The Atlas of AI_ Power, Politics, and the Planetary Costs of Artificial Inte.pdf

1、Atlas of AIThis page intentionally left blank Atlas of AIPower,Politics,and the Planetary Costs of Artificial IntelligenceK AT E C R AW F O R DNew Haven and LondonCopyright 2021 by Kate Crawford.All rights reserved.This book may not be reproduced,in whole or in part,including illustrations,in any fo

2、rm(beyond that copying permitted by Sections 107 and 108 of the U.S.Copyright Law and except by reviewers for the public press),without written permission from the publishers.Yale University Press books may be purchased in quantity for educational,business,or promotional use.For information,please e

3、-mail sales.pressyale.edu(U.S.office)or salesyaleup.co.uk(U.K.office).Cover design and chapter opening illustrations by Vladan Joler.Set in Minion by Tseng Information Systems,Inc.Printed in the United States of America.Library of Congress Control Number:2020947842ISBN 978-0-300-20957-0(hardcover:al

4、k.paper)A catalogue record for this book is available from the British Library.This paper meets the requirements of ANSI/NISO Z39.48-1992(Permanence of Paper).10 9 8 7 6 5 4 3 2 1For Elliott and MargaretThis page intentionally left blank ContentsIntroduction1ONe.Earth23twO.Labor53three.Data89fOur.Cl

5、assification123fIve.Affect151SIx.State181CONCluSION.Power211COdA.Space229Acknowledgments239Notes245Bibliography269Index315IntroductionThe Smartest Horse in the WorldAt the end of the nineteenth century,Europe was captivated by a horse called Hans.“Clever Hans”was nothing less than a marvel:he could

6、solve math problems,tell time,identify days on a calendar,dif-ferentiate musical tones,and spell out words and sentences.People flocked to watch the German stallion tap out answers to complex problems with his hoof and consistently arrive at the right answer.“What is two plus three?”Hans would dili-

7、gently tap his hoof on the ground five times.“What day of the week is it?”The horse would then tap his hoof to indicate each letter on a purpose-built letter board and spell out the correct answer.Hans even mastered more complex questions,such as,“I have a number in mind.I subtract nine and have thr

8、ee as a remainder.What is the number?”By 1904,Clever Hans was an international celebrity,with the New York Times championing him as“Berlins Wonderful Horse;He Can Do Almost Every-thing but Talk.”1Hanss trainer,a retired math teacher named Wilhelm von Osten,had long been fascinated by animal intellig

9、ence.2 IntroductionVon Osten had tried and failed to teach kittens and bear cubs cardinal numbers,but it wasnt until he started working with his own horse that he had success.He first taught Hans to count by holding the animals leg,showing him a number,and then tapping on the hoof the correct number

10、 of times.Soon Hans responded by accurately tapping out simple sums.Next von Osten introduced a chalkboard with the alphabet spelled out,so Hans could tap a number for each letter on the board.After two years of training,von Osten was astounded by the animals strong grasp of advanced intellectual co

11、ncepts.So he took Hans on the road as proof that animals could reason.Hans became the viral sensation of the belle poque.But many people were skeptical,and the German board of education launched an investigative commission to test Von Ostens scientific claims.The Hans Commission was led by the psych

12、ologist and philosopher Carl Stumpf and his assis-tant Oskar Pfungst,and it included a circus manager,a retired schoolteacher,a zoologist,a veterinarian,and a cavalry officer.Yet after extensive questioning of Hans,both with his trainer present and without,the horse maintained his record of cor-rect

13、 answers,and the commission could find no evidence of deception.As Pfungst later wrote,Hans performed in front of“thousands of spectators,horse-fanciers,trick-trainers of first rank,and not one of them during the course of many months observations are able to discover any kind of regular signal”betw

14、een the questioner and the horse.2The commission found that the methods Hans had been taught were more like“teaching children in elementary schools”than animal training and were“worthy of scientific examination.”3 But Strumpf and Pfungst still had doubts.One finding in particular troubled them:when

15、the questioner did not know the answer or was standing far away,Hans rarely gave the correct answer.This led Pfungst and Strumpf to con-Introduction 3sider whether some sort of unintentional signal had been pro-viding Hans with the answers.As Pfungst would describe in his 1911 book,their intu-ition

16、was right:the questioners posture,breathing,and facial expression would subtly change around the moment Hans reached the right answer,prompting Hans to stop there.4 Pfungst later tested this hypothesis on human subjects and confirmed his result.What fascinated him most about this discovery was that

17、questioners were generally unaware that they were providing pointers to the horse.The solution to the Clever Hans riddle,Pfungst wrote,was the unconscious di-rection from the horses questioners.5 The horse was trained to produce the results his owner wanted to see,but audiences felt that this was no

18、t the extraordinary intelligence they had imagined.The story of Clever Hans is compelling from many angles:the relationship between desire,illusion,and action,the busi-ness of spectacles,how we anthropomorphize the nonhuman,Wilhelm von Osten and Clever Hans4 Introductionhow biases emerge,and the pol

19、itics of intelligence.Hans in-spired a term in psychology for a particular type of conceptual trap,the Clever Hans Effect or observer-expectancy effect,to describe the influence of experimenters unintentional cues on their subjects.The relationship between Hans and von Osten points to the complex me

20、chanisms by which biases find their ways into systems and how people become entangled with the phenomena they study.The story of Hans is now used in ma-chine learning as a cautionary reminder that you cant always be sure of what a model has learned from the data it has been given.6 Even a system tha

21、t appears to perform spectacularly in training can make terrible predictions when presented with novel data in the world.This opens a central question of this book:How is intel-ligence“made,”and what traps can that create?At first glance,the story of Clever Hans is a story of how one man constructed

22、 intelligence by training a horse to follow cues and emulate humanlike cognition.But at another level,we see that the prac-tice of making intelligence was considerably broader.The en-deavor required validation from multiple institutions,includ-ing academia,schools,science,the public,and the military

23、.Then there was the market for von Osten and his remarkable horseemotional and economic investments that drove the tours,the newspaper stories,and the lectures.Bureaucratic au-thorities were assembled to measure and test the horses abili-ties.A constellation of financial,cultural,and scientific inte

24、r-ests had a part to play in the construction of Hanss intelligence and a stake in whether it was truly remarkable.We can see two distinct mythologies at work.The first myth is that nonhuman systems(be it computers or horses)are analogues for human minds.This perspective assumes that with sufficient

25、 training,or enough resources,humanlike intel-ligence can be created from scratch,without addressing the Introduction 5fundamental ways in which humans are embodied,relational,and set within wider ecologies.The second myth is that intelli-gence is something that exists independently,as though it wer

26、e natural and distinct from social,cultural,historical,and politi-cal forces.In fact,the concept of intelligence has done inordi-nate harm over centuries and has been used to justify relations of domination from slavery to eugenics.7These mythologies are particularly strong in the field of artificia

27、l intelligence,where the belief that human intelligence can be formalized and reproduced by machines has been axi-omatic since the mid-twentieth century.Just as Hanss intel-ligence was considered to be like that of a human,fostered carefully like a child in elementary school,so AI systems have repea

28、tedly been described as simple but humanlike forms of intelligence.In 1950,Alan Turing predicted that“at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.”8 The math

29、e-matician John von Neumann claimed in 1958 that the human nervous system is“prima facie digital.”9 MIT professor Marvin Minsky once responded to the question of whether machines could think by saying,“Of course machines can think;we can think and we are meat machines.”10 But not everyone was convin

30、ced.Joseph Weizenbaum,early AI inventor and creator of the first chatbot program,known as elIZA,believed that the idea of humans as mere information processing systems is far too simplistic a notion of intelligence and that it drove the“perverse grand fantasy”that AI scientists could create a ma-chi

31、ne that learns“as a child does.”11This has been one of the core disputes in the history of artificial intelligence.In 1961,MIT hosted a landmark lecture series titled“Management and the Computer of the Future.”A stellar lineup of computer scientists participated,including 6 IntroductionGrace Hopper,

32、J.C.R.Licklider,Marvin Minsky,Allen Newell,Herbert Simon,and Norbert Wiener,to discuss the rapid ad-vances being made in digital computing.At its conclusion,John McCarthy boldly argued that the differences between human and machine tasks were illusory.There were simply some complicated human tasks t

33、hat would take more time to be formalized and solved by machines.12But philosophy professor Hubert Dreyfus argued back,concerned that the assembled engineers“do not even consider the possibility that the brain might process information in an entirely different way than a computer.”13 In his later work What Computers Cant Do,Dreyfus pointed out that human intelligence and expertise rely heavily on