anglo-French Trade Relations Under Charles II,” History 7, no. 25 (1922): 17–30, at 23; Jacob Soll, “For a New Economic History of Early Modern Empire: Anglo-French Imperial Codevelopment Beyond Mercantilism and Laissez-Faire,” William and Mary Quarterly 77, no. 4 (2020): 525–550.
第八章 太阳王的噩梦和利伯维尔场的美梦
我们的美德往往是经过伪装的恶行。 ──拉侯谢傅科公爵（Duc de La Rochefoucauld），《格言录》（Maxims ），一六六五年
等到九年战争（一六八八年至一六九七年）结束时，法国和欧洲各国一样都疲惫不堪，他们经历的是二十多年间几乎未曾止歇的冲突。路易十四恐吓西属尼德兰，并利用他的影响力追捕与迫害各个邻国的法国新教难民。他的战争大臣，个性极为残忍的卢瓦侯爵（marquis de Louvois）在欧洲与世界各地推行暴力统治。为了应付战争的开支，法国征收了额外税金，使广大法国人民陷入悲惨的生活，多数人只能不断挨饿。
十七世纪最重要的其中一位探讨利己的哲学家，是著名的法国贵族法朗索瓦（François），即拉侯谢傅科公爵（Duc de La Rochefoucauld）。他的著作推动了人们相信个人机会主义能推动商业社会与市场，对利伯维尔场思想造成了重大的影响。拉侯谢傅科公爵质疑西塞罗那套“爱与友谊推动交易”的说法，他承袭圣奥古斯丁与霍布斯的观点，认为人类的行为并非出自仁慈，而是出自对于自身的关注。因此，他希望能了解欲望，也就是他所谓的“自爱”（self-love，法文为amour propre），会如何影响人类的所有行为。他相信在更好的环境条件下，人类确实可以透过斯多噶派的纪律找到美德。但当统治者是专制且道德破产的帝王时，这种道德自由是不可能的事。拉侯谢傅科公爵尤其反对路易十四用君主专制主义剥夺贵族的古老农业美德，他将凡尔赛宫的皇室比做交易荣誉和特权的“股票交易所”，而贵族们正试图从中获利。他谴责道，在路易十四的世界中，所有行为与友谊都“只以利己为基础”。3
对于路易十四压迫性的天主教主义，最主要的批判来自杨森主义天主教徒（Jansenist Catholics）。他们和拉侯谢傅科公爵一样，希望能找出一套系统来运用利己，将之转变成好的事物。法国的杨森主义信徒受到十七世纪初法兰德斯的伊珀尔主教（bishop of Ypres）康涅留斯．杨森（Cornelius Jansen）的启发，追求的不只是灵性上的完善，还要寻找一套能够减轻原罪与改善世俗生活的体系。杨森主义者是圣奥古斯丁的忠实深度读者，他们相信上帝创造出了一个完美的世界，人类的罪行却扰乱了这个世界。杨森主义者因为路易十四的贪婪与自恋而感到疲惫，认为自给自足的商业市场最可能让人类有机会把原罪与欲望转换成美德。他们相信奇迹的时代已经结束了，“上帝已经隐藏了”。除一小群被选中的人能透过上帝的恩典获得救赎之外，其他人类不会得到上帝的解救，只能赤身裸体地留在孤独之中，成为自身罪恶本质的猎物。包括著名的法京剧作家尚．拉辛（Jean Racine）在内，些许法国思想家因为杨森主义者的观点深受感动，从世俗中完全抽身并独自住在小房间里，追求奥古斯丁式的自我克制和虔诚美德。但是这种纯粹主义缺乏广泛的吸引力。广大人类中的绝大多数不可能在社会中生活的同时完全避免罪恶与利己。事实上在路易十四统治下的法国，若不参与他的政权就无法完全正常地生活。于是，有些人开始寻找新方法，希望至少能用这个方法来应付受到人类的贪婪与利己所主宰的世界。5
尚．多马（Jean Domat）是一位信奉杨森主义的著名罗马法学专家，他塑造了基督徒版本的旧佛罗伦萨理想，把商业视为能够使国家富强的一种公民货品。多马仔细研究市场机制如何疏导、甚至消除罪恶，为利伯维尔场思想设计了一套基督徒观点的框架，对后世产生长远的影响。他的著作《公民法之自然法则》（The Civil Law in Its Natural Order ，一六八九年至一六九四年）是一部国际知名的罗马法摘要集，清楚描述了市场如何自由地对人类的渴望与情绪做出回应。多马承袭了西塞罗的看法，认为人类可以在自然之中辨认出永恒不变的法则，一旦我们允许这些法则自然运作，就能启动一种动态的市场系统，控制住人类唯利是图的倾向。
若说拉侯谢傅科公爵和多马这一类的哲学家在寻找的，是一个把个人罪恶转变成公共美德的公式，那么其他更直接参与路易十四国家事务的哲学家，在寻找的就是能够治疗法国痼疾的解药。来自鲁昂的杨森主义税吏暨利伯维尔场与经济均衡的先驱理论家，布阿吉尔贝尔男爵皮耶．皮森特（Pierre Le Pesant, sieur de Boisguilbert）甚至直接向路易十四的财政大臣提出了利伯维尔场作为解决方案，其他提案参与者中，也包括柯尔贝的外甥和他在专业知识方面的继承人尼古拉斯．德马雷兹（Nicolas Desmaretz）。
布阿吉尔贝尔在柯尔贝最成功的其中一个商业区担任警方督察（intendant of police）：拥有羊毛加工业的繁荣城镇鲁昂。运用他在自己的贵族领地与行政辖区实施收税的经验，为国家政策的实际应用发展出了第一个自我延续市场的现代观念。他认为法国的经济困境源自人类的错误判断，于是开始撰写一本说明经济能如何自我驱动的著作。他在一六九五年出版的《详述法国》（Detail of France ）是史上第一本专门讨论自我延续市场机制之经济思想的详尽书籍。他在书中指责，虽然有货币在法国境内流通，但它们并没有在创造财富，这些货币若非只对富人的利益有帮助，就是被税收侵蚀掉。针对农民的税收制度既不公平又具有惩罚性，此一制度瘫痪了消费、破坏了农业、使货币的价值与流通性下降，还阻碍了能带来财富的生产与市场本身。7
在柯尔贝的直系继任者们所制定的政策中，利伯维尔场哲学发挥作用的例子并非只有这次。事实上，在十七世纪末，柯尔贝家族已站在利伯维尔场思想的先锋位置。德马雷兹并不是家族中唯一一个和其他人连手进行利伯维尔场改革的人。柯尔贝的女婿和康佩（Cambrai）主教法朗索瓦．萨利尼克．莫斯─芬乃伦（François de Salignac de la Mothe-Fénelon）密切合作，芬乃伦是一位狂热的自由放任主义理论家，也是当时影响力最大的作家之一。 芬乃伦在一六八九年至一六九七年担任路易十四的推定继承人勃艮第公爵（duc de Bourgogne）的导师，因而成为皇室家庭的成员，能定期接触到国王、他的家人和他的大臣。芬乃伦不但是一位才华洋溢的宗教演说家，后来也成为了提出自由放任主义愿景的十七世纪作者中，拥有最广大阅读群众的一位。芬乃伦的老师是路易十四的首席神学家雅克─贝尼涅．波苏维（Jacques-Bénigne Bossuet），负责在凡尔赛宫的皇家礼拜堂里布道的波苏维不仅支持宗教绝对主义的政治理论，也提倡宗教不宽容。在一六八五年的《南特诏令》废除后，路易十四派出波苏维和芬乃伦执行国家任务，到法国西南大西洋沿岸的拉荷歇尔（La Rochelle）周边改变新教徒的信仰。在拉荷歇尔的这段期间，芬乃伦对他们以暴力军事手段改变宗教信仰一事感到心灰意冷，也对路易十四的政治和经济政策感到失望。 芬乃伦在宫廷中的人脉很广，与柯尔贝的女婿第二代圣艾尼昂公爵保罗．波维利尔（Paul de Beauvilliers, 2nd duc de Saint-Aignan）过从甚密，并在其他人的引见下和德马雷兹变得关系密切。波维利尔的另一位密友是在宫廷中声势逐渐崛起的吕纳公爵（duc de Luynes）查尔斯．奥诺雷．达贝尔（Charles-Honoré d’Albert），他是柯尔贝的另一个女婿，一般对他的称呼来自另一个家族头衔谢夫勒斯公爵（duc de Chevreuse）。如今柯尔贝的女婿波维利尔和谢夫勒斯在宫廷中掌权，德马雷兹进入财政部，柯尔贝的侄子托尔西侯爵尚─巴提斯特．柯尔贝（Jean-Baptiste Colbert, marquis de Torcy，又称作托尔西的柯尔贝〔Colbert de Torcy〕）则在一六九六年被任命为外交事务大臣，于是柯尔贝家族集团得以在路易十四的宫廷与政府高层中呼风唤雨。我们可以从他们的通信中得知，他们是以家族为单位在运作，持续累积他们的财富，就连在支持芬乃伦的构想时也一样。在波维利尔和德马雷兹的带领下，这个强大的集团一起制定战略，希望能找回柯尔贝的优秀政府管理，建立更加自由的市场。13
波维利尔同时也是皇室未成年子女的监护人，因此在皇室中拥有绝大的影响力。路易十四知道他们是一个集团，所以在召开正式会议时，只会召集柯尔贝政府集团里的领导成员：托尔西的柯尔贝、波维利尔和德马雷兹。他让柯尔贝集团任命芬乃伦担任路易十四的七岁孙子的家教老师，这个孙子就是最终继承了王位的勃艮第公爵。波维利尔和芬乃伦相信，这名年幼的君主是通往改革的道路，更是能让他们获得更多权力的途径。他们打算以柯尔贝的治理方法为基础为这位年轻公爵制定学习计划。一六九七年，波维利尔和芬乃伦开始执行这项勃艮第公爵计划，使用一套庞大的统计书籍《绍讷列表》（The Tables of Chaulnes ），希望让这位继承人了解，要如何透过一套能带来经济自由的治理改革，来扩张法国的人口与商业规模。其内容聚焦于透过柯尔贝当年的统计法去计算、测量与在地图上标示法国的所有重要财富与管辖区。此外，计划的另一个目的是创造更好的税收制度：每一种形式的应税财产都要确实记录下来。14
一六九九年，柯尔贝家族密切支持芬乃伦撰写小说《忒勒马科斯的冒险》（The Adventures of Telemachus ），供勃艮第公爵的教育所用。《忒勒马科斯的冒险》是那个时代最明确、影响力也最大的农业利伯维尔场思想著作，也是十八世纪的畅销书，启发了从莫扎特到亚当斯密等多位重要人物。芬乃伦的小说填补了荷马的著作《奥德赛》（Odyssey）中缺漏的情节，描述了奥德修斯的儿子忒勒马科斯在冒险中学习的故事。故事中，有一位睿智的老师一直陪在忒勒马科斯身边，芬乃伦透露，这位老师其实是伪装过后的智慧女神密涅瓦（Minerva）。15
想当然耳，路易十四既没有听从芬乃伦的建议，也没有理会柯尔贝家族中的其他成员。芬乃伦提出的利伯维尔场改革方案全都没有问世。不如说，我们可以认为路易十四后来的统治彻底摧毁了柯尔贝与其后继者真正追求的目标。路易十四对于芬乃伦的批判怒火中烧，在一六九九年将他逐出宫廷，继续进行西班牙王位继承战争（War of Spanish Succession，一七○一年至一七一四年）。这正是芬乃伦曾提出警告的那种噩梦。路易十四的战争使得法国开始对抗英格兰大同盟（Grand Alliance of England），包括荷兰共和国、奥地利大公国以及后来的西班牙和萨伏依。根据军事史学家的估计，交战中的死亡人数大约落在七十万至一百二十万之间──且法国在之前一六九三年至一六九四年间的大饥荒已经死了一百二十万人。一七○九年，太阳黑子引起的气温骤降导致了大霜冻（Great Frost），法国在这段期间又死了六十万人。在虚弱、饥饿与绝望中，法国人口共减少了数百万之多。
路易十四践踏了柯尔贝留下的功绩，也抹煞了可能随之而来的商业自由与经济成长。不过，在这些惨烈的失败中，柯尔贝最重要的其中一些改革存活了下来。虽然法国仍是农业社会，受到贵族与专制君主的统治，但法国工业仍有持续产出，在全球商业的舞台上和英格兰继续竞争。法国非但仍是全世界的两大科学强国之一，而且还成为了欧洲启蒙运动的摇篮。启蒙运动是一场错综复杂的科学与思想进步的运动，事实将证明此运动是现代利伯维尔场思想哲学的核心。法国经济思想家将会透过哲学家查理．路易．德．色贡达（Charles-Louis de Secondat），也就是孟德斯鸠男爵（baron de Montesquieu）所谓的“温和”商业，以贸易的互利性取代自爱的战争本能，寻找通往和平与繁荣的永久道路。换句话说，自由贸易就是嫉妒、战争与贫困的解药。法国将会在这方面对英国经济哲学造成深远的影响。在这两个国家中，人们此刻还坚持认为，只要人类能靠着解放农业市场来妥善利用大自然，那么市场就能在和平之中创造奇迹，制造无穷尽的财富。21
1. Albert O. Hirschman, The Passions and the Interests: Political Arguments for Capitalism Before Its Triumph (Princeton, NJ: Princeton University Press, 1977), 16.
2. Thomas Hobbes, Leviathan , ed. Richard Tuck (Cambridge: Cambridge University Press, 1997), pt. 1, chaps. 13–14.
3. La Rochefoucauld, Maxims , trans. Leonard Tancock (London: Penguin, 1959), maxims 48, 85, 112, 563; Pierre Force, Self-Interest Before Adam Smith: A Genealogy of Economic Science (Cambridge: Cambridge University Press, 2003), 146, 176; Norbert Elias, The Court Society (New York: Pantheon Books, 1983), 105.
4. La Rochefoucauld, Maxims , 66, 77, 223, 305.
5. David A. Bell, The Cult of the Nation in France: Inventing Nationalism, 1680–1800 (Cambridge, MA: Harvard University Press, 2003), 28; Dan Edelstein, On the Spirit of Rights (Chicago: University of Chicago Press, 2019), 120; Pierre Nicole, “De la grandeur,” in Essais de morale , 3 vols. (Paris: Desprez, 1701), 2:186; Dale van Kley and Pierre Nicole, “Jansenism, and the Morality of Self-Interest,” in Anticipations of the Enlightenment in England, France, and Germany , ed. Alan C. Kors and Paul J. Korshin (Philadelphia: University of Pennsylvania Press, 1987), 69–85; Gilbert Faccarello, Aux origins de l’économie politique libérale: Pierre de Boisguilbert (Paris: Éditions Anthropos, 1985), 99.
6. Jean Domat, The Civil Law in Its Order Together with the Publick Law , 2 vols. (London: William Strahan, 1722), vol. 1, chap. 2, sec. 2; vol. 1, chap. 5, sec. 7; vol. 2, bk. 1, title 5; Faccarello, Aux origins de l’économie politique libérale , 146; Edelstein, On the Spirit of Rights , 120; David Grewal, “The Political Theology of Laissez-Faire : From Philia to Self-Love in Commercial Society,” Political Theology 17, no. 5 (2016): 417–433, at 419.
7. Pierre Le Pesant de Boisguilbert, Détail de la France (Geneva: Institut Coppet, 2014), 18, 61–63.
8. Boisguilbert, Détail de la France , 77, 89, 99.
9. Faccarello, Aux origins de l’économie politique libérale , 115, 119.
10. Gary B. McCollim, Louis XIV’s Assault on Privilege: Nicolas Desmaretz and the Tax on Wealth (Rochester, NY: University of Rochester Press, 2012), 106, 149; A. -M. de Boislisle, Correspondance des contrôleurs généraux des finances , 3 vols. (Paris: Imprimerie Nationale, 1883), 2:530.
11. Boisguilbert to Desmaretz, July 1–22, 1704, Archives Nationales de France, G7 721; Boislisle, 2:207, 543–547, 559.
12. Boislisle, Correspondance des contrôleurs généraux , 2:544.
13. Georges Lizerand, Le duc de Beauvillier (Paris: Société d’ÉditionLes Belles Lettres, 1933), 43, 153.
14. Lionel Rothkrug, Opposition to Louis XIV: The Political and Social Origins of the French Enlightenment (Princeton, NJ: Princeton University Press, 1965), 263–269, 286–287; Louis Trénard, Les Mémoires des intendants pour l’instruction du duc de Bourgogne (Paris: Bibliothèque Nationale, 1975), 70–82; David Bell, The First Total War: Napoleon’s Europe and the Birth of Warfare as We Know It (New York: Houghton Mifflin, 2007), 62; Lizerand, Le duc de Beauvillier , 46–77; marquis de Vogüé, Le duc de Bourgogne et le duc de Beauvillier: Lettres inédites, 1700–1708 (Paris: Plon, 1900), 11–23; Jean-Baptiste Colbert, marquis de Torcy, Journal Inédit , ed. Frédéric Masson (Paris: Plon, Nourrit et Cie, 1884), 57; Louis de Rouvroy, duc de Saint-Simon, Projets de gouvernement du duc de Bourgogne , ed. P. Mesnard (Paris: Librarie de L. Hachette et Cie, 1860), xxxix, 13; Edmond Esmonin, “Les Mémoires des intendants pour l’instruction du duc de Bourgogne,” in Études sur la France des XVIIe et XVIIIe siècles (Paris: Presses Universitaires de France, 1964), 113–130, at 117–119; Boislisle, Correspondance des contrôleurs généraux, 2:ii.
15. Georges Weulersse, Le movement physiocratique en France de 1756 à 1770 , 2 vols. (Paris: Félix Alcan, 1910), 2, 302; François Fénelon, Telemachus , ed. and trans. Patrick Riley (Cambridge: Cambridge University Press, 1994), 60, 195, 325.
21. Montesquieu, De l’Esprit des lois , ed. Victor Goldschmidt, 2 vols. (Paris: Garnier-Flammarion, 1979), vol. 2, bk. 20, chap. 1.
第九章 行星运动与英国自由贸易的新世界
贸易的本质是自由的，它会找到自己的渠道，决定最好的路线：所有针对贸易制定的规则、引导、限制和约束，往往都是对特定个人有利的法律，鲜少对公众有利。 ──查尔斯．达凡南特（Charles Davenant），《论东印度贸易》（An Essay on the East India Trade ），一六九六年
在十七世纪的前数十年，佛罗伦萨仕绅暨天文学家伽利略．伽利莱（Galileo Galilei）延续了哥白尼的研究，坚持认为基础物理可以透过严谨且客观的数学定律，应用在行星上。伽利略试着透过惯性的力量来了解行星运动，惯性力量会使行星能抗拒方向的变化，藉此维持绕行太阳的轨迹。伽利略的发现在该世纪早期带来了巨大的影响，但他并不是唯一一个致力于动力学的杰出科学家。一六二八年，英国医师威廉．哈维（William Harvey）发表了《论心脏与血液之运动》（Anatomical Account of the Motion of the Heart and Blood ），指出心脏会推动血液流往全身，形成自我延续的回路；人体像是一个能够运输与流动的有机器械，反映了星辰的运动方式。伽利略和哈维的作品启发了法国哲学家勒内．笛卡儿（René Descartes）写下《世界》（The World ，一六三三年），此著作描述了物质是如何遵循自身的自然轨迹运行，推动这种运行的并不是神秘学性质的力量，而是物质之间的相互作用力。他认为运动的动力并非来自上帝，而是来自较小的物体，也就是微粒（corpuscule）之间的机械式相互作用力。2 英国自然哲学家、数学家暨天文学家艾萨克．牛顿主张，大自然会按照物理的自我延续法则，以可预测的方式运作。牛顿因此建立了一套对于上帝神圣行动的崭新观点，认为上帝是大自然运行的监督者，而不是直接执行者。举例来说，上帝并没有创造闪电与暴风雨当作惩罚，彗星也不是预兆；这些只是大自然这个巨大机械中的零件在移动罢了。牛顿认为，自然现象所遵循的恒定物理定律，是人类可以藉由数学去理解的。更有甚者，他认为行星的运行定律也可以套用在社会与市场上。如果人类能了解社会与市场的运作机制的话，那么人类也将能预测社会与市场。3 牛顿相信，如果人类能理解大自然的运作流程，就可以揭露无限量创造黄金与白银的秘密方法。他遵循悠久且神秘的炼金术传统，推测地球是透过“植物精神”（vegetable spirit）的力量运作，此外，地球本身就是一种“巨大的动物”，会呼吸、寻求“更新”并维持自身的生命。牛顿确信地球内部有一种秘密能量，源自硫磺与水银组成的“贤者之石”（philosopher’s stone）。这其实并不只是幻想而已。牛顿在一六八七年写下的典范之作《数学原理》（Principia mathematica ）中描述了行星的引力运动与日心说的数学原理，希望能让无神论者别再主张宇宙的混乱代表了这个世界上没有所谓的神圣计划。牛顿认为，从根本上来说，这个世界的系统是以明确规律为基础在运行的机械式系统，而他相信这种规律让我们看见了上帝之手的创造痕迹。4 和牛顿同一时代的日耳曼新教哲学家戈特弗里德．威廉．莱布尼兹（Gottfried Wilhelm von Leibniz）也同样在寻找宇宙的驱动力。莱布尼兹是一名博学之士，他发明了微积分和现代物理学，认为是上帝创造了人类的生命和大自然，使这两者像精密的时钟一样运作，并且拥有无限种运动的可能性。他指出，手表中的平衡摆轮的德文是“Unruhe “，同时也有“不安”和“骚动”的意思。莱布尼兹认为，这种骚动不安就是制造出运动的源头。这个宇宙是所有事物在一个“预先建立的和谐系统”中不断流通的无限总和。他以辨给的口才指出，理解这种无休止运动的困难之处就像要理解“一座由连续体（continuum）构成的迷宫”。5
政治理论家约翰．洛克认为，人类社会是依据各种理性原则自行组织而成的，这些原则反映了牛顿的运动力学理论和佩第的观点，也就是个人可以透过自由选择创造出经济效率。洛克强烈反对政治专制主义，成为那个时代在宪政与个人权利方面影响力最高的理论家。洛克正是因为极端厌恶斯图亚特和波旁（Bourbon）的专制军权与践踏个人权利的行为，才写下了《政府论两篇》（Two Treatises on Government ，一六八九年）。他的灵感同时来自西塞罗和基督教，解释说私有财产是政治自由与有效运作市场的重要关键。伊甸园的所有事物都是共享的，而在亚当从伊甸园坠落至俗世时，也就创造出了我们对私有财产与人类劳动的需求。10
洛克和达凡南特的想法十分符合当时的科学与政治观点。事实上，在一六八八年的英国光荣革命（Glorious Revolution）中，奥兰治的威廉与他的英格兰妻子玛丽推翻了她的父亲，也就是倾向专制的詹姆士二世；威廉实施了《权利法案》（bill of rights ）与君主立宪制，带领英格兰迈入真正的全球商业时代。英法之间的全球经济霸权争夺战又再进一步升温。讽刺的是，这两个国家为了经济主导地位而进行的斗争，将会催化新的政治经济思想运动。英法愈是在商业与工业相互竞争，哲学家们就愈渴望把西塞罗对农业与和平的信念，结合到永恒运动和财富创造的概念中，藉此达成他们理想中的自由贸易。18
1. Ludwig Wittgenstein, Culture and Value , ed. Georg Henrik Wright, Heikki Nyman, and Alois Pichler, trans. Peter Winch (London: Blackwell, 1998), 18; Richard J. Blackwell, “Descartes’ Laws of Motion,” Isis 52, no. 2 (1966): 220–234, at 220.
2. Vincenzo Ferrone, “The Epistemological Roots of the New Political Economy: Modern Science and Economy in the First Half of the Eighteenth Century,” paper presented at the conference “Mobility and Modernity: Religion, Science and Commerce in the Seventeenth and Eighteenth Centuries,” University of California, Los Angeles, William Andrews Clark Memorial Library, April 13–14, 2018.
3. Margaret C. Jacob, The Newtonians and the English Revolution, 1689–1720 (Ithaca, NY: Cornell University Press, 1976), 174; Rob Iliffe, The Priest of Nature: The Religious Worlds of Isaac Newton (Oxford: Oxford University Press, 2017), 6.
4. Betty Jo Teeter Dobbs and Margaret C. Jacob, Newton and the Culture of Newtonianism (Amherst, NY: Humanity Books, 1990), 26, 100; William R. Newman, Newton the Alchemist: Science, Enigma, and the Quest for Nature’s “Secret Fire” (Princeton, NJ: Princeton University Press, 2019), 64, 70.
5. Dobbs and Jacob, Newton and the Culture of Newtonianism , 42; Gottfried Wilhelm Leibniz, Theodicy , ed. Austen Farrer, trans. E. M. Huggard (Charleston, SC: BiblioBazaar, 2007), 43, 158; G. W. Leibniz, “Note on Foucher’s Objection (1695),” in G. W. Leibniz, Philosophical Essays , ed. and trans. Roger Ariew and Daniel Garber (Indianapolis: Hackett, 1989), 146; G. W. Leibniz, The Labyrinth of the Continuum: Writings on the Continuum Problem, 1672–1686 , trans. Richard T. W. Arthur (New Haven, CT: Yale University Press, 2001), 566.
6. William Letwin, The Origins of Scientific Economics: English Economic Thought, 1660–1776 (London: Methuen, 1963), 128.
7. François Crouzet, “Angleterre et France au XVIIIe siècle: Essaie d’analyse comparé de deux croissances économiques,” Annales. Économies, sociétés, civilisations 21, no. 2 (1966): 254–291, at 268; T. S. Ashton, An Economic History of England: The Eighteenth Century (London: Methuen, 1955), 104; François Crouzet, Britain Ascendant: Comparative Studies in Franco-British Economic History (Cambridge: Cambridge University Press, 1991), 17–23, 73.
8. William Petty, “A Treatise of Taxes and Contributions,” in William Petty, Tracts Chiefly Relating to Ireland (Dublin: Boulter Grierson, 1769), 1–92, at 23–26, 32.
9. William Petty, “The Political Anatomy of Ireland, 1672,” in Petty, Tracts , 299–444, at 341.
10. John Locke, Two Treatises of Government , ed. Peter Laslett (Cambridge: Cambridge University Press, 1960), 171; John F. Henry, “John Locke, Property Rights, and Economic Theory,” Journal of Economic Issues 33, no. 3 (1999): 609–624, at 615.
11. Locke, Two Treatises , 291, 384.
12. John O. Hancey, “John Locke and the Law of Nature,” Political Theory 4, no. 4 (1976): 439–454, at 219, 439.
13. Holly Brewer, “Slavery, Sovereignty, and ‘Inheritable Blood’: Reconsidering John Locke and the Origins of American Slavery,” American Historical Review 122, no. 4 (2017): 1038–1078; Mark Goldie, “Locke and America,” in A Companion to Locke , ed. Matthew Stuart (Chichester: Wiley-Blackwell, 2015), 546–563; Letwin, Origins of Scientific Economics , 163–165; David Armitage, “John Locke, Carolina, and The Two Treatises of Government,” Political Theory 32, no. 5 (2004): 602–627, at 616; J. G. A. Pocock, The Machiavellian Moment: Florentine Political Thought and the Atlantic Republican Tradition (Princeton, NJ: Princeton University Press, 1975), 283–285, 339.
14. Charles Davenant, An Essay on the East India Trade (London, 1696), 25.
15. Pocock, Machiavellian Moment , 437, 443.
16. Pocock, Machiavellian Moment , 446; Charles Davenant, Reflections upon the Constitution and Management of the Trade to Africa (London: John Morphew, 1709), 25, 28.
17. Davenant, Reflections , 27, 36, 48, 50, 58.
18. Steven Pincus, 1688: The First Modern Revolution (New Haven, CT: Yale University Press, 2009), 308.
第十章 英国与法国：贸易战、赤字与找到天堂的美梦
因此，尽管每一个角落都充满了罪恶，但整体来说这里却是天堂。 ──伯纳德．曼德维尔，《蜜蜂的寓言》（The Fable of the Bees ），一七一四年
此时的英国正处于金融革命（Financial Revolution）之中。一六九四年，威廉三世的政府需要更好的信用条件才能在英格兰与法国的战争中继续坚持，而英格兰银行（Bank of England，通称英国央行）的成立对政府带来了很大的帮助，英格兰银行不但以合理的利率借钱给政府，让政府能管理债务，同时也在信贷市场中建立了信心，并资助创业计划。正如约翰．洛克的主张，社会需要信心与达成共识的体制，才能建立对市场的信任。但是债务仍然不断成长，从一六八八年的一百万英镑增加到一六九七年的一千九百万英镑，这些债务是个大杂烩，包括利率百分之七的年金、浮动债务、抽签公债（lottery loan），以及来自英格兰银行和南海与东印度公司的贷款。就算有了这间新银行，国家债务仍是一个棘手的问题。2
除此之外，英格兰也处于政治动荡之中。一七○七年，英格兰和苏格兰合并成为大不列颠（Great Britain）。威廉与玛丽的女儿安妮女王（Queen Anne）于一七一四年在没有继承人的情况下过世，这推动了宪制的《光荣革命嗣位法令》（Act of Settlement of the Glorious Revolution ）的制定，明确规定王位由女王关系最近且仍旧存活的新教徒亲戚来继承，当时的王位正好落在日耳曼血统的汉诺威选帝侯（imperial elector of Hanover），布伦瑞克─吕讷堡公爵乔治．路易（George Louis, Duke of Brunswick-Lüneburg）的身上，也就是后来的大不列颠国王乔治一世（George I of Great Britain）。他在一七一四年八月一日登基，同时也继承了国家的债务。3
这些想法很快就引起了社会大众的注意。一七○七年，伦敦出现了一本标题非常精彩的匿名小册子：《论有效应对方法；又名，图隆等式：改善美洲西南部贸易的友好认购提案，每年为东印度贸易和王室收入增加三百万黄金与白银，若得到鼓励则将会产生相应的结果》（An Account of What Will DO; or, an Equivalent for Thoulon: In a Proposal for an Amicable Subscription for Improving TRADE in the South-West Part of AMERICA, and Increasing BULLION to About Three Millions per Annum, Both for the East India Trade and the Revenue of the Crown, Which by Consequence Will Be Produced if This Is Encouraged ）。这本小册子主张，美洲是“所有黄金与白银的唯一泉源”，任何占领了美洲的国家就能拥有“这个世界上的所有物质财富 “，并控制“全天下的贸易”，并坚持英格兰应该要比法国先一步统治西印度群岛。英格兰应该要帮助“计划者”──也就是冒险家暨企业家──占领美洲，在必要时使用强烈手段，以便英国能控制美洲的所有财富。如此一来，英国就能打造一支胜过所有国家的海军，建立起一个全球帝国。5
在这样的氛围中，英荷讽刺作家、医师暨经济哲学家伯纳德．曼德维尔写下了《蜜蜂的寓言：又名，个人恶行，公众利益》（The Fable of the Bees: or, Private Vices, Public Benefits ，一七一四年），这是早期利伯维尔场哲学中最清楚好懂、也是引起最多争议且最知名的著作之一。《蜜蜂的寓言》为英国的商业社会总结出一个同时充满批判与希望的愿景。曼德维尔遵循马基维利、霍布斯、拉侯谢傅科描述人类本质时采取的愤世嫉俗观点，描述了一种充斥着恶行的商业文化，在这个宛如蜂巢的国家中，律师、商人、神职人员和乡绅都无异于“骗子、寄生虫、皮条客、赌徒、扒手、伪币制造者、江湖医师〔和〕占卜师”，全都对于“诈骗、奢侈品和傲慢”轻微上瘾。事实上，他还以押韵的文体指出：“所有交易和每个角落都必定有欺骗存在／没有任何志愿能免于诈欺的残害。”他相信是“自私”在推动人类的行为。6
法国就和英国一样，想要为他们的债务与不断衰退的经济系统找到神奇解方。法国被饥荒压垮了，现在已濒临破产。一七一四年，柯尔贝的外甥，也就是财政总监督尼古拉斯．德马雷兹正绞尽脑汁，希望能解决法国实际上已经面临的破产问题。所有改革都停滞不前，他仍在努力试着从法国饱受摧残的人民手中榨取每一分税收。法国没有国家银行，税收基础薄弱，这是因为法国贵族不需要定期缴税。德马雷兹已经无路可退。他曾听闻著名的苏格兰经济理论学家暨赌博玩家约翰．劳（John Law，在法语中，他的姓氏〔l’as〕念起来像是“王牌”〔the ace〕）提出一个计划，要在苏格兰建立国家银行并印制纸钞。一七○五年，劳出版了一本非同寻常的小册子《货币与贸易的思考》（Money and Trade Considered ），指出一个国家拥有愈多货币，就能进行愈大量的贸易。他的点子就是印制货币，这并不是在制造财富，而是制造一种推动财富创造的催化剂。8
这位苏格兰人与法国摄政王在法国的上层阶级赌场碰面。劳是一名赌徒，既会研究赚钱的机率方法，同时也对风险上了瘾。这样的个性着实不像是成为未来法国财政大臣的最佳人选。一七一六年，奥尔良公爵批准劳建立私人资助的通用银行（Banque Générale），可以依据法国的黄金储备量发行纸钞。法国政府接受人民用这些纸钞来缴税。一七一八年，劳创办的通用银行变成了皇家银行（Royal Bank）。这间银行承办存款与借贷业务，也进行有利可图的国家垄断，营运殖民地的烟草贸易与销售。劳在同一年新成立了西部公司（Company of the West，为密西西比公司〔Mississippi Company〕的前身），接着和几间在塞内加尔与几内亚进行奴隶贸易的公司合并。一七一九年，劳的公司并购了法属东印度公司与中国公司，成为全球金融集团“永存印度公司”（Perpetual India Company），靠着包括奴隶买卖在内的殖民贸易获利。摄政王希望劳成立的垄断公司能为国家管理财政，并带来他们急需的资金。11
乍看之下，所谓的“劳氏体制”（Law’s System）似乎和利伯维尔场没有半点关系。然而，劳的货币理论和创新构想──也就是可以靠着一间公司来处理整个国家的债务──至少被视为与被宣传为一种以市场为基础的因应方式。身为赌徒的劳深知在推动信贷与驱动市场的过程中，想象力将扮演重要的角色，因此他发起了一场大规模的宣传活动，宣扬美国有多少潜在财富，希望能说服社会大众投资他的银行和公司股份。密西西比河谷（Mississippi Valley）就是劳的黄金国与法国版的美国梦。劳引用了拉萨勒男爵勒内．罗伯特．卡维利耶（René-Robert Cavelier, sieur de La Salle）对密西西比探险经历的描述，又出版了制图师纪尧姆．迪莱尔（Guillaume Delisle）为路易斯安那州的广阔未开垦领地绘制的杰出地图，并聘请皇家学院的成员撰写书籍，颂扬法国新世界的自然财富。12
劳所描绘的愿景为：路易斯安那州是财富的奇迹，而对此最关键的一篇宣传就是法国的尚．特拉松神父（Jean Terrasson）撰写的《无限创造论》（The Treatise on the Creation of Infinity ，约一六九五年至一七一五年）。这篇文章声称地球具有“无限可能”，对于那些前往美洲的人来说，美洲的丰富资源也充满“无限可能”，这本书在巴黎风行一时，广受欢迎。特拉松断定国家经济不需要专家、金融管理人员和会计师的指导。只要有信心的驱使，经济就会逐渐进入一个能够自我调节的系统。皇家银行将会提供贷款给所有想要投资劳的公司的人，进而把“整个国家转变成一个商人主体”。这项国家投资计划将会得到永存印度公司的担保和纸钞产生的经济燃料作为支持。如此一来，财富就会普遍化，社会中的所有成员将公平地共享财富。这样的财富没有任何风险，“开明”且拥有无上权力的君主，也就是摄政王本人，将会克服所有困难。13
1. Guy Rowlands, The Financial Decline of a Great Power: War, Influence, and Money in Louis XIV’s France (Oxford: Oxford University Press, 2012), 2; Richard Dale, The First Crash: Lessons from the South Sea Bubble (Princeton, NJ: Princeton University Press, 2004), 77.
2. Carl Wennerlind, Casualties of Credit: The English Financial Revolution, 1620–1720 (Cambridge, MA: Harvard University Press, 2011), 68, 89; Stephen Quinn, “The Glorious Revolution’s Effect on English Private Finance: A Microhistory, 1680–1705,” Journal of Economic History 61, no. 3 (2001): 593–615, at 593; Julian Hoppit, Britain’s Political Economies: Parliament and Economic Life, 1660–1800 (Cambridge: Cambridge University Press, 2017), 149; P. G. M. Dickson, The Financial Revolution in England: A Study in the Development of Public Credit, 1688–1756 (New York: Macmillan, 1967), 80.
3. John Brewer, The Sinews of Power: War, Money and the English State, 1688–1783 (New York: Alfred A. Knopf, 1989), 116–117.
4. Wennerlind, Casualties of Credit , 10; Ian Hacking, The Emergence of Probability: A Philosophical Study of Early Ideas About Probability, Induction and Statistical Inference (Cambridge: Cambridge University Press, 1975); Lorrain Daston, Classical Probability in the Enlightenment (Princeton, NJ: Princeton University Press, 1988), 164.
5. An Account of What Will DO; or, an Equivalent for Thoulon: In a Proposal for an Amicable Subscription for Improving TRADE in the South-West Part of AMERICA, and Increasing BULLION to About Three Millions per Annum, Both for the East India Trade and the Revenue of the Crown, Which by Consequence Will Be Produced if This Is Encouraged (London: Mary Edwards, 1707), 3.
6. Bernard Mandeville, The Fable of the Bees , ed. Philip Harth (London: Penguin, 1970), 64.
7. Mandeville, Fable of the Bees , 67–68.
8. Antoin E. Murphy, John Law: Economic Theorist and Policy-Maker (Oxford: Oxford University Press, 1997), 94–95.
9. John Law, Money and Trade Considered (Glasgow: A. Foulis, 1750), 167.
10. Arnaud Orain, La politique du merveilleux: Une autre histoire du Système de Law (1695–1795) (Paris: Fayard, 2018), 10; Charly Coleman, The Spirit of French Capitalism: Economic Theology in the Age of Enlightenment (Stanford, CA: Stanford University Press, 2021), 119.
11. Coleman, Spirit of French Capitalism , 119.
12. Coleman, Spirit of French Capitalism , 20, 81.
13. Jean Terrasson, Lettres sur le nouveau Système des Finances , 1720, 2–5, 29, 32, 33; Jean Terrasson, Traité de l’infini créé , ed. Antonella Del Prete (Paris: Honoré Champion, 2007), 225–227.
14. Orain, La politique du merveilleux , 13.
15. Claude Pâris La Montagne, “Traité des Administrations des Recettes et des Dépenses du Royaume,” 1733, Archives Nationales, 1005, II: 3–8, 48–49, 55.
16. Norris Arthur Brisco, The Economic Policy of Robert Walpole (NewYork: Columbia University Press, 1907), 43–45; Richard Dale, The First Crash: Lessons from the South Sea Bubble (Princeton, NJ: Princeton University Press, 2004), 74.
17. Cited by Dickson, Financial Revolution in England , 83.
18. Jacob Soll, The Reckoning: Financial Accountability and the Rise and Fall of Nations (New York: Basic Books, 2014), 101–116.
第十一章 法国的自然崇拜与启蒙经济学的发明
所有能够制造出财富的泉源与物质，都来自土地。 ──理查德．卡丁伦（Richard Cantillon），《贸易本质概论》（Essay on the Nature of Trade in General ），约一七三○年
支持西塞罗与牛顿的自然崇拜学说的人们在法国组成了一个势力庞大的利伯维尔场游说团体。一七三○年代早期，爱尔兰裔的法国利伯维尔场经济学家理查德．卡丁伦写下了奠基性的农业经济著作《贸易本质概论》，该著作以手稿的形式流通，在一七五五年于作者逝世后正式出版。卡丁伦的著作拥护的是一个过度简化又机械式的观点：不受税制与法规约束的农业将会产生资本，并转化成经济成长。十九及二十世纪的两位经济学家威廉．史坦利．杰文斯（William Stanley Jevons）和约瑟夫．熊彼得（Joseph Schumpeter）一致将卡丁伦誉为比亚当斯密更早出现的第一位“系统性的”经济思想家。对他们来说，所谓系统性经济学意思就是所有听起来像是经济均衡理论的事物。事实上，许多思想家都对创新与工业蕴含的财富创造潜力有所误解，卡丁伦只是其中之一，他们都认为解放农业是创造富裕社会的唯一途径。3
其他思想家寻求的则是更通用的经济计划，能像万有引力定律和行星运动定律一样适用于所有时空。法国哲学家孟德斯鸠在影响力深远的著作《法的精神》（On the Spirit of Laws ，一七四八年）中指出，繁荣来自和平，社会与国家必须用和谐的方式自我管理。他进一步断言，“和平是商业自然而然带来的结果”。各国可以透过贸易合作分享共同的利益，使他们“温和”地对待彼此。11
一七五二年，在启蒙哲学和经济思想大量萌发的期间，法国商业总督雅克─克劳德─马里．文森．古尔奈（Jacques-Claude-Marie Vincent de Gournay）决定他要建立一个经济思想家的“圈子”，藉此处理法国面对的商业挑战，并发展出不同的方法来打造市场机制。古尔奈出生于法国圣马洛（Saint-Malo），曾在家族位于西班牙的公司中从事国际贸易产业工作。除了商业方面的实务经验外，他也因为柯尔贝的国家总督传统而接受过商业法规管理训练。他同样认为若想管理法国商业，就应该采用具有连贯性的国家经济政策。古尔奈很清楚法国需要改革，包括在政治与经济方面都需要更高的自由，他为此邀请了许多年轻的经济思想家加入他的团队。12
虽然古尔奈不支持某些政府干预，但他的格言是“放任作为，放任通行”（Laissez-faire, laissez-passer），也就是让商业随心所欲地自行发展。赫赫有名的哲学家暨经济思想家，也是利摩日（Limoges）总督与未来的财政大臣奥尼男爵安．罗伯特．雅克．杜尔哥（Anne-Robert-Jacques Turgot, baron de l’Aulne）写道，古尔奈的观点可以用两个词来表达：“自由与保护，但自由才是最重要的。”古尔奈也打造了官僚主义（bureaucratie）一词作为一个讽刺笑话，这意思是用办公桌来管理政府。虽然他大加批判法国的严格法规和保密机制，并希望公众的意见与喜好能协助推动市场，但他仍然在柯尔贝式发展和自由放任主义之间选边站。13
古尔奈的圈子是一群致力于研究经济思想的哲学家。法朗索瓦．维隆．福尔博纳（François Véron de Forbonnais）是来自布商家族的金融家，而后攀升至铸币监察长的高位，在古尔奈的团体中是主要成员，他不同意农业致富理论。福尔博纳是柯尔贝的崇拜者，支持自由开放版本的国内经济监督。他相信商业自由，认为国家不应该在没有具体目标的情况下帮助工业发展并干预经济。他的著作《商业要素》（Elements of Commerce ，一七五四年）是针对卡丁伦提出的谨慎批判。福尔博纳指出，虽然财富同时来自农业与制造业，但他不偏不倚地坚持，制造业和商业才是能创造财富的真正泉源。他和柯尔贝一样，认为一旦达到了特定的贸易平等水平，市场就可以自由化。14
魁奈在凡尔赛宫居住与工作，他撰写了卷帙浩繁的著作来描述放血这种致命的医疗技术在治疗病人上具有何种医学优势。他的医学背景让他相信，经济的运作原理就像血液循环一样。他是路易十五才华洋溢的情妇暨哲学家赞助者──庞巴杜夫人（Madame de Pompadour）─的医师，随后因此被封为贵族，这令他欣喜万分。他们两人都是新晋贵族，且都在路易十四的旧权力殿堂中爬升至具有重要影响力的职位。事实上，庞巴杜夫人后来还资助魁奈推广他的经济哲学。她与生俱来的聪慧、财富与远近驰名的谈吐技巧，使她成为巴黎文学沙龙中光彩夺目的人物。她主动去吸引路易十五的目光，在一七四五年成为正式情妇，为这位国王带来严重丑闻。路易十五为表达他对这位平民的爱，赐予了贵族头衔和土地，又替她买下巴黎最好的城市宫殿艾佛宅邸（Hôtel d’Évreux），这栋建筑如今被称作艾丽榭宫（Elysée Palace），是法国总统的居所。 在庞巴杜夫人权力窜起的一年之前，魁奈搬进了凡尔赛宫地下室的住所。这位即将领导早期最强大的利伯维尔场思想家运动的人，就在国王的宫殿中开始构思他的哲学观。利伯维尔场思想就这样在非常专制、非常亲工业的国家内部逐渐发展起来，许多利伯维尔场主义者都想用他们的哲学来抗衡这样的国家。但魁奈并没有因这种矛盾而感到困扰。他是“法治专制主义”这个巨大矛盾修辞的信奉者。他受到哲学家皮耶─保罗．卢梅希．利瓦伊耶赫（Pierre-Paul Lemercier de la Rivière）的启发，相信自然系统会透过君主的意志进行自我表达。魁奈说，只有国王才有能力解放谷物市场，为地主创造更多财富。18 魁奈时而前往庞巴杜夫人位于巴黎的宫殿，在那里举办晚宴招待当时的重要哲学家们。他邀请的客人包括畅销著作《百科全书》（Encyclopédie ，一七五一年至一七七二年）的主要作者丹尼斯·狄德罗（Denis Diderot）与尚·瑞恩·达朗贝尔（Jean le Rond d’Alembert）；无神论者、平等主义哲学家暨路易十五的虔诚波兰皇后玛丽．莱什琴斯卡（Marie Leszczyńska）的医师克劳德─安德林·艾尔维修（Claude-Adrien Hélvetius）；著名的自然学家与皇家植物园（Jardin des Plantes）管理者布丰伯爵乔治─路易．勒克莱尔（Georges-Louis Leclerc, comte de Buffon）；以及杰出的放任主义经济学家杜尔哥。庞巴杜夫人身为皇室的情妇，既不能正式邀请这些人参加餐宴，也不能自行举办沙龙，所以她会不时参加魁奈的聚会，这些宾客在优雅的环境中讨论有关形上学与经济学的新哲学。除了在关于农业放任主义的哲学对话中尽情畅谈，魁奈的高贵客人也能享受惊人的奢侈品、王室厨房提供的精致美食，此外还能透过庞巴杜夫人把话直接传进国王的耳中。19
重农主义者在巴黎沙龙滔滔不绝地主张人们应该重视农业财富胜过工业时，海峡的另一边出现了截然不同的景象。英国的第一次工业革命已然展开，大力驱动着英国经济。蒸气引擎登场了。英国人托马斯．萨维里（Thomas Savery）在一六九八年打造了无活塞引擎，托马斯．纽科门（Thomas Newcomen）在一七一二年制造了一种可以产生连续能量与运动的蒸气泵引擎。除了蒸气动力，到了一七○○年代，机械纺纱也出现了。一七三三年，约翰．凯（John Kay）发明了一种可以自动配线给线轴的飞梭，加快了手工编织的速度。一七三八年，刘易斯．保罗（Lewis Paul）和约翰．怀亚特（John Wyatt）则打造了能生产羊毛布和棉布的纺纱架。到了一七五○年代与六○年代，魁奈和他的重农学派追随者开始写作的当下，英国制造业已经开始在大规模工厂中广泛使用水力磨坊了。整个一七五○年，英国的手工纺织业共制造了两百五十万磅的原棉。到了一七八○年代末，英国织布机曾加工过的棉花总计已经有两千两百万磅。这对于欧洲和贵族地主的农业社会秩序造成了威胁。随着工业蒸蒸日上，法国这个仍然实施封建制度、农业挂帅的社会中展开了一场商业地位争夺战。利伯维尔场思想家努力想找回农业的优势。他们认为针对谷物的自由放任改革将能彻底激发大自然的潜能，届时农业将会气势如虹地返回经济主导地位。20 一七五六年，北美爆发了七年战争。战事从欧洲席卷至北美与南美，再蔓延到印度与非洲，这是史上第一场全球冲突，法国与英国陷入国际贸易控制权的争夺战，同时也把其他欧洲强权给牵扯了进来。这场战争像是法国利伯维尔场思想的催化剂，因其清楚显示出农业社会正在让位给一套新的商业秩序。出于显而易见的原因，保守派的法国贵族统治阶级不愿意顺从地坐视商人接手他们的位置；有些人甚至建议，贵族应该要掌控制造业的生产方法，把这些方法从工业阶级手中夺走。一七五六年，法国神职人员暨亲工业经济思想家盖比尔．法朗索瓦．科耶（Gabriel François Coyer）写下了一部颠覆性作品《商业贵族阶级》（The Commercial Nobility ），在其中大力抨击贵族农业社会秩序。科耶是古尔奈的圈子里的一员，他呼吁贵族对担任士兵与牧师的天职放手，别再被动地生活在他们的土地上，只想靠着农业榨取财富。他警告说，法国正承受着经济竞争和战争的压力，需要利用贸易与工业制造财富。科耶不认为坐拥土地的贵族是经济的驱动力，反而将他们视为寄生虫。科耶指控道，由于法国的封建法禁止这些贵族参与贸易，所以这些贵族在经济方面“一无是处”。21 科耶认为，相较于商业和制造业，农业和相关封建体系的生产力极为低落。科耶要求法国改变贵族的地位。根据他的计算，如果法国贵族能成为商人并去工作的话，法国会变得富有得多，像英格兰就让贵族的第二个儿子从事贸易。他这是在实质上呼吁要推翻法国的封建宪法。科耶的作品大受欢迎，被收录在广泛流通的期刊《法国信使》（Mercure de France ）中，而他的书也获得了无数次的再版与翻译。22
这部作品的回响来得很快。身为贵族的亚克骑士（chevalier d’Arcq）菲利普─奥古斯特．圣富瓦（Philippe-Auguste de Sainte-Foix）发表了《反对商业贵族的军事贵族，又名，法国爱国者》（The Military Nobility Opposed to the Commercial Nobility, or The French Patriot ，一七五六年）作为响应，捍卫传统秩序。一场文字论战随之而来，接着政府禁止了所有追随科耶并呼吁修法改变贵族地位的著作。不过作为商业与工业的信徒，古尔奈和福尔博纳继续公开支持科耶。23 科耶和他的追随者想要实现经济自由，但他们也希望透过工业化和商业来实现广泛的社会改革。地主必须对这种日益增长的威胁做出回应，而他们的响应则是更彻底的利伯维尔场农业主义。
魁奈开始寻求追随者，来将重农主义转变成一场日益壮大的意识形态运动。一七五七年，他邀请年轻的米拉波侯爵维克多．里克提（Victor de Riqueti, marquis de Mirabeau）到他位于凡尔赛宫地下室的住所，和他讨论农业经济学奠基者理查德．卡丁伦的著作。小米拉波（Mirabeau the Younger）出身贵族家庭（他的父亲是恶名昭彰的米拉波伯爵，将会成为法国大革命的领导人之一），是孟德斯鸠的朋友。他在《人类之友，又名，族群论》（The Friend of Mankind, or Treatise on Population ，一七五六年）中为贵族的财产权与免税权辩护，反对政府侵犯这些权利。魁奈请年轻的米拉波帮助他完成他的新计划《经济表》（Tableau économique ），这本书试图证明卡丁伦的理论，而他的理论是用伪科学方式主张财富来自土地。这本书后来成为重农主义与十八世纪利伯维尔场思想的《圣经》。26
魁奈大肆宣扬地主应该拥有市场自由的同时，他也相信只有强而有力的国家才能创造并维持这些市场自由。重农主义者希望国王能成为完整掌权的专制统治者，可以独断独行，并保证地主阶级获得经济自由。魁奈的典范就是中国。在他的著作《中国专制主义》（Despotism in China ，一七六七年）中，他指出皇帝能维护自然的父权制与农业秩序，经由训练他的子民聚焦在“种养”技能，让社会集中关注纪律严明的农业活动。魁奈认为，中国皇帝的绝对权力，代表他永远都不会违法，也不会做出任何违背普遍利益的事，因为他就代表了普遍利益。所以，魁奈相信中国皇帝的子民享有纯粹的自由，可以无拘无束地耕作养畜。30
对于重农主义者来说，所有批评都无关紧要，即使这些批评来自古尔奈的圈子里备受尊敬的成员、即使人们对魁奈的统计数据提出了具体质疑，都没有差别。福尔博纳直言不讳地批评了魁奈在数字方面的错误。他提出数据，指出法国的农业产量比魁奈声称的更高，且许多《经济表》中的数字都不准确。他无法理解为什么魁奈会认为农民有生产力，而商人却没有，他在魁奈对国家生产净值的计算中找到严重错误，货品与货币流通的部分也谬误百出。对福尔博纳而言，最后一个重大分歧点是魁奈认为经济可以一种用他在《经济表》中提出的“超然经济真理”来理解。福尔博纳不认同有一种普遍的经济模型能适用于任何时空，并断定魁奈的虚假统计数据不能证明经济能透过自由放任主义自动运作的理论。32 尽管面对种种批评，魁奈和他的信徒仍不知疲倦地捍卫与宣扬他们对农业与王室专制的愿景。在魁奈的追随者中，最成功的其中一位是皮耶─山缪．杜邦．内穆赫（Pierre-Samuel du Pont de Nemours），他是一名充满热忱的重农主义者、法国革命支持者，也是奴隶制度的批评者。杜邦．内穆赫是一个新教徒钟表匠的儿子，但他为了追求抱负而离家前往巴黎，加入米拉波成为重农主义教的信徒。一七六五年，杜邦．内穆赫针对“自然权利”撰写了一系列文章，这些文章奠定了他后来最著名的著作《重农主义》（Physiocracy ，一七六八年）。他透过这些文章为劳工与财产的积极自然权利辩护，自然权利代表人类有权拥有土地，也有权靠着在土地上的劳动赚进财富。杜邦重申了洛克的观点，认为个人享有自我保护的自由，且只要不去侵犯他人的财产或“所有权”，他们就应该有致富的自由。政府的作用是为民众确保个人自由与私有财产权。这种个人权利的观点使杜邦反对奴隶制，他认为此制度违反了全人类与生俱来的自由。在此要留意的是，杜邦和魁奈一样，都支持贵族封建主义原则。事实上，他热切地接受了路易十五赐予的贵族头衔。33 魁奈和杜邦联手合作，坚称自由的国际谷物贸易对农业有利，并能够建立起一套系统：各国透过天然的相对优势，和谐地只进口自己所需的农产品。对魁奈来说，自由贸易的重点不是竞争，而是和谐。大自然给予每个国家不同的在地农业资源。因此，他们不需要任何规则：国家只会进出口他们需要的货品，从而避免了直接竞争。当时英国在工业发展方面突飞猛进，而七年战争却已经使法国陷入更严重的贫困、债务与破产之中，这使得魁奈的讯息显得充满希望又容易理解。34
1. Charles M. Andrews, “Anglo-French Commercial Rivalry, 1700–1750: The Western Phase, I,” American Historical Review 20, no. 3 (1915): 539–556, at 547; David Hume, Selected Essays , ed. Stephen Copley and Andrew Edgar (Oxford: Oxford University Press, 1996), 189, 214.
2. Georges Weulersse, Le mouvement physiocratique en France (de 1756 à 1770) , 2 vols. (Paris: Félix Alcan, 1910), 1:23; Montesquieu, De l’Esprit des lois , ed. Victor Goldschmidt, 2 vols. (Paris: Garnier-Flammarion, 1979), vol. 2, bk. 20, chap. 2; David Hume, An Inquiry Concerning Human Understanding, with a Supplement: An Abstract of a Treatise on Human Nature , ed. Charles W. Hendel (Indianapolis: Liberal Arts Press, 1955), 173.
3. Robert B. Ekelund Jr. and Robert F. Hébert, A History of Economic Theory and Method , 6th ed. (Longrove, IL: Waveland Press, 2014), 70.
4. Tony Brewer, Richard Cantillon: Pioneer of Economic Theory (London: Routledge, 1992), 8.
5. Richard Cantillon, Essai sur la nature du commerce en général , ed. and trans. Henry Higgs (London: Macmillan, 1931), 58.
6. Cantillon, Essai sur la nature du commerce , 97, 123; Marian Bowley, Studies in the History of Economic Theory Before 1870 (London: Macmillan, 1973), 95.
7. Cantillon, Essai sur la nature du commerce , 51–55, 85; Bowley, Studies in the History of Economic Theory , 96.
8. Jean-François Melon, Essaie politique sur le commerce , in Eugène Daire, Économistes financiers du XVIIIe siècle (Paris: Guillaumin, 1851), 659–777, at 671, 666.
9. Melon, Essaie politique sur le commerce , 673, 708.
10. Melon, Essaie politique sur le commerce , 683, 746, 765.
11. Paul Cheney, Revolutionary Commerce: Globalization and the French Monarchy (Cambridge, MA: Harvard University Press, 2010), 22; Montesquieu, De l’esprit des lois , bk. 20, chaps. 1–2.
12. David Kammerling-Smith, “Le discours économique du Bureau du commerce, 1700–1750,” in Le Cercle de Vincent de Gournay: Savoirs économiques et pratiques administratives en France au milieu du XVIIIe siècle , ed. Loïc Charles, Frédéric Lefebvre, and Christine Théré (Paris: INED, 2011), 31–62, at 34.
13. R. L. Meek, The Economics of Physiocracy (London: Allen and Unwin, 1963), xiii.
14. François Véron de Forbonnais, Éléments du commerce , 3 vols. (Paris: Chaignieau, 1793–1794), 1:62.
15. Forbonnais, Éléments du commerce , 1:67–68, 75–76.
16. Forbonnais, Éléments du commerce , 1:3, 38, 45.
17. Steven L. Kaplan, Bread, Politics, and Political Economy in the Reign of Louis XV , 2nd ed. (New York: Anthem Press, 2012), 108; Gérard Klotz, Philippe Minard, and Arnaud Orain, eds. , Les voies de la richesse? La physiocratie en question (1760–1850) (Rennes, France: Presses Universitaires de Rennes, 2017), 11; Gustav Schachter, “François Quesnay: Interpreters and Critics Revisited,” American Journal of Economics and Sociology 50, no. 3 (1991): 313–322; Paul Samuelson, “Quesnay’s ‘Tableau Économique’ as a Theorist Would Formulate It Today,” in Paul Samuelson on the History of Economic Analysis: Selected Essays , ed. Steven J. Medema and Anthony M. C. Waterman (Cambridge: Cambridge University Press, 2015), 59–86, at 60.
18. Pierre-Paul Mercier de la Rivière, L’ordre naturel et essentiel des sociétés politiques , 2 vols. (London: Jean Nourse, 1767).
19. Liana Vardi, The Physiocrats and the World of the Enlightenment (Cambridge: Cambridge University Press, 2012), 42.
20. Vardi, Physiocrats , 84; David S. Landes, Unbound Prometheus: Technological Change and Industrial Development in Western Europe from 1750 to the Present (Cambridge: Cambridge University Press, 1969), 82.
21. Steven Pincus, The Global British Empire to 1784 , unpublished manuscript; Gabriel François Coyer, La noblesse commerçante (London: Fletcher Gyles, 1756), 33–34, 45, 72.
22. Simone Meyssonnier, La balance et l’horloge: La genèse de la pensée libérale en France au XVIIIe siècle (Paris: Les Éditions de la Passion, 1989), 264.
23. Meyssonnier, La balance et l’horloge , 265.
24. Meyssonnier, La balance et l’horloge , 249.
25. Meyssonnier, La balance et l’horloge , 80–81; Coyer, La noblesse commerçante , 33–34, 279.
26. Le marquis de Mirabeau, L’ami des hommes, ou traité de la population , 2 vols. (Avignon: 1756); Meek, Economics of Physiocracy , 15.
27. Meek, Economics of Physiocracy , 18.
28. Meek, Economics of Physiocracy , 23; E. P. Thompson, The Making of the English Working Class (New York: Vintage, 1966), 218; Boaz Moselle, “Allotments, Enclosure, and Proletarianization in Early Nineteenth-Century Southern England,” English Economic History Review 48, no. 3 (1995): 482–500.
29. Meek, Economics of Physiocracy , 109–114, 136.
30. François Quesnay, Despotism in China , trans. Lewis A. Maverick, in Lewis A. Maverick, China: A Model for Europe , 2 vols. (San Antonio: Paul Anderson and Company, 1946), 1:216; W. W. Davis, “China, the Confucian Ideal, and the European Age of Enlightenment,” Journal of the History of Ideas 44, no. 4 (1983): 523–548; Stefan Gaarsmand Jacobsen, “Against the Chinese Model: The Debate on Cultural Facts and Physiocratic Epistemology,” in The Economic Turn: Recasting Political Economy in Enlightenment Europe , ed. Steven L. Kaplan and Sophus A. Reinert (London: Anthem Press, 2019), 89–115; Cheney, Revolutionary Commerce , 203; Pernille Røge, Economists and the Reinvention of Empire: France in the Americas and Africa, c. 1750–1802 (Cambridge: Cambridge University Press, 2019), 10.
31. Quesnay, Despotism in China , 11; Røge, Economists and the Reinvention of Empire , 88.
32. Loïc Charles and Arnaud Orain, “François Véron de Forbonnais and the Invention of Antiphysiocracy,” in Kaplan and Reinert, Economic Turn , 139–168.
33. Meek, Economics of Physiocracy , 46–50.
34. Meek, Economics of Physiocracy , 70.
35. Jean Ehrard, Lumières et esclavage: L’esclavage colonial et l’opinion publique en France au XVIIIe siècle (Brussels: André Versaille, 2008); Røge, Economists and the Reinvention of Empire , 176; David Allen Harvey, “Slavery on the Balance Sheet: Pierre-Samuel Dupont de Nemours and the Physiocratic Case for Free Labor,” Journal of the Western Society for French History 42 (2014): 75–87, at 76.
第十二章 利伯维尔场与自然
人虽生而自由，却无处不在枷锁之中。 ──鲁索（Rousseau），《社会契约论》（The Social Contract ），一七六二年
在制造业蒸蒸日上、海外帝国扩张且国际贸易蓬勃发展的年代，重农主义可算不上受欢迎的经济理论。尽管重农主义哲学家的著作受到现代利伯维尔场思想家的热烈赞赏，但这些作品在他们那个年代并不畅销。事实上，十八世纪最畅销的那些经济学书籍都在批评“经济完全可以自我调节”的观点。处于经济成长前线的人都在寻找方法推动工业与利伯维尔场的发展。这意谓着除了自由放任的要素外，还必须让国家扮演具有建设性的经济角色。 于是无须讶异，接下来亲工业改革运动出现在意大利这个欧洲资本主义与贸易的起源地。意大利哲学家寻求的是更加贴近柯尔贝主义的道路，透过新的法律体系与开明的政府机构来建立市场。博学多闻的卢多维科．安东尼奥．穆拉多利（Ludovico Antonio Muratori）是神职人员、历史学家，也是米兰宏伟的安布罗西亚那图书馆（Ambrosiana Library）的图书馆员，他的著作《论公共幸福》（On Public Happiness ，一七四九年）受到柯尔贝和孟德斯鸠的启发。穆拉多利的文章解释了人类要如何透过政府改革与立法来改善安全、教育、健康与宗教生活，使这个世界变成一个“更幸福”的所在。包括奥地利女皇玛丽亚．特蕾莎（Maria Theresa）在内的几位专制君主都遵循他的建议，支持自然科学与宗教宽容，并透过宪政主义扩张个人与市场的自由──尽管是有限的自由。意大利和奥地利的启蒙运动思想家与巴黎、伦敦和苏格兰的思想家密切合作，致力于打造出更公正的社会，一些意大利人把这种概念称作“社会主义”，也就是透过现代化的法院与法典、学校和基础设施等国家机构来打造社会与市场的一套计划。（历史学家伊斯凡．洪特〔István Hont〕将此时社会主义“socialism”的追随者称作“society-ists”。）此一社会运动后来也影响了斯密。1
在意大利的国家市场建造者中，最重要的一位就是拿坡里的政治经济学家安东尼奥．杰诺维齐（Antonio Genovesi），他可以说是亚当斯密的前辈，认为经济是一系列能够自我延续的市场机制。身为一名有远见的市场思想家，他认为政府必须打造适合市场的条件。他不赞成劳动力本身就能创建价格的观点，而认为驱动价格的是无形的社会条件与劳动条件。在他广受赞誉的《商业课，又名，论公民经济》（Lessons on Commerce, or On Civil Economics ，一七六五年）中，他指出效用性、个人关系与公共信任决定了劳动与货品的价值。虽然国家必须给予市场自由，但同时也要小心翼翼地扶植市场。举例来说，政府必须修建道路，并保护道路不受盗匪侵扰。杰诺维齐引述了梅隆、休谟和孟德斯鸠，认为财富是有效率的农业与工业之间的互相作用。他和福尔博纳一样，认为消除商业上的障碍通常是好事，但商人仍然必须遵守法规与支付一定的关税。因此，利伯维尔场是国家与商人之间持续且小心地互相退让的成果。并不存在一种通用法则，反之，需要具备的是一种务实的意识：信任与商业自由必须根据当地环境去协商、建造与维持。2
在众多意大利经济思想家中，重农主义的头号敌人是一名翻译了洛克著作的拿坡里人，修道院长费迪南多．加利亚尼（Ferdinando Galiani）。一七五九年，拿坡里国王查理四世派遣这位杰出的经济学家到巴黎的拿坡里大使馆担任秘书。他成为巴黎社交场合与时尚沙龙的常客，和狄德罗交上朋友，并向狄德罗介绍了经济学研究。加利亚尼曾在拿坡里执行过货币改革，并因此和重农主义者有过密切往来，他向来没有耐心应对那些魁奈信徒无知的农业乐观主义。他相信社会必须和大自然彼此合作，而非只是追随自然。加利亚尼在《谷物商业对话》（Dialogues on the Commerce of Grains ，一七七○年）中坚称，只有国家才有足够的外界信用，能够在歉收、饥荒与战争的处境下处理食物短缺的问题。4 他同意自然与社会都是以系统的形式在运作的。他也认为制造业需仰赖农业。然而，他同时坚持农业仍然太不可靠，不能让农业完全控制市场体系。在歉收的时期，不只有农业，相关产业也会跟着停滞不前，接着社会就会陷入经济与财政灾难之中。若国家没有储备与管理粮食供应，农民很容易会“失去所有资金”而无法重新开始种植。换句话说，加利亚尼认为成功的农业系统既不能完全依赖自然，也不能完全依赖市场。他坚称大自然带来的灾难规模只有国家才能应对。5
虽然杜尔哥是利伯维尔场的支持者，但他在一七五七年出版的《百科全书》中的〈市集与市场〉（Fairs and Markets）一文中，表达得比魁奈反复强调重农主义观点的文章还要更加隐晦。杜尔哥主张，大型的中世纪市集──著名的现代法国历史学家费尔南．布劳岱尔（Fernand Braudel）后来把这些市集连结到资本主义的崛起──是一种压迫性垄断。中世纪的博览会往往坐落在各个国家或各个地区之间的主要贸易路线交会点，例如法国香槟区。每年都有数周的时间，农民、工匠、商人和银行家会带着他们的商品和技能来到这里，创建一个推动中世纪经济的巨大商业区。杜尔哥说，“方便性”使博览会地点不会变动；这也使得博览会成为控制价格的垄断场所。博览会有一群固定的参加者，因此限制了竞争与交易总量。固定地点的博览会也使国家得以简化和控制货品税收。他说这种做法“不理性”，让博览会只有利于税收，而不利于财富创造。7
在杜尔哥眼中，市场不是由拥有财产的个体驱动的，而是由农村的劳动者驱动的。杜尔哥和杜邦．内穆赫合作撰写了《对财富的形成与分配之反思》（Reflections on the Formation and Distribution of Wealth ，一七六六年），杜尔哥在书中透过效益主义劳动的概念，为封建贵族进行了革命性的现代辩护，即地主没有生产力，但地主是合乎情理的闲置者。他在他对贵族财产的辩护中，主张物业拥有者对经济制度来说具有社会必要性，他写道：“仅仅是因为人类习俗以及公民法律，耕种者需要物业拥有者。”杜尔哥的看法呼应了西塞罗、洛克和孟德斯鸠的论点，他认为虽然地主本身是闲置的，但对整个制度的平衡来说至关重要，这些地主产生了一个菁英阶层，他们具备道德能力，因此得以精通法律、博雅教育和科学，也能领导社会与农业耕种。9
一七七四年，杜尔哥有了机会可以更大范围地尝试他的政策，他接掌了曾经属于柯尔贝的、手握大权的财政总监督一职。杜尔哥上任后采取的第一步非常成功。他坚持中止国家借款，并设法降低了利率。然而，杜尔哥想要使谷物贸易自由化的尝试却一败涂地。他取消了价格控制与政府补贴，废除了法国境内复杂而古老的面粉与面包分配系统，接着他们马上遇到了歉收。食物短缺、混乱、投机买卖、价格上涨和饥荒酿成了一七七五年四月与五月的一系列抗议行动，史称面粉战争（Flour Wars）。加利亚尼利用这个机会重申了他的观点，也就是在自然灾害发生时，政府必须介入提供帮助。在法规松绑的同时若没有对穷人提供援助，将会导致一场大灾难。杜尔哥已经忘却他当初的市场发展原则了。13 在面粉战争的高峰期，贾克．内克（Jacques Necker）出版了《论立法与谷物商业》（On the Legislation and the Commerce of Grain ，一七七五年），抨击杜尔哥和重农主义。内克是一位非常成功的瑞士新教银行家、金融家暨哲学家，他住在巴黎，而且借了一大笔钱给法国。身为一名经济思想家，他同意自由比监管更好，而且一般来说，贸易自由都是好的。他主张人们应该有权利能依照自己想要的方式，来运用自己的金钱、劳力与产业。内克追随柯尔贝的观点，坚持认为国家立法者必须制定“禁制性法律”，如此一来，谷物贸易中才不会出现“对自由的滥用”而导致饥荒。他同意加利亚尼的想法，认为人们不能只是把谷物留给市场力量操作──自然太过反复无常，社会又太过脆弱。他就像加利亚尼一样，认为易受影响的食物供应需要政府提供护栏。因此，内克提出了古老的论点：虽然市场自由很重要，但这种自由比较适合非必需品。14 尽管受到了这样的批评，杜尔哥仍铁了心要进行他的自由化改革。他希望能打破封建制度中的强制性农民劳动与行会特权。他在这过程中成功与所有人为敌──从农民、商人到贵族。杜尔哥的改革和宫廷中的角力斗争导致所有政府派系都和他作对。一七七六年五月，国王路易十六令他辞职。他在农业自由放任方面进行的大型自由主义实验，被人们视为一次无比壮观的失败。在这场颜面尽失的惨败所带来的混乱中，他的许多其他现代化改革也化为泡影了。15
对于“利伯维尔场无需政府干预就能自动运作”这一观点的反对，因为杜尔哥的失败而更加牢不可破。有些基进派的哲学家认为封建社会与文化需要的不是改善，而是革命性的转变。政府首长在君主制度下未能取得成果，哲学家们于是又重新回到拉侯谢傅科公爵与曼德维尔的观点，也就是情绪感受是市场的主要驱动力。他们试着去理解这些人类情感能如何创造出更加公正的市场社会。 关于人类情感与经济之间的关系，出生于瑞士的哲学家尚─贾克．鲁索（Jean-Jacques Rousseau）提出了其中一些最有力的观点。尽管他也相信农业在经济上占首要地位，和杜尔哥不同的是，鲁索反对由贵族地主支配的社会制度。他设想的是一个民主而平等的农村社会，此社会以原始状态的自然为基础，人们共同管理财产，也共享地球上的果实。鲁索回过头去研究拉侯谢傅科公爵对市场运作方式的看法。他不相信大自然会自发性地打造出健康或和谐的社会与经济秩序。相反地，“自然”和农业创造出了社会阶级，导致贫困、不公正与不平等。他认为贵族拒绝纳税是法国经济问题的根源。鲁索对于法国社会的严重不平等感到怒火中烧，这启发他写下了基进立场的《论人类不平等的起源与基础》（Discourse on Inequality ，一七五五年）。这本书划下了一条清楚的战线，区分了菁英式的自由放任主义哲学，以及基进的共和式民主的呼吁，这种民主以马基维利和霍布斯的政治思想为基础，要求制衡市场与向富人征税。鲁索指出，很显然地多数派政府必须要严格监管财富、商业和地主掌握的权力。在他看来，西塞罗一派对自然状态的尊崇，以及效法大自然永恒法则的社会，都导致了不公正。民主政治必须介入并打破这种“自然”阶级制度，打造更加公正的世界。16 鲁索将会成为那个年代最负盛名的作家以及伟大的基进派领袖，他的思想将会启发托马斯．潘恩（Thomas Paine）和其他大西洋两岸的革命者。他的政治手册《社会契约论》（一七六二年）将会动摇欧洲体制的根基，为国家地位和民主奠定了框架。正是在这本着作中，鲁索写下了这句名言：“人虽生而自由，却无处不在枷锁之中。”与霍布斯以及洛克相反，鲁索并不认为社会能使人类变善良；相反地，他认为社会破坏了人类最原初的善良状态，从而堕落。真正的原罪就是社会与财产本身。对鲁索来说，不平等是自爱（self-love）与骄傲的产物，透过自爱与骄傲，个人只藉由与他人比较来定义自己。人会为了满足自己的骄傲，而创造出不自然的“常规”与“特权”，藉此在阶级制度中区分自己和歌颂自己。反洛克和反重农主义的思想在此昭然若揭。人类的枷锁就是私有财产和菁英阶级，是少数决的政治和经济规则。17
1. Erik S. Reinert and Fernanda A. Reinert, “33 Economic Bestsellers Published Before 1750,” European Journal of the History of Economic Thought 25, no. 6 (2018): 1206–1263; Derek Beales, Enlightenment and Reform in Eighteenth Century Europe (London: I. B. Tauris, 2005), 64; Istvan Hont, Jealousy of Trade: International Competition and the Nation-State in Historical Perspective (Cambridge, MA: Harvard University Press, 2005), 45, 134; Sophus A. Reinert, The Academy of Fisticuffs: Political Economy and Commercial Society in Enlightenment Italy (Cambridge, MA: Harvard University Press, 2018), 7; John Robertson, The Case for Enlightenment: Scotland and Naples, 1680–1760 (Cambridge: Cambridge University Press, 2005), 22; Koen Stapelbroek, “Commerce and Morality in Eighteenth-Century Italy,” History of European Ideas 32, no. 4 (2006): 361–366, at 364; Antonio Muratori, Della pubblica felicità: Oggetto de’buoni principi (Lucca, 1749), p. 3 of “To the Reader. ”
2. Eric Cochrane, Florence in the Forgotten Centuries, 1527–1800 (Chicago: University of Chicago Press, 1973), 461; Reinert, Academy of Fisticuffs , 299; Antonio Genovesi, Delle lezioni di commercio, o s’ia d’economia civile , 2 vols. (Naples: Fratelli di Simone, 1767), 2:77, 133; Robertson, Case for Enlightenment , 356–357.
3. Steven L. Kaplan and Sophus A. Reinert, eds. , The Economic Turn: Recasting Political Economy in Enlightenment Europe (London: Anthem Press, 2019), 3–13; Pietro Verri, Meditazioni sulla economia politica (Venice: Giambatista Pasquale, 1771), 18, 33–34.
4. Ferdinando Galiani, Dialogues sur le commerce des blés , ed. Philip Stewart (Paris: SFEDS, 2018), 59.
5. Galiani, Dialogues, 115–116; Franco Venturi, “Galiani tra enciclopedisti e fisiocrati,” Rivista storica italiana 72, no. 3 (1960): 45–64, at 53.
6. Jean-Claude Perrault, Une histoire intellectuelle de l’économie politique (XVII–XVIIIe siècles) (Paris: Éditions de l’EHESS, 1992), 238.
7. Perrault, Une histoire intellectuelle , 16–17.
8. Perrault, Une histoire intellectuelle , 19.
9. Meek, The Economics of Physiocracy (London: Allen and Unwin, 1963), 47–49.
10. Meek, Economics of Physiocracy , 51; Madeleine Dobie, Trading Places: Colonization and Slavery in Eighteenth-Century French Culture (Ithaca, NY: Cornell University Press, 2010), 14–15.
11. Benoit Malbranque, Le libéralisme à l’essaie. Turgot intendant du Limousin (1761–1774) (Paris: Institut Coppet, 2015), 44.
12. Emma Rothschild, Economic Sentiments: Adam Smith, Condorcet, and the Enlightenment (Cambridge, MA: Harvard University Press, 2001), 79; Malbranque, Le libéralisme à l’essaie , 58.
13. Cynthia A. Bouton, The Flour War: Gender, Class, and Community in Late Ancien Régime French Society (University Park: Penn State University Press, 1993), 81; Gilbert Foccarello, “Galiani, Necker, and Turgot: A Debate on Economic Reform and Policy in 18th Century France,” European Journal of the History of Economic Thought 1, no. 3 (1994): 519–550.
14. Jacob Soll, “From Virtue to Surplus: Jacques Necker’s Compte Rendu (1781) and the Origins of Modern Political Discourse,” Representations 134, no. 1 (2016): 29–63; Jacques Necker, Sur la législation et le commerce des grains (Paris: Chez Pissot, 1775), 50–52.
15. Steven L. Kaplan, Bread, Politics, and Political Economy in the Reign of Louis XV , 2nd ed. (New York: Anthem Press, 2012), 589–595.
16. Kaplan, Bread, Politics , 247; Istvan Hont, Politics in Commercial Society: Jean-Jacques Rousseau and Adam Smith , ed. Béla Kapossy and Michael Sonensher (Cambridge, MA: Harvard University Press, 2015), 18–19.
17. Antoine Lilti, The Invention of Celebrity (Cambridge, UK: Polity, 2017), 117; Jean-Jacques Rousseau, Du contrat social , ed. Pierre Burgelin (Paris: Garnier-Flammarion, 1966), 41; Jean-Jacques Rousseau, A Discourse on Inequality , ed. Maurice Cranston (London: Penguin, 1984), 77.
18. Rousseau, Discourse on Inequality , 101, 109, 127, 137.
第十三章 亚当斯密和良性自由贸易社会
他们〔商人与制造商〕正是凭借着对自身利益拥有较多知识，因此经常强迫利用他〔乡绅〕的慷慨，并说服他放弃自己的利益与公众的利益，出于非常简单且正直的信念：他们的利益才是公众的利益，而他的利益则不是。然而，无论在贸易或制造业的任何一个分支，商人的利益总是会在某些方面和公众利益有所分歧，甚至相反。 ──亚当斯密，《国富论》（The Wealth of Nations ），一七七六年
亚当斯密和鲁索一样不欣赏贪婪。并且他也同样有些担心曼德维尔在《蜜蜂的寓言》中表达的愤世嫉俗。斯密是在格拉斯哥大学（University of Glasgow）研究斯多噶道德哲学的教授，他不认为恶行会是美德。美德是一种艰苦的努力，而他的工作就是教导何谓美德。斯密不同意鲁索对于纯粹天生的人类情绪的看法，无论是贪婪还是怜悯都一样，他也不同意鲁索认为社会的本质是罪恶的论点。西塞罗的斯多噶哲学教导我们，个人可以学习自律和道德，进而使社会变得更美好，斯密相信这一点。如果要从斯密的经济作品中提炼出一个明确的概念，那这个概念就是：道德是市场运作的必备要素。我们可以从《国富论》（一七七六年）清楚看出，斯密不是现代所谓的经济自由主义者，更不用说自由意志主义者（libertarian）了。他认为只有道德农业社会搭配上强大的统治菁英阶级，才能够创造与维持利伯维尔场。 现代经济学家对斯密的看法多半不是这样。人们往往觉得他是个为贪婪与商业利益辩护的人。但就和柯尔贝一样，现代经济学家用讽刺的手法将他扭曲成一种截然不同的样貌。举例来说，一九四四年，弗里德里希．奥古斯特．海耶克（Friedrich August von Hayek）将斯密描绘成一个反对所有政府干预，并且聚焦于经济效率的思想家。米尔顿．傅利曼也依循同样的脉络，把斯密在《国富论》中提及看不见的手的段落，解读为呼吁社会将政府从经济生活之中完全移除。傅利曼主张，斯密的“关键见解”是经济合作应该维持“严格自愿”，必须“没有外力、没有胁迫、没有对自由的侵犯”。然而，海耶克和傅利曼引用的段落都经过精心挑选，在过程中把斯密从一位道德哲学家──不信任商人和企业，相信强大的菁英政府、殖民规范、奴隶制度、公共教育和针对性关税──转变成了一位现代企业的自由意志主义辩护者。1 不过老实说，要阅读斯密那本将近一千页的《国富论》确实是件苦差事，而且他引述的许多语句都使得他像是在提倡完全的自由放任主义。他提出警告，政府“试着指示人民要以何种方式应用他们的资本”是一种愚行。他也批判政府不该干预个人的直接经济决策：“在人类社会这个巨大的棋盘上，每一枚棋子都有自身的移动原则，与立法机关可能选择强迫采用的原则完全不同。”此外，尽管他在未来成为了关税部长，但他也对税收带来的痛苦有所深思：“一个政府向另一个政府学习经验时，学得最快的就是从人民的口袋里搜刮钱财的艺术。”斯密认为，生产和消费必须免受政府的任何阻碍：“消费行为是所有生产行为的唯一终点和目的；生产者的利益只应在促进消费者利益的必要范围内予以关注。”斯密的部分文章段落使他看起来像是彻头彻尾的利伯维尔场支持者：“〔在没有贸易限制的状况下，〕自然自由（natural liberty）这个理所当然又单纯的系统会自行建立起来。每个人……都可以全然自由地以自己的方式追逐自己的利益。”2 然而，如果我们按照当时的历史脉络去解读斯密针对市场自由所写的这些引述内容，就会清楚看到他的愿景和现代利伯维尔场思想家相去甚远。《国富论》是一部充满雄心壮志的作品，旨在调和当时实际存在的农业寡头和愿景中的自我调节的市场，同时应对商业与帝国的崛起。斯密认为，贸易只会在农业主导的社会中蓬勃发展，在这样的社会中，拥有大量土地的统治阶级菁英能够限制商人的利益、推广学习与提倡斯多噶美德。斯密是罗马道德哲学教授，这个身分很适合协助引导这种西塞罗式的道德复兴。
英国与法国之间的持续冲突，打碎了重农主义者对于农业、利伯维尔场与国际和平能卷土重来的希望。这两个国家都采取了保护性策略，藉此发展国内产业，相互争夺全球市场的主导地位。十八世纪上半叶，英国的经济景气衰退。法国的布料制造业正在蚕食英国经济。法国紧密控制地中海市场，阻碍了英国与土耳其以及西班牙的贸易。法国也主宰着糖业市场，他们的国家出口总糖量和英国持平，甚或略胜一筹。到了一七四○年代，法国的海外贸易成长速度是英国的三倍。在一七二○至一七五○年代间，法国的出口以每年百分之三至五的速度成长，英国的出口成长率则是百分之一点五。奥地利王位继承战争（War of Austrian Succession，一七四○年至一七四八年）是英法的全球代理战争，将这两大强权的对抗置于帝国的舞台上，而七年战争（一七五六年至一七六三年）则成为一场更大规模的全球商业与帝国霸权斗争。战事从欧洲扩及美洲、印度和西非。人们需要达成某种协议来平息纷乱，而许多经济思想家认为利伯维尔场就是能带来和平的解决方案。3 斯密是一名学者，他认为国际学术互动证明了自由交流是一种互惠的模式。在法国与英国军事上互相对抗的期间，两国在知识与科学方面的合作仍十分自由。英法两国的杰出思想家时常进行跨海峡的研究工作，这是源远流长的传统，他们在冲突、友谊与学习中共同发展。托马斯．霍布斯在一六三○年代于法国接受教育，一六四○年代再次为了躲避英国内战初期的政治冲突而逃到法国，并在这里写下了《利维坦》（一六五一年）。这样的交流是双向的。法国哲学家伏尔泰流亡至伦敦，写下了有关英国哲学、政治与生活的作品。到了十八世纪中叶，全欧洲与美洲的知识分子都涌入了巴黎的沙龙，哲学家在那里谈论科学、政治、无止尽全球冲突的可能解决方案，以及如何面对市场带来的挑战。英法知识交流的悠久传统对于斯密的利伯维尔场理论来说至关重要。4 此外，斯密在社交与知识两种层面上也很依赖他的导师，苏格兰哲学家戴维．休谟；休谟的法国知识渊源和关于利伯维尔场思想的文章，为斯密铺设了一条通往《国富论》的道路。休谟的作品是斯密的作品蓝图。自小就是神童的休谟出生在贫困的贵族家庭，拥有爱丁堡大学（University of Edinburgh）的学位，他到法国继续接受教育以“增进”他的“文学才能”。一七三四年至一七三九年，休谟在罗亚尔河谷（Loire Valley）的安朱（Anjou）就读弗莱彻耶稣会学院（Jesuit college of La Flèche），该学校以笛卡儿曾就读过而闻名。许多当地的耶稣会士曾是传教士，他们向年轻的休谟讲述他们旅行至亚洲与南美洲的故事，听得津津有味的休谟因此对于各个社会与民族之间的对比深感着迷。他充分利用了学校图书馆中有关希腊哲学、欧陆哲学、法国历史、道德与经济思想的广泛藏书。5
休谟在弗莱彻学院写下了开创性的著作《人类理解论》（Essay on Human Understanding ），而后在一七三八年返回伦敦后发表此作。休谟的书是启蒙认识论的基础──认识论是研究人类如何学习与认识事物的一种学科。休谟认为，人类可以透过对伦理的了解，建立道德的经济制度与社会。他描述了斯多噶学派与伊比鸠鲁学派的希腊哲学家如何对自然运动与行为建立历久不衰的原则，并将这些原则拿去和托勒密（Ptolemy）以及哥白尼如何发展出他们对行星运动的理解进行比较。他相信若能把斯多噶主义和天文学结合起来，就能更深入了解人类行为与经济。这个方法后来对斯密的经济思想产生了深刻的影响。6
休谟和斯密写作的时间都是在一七○七年《合并法案》（Act of Union ）签订之后的那段期间，英格兰与苏格兰根据此法案合并为大不列颠。苏格兰因为《合并法案》而进入了英格兰市场与殖民市场。爱丁堡与格拉斯哥（Glasgow）成为富裕的帝国贸易城市，取得筹码可以进行有利的条款与契约协商。休谟与斯密都见证了当时的经济扩张，也都因此受益。一七四七年，格拉斯哥市经交涉后签署了一项从法国殖民地进口烟草的垄断协议。克莱德河（Clyde）变成了烟草与制造业商品的贸易枢纽，苏格兰商人在此处的贸易圈交易奴隶，这对五十年前的格拉斯哥人来说是作梦也想不到的。烟草、奴隶、棉花、糖和兰姆酒使苏格兰商人发家致富，使学院和优秀的大学蓬勃发展。苏格兰人终于品尝到了财富的滋味，那滋味令人陶醉又充满诱惑力。很显然的，正是这种帝国自由贸易带来的确凿承诺与随之而来的富饶，使得戴维．休谟与其门生亚当斯密支持《合并法案》，也支持自由贸易和帝国的广阔愿景。10
亚当斯密就是在这么一个充满冲突、经济扩张和知识野心的时代下步入成年。他于一七二三年出生于苏格兰的古老商业制造城镇克尔卡迪（Kirkaldy），隔着福斯湾（Firth of Forth）与爱丁堡遥遥相望。他的父亲（在他两个月大时去世）是一名律师与海关首长。他的母亲来自拥有土地的乡绅家族，而斯密就读的是镇上一所出色的自治学校，他在那里接受丰富的古典教育，打下扎实的拉丁语基础。斯密从小聪颖过人，十四岁就进入格拉斯哥大学就读，他的老师是杰出的道德哲学家弗朗西斯．哈奇森（Francis Hutcheson）。在哈奇森充满感召力的鼓励下，斯密开始对当时的启蒙运动风潮产生了兴趣，启蒙运动重视罗马伦理、科学、言论自由与洛克的自由思想。一七四○年，斯密获得了奖学金，成为牛津大学贝里欧学院（Balliol College）的研究生。斯密痛恨这个地方，觉得这里既堕落又缺乏智识上的挑战。他靠自己大量广泛地阅读，但却受神经颤抖所苦。他在奖学金耗尽之前，于一七四六年离开了牛津。一七四八年，他开始在爱丁堡大学（University of Edinburgh）授课，一七五○年，他成为格拉斯哥大学的教授，教学内容包括古典修辞学、道德哲学、法律与纯文学。
一七五九年，斯密出版了《道德情感论》（Theory of Moral Sentiments ），在书中提出了他的核心思想：人可以透过斯多噶式的道德哲学建立道德的社会。在霍布斯和鲁索的描述中，情绪的根源是与生俱来且野蛮的，斯密则不同，他依循的是斯多噶派的理想，认为道德情绪是可以培养的，而我们可以藉此创造美好的社会。斯密认为：“悲痛与憎恨带来的情绪是苦涩且疼痛的，更加需要同情的治疗与安慰。”他撰写此书的背景是一七五○年代末的英法冲突期间，他希望能找到一种哲学方法以摆脱战争的控制，在他看来，战争是人类在道德方面失败后制造出来的产物。12
虽然斯密的行文带有一种基督教的口吻，但他的作品没有提及过《圣经》。他使用的语言是绝对的自然神论。他将神描述成“自然的全智创作者”，这个作者创造了人类当作“他在人间的代理人，监督他的弟兄的所作所为”。斯密也把神称作“宇宙监督者”。但这位神祇并不是道德判官。取而代之的是，人类必须成为彼此行为举止的道德判官。斯密希望人类可以透过道德、透过牛顿式的因果概念，建立一个自我规范的社会。而后，他在一七七三年的著作《天文学历史》（The History of Astronomy ）中写道：“一连串看不见的对象，链接着两个按照全世界都很熟悉的顺序发生的事件。”在牛顿提出的“系统”中，是一只“看不见的手”设置了一种理性的、发条式的平衡状态。14 在斯密看来，人类的道德行为、爱与合作都是杠杆，共同维持社会机制的平衡与恒动。他认为在劳动分工的机制中，自由、合乎道德、以农业为重点的贸易是必不可少的一个零件。这种分工机制能有效率地分配具有差异且相互协作的制造业活动与贸易活动，使人们能够共同努力，和平地创造出财富。斯密把论述导向西塞罗，并写道，商业“应当是联系国与国、人与人的一种友谊团结的纽带”。斯密的杰出见解是，如果人类和国家能在经济上彼此合作，就能为所有人创造财富。15 然而，斯密理想中那个仁慈、合作且自我规范的社会是无法单靠自己实现的；这个社会需要领导人与立法者，而对斯密来说，这些人只能是受过教育的富裕贵族地主。斯密很早以前就注意到，鲜少有人能真正理解治理的法律原则，就连瑕不掩瑜的都很少见。用一种带有亚里士多德和西塞罗色彩的观点，他把理想的立法者描述成受过良好教育、礼貌、仁慈并且只会对法律偏心的人。只有这种人才能实践公民法律所需的自我约束和“科学精神”。16 具有道德良知的贵族政府，将会为国家带来著名的路易十四批评家芬乃伦在小说《忒勒马科斯的冒险》中所描述的那种自由与富裕。斯密主张，法国也许比英国有钱，但法国缺乏成为商业领导国家的道德社会特质，原因在于法国没有自由的议会政府能维持“我国公民享有的安全、体面且幸福的境况”。法国的君主制专制且不容异己，在这种缺乏政治与社会美德的国家中，社会无法实现真正的仁慈。斯密相信，英国从一六八八年的光荣革命后开始实施的菁英代议制政府，是唯一能够避免“国际战争与国内派系斗争”并打造一个幸福、阔绰国家的途径。这也是唯一能成就利伯维尔场的方法。值得注意的是，斯密的理论未能解释英国为什么会和法国交战将近一个世纪，而且仍然没有通过利伯维尔场法规。但是，他似乎十分乐观，觉得英国有道德基础能做到他热切相信的这些进步。17
我们在检视亚当斯密的哲学时，绝不能忽略他的个人生活与物质环境，正是他的所处环境使他的第一本书《道德情感论》大获成功。在休谟的帮助下，斯密悉心建立了有权有势的朋友网络，藉此累积财富与推广他的作品。《道德情感论》在一七五九年首次出版时，休谟和斯密在《爱丁堡评论》的朋友联络了斯密的出版商安德鲁．米勒（Andrew Millar），确保他将其中几本书寄给拥有权力与影响力的几位著名苏格兰贵族：王室宠儿暨首相比特伯爵（Earl of Bute）、阿盖尔公爵（Duke of Argyll）、曼斯菲德勋爵（Lord Mansfield）、塞尔伯尔尼伯爵（Earl of Shelburne）与查尔斯．汤森（Charles Townshend），也就是巴克勒公爵（Duke of Buccleuch）的继父。经由休谟优越的人脉关系，《道德情感论》“送到了所有受欢迎人物的手中”。这些权贵之手能够形塑斯密的职业生涯与社会大众对其作品的接受度。18 一七五九年的夏天，斯密成为了第一代塞尔伯尔尼伯爵（Earl of Shelbourne）的小儿子托马斯．费兹莫里斯（Thomas Fitzmaurice）的老师。对斯密来说，这是一段激动人心的时期，他开始教授许多伟大苏格兰贵族的儿子。他引导这些晚辈认识古代哲学、法律与罗马贵族美德。作为一个长年单身的学者，斯密喜欢奢侈品，也渐渐喜欢上昂贵的服装。他生活在所谓的英国“寡头时代”（Age of Oligarchy），当时主导社会的是“独立的乡村仕绅”，他们往往是托利党员（Tories）或保守派的辉格党员（Whigs），一手掌控着下议院。这些世袭的贵族族长在议会掌握的权力几乎达到了有史以来的最高峰。尽管斯密曾批评过专断的社会阶级制度，但他成功爬上苏格兰地主社会的顶端，对此感到称心如意。如果他的经济愿景看起来像是为他的赞助人量身打造的，或许并非偶然。19
如往常一般，休谟为这位门生铺平了道路，并确保他会在成功之后与老师共享。一七六三年，赫特福德伯爵（Earl of Hertford）招揽休谟担任英国驻巴黎大使馆的秘书，这是一个有利的职位。休谟写信给斯密，表示这项工作邀约“伴随着绝佳的前景与期望”。法国在七年战争败北后陷入经济萧条。尽管如此，休谟的巴黎社交生活还是非常丰富，他几乎连“翻开书”的时间都没有，忙着和其他的知名哲学家往来。斯密在汤森的重金资助下，于一七六四年跟随休谟的脚步前往欧陆。他曾提及他利用这个机会开始“撰写一本小书来打发时间”。一般认为这本书就是《国富论》。21
英国社会的看不见的手，得负责将英国的文明力量带到殖民地，这意谓着要教育殖民地的人口，他们因为距离大都市很遥远，需要花时间才能发展为成熟的商业社会。斯密以美洲为例，说明商人之所以不适合执政，是因为他们在决策过程中只会考虑自身利益。斯密并没有提到是约翰．洛克自己创造出马里兰州的烟草垄断的，只是抱怨商人“出于怪异的荒谬想法”，认为“君主的特质”只不过是贸易与商人利益的“附属品”，一心只想要排除竞争对手。对于先进商业社会尚未完全形成的地方，一个洛克的菁英式开明政府，必须先透过文明的影响力介入，将自然之手引导向适当的位置。斯密写作的时候正值美国独立战争（American War of Independence，一七七五年至一七八三年），虽然他反对美国殖民地脱离大英帝国，但若这件事真的发生了，他希望两国能结成自由贸易联盟。但新生的美利坚合众国做的决定却正好相反，美国在一七八三年对所有外国商品征收关税，以保护正在发展中的脆弱经济。30
1. Friedrich Hayek, The Road to Serfdom , ed. Bruce Caldwell (Chicago: University of Chicago Press, 2007), 88, 100; Milton Friedman, Free to Choose: A Personal Statement, 3rd ed. (New York: Harcourt, 1990), 1–2.
2. Adam Smith, An Inquiry into the Nature and Causes of the Wealth of Nations , ed. Roy Harold Campbell and Andrew Skinner, 2 vols. (Indianapolis: Liberty Fund, 1981), vol. 1, bk. I, chap. vii, para. 12; vol. 2, bk. V, chap. iih, para. 12; vol. 2, bk. IV, chap. viii, para. 49; vol. 2, bk. IV, chap. 9, para. 3; Adam Smith, The Theory of Moral Sentiments , ed. D. D. Raphael and A. L. Macfie (Indianapolis: Liberty Fund, 1984), pt. 6, sec. 2, chap. 2, para. 17.
3. Steven Pincus, The Global British Empire to 1784 , unpublished manuscript; Paul Butel, “France, the Antilles, and Europe in the Seventeenth and Eighteenth Centuries: Renewals of Foreign Trade,” in The Rise of Merchant Empires , ed. James D. Tracy (Cambridge: Cambridge University Press, 1990), 168–172; T. S. Ashton, An Economic History of England: The Eighteenth Century (London: Methuen, 1955), 104; François Crouzet, “Angleterre et France au XVIIIe siècle: Essaie d’analyse comparé de deux croissances économiques,” Annales. Économies, sociétés, civilisations 21, no. 2 (1966): 254–291, at 268; Ralph Davis, “English Foreign Trade, 1700–1774,” Economic History Review , n. s. , 15, no. 2 (1962): 285–303, at 286; François Crouzet, La guerre économique franco-anglaise au XVIIIe siècle (Paris: Fayard, 2008), 367–370; Paul Cheney, Revolutionary Commerce: Globalization and the French Monarchy (Cambridge, MA: Harvard University Press, 2010), 101; François Crouzet, Britain Ascendant: Comparative Studies in Franco-British Economic History , trans. Martin Thom (Cambridge: Cambridge University Press, 1990), 216.
4. Dan Edelstein, The Enlightenment: A Genealogy (Chicago: University of Chicago Press, 2010), 9.
5. David Hume, An Inquiry Concerning Human Understanding , ed. Charles W. Hendel (Indianapolis: Library of the Liberal Arts, 1955), 1–11, 17; Dario Perinetti, “Hume at La Flèche: Skepticism and the French Connection,” Journal of the History of Philosophy 56, no. 1 (2018): 45–74, at 57–58; Margaret Schabas and Carl Wennerlind, A Philosopher’s Economist: Hume and the Rise of Capitalism (Chicago: University of Chicago Press, 2020), 33; Pedro Faria, “David Hume, the Académie des Inscriptions, and the Nature of Historical Evidence in the Eighteenth Century,” Modern Intellectual History 18, no. 2 (2020): 288–322.
6. Perinetti, “Hume at La Flèche,” 54; Hume, Concerning Human Understanding , 168.
7. Hume, Concerning Human Understanding , 172–173; James A. Harris, Hume: An Intellectual Biography (Cambridge: Cambridge University Press, 2015), 97.
8. Carl L. Becker, The Heavenly City of the Eighteenth-Century Philosophers (New Haven, CT: Yale University Press, 1932), 85, 102; Anthony Grafton, The Footnote: A Curious History (Cambridge, MA: Harvard University Press, 1997), 103; David Hume, Selected Essays , ed. Stephen Copley and Andrew Edgar (Oxford: Oxford University Press, 1998), xiii, 56, 58, 61.
9. Hume, Selected Essays , 188–189, 193, 194.
10. Jesse Norman, Adam Smith: The Father of Economics (New York: Basic Books, 2018), 194.
11. Smith, Theory of Moral Sentiments , sec. 1, chap. 1, para. 1; sec. 3, chap. 2, para. 9; Adam Smith, “Letter to the Edinburgh Review ,” 1755, in Smith, Essays on Philosophical Subjects , with Dugald Stewart’s “Account of Adam Smith,” ed. W. P. D. Wightman, J. C. Bryce, and I. S. Ross (Indianapolis: Liberty Fund, 1982), 253.
12. Smith, Theory of Moral Sentiments , pt. 1, sec. 1, chap. 2, para. 5.
13. Epictetus, The Discourses, The Handbook, Fragments , ed. J. M. Dent (London: Orion Books, 1995), 42, 44, 58; Smith, Theory of Moral Sentiments , pt. 1, chap. 1, para. 5.
14. Smith, Theory of Moral Sentiments , pt. 3, chap. 5, paras. 6–7; pt. 7, sec. 2, chap. 1, para. 39; Adam Smith, Essays on Philosophical Subjects , ed. W. P. D. Wightman and J. C. Bryce (Indianapolis: Liberty Fund, 1980), 45, 49, 104; Emma Rothschild, “Adam Smith and the Invisible Hand,” American Economic Review 84, no. 2 (1994): 319–322, at 319.
15. Smith, Wealth of Nations , vol. 1, bk. IV, chap. iiic, pt. 2, para. 9.
16. Smith, Theory of Moral Sentiments , sec. 2, chap. 3, para. 1; sec. 5, chap. 2, paras. 10–13; sec. 7, chap. 4, paras. 36–37; Donald Winch, Riches and Poverty: An Intellectual History of Political Economy in Britain, 1750–1834 (Cambridge: Cambridge University Press 1996), 98–99; Fonna Forman-Barzilai, Adam Smith and the Circles of Sympathy: Cosmopolitanism and Moral Theory (Cambridge: Cambridge University Press, 2010), 226.
17. Smith, Theory of Moral Sentiments , pt. 6, sec. 2, chap. 2, para. 13.
18. Nicholas Phillipson, Adam Smith: An Enlightened Life (New Haven, CT: Yale University Press, 2010), 159–166.
19. Phillipson, Adam Smith , 166; Geoffrey Holmes and Daniel Szechi, The Age of Oligarchy: Pre-Industrial Britain, 1722–1783 (London: Longman, 1993), 282.
20. Phillipson, Adam Smith , 182.
21. Harris, Hume , 409–415; Phillipson, Adam Smith , 188.
22. Phillipson, Adam Smith , 193.
23. Smith, Wealth of Nations , vol. 2, bk. IV, chap. ix, para. 38; vol. 1, bk. II, chap. v, para. 12.
24. Smith, Wealth of Nations , vol. 1, bk. I, chap. viii, paras. 15–22; vol. 1, bk. I, chap. x, paras. 19, 31.
25. Smith, Wealth of Nations , vol. 2, bk. IV, chap. ix, paras. 11–14, vol. 2, bk. IV, chap. ii, para. 9; vol. 1, bk. I, chap. viii, para. 35; vol. 1, bk. IV, chap. ii, para. 9; vol. 2, bk. IV, chap. ix, para. 9; vol. 2, bk. V, chap. iik, para. 7.
26. Smith, Wealth of Nations , vol. 1, bk. I, chap. ii, paras. 1–2.
27. Emma Rothschild, Economic Sentiments: Adam Smith, Condorcet, and the Enlightenmen t (Cambridge, MA: Harvard University Press, 2001), 127.
28. Smith, Wealth of Nations , vol. 1, bk. IV, chap. ii, para. 38; vol. 2, bk. IV, chap. ix, paras. 1–3; vol. 1, bk. IV, chap. ii, para. 30.
29. E. P. Thompson, “Eighteenth-Century English Society: Class Struggle Without Class?,” Social History 3, no. 2 (1978): 133–165, at 135; Frank McLynne, Crime and Punishment in Eighteenth-Century England (London: Routledge, 1989); Smith, Wealth of Nations , vol. 1, bk. I, chap. xic, para. 7.
30. Smith, Wealth of Nations , vol. 2, bk. IV, chap. viib, para. 20; vol. 2, bk. IV, chap. viic, para. 103.
31. Smith, Wealth of Nations , vol. 1, “Introduction and Plan of the Work,” para. 4; vol. 2, bk. IV, chap. viib, para. 54.
32. John Rae, Life of Adam Smith: 1895 , ed. Jacob Viner (New York: Augustus M. Kelley Publishers, 1977), 71–72.
33. Rothschild, Economic Sentiments , 133; Dugald Stewart, Account of the Life and Writings of Adam Smith , in Works, ed. Dugald Stewart, 7 vols. (Cambridge, MA: Hilliard and Brown, 1829), 7:1–75, at 67.
34. Smith, Wealth of Nations , vol. 1, bk. III, chap. iv, para. 20.
35. Smith, Wealth of Nations , vol. 2, bk. IV, chap. ii, paras. 10–20.
36. Smith, Wealth of Nations , vol. 1, bk. IV, chap. iiic, paras. 9, 13.
37. Rothschild, Economic Sentiments , 133–136; Voltaire, Candide , ed. Philip Littell (New York: Boni and Liveright, 1918), 168; Jacob Soll, The Reckoning: Financial Accountability and the Rise and Fall of Nations (New York: Basic Books, 2014), 129–130.
第十四章 利伯维尔场帝国
你们认为保护政策如何能增加一个国家的财富？你们能否透过立法使国家的财富增加任何一文？你们或许可以透过立法，在一夜之间摧毁一世纪的劳动带来的成果和累积；但在我看来，你们不可能透过本院的立法，为国家财富增加任何一文。财富来自勤奋与智慧，你们无法找到比任其自行发展更好的方法。 ──理查德·科布登（Richard Cobden），《下议院演讲》（Speech to the House of Commons ），一八四六年
十九世纪初，李嘉图形塑与捍卫着斯密遗留下来的建树，坚持认为财富来自农业。不过他跟斯密不同的地方在于，他认为财富是有限的。在《论政治经济与赋税原则》（On the Principles of Political Economy and Taxation ，一八○九年）一书中，他发展出了地租法则（Law of Rent），此法则的基础概念是土壤的肥沃决定了劳动的价值。他认为定价与薪水会随着土地的生产能力而起伏，而需求不会带来任何影响。李嘉图在马尔萨斯的影响下，发展出了工资铁律（Iron Law of Wages），根据该定律的描述，穷人的收入总是会持续下降到可维生的最低水平。一旦农场工人得到报酬，他们就会生下更多孩子，这只会使他们变得更加贫困，抵销任何工资增长。唯一能够大幅提升工资的方式就是解放国际谷物市场以创造竞争，如此一来，英国的土地拥有者就会投资农场，推高生产率与工资，也可能一并提高生活水平。然而，李嘉图警告如果土地拥有者是靠着固定的总资本来支付工人高薪，他们以后就没有钱重新投资农场了，这将会再次压低工资。6
到了十九世纪初，英国无庸置疑成为了世界工厂──在工业与殖民方面首屈一指的国家。同时英国也是谷物的主要生产国。李嘉图身为议员的伟大计划就是支持自由贸易。他支持废除谷物法，也就是一八一五年拿破仑战争结束时设立的保护主义谷类关税，当时设立关税的目的是保护英国地主不受定价更便宜的外国谷物影响。李嘉图借鉴了斯密对于自由贸易自我调节本质的牛顿式信念，主张土地拥有者只不过是利用关税来创造国家对谷物的垄断，并推高价格。尽管李嘉图没来得及亲眼目睹，但后来在实业家理查德．科布登的带领之下，反谷物法联盟（Anti-Corn Law League）的自由放任提倡者施加压力，使英国的谷物法于一八四六年遭到废除，科布登是来自制造业中心──曼彻斯特的企业家与国会议员，他代表了历史学家称作“自由贸易国度”的英国时代之起始。9
即使在世界市场占据了主导地位，英国仍必须面对贫困与财富不均的棘手问题。正如马尔萨斯所警告的那样，任由市场自生自灭是无法解决这些问题的。经济与政治哲学家约翰．史都华．弥尔（John Stuart Mill）认为，自由贸易是一把双面刃，我们在欢庆自由贸易的自由面时，也必须承认它并没有为穷人带来更好的生活水平。从许多方面来说，弥尔都是最能代表十九世纪早期利伯维尔场思想内部矛盾的思想家──他相信利伯维尔场的生产能力，同时也承认国家需要为了打造出更公正的经济系统而进行社会改革，并在两者间达到平衡。
弥尔在一八六九年写下了《论社会主义诸篇》（Chapters on Socialism ），距离查尔斯．达尔文出版《物种起源》（The Origin of Species ，一八五九年）正好十年。达尔文透过商业的视角思考生物学，他的演化理论将会对利伯维尔场思想留下深远影响。根据他的理论，演化看起来就像是把斯密的理想主义进步观点结合马尔萨斯认为自然会剔除弱者的想法，形成了某种积极的、超出道德范畴的演化方式。虽然达尔文在《人类的由来及性选择》（The Descent of Man, and Selection in Relation to Sex ，一八七一年）引用了马尔萨斯“令人永远难忘”的著作，但达尔文与马尔萨斯的基督教道德观完全切割。达尔文不再受《旧约圣经》的创世纪故事所限制，他眼中的大自然只会按照自然本身的无情逻辑运作。在自然选择（natural selection，又称天择或物竞天择）中，既没有高尚的西塞罗观点，也没有基督教伦理的存在，只有适者才能生存与繁衍。15
哈密尔顿坚信，共和体制必须由强大的政府来建立。他认为国家应该要由多位握有重权的首长来管理，“就像法国的那些首长一样”──正如他后来在《联邦党人文集》（Federalist Papers ）第三十五篇中坚持的──这些人应该各自专精不同的领域，像是金融。一七九一年，哈密尔顿在“致国会之制造业报告”（Report to the Congress on the Subject of Manufactures）中坚称，处于起步阶段的国家政府必须把焦点放在发展工业上，而非农业。虽然农业是生活中不可或缺的，但农业其实不如重农主义者、休谟和斯密所说的是创造财富的基础。事实上，哈密尔顿深深认为这个概念必须在公众面前接受挑战，并由此明确声明，真正使得英国获得“大幅进步”的是工业的“棉花纺织厂”，而不是农耕。19
德国经济学家佛瑞德里克．李斯特（Friedrich List）也将会从哈密尔顿和克莱提出的美国体制中获得灵感。李斯特在一八二五年移居宾州，因为美国内部受到外部关税保护的自由贸易区而获得启发，主张要建立德国关税同盟（Zollverein ），将德国各州都纳入经济同盟的各个方面。李斯特在《政治经济学的国家体系》（National System of Political Economy ，一八二七年）中，解释了德国各州之间为何需要贸易条约来支持德国国内工业。关税将会在他们遇到国外竞争力时保护他们，如此一来，德国才能顺利发展，养成国际竞争力。李斯特的想法在法国也很受欢迎。这些观点反映了内部自由贸易的有效性，并且可以由内部关税同盟来促进，此外，策略性保护主义可以刺激德国在面对英国工业巨头时蓬勃发展。
值得注意的是，就在实施保护主义的经济大国：美国、德国和日本在经济成长方面赶上了英国时，剑桥大学哲学家阿尔弗雷德．马歇尔（Alfred Marshall）则在继续挥舞着教条式的自由贸易旗帜。就好像剑桥与世隔绝一样。马歇尔的《经济学原理》（Principles of Economics ，一八九○年）取代了弥尔的《论政治经济与赋税原则》，成为英国最重要的经济学教科书，马歇尔也成为了剑桥大学最举足轻重的经济思想家。他不但继续发展杰文斯提出的边际效用等概念，也提出了新的构想，诸如价格弹性、需求与定价的关系，以及部分均衡理论，这些构想对往后的经济学思想来说至关重要。他深入研究单一市场（例如羊毛）的供需流动，针对特定经济领域的运作提出细部分析，而不是提出他对整体经济的综合看法。马歇尔认为供需的运作就像机械一样，能创造出经济活动的“连续链”，他指出正是这具机械决定了价格。这具机械能为市场带来“均衡”，使市场能够靠自身运作，创造恒定的回报。30 马歇尔和斯密一样，是一名道德哲学教授。虽然他把焦点放在总量与边际效用价值等，但他仍在大自然中寻求经济“法则”，他认为这套法则能使得经济学变得类似于天文学等自然科学。因此，马歇尔盼望能靠着与天文学和物理学的模拟，去理解斯密所说的普遍驱动经济系统。他希望经济学的“个别学生”能够变得有资格“使用他的科学权威发话”。对马歇尔来说，在理解创造财富与经济活动时，必须结合工业生产价格、数量、效率，以及“需求层次”和竞争一起理解，这些要素彼此连结在一起后才创造出了成长。31 尽管马歇尔对于一直持续存在着的贫困感到有些不知所措，但他相信，只要靠着市场就能解决经济问题，工资终究会上涨，生活水平终究会提高。他没注意到的是，他这具巨大的经济机械已经快解体了。他在一九二四年逝世，五年后发生了一九二九年的华尔街大崩盘，美国开始步入经济大萧条。马歇尔不断寻找新的市场机制，而从没想过市场会崩盘。有一些二十世纪利伯维尔场思想家一心追随马歇尔的思想──他们就像《白鲸记》中的船长亚哈（Captain Ahab）一样，站在对市场的固定立场，愈来愈执着于传统观念：市场会自行运作，政府对经济事务几乎没有影响。
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一九○五年，阿尔弗雷德．马歇尔在剑桥的同事威廉．康宁汉（William Cunningham）发表了《自由贸易运动的兴衰》（The Rise and Decline of the Free Trade Movement ），表达他对正统利伯维尔场思想的控诉。康宁汉在这篇针对英国正统经济观念的抨击文章中指出，传统观念源自杜尔哥和斯密的观点，在这些观点中，“经济学把社会视为一种机械”，提供了“宝贵的真理，至少就目前状况来说是如此；但问题在于这并不是完整的真相”。康宁汉主张，如果经济学想要被视为科学的话，就必须承认，经济学中的许多人类活动根本和机械运作截然不同。他使用了达尔文的说法，说社会应该是一种“在面对环境时具有自我适应能力的有机体”。因此，市场只是整具机械的一部分，而且还常常故障。为了让机械保持运转，必须“一遍又一遍地测试”，即便如此，这种利伯维尔场思想的伟大机械真理仍有可能根本行不通。1 康宁汉认为，经济学只不过是一种“沉闷的阅读材料”，人们可以利用供需原则等简明扼要的原理来代替整段沉闷的经济学阅读。他明白“自由贸易原则”，根据该原则所述，货品与服务的交换是没有限制的，而消费者可以依照此原则自由选择货品，追求舒适与效率。康宁汉用讽刺又强而有力的言词指出，他“打从心底完全支持自由贸易倡导者所假设的目标”，但如果他到富裕又实施保护主义的美国去，询问一个住在纽约的美国人，想必会发现这个人对自由贸易学说抱持着截然不同的态度。2 一九○○年，英国仍是一个实施自由贸易的国家，自由贸易的理念几乎就像是邪教一样：消费者就是国王，人们把自由贸易的圣战士理查德．科布登视为国家英雄，建立雕像与纪念碑来荣耀他。然而康宁汉主张这种意识形态已经破产。从剑桥大学这块阴暗、舒适且与世隔绝的区域深处，他所发出的批判开始萌芽。康宁汉提出警告，欧洲和羽翼未丰的美国提出的“柯尔贝派”改革计划将会成为英国最大的敌人。他指出，佛瑞德里克·李斯特的发展模型在欧洲与美国奏效了，这是各国能顺利通往自由贸易先进国家的唯一可行路径。除此之外，科布登对和平与裁军的盼望一直都没有实现。康宁汉预测，军国主义在欧洲与美国已逐渐发展起来，作为优势帝国的英国将会继续仰赖国家的海军和其他军事的压制力量。帝国竞争仍在持续引发殖民冲突，一八九九年在南非爆发的波耳战争（Boer War）就是一例。3
在两次世界大战期间，阿尔弗雷德．马歇尔的学生开始攻击市场系统能完全自我调节的概念。剑桥经济学家约翰．梅纳德．凯因斯（John Maynard Keynes）支持的是利伯维尔场──他在一九二○年代警告，共产主义与个人自由放任主义将会交战，而自由放任主义必须获胜。但凯因斯认为，利伯维尔场主义是有漏洞的，并且为了生存和对抗共产主义，而必须去理解自己的弱点。凯因斯指出，他和导师马歇尔的不同之处在于他认为利伯维尔场需要保护，凯因斯相信放任市场自行运作是不行的。他在《就业、利息和货币的一般理论》（General Theory of Employment, Interest, and Money ，一九三六年）中提出了一项根本性的经济新发现，他认为薪资并不是透过市场机制自然调节而出现的。凯因斯主张，在经济大萧条期间，只有透过政府、公司与劳工之间进行的“谈判”，才能让市场创造出充分就业的结果。经济大萧条让我们看到的是，如果经济体的支出──也就是“总需求”──出现了急剧下降，就像一九二九年的股市崩盘与接踵而至的经济大萧条那样，那么就业率也会下降，这将会再次使总需求随之下降，造成恶性循环。更糟的是，边际价值理论可能反过来损害市场，将之吞噬。如果不能实现资本的边际效率（也就是由于投资回报大于利息，使得投资在通货膨胀的状态下仍然能长期获得利润），那么市场就不会提供投资的动机，进一步削弱成长与就业的希望。消费者无法只靠自己维持总需求，正如美国总统赫伯特．胡佛（Herbert Hoover）发现他放任市场的做法只让经济大萧条变得更糟那样。8 这也就代表了，如果政府不愿透过支出与推动市场流动来帮助提高总需求的话，经济危机将会愈滚愈大，让更多人失去他们的工作和财富。以经济大萧条这种情况来说，光靠有钱人是没办法把总支出的水平提高到足以停止经济危机恶性循环的程度。唯有国家才有资源透过总支出来催化整体的就业与经济机能。简而言之，在大规模的金融或经济危机中，必须由政府这只可见的手来增加总需求。任何无形的市场力量都无法做到这一点。国家必须承担“直接参与和规划投资的更重大责任”。凯因斯在批判的是提倡利伯维尔场的“古典经济学”和马歇尔认为供给与需求可以自我调节的构想。9 马歇尔的另一位知名学生琼．罗宾逊（Joan Robinson）和凯因斯一起加入论战，并告诉我们所有所谓的自我调节市场系统都可能失败的原因。罗宾逊是剑桥大学的教授，也是最早的重要女经济学家之一，至今人们仍无法理解，她为什么会在中国共产党主席毛泽东执行了可怕且造成经济灾难的文化大革命期间（一九六六年至一九七六年）支持毛泽东。无论是否受到误导，她之所以会支持毛泽东对社会与经济方面的暴力国家干预，都是基于她的此一信念：贫困国家无法在经济上和富裕国家竞争，需要冲击式的刺激。罗宾逊成为发展经济学的创始人，激发人们对马克思研究产生了新一波的兴趣。发展经济学旨在为没有大规模商业与工业基础的国家寻求致富的途径。此经济学可溯源至十七世纪所谓的重商主义著作，以及柯尔贝和亚历山大．汉米尔顿的政策。发展经济学在二十世纪的出现与经济未开发国家（所谓的第三世界）有关，这类国家没有能力进行必要的结构性经济改革，因此无法实现现代化并建立具有竞争力的商业与工业基础。
罗宾逊带头指出，经济未开发的国家在实质上无法与经济已开发的国家竞争，那些属于弱势群体的人们也无法与根基稳固的外国公司或个人竞争。她的著作《不完全竞争经济学》（Economics of Imperfect Competition ，一九三三年）创造出了“买方垄断”（monopsony，又称独买）的概念，指的是具有强大权力的单一买家控制了商品出售给其他买家的定价，因此市场价格会被一种买家对薪资的垄断所扭曲──就像是在一个“公司市镇”（company town，指大部分居民受雇于同一家公司的城镇）中，所有薪资与经济生活都由单一公司所控制的状况。买方垄断破坏了边际效用的逻辑。买方垄断的基础并不是市场力量，而仅仅是少数买家的决定或偏见，他们可以把薪资压低到低于边际价值的水平。买方垄断也解释了为什么女性的薪资比男性低，和少数族群的薪资比其他族群低。举例来说，如果一名雇主单纯出于偏见而决定要降低所有女性的薪资，那么这就会协助确立一个既定的市场价值；其他公司也可能效法此一趋势，而女性薪资就会受到整体削弱。10
一九五六年，罗宾逊出版了《资本的累积》（The Accumulation of Capital ），延续了凯因斯的传统，指出在一些未发展的经济体中，存在的只有资本家和劳工。劳工的薪资只能勉强维持生活，资本家在这个原始生产经济体中的消费很少，把钱都拿去买外国商品，损害了能够创造财富的当地消费者社会的发展。她提出的模式批判了由供需驱动的经济模型在较贫困国家的适用性。在较贫困国家中，不仅资本成长极低，而且资本会被拉向经济发展较高的市场，近一步削弱国内经济发展。11
剑桥曾是福音派利伯维尔场经济学的发源地，但后来成为了凯因斯主义的中心。如果说注重均衡的利伯维尔场思想在英国失去了优势，那么此种思想将会在奥地利找到最有力的新追随者。现代自由意志主义经济传统正是在奥地利出现，而在之后流传到了美国，在二次世界大战期间造成了巨大的影响。律师、记者暨奥地利经济学派创始人卡尔．门格尔（Carl Menger）大力抨击斯密的劳动价值理论，并用边际效用理论取而代之，根据后者所述，驱动经济的是互利的交易。他的自由主义思想，是斯密和边沁提出的“透过实现由市场驱动的人类需求来实现人类进步”之概念的简化版本。一八七一年，也就是杰文斯出版《政治经济学》的那一年，门格尔出版了《经济学原理》（Principles of Economics ）。门格尔清楚地认识到，斯密和李嘉图的劳动价值理论是行不通的。他带我们回到曼德维尔的《蜜蜂的寓言》，宣称能够推动经济发展的只有一件事：对商品的渴望。与曼德维尔不同的是，门格尔不认为恶行能创造出美德，他描绘了一个简陋而单纯的经济系统，单单只由“渴望”造成的“因果关系”来驱动，并且是这些因果关系建构了社会关系与经济关系。他认为社会主义者──无论是民主的或其他形式的──是不能去计划经济关系的。人类渴望各种事物，这种需求会创造供给，在这个不断循环的循环中持续发展成更加复杂的商业与工业社会。12
备受尊敬的经济学家暨学者路德维希．冯．米塞斯（Ludwig von Mises）是名犹太裔的利伯维尔场思想家，住在国际化且学术思想丰富的奥地利城市维也纳，他改信基督教的行为十分符合自身的经济意识形态。利伯维尔场思想已经远离了原本的自然神论源头，变得更加贴近基督教运动。冯．米塞斯和科布登一样，反对政府干预经济，他谴责战争，也谴责战争使个人屈从于一个虚无目标的可怕行为。一九二○年，冯．米塞斯根据他的信念，以惊人的先见之明痛斥了“社会主义国家联合体”中的国家中央经济计划。他认为当时苏联的中央计划方式在预测商品价值时，其准确度与效率都比不上供给与需求的自然定价过程。早在苏联出现惊人的经济崩溃之前，冯．米塞斯就看出了社会主义的中央计划经济无法有效地选出应该重视哪些产业，只有利伯维尔场能做到这一点。13
傅利曼和许多利伯维尔场思想家一样，生活在矛盾之中。他的事业始于富兰克林．罗斯福（Franklin Roosevelt）的罗斯福新政（New Deal），协助政府进行预算研究，接着进入国家经济研究局（National Bureau of Economic Research）工作。他后来指出，虽然政府的创造就业计划并不完美，但在遭遇经济大萧条时，这种计划是必要的。不过，傅利曼认为罗斯福新政的其余部分都在以马克思主义的方式“控制”个体的经济生活。傅利曼在回顾罗斯福的改革时，避开了尖锐的党派偏见，称赞总统怀抱着“崇高的意图”，但同时也十分遗憾地指出，他认为社会安全保险、国家福利、公共住宅与其他政府计划全都彻底失败了。斯密同样曾警告过，亲商的经济政策只会对特殊利益有利。傅利曼坚持认为社会政策也是一样的，他指出政府的援助破坏了“上帝面前人人平等”的原则。22
傅利曼对经济学的重要贡献始于一九五六年，他在那年发表了对于货币主义的研究，利用此理论与方法指出，控制货币供应量是稳定经济的主要方法。他在著名文章〈货币数量理论：重述〉（Quantity of Money Theory: A Restatement）中主张，经济体在逐年成长的过程中会创造出稳定的货币需求。他的看法与早期的货币数量理论学家互相呼应，认为货币的价值与经济体中的货币数量互有关联，但是他比早期的理论学家更像是柯尔贝，原因在于他担心经济体若没有定期提供货币，就会使经济交易的速度变慢、数量减少。他感兴趣的并非货币的价值，而是经济体如何创造出了必定出现又必须被满足的货币需求。这也就代表了政府必须每年都提供货币，而供给量应该相当于经济体的平均成长值。他回到了约翰．劳提出纸币理论时的中心思想，也就是政府必须稳定供应才能打造出信心，而傅利曼将这套观点称为经济行为者的“理性期待”。23
傅利曼的货币数量理论批判了凯因斯的“政府能靠支出刺激经济”的观点。傅利曼认为，除了军队和警察之外，所有国家支出都是错误，所有涉及联准会（Federal Reserve）的事情都很危险。事实上，他认为美国应该完全废除联准会，直接根据统计出来的预期成长数字来发行货币。他和共同作者安娜．舒瓦兹（Anna Schwartz）一起写下的巨著《美国货币史》（Monetary History of the United States ，一九六三年）指出，美国的货币存量正随着时间推移而不断成长。然而在经济大萧条期间，联准会限制了货币供给，希望能藉此抑制通膨。根据傅利曼所述，这些行为加剧且延长了经济大萧条的“大收缩”（great contraction）。他和舒瓦兹做出结论，认为联准会能够为国家的成长与扩张做出贡献的方式只有两种，一是什么都不做，二是拿出更多钱。24
当保护公司免受政府干预的运动在美国展开，希望能阻止罗斯福新政在社会、教育与社会福利方面的计划，杜邦兄弟也在行列之中。当时有许多亲利伯维尔场的团体都获得了工业家的支持，杜邦兄弟支持的是美国自由联盟（American Liberty League），他们与该联盟同心协力，试图撤销罗斯福的政策。若想达成目标，他们就需要一套意识形态。到了一九四○年代后期，另一个保守的基督教团体也开始反对罗斯福新政，这些福音派信徒认为罗斯福新政正在把人民的信仰从基督教转移到世俗国家。30
如今，当来自各方的批评者开始抨击傅利曼的利伯维尔场思想时，我们不禁要问：哪些版本的利伯维尔场思想是到了现今仍然有用的？正如我们在中国、新加坡乃至所有经济已开发国家中看到的，没有一种经济模式能占据主导地位。从以前到现在，从来没有任何一个。我们总是根据环境状况而不断变化。但我们能确定一件事：在没有政府的地方，例如南苏丹这类充满极端暴力的“边境经济体”，正统的自由意志主义利伯维尔场模式并不存在，也从未存在过。大多数已开发工业经济体都会遵循一种相对类似的配方，即自由社会民主制度，搭配上普遍的利伯维尔场机制，以及政府对于经济体的广泛监督和参与。多数私营公司会根据供给与需求的市场机制来生产和销售商品及服务，但也有些公司的根据来自私人国家垄断（如波音公司〔Boeing〕和空中巴士〔Airbus〕），有些则依据政府合约（如ＩＢＭ和微软〔Microsoft〕）、或者依据国家补贴公司和社会福利的计划来获得可观的国家援助（请回想一下亚马逊〔Amazon〕早期使用美国邮政署〔United States Postal Service〕，或者沃尔玛和麦当劳靠着国家医疗补助〔Medicaid〕作为低工资战略的一部分）。34 每个国家都会依据环境的不同，在发展的过程中采用极独特的方法与途径，这些发展往往违背了纯粹的经济模式。因此，我们不可能把新加坡拿去和中国、德国或美国相提并论，中美德皆拥有庞大且多样化的国内市场。虽然全球规模最大的公司大多都位于美国，但目前看来，亚洲的公司成长率比美国高得多。它们全都具有不同的优势与策略。把美国拿去和中国比较，就像是在一七○○年把英国与法国拿来比较一样。双方需要的是彼此不同的一系列经济政策，藉此发展经济状况并进行有效的竞争。35
1. William Cunningham, The Rise and Decline of the Free Trade Movement (Cambridge: Cambridge University Press, 1905), 5–9.
2. Cunningham, Rise and Decline ; Frank Trentmann, Free Trade Nation: Commerce, Consumption, and Civil Society in Modern Britain (Oxford: Oxford University Press, 2008), 91–98, 243.
3. Cunningham, Rise and Decline , 37, 85.
4. Cunningham, Rise and Decline , 97.
5. Cunningham, Rise and Decline , 119, 121–123, 158, 160.
6. Cunningham, Rise and Decline , 191–194, 197–198.
7. Cunningham, Rise and Decline , 200, 210.
8. John Maynard Keynes, Laissez-Faire and Communism (New York: New Republic, 1926), 65.
9. Keynes, Laissez-Faire , 31, 164.
10. Joan Robinson, The Economics of Imperfect Competition , 2nd ed. (London: Palgrave Macmillan, 1969), 211–228.
11. Joan Robinson, The Accumulation of Capital (New York: Palgrave Macmillan, 2013), 248, 330.
12. Carl Menger, Principles of Economics , trans. James Dingwall and Bert F. Hoselitz (Auburn, AL: Ludwig von Mises Institute, 2007), 51, 72–73; Janek Wasserman, The Marginal Revolutionaries: How Austrian Economists Fought the War of Ideas (New Haven, CT: Yale University Press, 2019), 33; Wasserman, Marginal Revolutionaries, 73.
13. Ludwig von Mises, Economic Calculation in the Socialist Commonwealth , trans. S. Alder (Auburn, AL: Ludwig von Mises Institute, 1990), 1–10.
16. Stephan A. Marglin and Juliet B. Schor, eds. , The Golden Age of Capitalism: Reinterpreting the Postwar Experience , 2nd ed. (Oxford: Oxford University Press, 2007), 41.
17. Henry Ashby Turner Jr. , “Big Business and the Rise of Hitler,” American Historical Review 75, no. 1 (1969): 56–70.
18. Friedrich Hayek, The Road to Serfdom , ed. Bruce Caldwell (Chicago: University of Chicago Press, 2007), 35, 76, 89, 100, 110.
19. Elisabetta Galeotti, “Individualism, Social Rules, Tradition: The Case of Friedrich A. Hayek,” Political Theory 15, no. 2 (1987): 163–181, at 169.
20. David Levy, “Interview with Milton Friedman,” Federal Re serve Bank of Minneapolis, June 1, 1992, www.minneapolisfed.org/article/1992/interview-with-milton-friedman .
21. Milton Friedman, “Market Mechanisms and Central Economic Planning,” in Milton Friedman, Sidney Hook, Rose Friedman, and Roger Freeman, Market Mechanisms and Central Economic Planning (Washington, DC: American Enterprise Institute, 1981), 1–19, at 9.
22. Milton Friedman, Free to Choose: A Personal Statement , 3rd ed. (New York: Harcourt, 1990), 94–97, 129.
23. Milton Friedman, “Quantity of Money Theory: A Restatement,” in Milton Friedman, ed. , Studies in the Quantity Theory of Money (Chicago: University of Chicago Press, 1956), 3–21, at 12.
24. Milton Friedman and Anna Jacobson Schwartz, A Monetary History of the United States, 1867–1960 (Princeton, NJ: Princeton University Press, 1963), 7, 11.
25. Milton Friedman, “The Demand for Money: Some Theoretical and Empirical Results,” National Bureau of Economic Research, Occasional Paper 68, 1959, www.nber.org/system/files/chapters/c5857/c5857.pdf , 1–25, at 2.
26. Milton Friedman, Capitalism and Freedom , 3rd ed. (Chicago: University of Chicago Press, 2002), 137.
27. Milton Friedman, An Economist’s Protest: Columns in Political Economy (Sun Lakes, AZ: Thomas Horon and Daughter, 1972), 6; Milton Friedman, “Say ‘No’ to Intolerance,” Liberty Magazine 4, no. 6 (1991): 17–20.
28. Kim Phillips-Fein, Invisible Hands: The Businessmen’s Crusade Against the New Deal (New York: Norton, 2009), 3.
29. Phillips-Fein, Invisible Hands, 4, 61 (du Pont quotation p. 4); Kevin M. Kruse, One Nation Under God: How Corporate America Invented Christian America (New York: Basic Books, 2015), 25.
30. Kruse, One Nation Under God , 61.
31. Kruse, One Nation Under God , 35; Phillips-Fein, Invisible Hands , 69, 77; Barry Goldwater, The Conscience of a Conservative (Shepherdsville, KY: Victor Publishing, 1960), 53.
32. Phillips-Fein, Invisible Hands , 228.
33. Jennifer Burns, “Godless Capitalism: Ayn Rand and the Conser vative Movement,” Modern Intellectual History 1, no. 3 (2004): 359–385; Brian Doherty, Radicals for Capitalism: A Freewheeling History of the Modern Libertarian Movement (New York: Public Affairs, 2008), 11.
34. Doug Bandow, “The West Fails to Social Engineer South Sudan,” American Conservative , September 19, 2019, www.cato.org/commentary/west-fails-social-engineer-south-sudan .
35. Richard H. K. Vietor, How Countries Compete: Strategy, Structure, and Government in the Global Economy (Boston: Harvard Business School Press, 2007), 18.
1. Isabella M. Weber, “The (Im-)Possibility of Rational Socialism: Mises in China’s Market Reform Debate,” 2021, University of Massachusetts, Amherst, Economics Department Working Paper Series, no. 2021-19, available at ScholarWorks@UMassAmherst, https://scholarworks.umass.edu/econ_workingpaper/316 ; Isabella M. Weber, How China Escaped Shock Therapy: The Market Reform Debate (Abingdon, Oxon, UK: Routledge, 2021); Steven Mark Cohn, Competing Economic Paradigms in China: The Co-Evolution of Economic Events, Economic Theory and Economics Education, 1976–2016 (Abingdon, Oxon, UK: Routledge, 2016), 26; Milton Friedman, Friedman in China (Hong Kong: Chinese University Press, 1990), 74; Milton Friedman, Capitalism and Freedom , 3rd ed. (Chicago: University of Chicago Press, 2002), 3–4; Milton Friedman, Free to Choose: A Personal Statement , 3rd ed. (New York: Harcourt, 1990), 57.
2. Cited in Weber, “The (Im-)Possibility of Rational Socialism. ”
3. Isabella Weber, “Origins of China’s Contested Relation with Neoliberalism: Economics, the World Bank, and Milton Friedman at the Dawn of Reform,” Global Perspectives 1, no 1 (2020): 1–14, at 7; Milton Friedman, “Market Mechanisms and Central Economic Planning,” in Milton Friedman, Sidney Hook, Rose Friedman, and Roger Freeman, Market Mechanisms and Central Economic Planning (Washington, DC: American Enterprise Institute, 1981), 3; Weber, “The (Im-)Possibility of Rational Socialism. ”
4. Keith Bradsher and Li Yuan, “China’s Economy Became No. 2 by Defying No. 1,” New York Times , November 25, 2018.
5. Justin Yifu Lin, Economic Development and Transition: Thought, Strategy, and Viability (Cambridge: Cambridge University Press, 2009); Barry Naughton, The Chinese Economy, Adaptation and Growth (Cambridge, MA: MIT Press, 2018); Pankaj Mishra, “The Rise of China and the Fall of the ‘Free Trade’ Myth,” New York Times , February 7, 2018; Keith Bradsher and Li Yuan, “The Chinese Thought They Had Little to Learn from Conventional Wisdom. Now It’s the West That’s Taking Notes,” New York Times , November 25, 2018.
6. Jason Brennan, Against Democracy (Princeton, NJ: Princeton University Press, 2016), 192–193.
7. Karl Polanyi, The Great Transformation: The Political and Economic Origins of Our Time (Boston: Beacon Press, 1957).
8. Ellen Frankel Paul, “W. Stanley Jevons: Economic Revolutionary, Political Utilitarian,” Journal of the History of Ideas 40, no. 2 (1979): 263–283, at 279.
这是紧接着的一个诗句。石头是痛苦的山脉[此处“山脉”原文为 das Ge-birge。海德格尔在此似要强调它与下文的“庇藏、庇护”（bergen）的字面和意义联系。-译注]。岩石把镇静力量聚集起来，庇藏在石块中；作为镇静之力，痛苦静默出入于其本质要素中。“在蓝光面前”，痛苦沉默了。面对蓝光，野兽的相貌收敛起来了，变得温柔了。因为按照字面来讲，温柔乃是安静地聚敛着的东西。温柔克服了暴虐和酷烈的野蛮，使之进入平静了的痛苦之中，从而改变了不和。
但同时，这灵魂也离去。去往何处？去那个异乡人所去的地方。有进修，诗人仅仅用一个指示代词把这个异乡人称为“那人”(Jener）。“那人”在古语言中叫“ener”，意即“他人”。所谓“Enert dem Bach”就是小溪的另一边。“那人”，即异乡人，就是对于那些他人（即对于腐朽的种类）而言的他人。那人是被召唤离开那些他人的人。异乡人乃是是孤寂者。[此处“孤寂者”被写作 der Ab-geschiedene，按字面直译就是“离去者”，故可承接上文的解说]
