The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity

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The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity

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A call-to-arms about the broken nature of artificial intelligence, and the powerful corporations that are turning the human-machine relationship on its head. We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we -- the everyday people whose data powers AI -- aren''t actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can''t see and have no input into -- one largely free from regulation or oversight. The big nine corporations -- Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain. In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI -- the people working on the system, their motivations, the technology itself -- is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don''t share our motivations, desires, or hopes for the future of humanity. Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations.

Copyright Copyright © 2019 by Amy Webb Cover design by Pete Garceau Cover copyright © 2019 Hachette Book Group, Inc Hachette Book Group supports the right to free expression and the value of copyright The purpose of copyright is to encourage writers and artists to produce the creative works that enrich our culture The scanning, uploading, and distribution of this book without permission is a theft of the author’s intellectual property If you would like permission to use material from the book (other than for review purposes), please contact permissions@hbgusa.com Thank you for your support of the author’s rights PublicAffairs Hachette Book Group 1290 Avenue of the Americas, New York, NY 10104 www.publicaffairsbooks.com @Public_Affairs First Edition: March 2019 Published by PublicAffairs, an imprint of Perseus Books, LLC, a subsidiary of Hachette Book Group, Inc The PublicAffairs name and logo is a trademark of the Hachette Book Group The Hachette Speakers Bureau provides a wide range of authors for speaking events To find out more, go to www.hachettespeakersbureau.com or call (866) 376-6591 The publisher is not responsible for websites (or their content) that are not owned by the publisher Library of Congress Cataloging-in-Publication Data Names: Webb, Amy, 1974- author Title: The Big Nine : how the tech titans and their thinking machines could warp humanity / Amy Webb Description: New York : PublicAffairs, [2019] | Includes bibliographical references and index Identifiers: LCCN 2018048107| ISBN 9781541773752 (hardcover) | ISBN 9781541773745 (ebook) Subjects: LCSH: Artificial intelligence—Social aspects | Artificial intelligence —Economic aspects | Internet industry—Social aspects | Social responsibility of business Classification: LCC Q334.7 W43 2019 | DDC 006.301—dc23 LC record available at https://lccn.loc.gov/2018048107 ISBNs: 978-1-5417-7375-2 (hardcover); 978-1-5417-7374-5 (ebook); 978-15417-2441-9 (international) E3-20190122-JV-NF-ORI CONTENTS Cover Title Page Copyright Dedication Introduction: Before It’s Too Late Part I: Ghosts in the Machine 1 Mind and Machine: A Very Brief History of AI 2 The Insular World of AI’s Tribes 3 A Thousand Paper Cuts: AI’s Unintended Consequences Part II: Our Futures 4 From Here to Artificial Superintelligence: The Warning Signs 5 Thriving in the Third Age of Computing: The Optimistic Scenario 6 Learning to Live with Millions of Paper Cuts: The Pragmatic Scenario 7 The Réngōng Zhìnéng Dynasty: The Catastrophic Scenario Part III: Solving the Problems 8 Pebbles and Boulders: How to Fix AI’s Future Acknowledgments Discover More Amy Webb About the Author Praise for The Big Nine Bibliography Notes Index To my father, Don Webb, the most authentically intelligent person I’ve ever known Discover More! Including giveaways, contests, and more Tap here to get started INTRODUCTION BEFORE IT’S TOO LATE Artificial intelligence is already here, but it didn’t show up as we all expected It is the quiet backbone of our financial systems, the power grid, and the retail supply chain It is the invisible infrastructure that directs us through traffic, finds the right meaning in our mistyped words, and determines what we should buy, watch, listen to, and read It is technology upon which our future is being built because it intersects with every aspect of our lives: health and medicine, housing, agriculture, transportation, sports, and even love, sex, and death AI isn’t a tech trend, a buzzword, or a temporary distraction—it is the third era of computing We are in the midst of significant transformation, not unlike the generation who lived through the Industrial Revolution At the beginning, no one recognized the transition they were in because the change happened gradually, relative to their lifespans By the end, the world looked different: Great Britain and the United States had become the world’s two dominant powers, with enough industrial, military, and political capital to shape the course of the next century Everyone is debating AI and what it will mean for our futures ad nauseam You’re already familiar with the usual arguments: the robots are coming to take our jobs, the robots will upend the economy, the robots will end up killing humans Substitute “machine” for “robot,” and we’re cycling back to the same debates people had 200 years ago It’s natural to think about the impact of new technology on our jobs and our ability to earn money, since we’ve seen disruption across so many industries It’s understandable that when thinking about AI, our minds inevitably wander to HAL 9000 from 2001: A Space Odyssey, WOPR from War Games, Skynet from The Terminator, Rosie from The Jetsons, Delores from Westworld, or any of the other hundreds of anthropomorphized AIs from popular culture If you’re not working directly inside of the AI ecosystem, the future seems either fantastical or frightening, and for all the wrong reasons Those who aren’t steeped in the day-to-day research and development of AI can’t see signals clearly, which is why public debate about AI references the robot overlords you’ve seen in recent movies Or it reflects a kind of manic, unbridled optimism The lack of nuance is one part of AI’s genesis problem: some dramatically overestimate the applicability of AI, while others argue it will become an unstoppable weapon I know this because I’ve spent much of the past decade researching AI and meeting with people and organizations both inside and outside of the AI ecosystem I’ve advised a wide variety of companies at the epicenter of artificial intelligence, which include Microsoft and IBM I’ve met with and advised stakeholders on the outside: venture capitalists and private equity managers, leaders within the Department of Defense and State Department, and various lawmakers who think regulation is the only way forward I’ve also had hundreds of meetings with academic researchers and technologists working directly in the trenches Rarely do those working directly in AI share the extreme apocalyptic or utopian visions of the future we tend to hear about in the news That’s because, like researchers in other areas of science, those actually building the future of AI want to temper expectations Achieving huge milestones takes patience, time, money, and resilience—this is something we repeatedly forget They are slogging away, working bit by bit on wildly complicated problems, sometimes making very little progress These people are smart, worldly, and, in my experience, compassionate and thoughtful Overwhelmingly, they work at nine tech giants—Google, Amazon, Apple, IBM, Microsoft, and Facebook in the United States and Baidu, Alibaba, and Tencent in China—that are building AI in order to usher in a better, brighter future for us all I firmly believe that the leaders of these nine companies are driven by a profound sense of altruism and a desire to serve the greater good: they clearly see the potential of AI to improve health care and longevity, to solve our impending climate issues, and to lift millions of people out of poverty We are already seeing the positive and tangible benefits of their work across all industries and everyday life The problem is that external forces pressuring the nine big tech giants—and Brain; Google Cloud; Google Green households; Google Home; Google households; Google mega-OS; Google Play; Google Voice; Google Yellow households Google AdSense, 114, 122 Google Blue households: in catastrophic scenario of future, 217, 219, 225 Google Brain, 49, 54, 61, 67, 116, 184 Google Cloud, 65 Google Green households: in catastrophic scenario of future, 217, 219, 224, 225 Google Home, 69, 90 Google households: in catastrophic scenario of future, 216–217, 218 Google mega-OS: in pragmatic scenario of future, 187, 188, 189, 190 Google Play, 202 Google Voice, 43 Google Yellow households: in catastrophic scenario of future, 217, 219, 225 Grocery shopping and delivery services: in optimistic scenario of future, 161– 162 Hackers and hacking: Chinese in catastrophic scenario of future, 215; in pragmatic scenario of future, 183; Russian during 2016 U.S Presidential campaign and election, 138 HAL 9000, 2, 35, 39 Hanjin Lee, 45 Harvard University, 60; Berkman Klein Center, 61 Hassabis, Demis, 43 Hayden, Franz Joseph, 16 Health and wellness minders: in catastrophic scenario of future, 219; in pragmatic scenario of future, 194 Health care systems: in catastrophic scenario of future, 224–226; in optimistic scenario of future, 163–164, 173–174; in pragmatic scenario of future, 182, 194, 195–196, 204; Tencent, 71, 76 See also Watson-Calico Health System; Watson Health Health data: open access in catastrophic scenario of future, 209 Healthy lifestyles: G-MAFIA nagging individuals toward in pragmatic scenario of future, 194; G-MAFIA nudging individuals toward in optimistic scenario of future, 162–163 Hinton, Geoff, 41, 42–43, 59, 116 Hispanic computer science PhDs, 64 History, AI: AI language-translation program, 36; ancient Greece, 17–18; British, 38; Chinese, 43; Dartmouth Workshop, 29–31, 32, 33, 34, 157, 158; early AI systems, 34; early automata, 18, 21–22; 18th century, 21–23; first artificial neural network, 32; first automatic calculator, 21; first automaton, 18; first electric computer, 27; first era of computing, 33; introduction of “neural network” concept, 26–27; introduction of programmable computer concept, 33; Japanese, 38; machines learning to play games, 38–50; 1980s, 38–39; 1950s, 29–35; 1940s, 26–28; 1970s, 41; 1960s, 35–37; 1930s, 24– 25; 19th-century computers, 23; relay-based robot, 25; second era of computing, 33; 17th-century philosophers and, 19–20; 21st century, 39, 42– 49 Hobbes, Thomas, 19, 27; De Corpore, 19 HoloLens, 92 Home AI systems/appliances: glitches in catastrophic scenario of future, 214– 215; in optimistic scenario of future, 161, 172–173; in pragmatic scenario of future, 203–204 Hotmail, 139 Human-animal chimeras: in pragmatic scenario of future, 204–205 Human intelligence, measurement of, 145–146 Human Values Atlas: need for adherence to, 239; need for creation of, 237–238 See also Values Hume, David, 22, 27; A Treatise of Human Nature, 22 I AM AI, 15 IBM, 2, 3, 29, 30, 85, 96, 143; AI chip development, 92; in catastrophic scenario of future, 209, 215, 223; chip technology, 139; consumer connections to, 88; Deep Blue, 39, 45; ethics and AI articles from, 129; Georgetown University and Russian-English machine translation system, 36; in optimistic scenario of future, 159, 163, 167, 173; in pragmatic scenario of future, 182, 186, 188, 194, 195, 201, 202, 203, 205; senior leadership, 56; Socratic AI, 167; Summit supercomputer and, 146 See also Watson; Watson Health ImageNet, 181, 252 India, China’s cybersecurity laws and practices and, 83 Infoseek, 67 Intel, 36; Apollo partnership, 68; Facebook partnership, 92 Intelligence explosion, 148–149; in optimistic scenario of future, 177 Intelligence quotient (IQ), 145–146, 147 Internet, 137 iOS mobile operating system, 139, 188, 191 Japan: Fifth Generation AI plan, 38; Fukushima disaster, 136; indirect communication in, 124, 125 Jennings, Ken, 39; versus Watson, 39 Jetsons, The: Rosie, 2 Jiang Zemin, 80 Job displacement and unemployment: in catastrophic scenario of future, 220, 226; in optimistic scenario of future, 172; in pragmatic scenario of future, 197 Job search and AI: in pragmatic scenario of future, 196–197 Jobs, blue-collar glut of: in catastrophic scenario of future, 221 Joint Artificial Intelligence Center, Pentagon creation of, 243 Journalism: in optimistic scenario of future, 167–168, 175; in pragmatic scenario of future, 198 See also Fake news, proliferation of in pragmatic scenario of future Kahn, Herman, 141 Kahneman, Daniel, 108, 109 Kasparov, Garry, 39; versus Deep Blue, 39 Kratsios, Michael, 86 Kubrick, Stanley, 35 See also 2001: A Space Odyssey La Mettrie, Julien Offray de, 22 Law enforcement: in optimistic scenario of future, 176; in pragmatic scenario of future, 199; social policing in China, 80 Leadership, need for courageous, 246 Learned helplessness: in pragmatic scenario of future, 190–201 Learning See AlphaGo; AlphaGo Zero; Learning machines; Machine learning; Watson Learning machines, 30, 31–32 See also AlphaGo; AlphaGo Zero; Watson Lecun, Yann, 41, 42, 59 Lee, Peter, 122 Legg, Shane, 43 Leibniz, Gottfried Wilhelm von, 20, 21, 27; step reckoner, 21, 24 Levesque, Hector, 50 Li, Fei-Fei, 65 Li, Robin, 67, 82, 129 Li Deng, 43 LibriSpeech, 181 Life expectancy: in catastrophic scenario of future, 225 Lighthill, James, 37, 38 Liu Guozhi, 79 Logic Theorist program, 30, 34 Lovelace, Ada, 23, 259; Analytical Engine, 23, 24; Difference Engine, 23 Lyft, BAT investment in, 72 Ma, Jack, 68, 69, 70 Ma Huateng, 70 Machine learning, 29, 31, 32–33, 36, 41, 77, 93, 114; algorithms, 123, 183, 237; machines playing games, 38–50; models, 49, 91; platforms, 91; systems, 182, 184, 257; techniques, 253; technologies, 110 See also Deep learning; TensorFlow Magic Leap: BAT investment in, 72; in optimistic future scenario, 165 Manning, Toby, 44 Mao Zedong, 6, 73, 80, 82, 223 McCarthy, John, 29–30, 31, 37–38, 259 See also Dartmouth Workshop McCulloch, Warren, 26; neural network theory, 26–27 McGill University, 60 Medicine, personalized: in catastrophic scenario of future, 224 Medopad, Tencent partnership with, 71 Megvii, 5 Microelectronics and Computer Technology Corporation, 38 Microsoft, 2, 3, 85, 96; AI apps in Azure Cloud, 119; AI chip development, 92; in catastrophic scenario of future, 209, 215, 223; classified data certificate, 101; computer vision, 119; consumer connections to, 88; Cortana, 119; Edge computing, 90, 119; FATE team, 129; GitHub acquisition, 92; machine reading comprehension, 119; mixed reality headset, 92; natural language processing, 119; in optimistic scenario of future, 159, 165, 171; in pragmatic scenario of future, 186, 188, 201; senior leadership, 56; Tencent experimental project with, 119; Xiaoice/Tay.ai debacle, 118–122 Minsky, Gloria, 30 Minsky, Marvin, 29, 30, 31, 41, 259; predictions about intelligent machine, 34– 35 See also Dartmouth Workshop MIT, 34, 60, 67; Computer Science and Artificial Intelligence Laboratory (CSAIL), 65, 111; Media Lab, 61 Mixed-reality products and services: G-MAFIA partnerships in optimistic scenario of future, 160–161, 165 Mobile operating systems, 139, 188, 191 Montreal, Canada: desired location of GAIA, 235–236 Moore, Gordon, 36; “Cramming More Components onto Integrated Circuits,” 36 Moore’s law, 36, 38, 147 Morgenstern, Oskar, 27; game theory and, 27 Mouton, Jean, 16 Mozart, Wolfgang Amadeus, 16 Music: composed by AI system, 15–16; in optimistic scenario of future, 174– 175 See also names of specific composers; Amper Musk, Elon, 193 Nadella, Satya, 120, 122 Nagging, healthy-lifestyle: in pragmatic scenario of future, 194 Nanny AGIs (NAGIs): in pragmatic scenario of future, 202–203, 205 Nanobots, catastrophic scenario of future and: abortions induced by, 225; deaths induced by, 225–226; health monitoring and treatment, 224–226 NASNet, 49, 149 National Academy of Sciences: advisory committee on AI, 37 National service program, AI, 249 Natural language simulation, 30, 34 Nemesis, 41 Neural networks, 30; introduction of concept, 26–27; McCulloch and Pitts’ theory, 26–27; as part of AI ecosystem, 17; Turing concept of, 27–29; workshopping, 41 See also Artificial neural networks (ANNs); Deep neural networks (DNNs) New York University, 65 Newell, Allen, 30, 34; Logic Theorist program, 30, 34 See also Dartmouth Workshop Next Generation Artificial Intelligence Development Plan, 4–5 Ng, Andrew, 67, 68 Nicolelis, Miguel, 204 Nowist thinking, 4 Nudging: 122–123; by Big Nine, 123; healthy-lifestyle, 162–163 Obama administration, 2016 AI plan of, 179 Ockeghem, Johannes, 16 Odd paradox, 13 Office of Net Assessment, 247 Office of Technology Assessment (OTA), reinstatement of, 246–247; renaming, 247 OICQ, 70 OmniVision smart glasses: in catastrophic scenario of future, 221 Open source, 92 Ops, 146 Optimization effect, 113, 114–122, AI system glitches and, 117–122 Organization Data Records: in catastrophic scenario of future, 226 Outlook, 215 Page, Larry, 99 See also Alphabet; Google Palantir, 87 Parrot attacks: in pragmatic scenario of future, 193 Pascal, Blaise, 20–21 Patagonia, 210 Peking University, China Credit Research Center at, 80 Peloton, 87 People’s Liberation Army, 78 People’s Republic of China (PRC), Centennial of, 223 Perception system, 32 Personal data records (PDRs), catastrophic scenario of future and, 208–209, 218, 226; as social credit score, 209; corporate ownership of, 209 Personal data records (PDRs), optimistic scenario of future and, 152–153; China and, 152, 154; as heritable, 153; individual ownership of, 159; privacy and, 168; treated as distributed ledgers, 159 Personal data records (PDRs), pragmatic scenario of future and: G-MAFIA ownership, 187; linked to insurance premium, 194; third-party use, 189 Personally identifiable information (PII), 237; need for citizen-owned, 237 Pets, robotic: in optimistic scenario of future, 162 Pharmacists and pharmacies: computational in optimistic scenario of future, 173 Pichai, Sundar, 64–65, 101 Pitts, Walter, 26; neural network theory, 26–27 Plato, 17 Police Cloud, 6, 82 Portal, 54 Pratt, Gill, 149 Privacy: Chinese view of, 79–82; Cook, Tim, on future of, 95; G-MAFIA commitment to in optimistic scenario of future, 168; PDRs and in optimistic scenario of future, 168 Processors: as part of AI ecosystem, 17 Project Maven, 78–79; Google employee resignations and, 79, 101 Purcell, Henry, 16 Python programming language, 60 R programming language, 60 Recursive self-improvement, 149 Regulations, government: eliminating most for G-MAFIA AI development, 250 Reinforcement learning, 49 Réngōng Zhinéng (Artificial Intelligence) Dynasty: in catastrophic scenario of future, 223, 229, 233 Reward hacking, pragmatic scenario of future and, 183 Robots, physical: Electro the Moto-Man, 25; in film and TV, 2; harassment by in pragmatic scenario of future, 199; physical danger from, 58 See also Automata; Automaton, first; Pets, robotic Rochester, Nathaniel, 29 See also Dartmouth Workshop Rongcheng, China, 81, 168 Rosenblatt, Frank, 32, 34, 41; Perception system, 32–33 See also Dartmouth Workshop Royal Dutch Shell company, 141–142 Rubin, Andy, 55 Rus, Daniela, 65 Russell, Bertrand: Principia Mathematica, 30–31 Ryder, Jon, 41 Safety issues, AI: robots, 58; self-driving cars, 58 See also Accidents and mistakes, AI Safety standards, AI: establishment of global, 251 Salieri, Antonio, 16 Scenario planning, 141; Royal Dutch Shell company use of, 141–142 See also Scenarios Scenarios, 141; as cognitive bias behavioral economics coping tool, 142; preferred outcomes and, 141; probability neglect and, 142; purpose of, 143 See also Future and AI, catastrophic scenario of; Future and AI, optimistic scenario of; Future and AI, pragmatic scenario of Schmidt, Eric, 211–212 Self-driving taxi services, catastrophic scenario of future and: Amazon riders, 218–219; Google riders, 219 SenseTime, 5 Sentinel AIs, need for, 241 Shannon, Claude, 24, 25, 29, 31; “A Symbolic Analysis of Switching Relay Circuits,” 24 See also Dartmouth Workshop SharePoint, 215 Shaw, Cliff, 30 See also Dartmouth Workshop Shopping, brick-and-mortar store: in optimistic scenario of future, 162 Simon, Herbert, 30, 34; Logic Theorist program, 30, 34 See also Dartmouth Workshop Siri, 13, 43, 119 Skype, 215 Smart city pilot programs: in optimistic scenario of future, 168, 176 Smart glasses: Apple, 161; Applezon, 191; in catastrophic scenario of future, 221; Google, 191; in pragmatic scenario of future, 191, 192 Smartphones: Apple, 94; in pragmatic scenario of future, 191 Social Credit Score system, 6, 80, 82, 152, 154, 209; in Rongcheng, 81; tradeoffs for desirable, 211 Socrates, 17 Sorenson, Arne, 75 South China Morning Post, 69–70 Southern, Taryn, 15 SpaceX, 87 Splinternets, 83; pragmatic scenario of future and, 198 Spy birds, 77–78 Stanford, 60, 63; Artificial Intelligence Lab, 65 Stasis: among U.S policymakers and think tanks, 213; cigarette smoking danger and, 213; climate change and, 213 Step reckoner, 21, 24 Subscription model, smart wearables and tools: in pragmatic scenario of future, 192–193 Suleyman, Mustafa, 43, 117 Summit supercomputer, 146 Sunstein, Cass, 142 Supercomputers, 146 Surveillance capitalism, 95 Sweeney, Latanya, 113–114, 122 Syllogistic logic, Aristotle and, 18 Synthetic data, 182 Tanzania, 83, 200, 210 Taobao, 68–69 Technology, deployment of: need for technical simulations and risk mapping before, 241–242 Tencent, 3, 5, 9, 49, 65, 67, 70–71, 96, 158; cloud service, 71; conversational interfaces, 76; corporate slogan, 70; digital assistant, 71; facial and object recognition lab, 71; healthcare partnerships, 71, 76; management philosophy, 100; market value, 71; mobile payment system, 71, 186; movie studio, 71; original product, 70; pharmaceutical company investments, 71 Tencent Pictures, 71 Tenpay, 71, 186 Tensor Processing Units (TPUs), 91 TensorFlow, 91, 92, 139 TensorFlow Object Detection API, 91 TensorFlow-GAN, 91 Terminator, The: Skynet, 2 Tesla, BAT investment in, 72 Thinking machines, 23, 24, 25, 35, 36, 50–51, 60, 98, 106, 127, 135, 138, 149, 150, 154; ceding control to, 131; computers as, 22; first, 145; generally intelligent, 159, 189 Thousand Talents Plan, 84–85 Tiān Māo, 13 Tianhe-1 supercomputer, 146 Tinsley, Marlon, 39; versus CHINOOK, 39 Transparency: among G-MAFIA in catastrophic scenario of future, 208; GMAFIA Coalition adoption of as core value in optimistic scenario of future, 157; in pragmatic scenario of future, 188 See also Transparency standards Transparency standards: establishment of for Big Nine, 251; establishment of global, 252 Tribes, AI: anti-humanistic bias in, 57; characteristics, 56; groupthink, 53; homogeneity, 52; lack of diversity, 56; leaders, 53–65; need to address diversity within, 57–58; sexual assault and harassment by members, 55–56; unconscious bias training programs and, 56; unconscious biases of members, 52; university education and homogeneity of members, 58–61, 64 Trudeau, Justin, 236 TrueNorth neuromorphic chip, 92 Trump, Donald: administration, 70, 75, 85; campaign climate change comments, 75; science and technology research budget cuts, 243 Turing, Alan, 24–25, 26, 27–29, 30, 31, 35, 259; morphogenesis theory, 204; neural network concept, 27–29;“On Computable Numbers, With an Application to the Entscheidungsproblem,” 24 See also Turing Test Turing test, 27–28, 50, 146, 169, 184 Turriano, Juanelo: mechanical monk creation of, 18, 25 Tversky, Amos, 108 2000 HUB5 English, 181 2001: A Space Odyssey, 2, 35: HAL 9000, 2, 35, 39 U.S Army: ENIAC, 27; Futures Command, 212 U.S Department of Energy, Summit supercomputer and, 146 U.S Digital Service, 212 U.S Government: AI working knowledge necessary for leaders/managers/policymakers, 242; competition with G-MAFIA for computer scientists and, 248–249; defunding of AI R&D program, 179; deprioritizing AI/advanced science research, 179; ignoring G-MAFIA, 86; installing AI experts in, 242; internal capacity for AI research/testing/deployment, 242; necessary changes by, 242–250; need for reasonable AI budget, 244; reliance on G-MAFIA, 86; transactional relationship with G-MAFIA in catastrophic scenario of future, 212; view of G-MAFIA as strategic partners, 249–250 See also names of specific departments and services of the U.S government Uber, 87; BAT investment in, 72 Uighurs, 6 Ultraintelligence machine, 33 Unemployment See Job displacement and unemployment; Job search and AI Université de Montréal, 60 Universities: as AI hubs, 60; China’s brain drain from North American, 84; ethics courses, 61, 63; homogeneity of AI tribe members and, 58–61, 64; offering hybrid degrees, 256; inclusive recruiting by, 257; integration of ethics into courses, 256; women professors, 65 See also names of specific universities University of California, Berkeley, 60, 67 University of Washington, 60 Values: Big Nine shared, 100; cataloging basic, 237; decision-making and personal, 108–113; defining basic, 237; economic, 100, 102; gap, 102; humanity’s shared, 122–126; social, 100–101, 102; technological, 100, 102 See also Values algorithms, Big Nine Values algorithms, Big Nine, 99–103; Alibaba, 100; Amazon, 99; Facebook, 100; Google, 99, 101–102; missing, 100; Tencent, 100 Vietnam, adoption of China’s cybersecurity laws by, 83 Vivaldi, Antonio, 16 von Neumann, John, 27, 30, 89; game theory and, 27 von Neumann bottleneck, 89–90 Voting, consideration of AI and future when, 258 War Games: WOPR, 2 Warner, Mark: 2018 policy paper for tech giants, 94 Washington Post, 70 Watson, 39, 167, 215; versus Ken Jennings, 39, 259 Watson-Calico Health System: pragmatic scenario of future and, 195, 196, 204 Watson Health, 181–182, 194 WaveNet, 48; DeepMind and, 117 WeChat, 70, 81, 119; number of users, 70, 71 Weibo, 6, 119 Weiyun, 71 Weizenbaum, Joseph: ELIZA program, 34 Westinghouse, Electro the Moto-Man creation of, 25 Westworld: Delores, 2 Whitehead, Alfred North: Principia Mathematica, 30–31 WikiText, 181 Winograd schema, 50 Women: AI researchers, 64; computer science PhDs, 64; as university professors, 65 Word2vec, 61 Workforce preparation, computing’s third era and: optimistic scenario of, 157 Workplace bias, evaluation of by citizen/consumer, 258 See also Big Nine World Wide Web, decentralization of, 137 World’s Fair, 1939, 25 Wu, John, 67 Xi Jinping, 5, 6, 7, 73–74, 75, 76, 82–83, 86, 150, 210, 212–213, 245; in catastrophic scenario of future, 223; long-term strategic AI plan, 93; in pragmatic scenario of future, 185–186, 189; public release of CCP’s AI plans, 243; 13th five-year plan and, 73 Xiaoice/Tay.ai, 118, 119–122 See also Microsoft Xiaowei, 71 XtalPi, Tencent investment in, 71 Xu, Eric, 67 Yahoo, 67; email, 139 YouTu Lab, 71 Zhang Zhidong, 70 Zhima Credit service, 81–82 Zuckerberg, Mark, 56; post-Cambridge Analytica debacle apology, 54, 94 PublicAffairs is a publishing house founded in 1997 It is a tribute to the standards, values, and flair of three persons who have served as mentors to countless reporters, writers, editors, and book people of all kinds, including me I.F STONE, proprietor of I F Stone’s Weekly, combined a commitment to the First Amendment with entrepreneurial zeal and reporting skill and became one of the great independent journalists in American history At the age of eighty, Izzy published The Trial of Socrates, which was a national bestseller He wrote the book after he taught himself ancient Greek BENJAMIN C BRADLEE was for nearly thirty years the charismatic editorial leader of The Washington Post It was Ben who gave the Post the range and courage to pursue such historic issues as Watergate He supported his reporters with a tenacity that made them fearless and it is no accident that so many became authors of influential, best-selling books ROBERT L BERNSTEIN, the chief executive of Random House for more than a quarter century, guided one of the nation’s premier publishing houses Bob was personally responsible for many books of political dissent and argument that challenged tyranny around the globe He is also the founder and longtime chair of Human Rights Watch, one of the most respected human rights organizations in the world For fifty years, the banner of Public Affairs Press was carried by its owner Morris B Schnapper, who published Gandhi, Nasser, Toynbee, Truman, and about 1,500 other authors In 1983, Schnapper was described by The Washington Post as “a redoubtable gadfly.” His legacy will endure in the books to come Peter Osnos, Founder ... Their quest? ?and ours, in this chapter—is to understand the connection between thinking and containers for thought What is the connection between the human mind and? ??or in spite of—machines being built by the Big Nine in China and the United States?... America, Western Europe, and China, and are tied, in some way, to the Big Nine The soul of AI is a manifestation of their vision and intent for the future And finally, yes, thinking machines are... Title: The Big Nine : how the tech titans and their thinking machines could warp humanity / Amy Webb Description: New York : PublicAffairs, [2019] | Includes bibliographical references and index

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    Introduction: Before It’s Too Late

    Part I: Ghosts in the Machine

    1 Mind and Machine: A Very Brief History of AI

    2 The Insular World of AI’s Tribes

    3 A Thousand Paper Cuts: AI’s Unintended Consequences

    Part II: Our Futures

    4 From Here to Artificial Superintelligence: The Warning Signs

    5 Thriving in the Third Age of Computing: The Optimistic Scenario

    6 Learning to Live with Millions of Paper Cuts: The Pragmatic Scenario

    7 The Réngōng Zhìnéng Dynasty: The Catastrophic Scenario

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