Index
Note: Information in figures is indicated by f in page numbers.
- Abbosh, Omar, 73–81
- access
- as currency, 37
- digital agency and, 122, 126, 130
- in voice shopping,
- ACCESS Act, 124
- accuracy, in talent management, 28, 30
- agency
- data, 122, 125
- digital, 122, 124, 127, 130, 131
- Agile, 208
- AI. See artificial intelligence (AI)
- AirPods, 96
- Alexa, , , , , 10, 95–96
- Allbirds, 146
- AlterEgo, 98–100
- Amazon, , 28, 146, 147–149
- Amazon Echo, , ,
- Anthony, Callen, 51
- Apple, 96, 125
- AR. See augmented reality (AR)
- artificial intelligence (AI)
- and distancing of experts from work, 52–54
- learning to work with, 47–69
- and obstacles to learning, 50–57
- on-the-job learning and, 49–50
- shadow learning and, 67–68
- in talent management, 25–33
- voice assistants and,
- wearable, 95–103
- augmented reality (AR), 15–22, 99–100
- BCI. See brain-computer interfaces (BCI)
- Beane, Matt, 47–69
- Berners-Lee, Tim, 127
- BevMo!,
- Big Tech
- breakup of, 125
- regulation of, 124
- startups and, 145–152
- user data control and, 125
- biometrics, 83–92, 90f, 96
- Blippar, 16–17
- blockchain, 35–45
- Blumenthal, Richard, 124
- “bot crisis,” 86
- brain-computer interfaces (BCI), 98
- Brayne, Sarah, 55–56
- Brouwer, Jack, 141
- California Consumer Privacy Act (CCPA), 124, 131
- cars, 8–9
- CCPA. See California Consumer Privacy Act (CCPA)
- Chakravorti, Bhaskar, 121–132
- Chamorro-Premuzic, Tomas, 25–33
- chats, group, 107–109
- cities, smart, 77
- civic data trust, 126
- cognitive load, with voice assistants, 10
- commission, with voice assistants,
- Community (messaging service), 108–109
- competition, , 43
- contracts
- blockchain in, 36, 40, 43
- as currency, 37
- crime, 56–57, 62
- cyberattacks, 133–143
- DASHBOARD Act, 124
- data
- as currency, 37
- as labor, 126
- self-reported, 86
- training, 26, 28
- user control of, 121–132
- valuation, 129
- data agency, 122, 125
- data democracy, 127
- data governance, 128–130
- data ownership, , 127
- Data Transfer Project, 125
- Dattner, Ben, 25–33
- Depository Trust and Clearing Corporation (DTCC), 40
- digital agency, 122, 124, 127, 130, 131
- digital campfires, 106–115
- Discord (chat platform), 110–111
- Downes, Larry, 73–81
- Dropbox, 149
- DTCC. See Depository Trust and Clearing Corporation (DTCC)
- edX, 54–55, 63–64
- ethics
- of intelligence amplification, 99
- of predictive policing, 56
- in talent management, artificial intelligence and, 25–33
- evolutionary solutions, with blockchain, 41–42, 45
- expertise, shadow learning and, 57, 64
- experts, distancing of, from work, 52–54
- eyewear, smart, 99–100
- Facebook, 105, 114, 122–123, 125, 146, 150
- Facebook Groups, 109–111
- Facebook Messenger, 108
- fairness, in talent management, 28, 30, 32–33
- fear of missing out (FOMO), 38–39, 44
- 5G, 73–81
- food-tracking blockchain, 39–40
- Foroohar, Rana, 126
- Fortnite (video game), 112–113
- Furlonger, David, 35–45
- furniture, 17–18
- galvanic skin response (GSR), 84, 85–86, 87–88, 90f, 92
- gaming, 43, 112–113
- General Data Protection Regulation (GDPR), 28, 124, 125, 131
- Gillespie, Matthew, 83–92, 90f
- Glaeser, Bree,
- Glossier, 111–112
- Goel, Asit, 15–22
- Google Assistant, , 10
- Google Home Nest Hub,
- group chats, 107–109
- GSR. See galvanic skin response (GSR)
- idatity, 126
- Ikea Place, 17–18
- Instagram, 108, 123, 146
- Instagram Stories, 109–110
- insurance
- car, 36, 78
- data democracy and, 127
- intelligence amplification, 95–103
- Internet of Things (IoT), 76, 96
- Kapur, Arnav, 99
- Khan, Shaharyar, 139–140
- Kim, Juho, 67
- labor, data as, 126
- Lasso (app), 150
- law enforcement, 56–57, 62, 67
- laws
- hiring and, 31
- privacy, 123–124
- user data control and, 123–125
- learnersourcing, 67
- learning
- machine, 53
- methodological overload and, 54–55
- methods, standard, 55–57
- obstacles to, 50–57
- on-the-job, 49–50
- shadow, 57–68
- struggle and, 58–59
- “learning edge,” 51–52
- LectureScape, 67
- Libert, Kelsey, 83–92, 90f
- machine learning, 53. See also artificial intelligence (AI)
- Madnick, Stuart, 133–143
- Maes, Pattie, 100
- mall, shopping, 8–11
- marketing, viral, 83–92, 90f
- Mars Agency,
- Marshmello (artist), 112–113
- Merton, Robert, 57
- methodological overload, 54–55
- micro-communities, 109–112, 116
- Microsoft Teams, 146
- mobile network technology, 73–81
- network, 5G, 73–81
- Nilekani, Nandan, 127
- Ocean Protocol, 127
- on-the-job learning (OJL), 49–50
- opportunistic solutions, with blockchain, 40–41, 44
- ownership, data, , 127
- Own Your Own Data Act, 125
- Pokémon Go, 15–16
- policing, 56–57, 62, 67
- Polli, Frida, 25–33
- Posner, Eric, 126
- prediction, of viral content, 83–92, 90f
- predictive policing, 56–57, 62, 67
- PredPol, 56–57, 62, 67
- privacy
- intelligence amplification and, 99, 101
- legislation, 123–124
- privacy paradox, 121, 131
- private messaging, 107–109, 115
- Schwab, Nick,
- SecuTix, 41–42
- self-reported data, 86
- Sephora, 16
- shadow learning, 57–68
- shared-experience campfires, 112–115, 116
- Shestakofsky, Benjamin, 53–54
- shopping
- with augmented reality, 17–18
- by voice, 4–13
- Simms, Kane, 3–13
- skins, 113–114
- Slack (messaging tool), 110–112, 146
- SmartAisle,
- smart cities, 77
- smart eyewear, 99–100
- Snapchat, 146, 150
- social media, 105–116, 124
- speakers, smart,
- Sprite, 111
- startups, 145–152
- Streamr, 127
- struggle, in shadow learning, 58–59
- Susskind, Lawrence, 136
- Swash (app), 127
- talent management, artificial intelligence in, 25–33
- Teixeira, Thales S., 145–152
- Text Rex, 108
- Threads (app), 108
- ticketing, , 41–42
- TikTok, 150
- ToolScape, 67
- training data, 26, 28
- trapped value, 76, 77, 78
- Trojan horse solutions, with blockchain, 39–40, 44
- Twitch (livestreaming platform), 113
- Union of European Football Associations (UEFA), 41–42
- utilities, cyberattacks on, 133–143
- Uzureau, Christophe, 35–45
- value
- of augmented reality, 17–18
- of blockchain, 35–36, 38
- trapped, 76, 77, 78
- viral marketing, 83–92, 90f
- voice assistants, 3–13
- voice user interface (VUI), , 11
- Voysis,
- Vu, Mikey, 15–22
- VUI. See voice user interface (VUI)
- Wara, Michael, 133–134
- Warner, Mark, 124
- Warren, Elizabeth, 125
- Wayfair, 147–148
- wearables, 95–103
- Weyl, Glen, 126
- Wilson, Sara, 105–116
- Woolf University, 42–43
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