Index
- Page numbers followed by f refer to figures.
- Academic institutions:
- Action to advance AI:
- Adidas, 60
- Adoptive coalitions, 220
- Afghanistan war, 53
- AI, see Artificial intelligence
- AIAI (American Institute of Artificial Intelligence), ix, 223
- AI caucuses:
- AICT (Artificial Intelligence Capabilities and Transparency) Act, 170–171
- AI.gov, 86
- AI-IA (Artificial Intelligence Initiative Act), 167–169, 171
- AI industrialization, 139
- AI leadership:
- by America, claim of, 76–77
- in American private sector and universities, 135–136
- America's loss of, ix–x, 9–11, 227
- Biden on, 83, 85
- by China, 8, 16
- Cruz on, 147
- drivers of, 64, 136–138, 226
- executive leadership for, 73–75
- inspirational, need for, 141
- lack of, 87–88
- national plan for (see National AI strategy (US))
- NSCI statement on maintaining, 137
- and supply-side thinking, 125, 127
- AI War, 62–64, 228. See also Losing the AI battle
- Albert, Tom, 2–3
- Algorithms, in AI supply chain, 196–197, 196f
- Allies and alliances:
- AlphaGo, 43–44
- America, see United States of America
- “America first” paradigm, 5, 207, 224
- American AI Initiative, see American Artificial Intelligence Initiative
- American AI plan. See also Containment strategy
- deficiencies of, 48 (See also Losing the AI battle)
- strategies of, 20–22, 120
- American Artificial Intelligence (AI) Initiative, 75–80
- American Institute of Artificial Intelligence (AIAI), ix, 223
- American institutions:
- academic (see Academic institutions)
- attacks on, 28–30
- belief in integrity of, 47
- Anchoring bias, 171, 221
- Armed Forces Digital Advantage Act, 167
- Artificial intelligence (AI). See also specific topics
- Chaillan's vision for, 2
- China's deployment of, 213
- China's power in, 40
- in cognitive warfare, 28
- complexity and extent of, 74
- as critical capability, 63
- disruptive rise of, 14–16
- factors in development of, 194
- in identifying and solving problems, 7–8
- IT development vs. development of, 40–42, 195
- IT's differences from, 62–63
- leadership in (see AI leadership)
- link between supply chains and, 32, 212–214
- major American “clubs” of, 142–143
- Musk on, 151
- as paradigm change vs. as technology, 5
- problems and solutions related to, 225–226, 226f
- problems in deployment of, 7
- in rethinking and new types of work, 176–177
- social perception of, 16–18, 82–83, 202–203, 227
- as a supply chain (see AI supply chain)
- technology development model for, x
- theory underlying concerns about, 220–222
- as transformative force, 82, 154–155, 226, 226f
- US government's approach to, 2, 34 (See also National AI strategy (US))
- viewed as a national asset, 205–206
- Artificial Intelligence Capabilities and Transparency (AICT) Act, 170–171
- Artificial Intelligence Initiative Act (AI-IA), 167–169, 171
- Ashford, Emma, 36–37
- Associations, RFI responses from, 98, 99f, 107–110, 115, 116
- Austin, Lloyd, 5, 87
- Australia, 68
- Automation Anywhere, 208
- Autonomous driving, 176–177
- Avoidance, fallacy of, 140
- Big Tech, 41–42
- abusive AI policies of, 81, 84
- China's control of, 164–165
- commercialization of innovations by, 127
- in creating national AI strategy, 86
- and development of AI policy, 137
- in driving AI results, 131–132
- ethics and governance in, 129, 153, 204
- growth opportunities for, 143
- lobbyists for, 125, 212
- political stance of, 206
- responses to RFI from, 115, 116
- Cantwell, Maria, 154
- Capitol Hill attack (January 6, 2021), 27, 29
- Castro, Daniel, 149
- CDOs (chief data officers), 198–199
- Chaillan, Nicolas, 1–2, 6, 219
- Chemonics, 213
- Chief data officers (CDOs), 198–199
- Chief information officers (CIOs), 186–187, 199
- Chien, Steve, 147
- China:
- AI adoption in, 219
- AI and productivity in, 42–43
- AI development in, 152
- AI revolution in, 43–44, 60
- AI superiority of, 8, 16
- in AI War with US, 62–64, 228
- America's economic dependence on, 56
- America's strategic moves against, 228
- ban on Chinese companies operating in US, 61–62, 212
- Big Tech reigned in by, 164–165
- bullet train launch in, 27
- capabilities of, 146
- competition with, 20–21
- competitive advantage of, 6, 19
- concept of AI in, 202–203
- countering AI advances by, 21, 22 (See also Containment strategy)
- Covid management in, 20, 31
- deployment of AI in, 213
- economy of, 38, 55–58
- in great-power competition, 35–37
- humanitarian projects of, 213–214
- Le on economic status of, 11–12
- military weapons of, 19
- narrative about threat of, 45–47
- national AI strategy of, 129–130
- NSCAI on, 136, 141
- power projection by, 39, 44
- rise of, 37–40
- in semiconductor market, 212
- surrender of AI war against, 1–2
- tariffs on, 47–48, 59
- top professors’ relationships with, 211
- unexpected technological emergence of, 15–16
- US imports from and exports to, 59
- US reactivity to, 140–141
- US strategic confusion about, 14
- warnings about doing business with firms of, 64–68, 76
- Western influence in, 68
- wolf warrior diplomacy of, 12–14
- Xi's meetings with Biden, 54
- CIOs (chief information officers), 186–187, 199
- CIO Council, 187
- Clinton, Bill, 43, 71–73, 75, 88, 131
- Cognitive automation, 202
- Cognitive warfare, 27–30
- Cold War, 25–26, 47, 62
- Commercialization of technology, 127–128
- Committee for AI strategy development:
- Companies, RFI responses from, 98, 99f, 106–107, 115, 116
- Competition:
- AI capabilities defining, 20–21, 152
- between America and China, 12, 136
- America's assessed readiness for, 134 (See also National Security Council of Artificial Intelligence (NSCAI) report)
- among great powers, 34–37
- beginning of, 17
- with mega investment model, 209–210
- power dynamics of, 51–52
- research priorities and nature of, 218
- in semiconductor market, 212
- Competitive advantage:
- Conference on AI (March 2019), 113, 114
- Congress, 145–171
- AI caucuses of, 150–152, 166–167
- bills containing term “artificial intelligence,” 155–156, 156f–162f
- bills introduced since 2020, 165–171
- focus to advance AI needed by, 164–165
- and Foster's interview on AI, 162–164
- FUTURE of AI Act, 153–155
- “Japan-bashing” by members of, 145, 146f
- limited understanding of AI in, 152–153
- need to expect more from, 139
- Senate hearings on artificial intelligence, 146–150
- tone and messaging about AI in, 165
- Data:
- Data management, 197–200
- Data science, 198, 211
- Data sensors, 200–201
- Data War, 61–64
- “The Dawn of Artificial Intelligence,” 146–149
- Decoupling/recoupling:
- Deep learning, 15, 43–44, 202–203
- Defense Logistics Agency (DLA), 188–189
- Delaney, John K., 150, 152, 155
- Dell, 60
- Demand pattern changes, 33–34
- Denison, Benjamin, 51–52
- Department of Defense (DoD; Pentagon):
- Deployment of AI, 7, 213
- Deployment of technology, 127–128
- “Digital Decision-Making,” 149
- Digital World Acquisition Corp (DWAC), 207
- Discover, predict, automate (DPA) cycle, 42–43
- DLA (Defense Logistics Agency), 188–189
- DoD, see Department of Defense
- Domestic conflict in America, 19, 31–32
- DPA (discover, predict, automate) cycle, 42–43
- Dransfield, Joe, 4
- Drivers of AI leadership, 64, 136–138, 226
- Dunford, Joseph, 4
- DWAC (Digital World Acquisition Corp), 207
- Facebook, 206
- Fear of AI. See also Threats to America
- Felten, Edward, 149
- Financial activity, 82, 163–164
- Financial capital, access to, 67–68. See also Investment in AI
- Fiscal policy, 47–48
- Ford, Christopher, 13
- Foster, Bill, 151, 162–164
- Futreal, Andrew, 147
- FUTURE of AI Act, 153–155
- Futurists:
- FY21 NDAA (National Defense Authorization Act for Fiscal Year 2021), 169–170
- General Services Administration (GSA), 176, 177
- Georgieva, Kristalina, 35
- Gil, Dario, 149
- Google, 17, 43, 74
- Gore, Al, 43, 71–73, 75, 88, 131
- Governance of AI, 10, 154–155, 227
- Government:
- lack of private sector direction from, 191–193
- NSCAI on role played by, 136
- in shaping concept of what AI is to, 179
- Silicon Valley's perspective on, 205
- strategy development by (see Strategy development process)
- Government agencies, 175–189. See also individual agencies
- challenges for ML projects in, 185–187
- DLA's materials management system, 188–189
- DoD's strategic plans, 181–185
- in driving AI results, 131–132
- information coordination among, 177–181
- investment in AI by, 121
- procurement of AI by, 144
- responses to RFIs from, 99, 99f
- sourcing and adoption of AI projects in, 175–177, 180
- strategy development process in, 187–188
- Ideological struggle in America, 45, 225
- India, 68
- Individuals, RFI responses from, 99, 99f, 115
- Industrialization mindset, 5. See also AI industrialization
- Inflation, 19, 47–48
- Information:
- Infrastructure:
- Innovation(s):
- Intel, 210–212, 220
- Intellectual property theft, 53–54
- Internet, 14, 17, 28–30, 40, 71–75
- Investment (generally):
- Investment in AI, 205–215
- under American AI Initiative, 79–80
- Biden's promise for, 82, 83
- concerns about, 214–215
- in data, 210
- economic compatibility of, 221
- elitism in, 221–222
- by government agencies, 121
- and link between AI and supply chains, 212–214
- new mega investment model of, 208–210
- new phase of, 206–207
- as OSTP goal, 119
- in private sector, 207–208
- problems with, 221–222
- R&D-centric federal strategy for, 9–11
- recommendations for, 139–144
- research focus in, 6
- in semiconductors, 211–212
- in skills development, 211
- understanding of value chain needs for, 120
- Irrelevance, 5–7
- IT, see Information technology
- Latin American Logistics Organization, 60–61
- Leadership:
- Lee, Kai-Fu, 43
- Legislation. See also individual legislation
- Le Keqiang, 11–12
- LG, 212
- Li, Cheng, 37
- Losing the AI battle, 25–48
- attacks on American institutions, 28–30
- change in demand patterns, 33–34
- changing mood of the nation, 27–30, 45
- China's opportunity to strike, 42–43
- China's technology revolution, 43–44
- to cognitive warfare, 27–29
- Covid pandemic, 31
- domestic conflict/tensions, 31–32
- “great-power competition,” 34–37
- ideological struggle in America, 45
- inflation and supply chain failures, 47–48
- IT and AI development, 40–42
- rise of China, 37–40
- shaping of China threat narrative, 45–47
- supply chain meltdown, 32–33
- Lv, H., 20
- McCaul, Michael, 66
- Machine learning (ML):
- Machine learning projects, 87–88, 175, 185–187, 192
- Maher, Tom, 219
- Manufacturing, 31, 33–34, 37–38, 196
- Markey, Edward J., 154–155
- Mattis, James Norman, 3–4, 6
- Mega investment model, 208–210
- Microsoft, 114, 202
- Military, RFI responses from, 99, 99f
- Military capacity, 19
- ML, see Machine learning
- Monetary policy, 47–48
- Mood of the nation, 27–30, 45, 88–89
- Moore, Andrew, 147
- Morrison, Scott, 85
- Moynihan, Daniel P., 145
- Musk, Elon, 151
- National AI R&D Strategic Plan (2019), 114–120
- National AI strategy (China), 129–130
- National AI strategy (US), 75–89, 219–228
- 2016 National AI R&D Strategic Plan, 91–95
- 2019 National AI R&D Strategic Plan, 114–120
- Albert on, 2–3
- American AI Initiative as, 5–7, 11
- under Biden, 81–87
- building a plan for, 20–22
- Chaillan on, 2, 6, 219
- to counter China's advances (see Containment strategy)
- developed in government agencies, 187–188 (See also Government agencies)
- distinguishing between R&D plans and, 9–11, 128, 222–223, 227
- drivers of leadership for, 64
- ethics, governance, and values in, 10, 80–81
- executive leadership of, 73–75, 87–88 (See also AI leadership)
- experts' opinions on, 148–149
- failure of, 18–20
- flaws in, 219, 221–222
- focus of, 224–225
- Heinrich on, 168
- launches and relaunches of, 86–87
- and mood of the nation, 88–89
- under Obama, 77, 86, 93
- OSTP's development of, 9, 227 (See also Office of Science and Technology Policy (OSTP))
- other countries' adoption/copying of, 128–129
- outside of OSTP, need for, 140
- politics, talent, and priorities in, 131–132
- problems in developing, 17–20, 18f, 225–226, 226f
- proper development process for, 9–11
- recommendations for developing, 223–225
- supply side thinking in, 125–128, 126f
- under Trump, 75–80, 87, 113
- National Artificial Intelligence Research Development Initiative, 168
- National Counterintelligence and Security Center (NCSC), 64–65
- National Defense Authorization Act for Fiscal Year 2021 (FY21 NDAA), 169–170
- “The National Defense Strategy” (NDS), 3–4
- Nationalism, 74–75, 205–207
- National narratives (US):
- National security. See also Cybersecurity
- National Security Commission on Artificial Intelligence, 219
- National Security Council of Artificial Intelligence (NSCAI) report, 133–144
- National Strategy for Artificial Intelligence, 167
- NCSC (National Counterintelligence and Security Center), 64–65
- NDS (“The National Defense Strategy”), 3–4
- Nike, 60
- NITRD (Subcommittee on Networking and Information Technology Research and Development), 94
- Nonprofits, RFI responses from, 98–99, 99f, 107–110
- NSCAI report, see National Security Council of Artificial Intelligence report
- Obama, Barack:
- Office of Science and Technology Policy (OSTP), 113–124
- 2016 National AI R&D Strategic Plan of, 76–79, 91–95
- in 2017 and 2018, 114
- 2019 National AI R&D Strategic Plan of, 114–120
- as barrier to success/innovation, x, 78
- cognitive dissonance of, 138
- credibility of, 154
- groupthink in, 128–129
- initial conditions for change created by, 221
- and loss of America's leadership position, 9–11, 227
- mission of, 9, 80
- national narrative created by, 10, 81
- recommended focus for, 140
- RFI developed by, 95–97 (See also Requests for Information (RFIs))
- and timeline of AI initiatives, 120–121, 122f–124f
- Olson, Pete, 150–152, 155
- OpenAI, 148
- Orlando, Michael, 65
- OSTP, see Office of Science and Technology Policy
- Pakistan, 66
- Palihapitiya, Chamath, 46
- Parker, Lynne, 93, 94
- Pentagon, see Department of Defense
- Performance measures, 222
- Ping An, 213
- Plan A, 21. See also Competitive advantage
- Plan B, 21–22, 48. See also Containment strategy
- Political environment of R&D systems, 217–219
- Portman, Rob, 165–167, 169–171
- Private sector, 191–204. See also Big Tech
- absence of government direction for, 191–193
- AI supply chain in, 196–197, 196f
- America's AI leadership in, 135–136
- in Covid pandemic, 31
- and data management, 197–200
- and development of national AI strategy, 87
- and futurism and value signaling about AI, 203–204
- investment in AI in, 207–208
- and need for data sensors, 200–201
- RFI responses from, 98, 99f, 106–107, 115, 116
- and RPA as AI in America, 201–203
- and sensemaking about AI, 194–195
- supply side issues for AI, 193–194
- Raimondo, Gina, 57–58, 88
- Raytheon, 4
- R&D, see Research and development
- R&D systems, 217–221
- Reinsch, William, 66
- Requests for Information (RFIs), 91–111
- for 2016 National AI R&D Strategic Plan, 96–111
- and AI plan under Obama, 93
- comments received from, 98
- OSTP's development of, 95–97
- and process for formulating 2016 plan, 91–95
- questions answered in, 100–104, 101f–103f
- respondents to, 98, 99, 99f, 100f, 104–111, 115–118
- for updating 2016 National AI R&D Strategic Plan, 91, 115–118
- Research and development (R&D):
- Research and development plans, distinguishing between national AI strategy and, 9–11, 128, 222–223, 227
- Research and development (R&D) systems, 217–221
- RFIs, see Requests for Information
- Richardson, John, 4
- Robotic process automation (RPA), 179, 186, 201–203, 207–208
- Rogers, Dale, 58–61
- Rosenberg, Nathan, 220–221
- RPA, see Robotic process automation
- Rubio, Marco, 35–36, 38, 155
- Russia, 16, 35, 37, 46, 206, 212
- Safety of AI, in DoD 2018 Plan, 182–183
- SAMMS (Standard Automated Materials Management System), 188–189
- Samsung, 212, 220
- Schmidt, Eric, 135
- Science, US leadership in, 38
- Select Committee on Artificial Intelligence, 77, 114, 115
- Selling AI, 191–193. See also Private sector
- Semiconductors, 211–212
- Sensemaking about AI, 194–195
- Sensors, data, 200–201
- Silos, breaking down, 142–144
- Singapore, 66
- SK Group, 212
- Skills development, 197, 211, 225
- SMIC, 66
- Social environment of R&D systems, 217–219
- Social media, 31, 41, 45, 206
- Social perception of AI:
- Society, AI as transforming force for, 82, 154–155
- Sourcing of government AI projects, 175–177
- Soviet Union, 25–26
- Speed of relevance, 2–7, 228
- SS&C Technologies, 208
- Standard Automated Materials Management System (SAMMS), 188–189
- STEM (science, technology, engineering, and math), 63, 77
- Stieb, Matt, 26
- Strategic plans for AI, 181, 224–225. See also National AI strategy (US)
- Strategy 8, 120, 131–132
- The Strategy Bridge, 4
- Strategy development process, 9–11
- employing rigor in, 223
- in government agencies, 187–188
- by governments (see National AI strategy (China); National AI strategy (US))
- recommendation for, 223–225
- Students, RFI responses from, 99, 99f
- Subcommittee on Networking and Information Technology Research and Development (NITRD), 94
- Supply chain(s):
- AI (see AI supply chain)
- with AI, 225
- and change in demand patterns, 33–34
- and Covid management, 31
- humanitarian, 213–213
- link between AI and, 32, 212–214
- linked to China, 13–14
- problems in, 7, 18, 19, 47–48
- rebuilding, 34, 225
- resiliency of, 219
- Rogers on failure of, 58–61
- for semiconductors, 212
- US, meltdown of, 32–33
- work on options for, 65
- Taiwan Semiconductor Manufacturing Corp (TSMC), 212, 220
- Tame, Jacqueline, 185
- Tariffs, 47–48, 58–59
- Technological change, 2, 15–16, 85, 220–221
- Technological environment of R&D systems, 217–219
- Technological leadership, 8, 38, 40–44
- Technology(-ies). See also specific technologies
- Technology revolutions:
- Technology sector. See also Big Tech
- Terminology, 36–37
- Theologians, RFI responses from, 99, 99f
- Think tanks, RFI responses from, 115
- Threats to America. See also Fear of AI
- Transformation:
- Trump, Donald:
- blocking of social media of, 41, 206
- on China, 12
- Chinese firms blacklisted by, 66
- comments on AI by, 74, 118–119
- GPC policy under, 51
- lack of tech sector attention by, 40, 41
- and Mattis, 3
- national AI strategy under, 75–80, 86, 87, 113
- and power dynamics of US, 40
- style of, 62
- on Uyghur Muslims, 46
- UiPath, 208
- Ukraine invasion, 46, 206, 212
- United States of America. See also Congress; Government agencies
- 2016 election in, 29, 30, 88, 177
- AI “clubs” in, 142–144
- AI supply chain in, 197–200
- AI technology development model of, x, 34
- in AI War with China, 62–64
- changes in mood of, 27–30, 45, 88–89
- Chinese imports to and exports from, 59
- competitive power of, 20–21, 209, 226–227 (See also National Security Council of Artificial Intelligence (NSCAI) report)
- Covid management in, 20, 31
- economy of (see Economy of the United States)
- elections of 2016 in, 29, 30, 88, 177
- factors underlying technological change in, 220–221
- humanitarian aid model of, 214
- as IT leader, 40, 41
- loss of AI superiority in, 1–2, 8, 11, 16 (See also Losing the AI battle)
- national AI strategy for (see National AI strategy (US))
- national narratives in (see National narratives (US))
- political environment of, 44–45, 225
- politically-charged social media in, 206
- power projection by, 39–40, 44, 54
- R&D systems in, x, 217–221
- RPA as AI in, 179, 201–203
- social perception of AI in, 16–18, 82–83, 202–203, 227
- social psychological state of, 88–89
- strategic confusion in, 14
- strategic geopolitical moves by, 228
- world's perception of, 53
- Unleash, 212–213
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