by Amy Webb
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; G-MAFIA 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 theor
y, 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
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