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WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

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INDEX

The pagination of this electronic edition does not match the edition from which it was created. To locate a specific entry, please use your e-book reader’s search tools.

abstraction vs. reality, 21–22

achievement

        aspiring to be better, 357–58

        climate change scenario, 360–63

        creating more value than you capture, 17, 104, 246, 249–50, 291–92, 296–97, 354–55

        developing a robust strategy, 358–67

        and disruptive technology, 351–52

        rising to great challenges, 369–72

        spotting opportunities, 367–69

        taking the long view, 355–57

        technology and the future scenario, 364–67

        working on what matters to you, 352–54

Active/X, 10

advertising, 79–81, 161–62, 225

Afghanistan, 116–17

Agrarian Justice (Paine), 306

agricultural productivity, 326

AI (artificial intelligence), x, xx–xxi, xxiv, 232–36

        and cybercrime, 208–9

        expanding research, 231–32

        human fears about, ix, xv–xvi, 300

        machine learning, 155, 163–69, 235–36, 334–36

        personal agents, xiii, xiv–xvi, 82, 232, 233

        and power efficiency, 302

        social purpose for, 353–54

        system design leads to predictable outcomes, 238–41

Airbnb, x, 64, 75, 97–98, 293

Akerlof, George, 249

Albright, Jonathan, 207–8

algorithms, xx, xxiv, 68

        filter bubble, 199–200

        human judgment vs. fact checking with, 211

        management by, 59–61, 68

        minimum-wage mandate vs. market-based algorithms, 197–98

        and regulations, 180–81

        trust in algorithmic systems, 224–28

        and whac-a-mole (fake news), 201–9, 211

        See also AI

Alibaba, 294

Allchin, Jim, 24

AlphaGo, 165, 167

Altman, Sam, 306, 307

Alvarez, José, 197

Amazon, xi, 9, 34, 52–53, 90, 95, 103

        1-Click e-commerce patent, 71–75

        accessibility of data leads to AWS, 110–13

        Andon Cord, 117–18

        continuous improvement, 120–21, 122

        and DevOps, 121–23

        and electricity, 121, 124

        on Linux operating system, 24

        long-term investment priority, 245

        and machine learning, 166

        as a platform, 111–13

        promise theory, 114–17

        superior data and search returns, 39–40

        teams, 113–14

        uses for automation, 91–92

Amazon Echo, 82

Amazon Flex delivery service, 94

Amazon Go app, 78, 79

“Amazon’s Stranglehold” (LaVecchia and Mitchell), 103

Amazon Way, The (Rossman), 117

Amazon Web Services (AWS), 110–11

Andon Cord, 117

Andreessen, Marc, 15

Android smartphones, 52, 101

AOL, 276–77

Apache server, 99

Apple, xiii, xiv, 32, 53, 78, 101, 128, 136, 313, 321–22

Application Program Interface (API), 26, 128

Arora, Ashish, 246

artificial general intelligence, 233–34

art market, 312–19

Art of the Long View, The (Schwartz), 359

asylum application, automated, 332

AT&T, 6–7

augmented reality, xviii–xix, 344–45

augmented workers, 320–21, 326–32

        access to opportunities, 332–34

        cognitive augmentation/cyborgs, 321–22

        importance of learning, 334–36

        neurotech interfaces, 328–32

        at Uber or Lyft, 58–59, 69–70, 332

        See also education/training; employees

Autodesk, 327–28

Autor, David, 305–6

Avent, Ryan, 304, 348–49

Bad Samaritans (Chang), 134

Baer, Steve, 295–97

Baird, Zoë, 342

Baldwin, Laura, 262, 349

bankruptcy for profit, 249

Basecamp, 287

Battelle, John, 29, 161

Bayha, Carla, 10, 355

Beam, Inc., 48–49, 51

Behr, Kevin, 122

Belenzon, Sharon, 246

beliefs, truth, and fake news, 210–14, 220–24

benefit corporations “B corps,” 292, 293

Berkeley Unix project, 6–7, 16

Berners-Lee, Tim, 99

Bersin, Josh, 111

Bessen, James, 345–47

Bezos, Jeff, 44, 71–75, 110–13, 114–15, 124, 366–67

Bharat, Krishna, 215

big data, 155–56, 163, 325, 326–27, 335–36

Blecharczyk, Nathan, 97–98

Blyth, Mark, 239

Boston, Massachusetts, 138–40

Bostrom, Nick, 234

Bouganim, Ron, 140

Bowling Alone (Putnam), 218–19

Boyd, John, 209

Bregman, Rutger, 307

Brin, David, 177, 179

Brin, Sergey, 132, 157, 160, 289–90

Browder, Josh, 332

Brown, John Seely, 341

Brynjolfsson, Erik, 303

Bucheit, Paul, 306–7, 308, 309

Buffett, Warren, 225, 242–43, 265, 272

“Building Global Community” (Zuckerberg), 218

Burdick, Brad, 126

Burgess, Mark, 114, 115

businesses

        declining R&D, 245–46

        economic impact reports, 290–95

        fitness function, 226, 239–41, 274, 352

        limiting CEO salaries, 247

        management, xxi, 153–54, 247, 279–80

        and media content, 226–28

        social conscience squashed, 240–41

        startups, 41, 186, 247, 275, 279, 282–85, 316

        stock price vs. long-term investment, 242–50

        and tragedy of the commons, 249–50

        uncertain job opportunities, 301–2

        See also financial markets

Business Insider, 211–12

business model mapping, 48–51, 57–61, 62–70

Cabulous, 56

Cadwalladr, Carole, 202–3, 214

Camp, Garrett, 54, 75

Car2go, 85

Carlsen, Magnus, 330

Carr, Nicholas, 64

Casey, Liam, 66

“Cathedral and the Bazaar” (Raymond), 8–9

central banks, xxi–xxii

centralization and decentralization, 105–8

Central Park, New York, 132–33

Cerf, Vint, 107

Chan, Priscilla, 302–3

Chase, Robin, 84–85

Chastanet, Vidal, 371

Chesky, Brian, 97–98

chess and AI, 330

Chinese companies, 53

Chrapaty, Debra, 121

Christensen, Clayton, 24–25, 33–34, 315, 331, 351

Church, George, 328

Clark, Dave, 107

climate change, 300, 302, 360–63

Climate Corporation, 326

Cline, Craig, 29

“Clothesline Paradox, The” (Baer), 295–97

cloud computing, 35, 41, 53, 78, 84, 110–11, 119

Coase, Ronald, 89

Code for America, 138–44, 147, 148–49, 187, 222

Cohen, Stephen, 134

Cohler, Matt, 54

Collins, Jim, 352

combinatorial effects, 96–98

Common Gateway Interface (CGI), 81

communication, 44–45, 84, 90, 114, 115–19, 117

community. See social infrastructure

competition, outcomes of, 104

computer hardware, 7, 11–12, 165, 167

computer industry, 5–17, 186–87, 301, 334–36, 343–44. See also cloud computing; software

Concrete Economics (Cohen and DeLong), 134

consumer reviews, 34, 92, 182

Conte, Jack, 316–17

corporate raiders, 242–52, 249

corporations. See businesses

Craigslist, 39, 97, 101–2

Creative Commons licenses, 180

creative economy, 312–19

“creep factor,” 178

Cronin, Beau, 236

crowdfunding, 39, 305, 316–17

Culkin, Father John, 163

customers, 58, 250–52, 264, 271, 357

Cutting, Doug, 325

cybercrime, 208–9

Dalio, Ray, 223

DARPA Cyber Grand Challenge, 209

“Darwin’s Bulldog” (Huxley), 44

data

        accessibility of, 110, 128–31

        big data, 155–56, 163, 325, 326–27, 335–36

        as collective intelligence, 32–35

        data-driven regulatory systems, 175–76

        failure to provide or utilize, 188, 189–90

        hidden intelligence in web links, 39

        increasing creativity with, 46

        SEC’s EDGAR documents, 125–26

        for self-driving cars, 32–33, 34–35

        from sensors, xviii–xix, 33, 34–35, 40, 41, 85, 176–77, 326

        from surveillance, 177–81

        unreasonable effectiveness of, 154–63

data aggregators, 179–80, 236

data science, 156

Davison, Lang, 341

Dawkins, Richard, 44

decentralization and centralization, 105–8

DeepMind, 165, 167, 168–69, 235

de Havilland Comet commercial jet, 217–18

Dell, Michael, 12

DeLong, Brad, 134

Denmark, 268

DevOps, 121–23

Dickens, Charles, 346

Dickerson, Mikey, 118–19, 146–47, 148

DiGiammarino, Frank, 129

digital footprint, physical assets with, 66–67

Digital Millennium Copyright Act, 202

disease elimination jobs, 300, 302–3

disinformation. See fake news

disruptive forces, xxiii

disruptive technology, 351–52

Dobbs, Richard, xxiii

“Dog and the Frisbee, The” (Haldane), 175

Doing Capitalism in the Innovation Economy (Janeway), 104–5, 274

DonorsChoose, 183

dot-com boom, 29

Dougherty, Dale, 28–29, 81, 99–100, 337

Drucker, Peter F., 250

Dvorak, John, 41

Dyson, George, 45

eBay, 39, 182–83, 294

“Economic Mechanism Design for Computerized Agents” (Varian), 261

“Economic Possibilities for Our Grandchildren” (Keynes), 298–99

economics, 271–73

        assigning a value to caregiving, 310–11

        efficiency wages, 197

        employers’ 29-hour loophole, 194–95, 196

        fundamental law of capitalism, 268

        invisible hand of competition, 262–70

        the “laws” of economics, 257–62

        and leisure time, 308–11

        machine money and people money, 306–7, 308, 309

        minimum wage, 197–98, 264–68

        secular stagnation, 271

        Stiglitz exposes the 1%, 255

        trickle down, 244, 265, 273

        universal basic income, 305–6, 307–11

        wealth inequality, 263–65

        welfare economics, 263, 266, 307

economy, xxii

        and adaptations to change, xxiv–xxv

        creativity-based, 312–19

        financial crisis of 2008, 172–73, 175, 238, 265, 275, 359

        as government’s thick marketplace, 133

        of Korea, 134

        technology and the future of the economy scenario plan, 364–67

        See also financial markets

economy and Silicon Valley, 274–75

        the Clothesline Paradox, 295–97

        digital platforms and the real economy, 288–89

        market capitalization/supermoney, 276–79, 280–84, 289

        measuring value creation, 289–95

        pool of qualified workers, 347–50

        venture capital-backed startups, 275, 282–84

        Y Combinator program for VC-funded companies, 286–87

education/training

        creating, sharing, and embedding into tools, 323–32, 334–36

        as investment in other’s children, 320–21

        for jobs, 303, 304, 321

        lagging behind technology, 335–36

        learning by doing, 337–41, 345–50

        on-demand education, 341–45

        Open Cloud Academy at Rackspace, 350

        play element, 340–41

        and social capital, 345–50

efficiency wages, 197

efficient market hypothesis, 259–61

“Eight Principles of Open Government Data” (Malamud, Lessig, and O’Reilly), 130–31

electric cars, safety-related load of, 66–67

Eliot, T. S., 41

Emerging Technology Conference, 27

employees

        continuous partial employment, 190–98

        corporate investment choices vs., 246, 247–48

        de-skilling without re-skilling, 349–50

        full time vs. 29-hour loophole, 194–95, 196

        increasing earning potential of, 243

        independent contractor vs., 190–92

        as job-creating customers, 250–52, 264, 271, 357

        labor movement, 262–63

        and living wage, 194

        minimum-wage mandate vs. market-based algorithms, 197–98

        new paradigm for, 196

        stock-based compensation and company size, 280–81

        valuing skills vs. degrees, 342–43, 345–50

        See also augmented workers; jobs

English, Paul, 330–31

Eno, Brian, 355–56

Entrepreneurial State (Mazzucato), 296

Etsy, 292–93

“Everything Is Amazing and Nobody’s Happy” (Louis CK), 377n

Facebook, 52, 315–16

        advertising, 162

        building social infrastructure, 218–20

        and clickbait, 224

        and fake news, 201–2, 204, 205–7, 215–17

        and global affairs, 43

        as network of people and advertisers, 64

        News Feed, 162

        ownership and control of central user network, 101

        and presidential election of 2016, 199–201

        raising money for causes, 371

        study of emotional effects of content, 227

fact checking, 210–14

Fadell, Tony, 82

fake news

        algorithmic whac-a-mole, 201–8

        dealing with disagreement, 220–24

        eliminating incentives, 224–28

        fact checking, 210–14

        presidential election of 2016, 199–201

        and process of abstraction, 21, 211

        responding to, 215–20

Farrell, Henry, 220, 223

Faurot, Eric, 128–29

Feynman, Richard, 22, 340

“Fight for 15,” 267–68

Fin AI-based personal assistant startup, 331

financial markets

        corporate raiders, 242–52

        and crisis of 2008, 172–73, 175, 238, 265, 275, 359

        and fitness function, 238–40, 242, 248, 303

        focus on stock price vs. long-term investment, 242–51

        fraud potential, 277, 283

        high-frequency trading impact, 236–37, 272

        inflation, 239–40

        IPOs, 274, 277, 278–79, 293

        the market as programming run amok, 231–32, 236–38

        market of goods and services vs., 257

        and misinformation, 210–11

        and regulations, 172–73

        serving itself vs. real economy, 251–52

        shareholder capitalism, 240–41, 245–51, 256, 263–68, 292

        social values as anathema, 240–41, 251

        stock prices as a bad map, 243–45

        system design leads to predictable outcomes, 238–41, 256–62

        value investing, 271–72, 284–85

Fink, Larry, 242–43, 272

Firestein, Stuart, 340

fitness function, 106

        of Amazon teams, 114, 118

        for economy, 269, 367–68

        of Facebook, 162–63, 219–20

        and fake news, 225

        and financial markets, 238–40, 242, 248, 303

        of Google’s Search Quality team, 156–57, 173–74

        making money as, 226, 239–41, 274, 352

        and search engine ratings, 158

fitness landscape, xxii, 106

Flash Crash of stock market (2010), 237

Foo Camp (annual unconference), 50

Ford, Martin, 269

Foroohar, Rana, 251–52, 271

Foursquare, 84

Fox News, 208

free software, 16–19. See also open source software

Freeware Summit (1998), 15–16, 19

Fried, Limor, 369–70, 371–72

Friedl, Jeffrey, 120–21

Friedman, Milton, 240

future

        effect of individual decisions, 13

        Apple Stores, 321–22

        business model map for, 65–70

        gravitational cores and gradually attenuating influence, 65

        inventing the future, 46–47, 153–54

        living in, prior to even distribution, 19, 23, 29, 316

        questions about, 300

        seeing via innovators in the present, 14

        and worker augmentation, 69

“Future of Firms, The” (Kilpi), 89

Gage, John, 28

Gall, John, 106

Gates, Bill, 17, 307, 360

Gebbia, Joe, 97–98

Gelsinger, Pat, 13

General Electric (GE), 241, 249, 303

General Theory of Employment, Interest, and Money (Keynes), 271–72

Generation Z, 341–42

genetic programming, 106

Getaround, 85

GiveDirectly, 305

global brain. See Internet; World Wide Web

Global Entrepreneurship Summit, 315

Global Network Navigator (GNN), 28–29, 38–39, 79–81, 89, 276

GNU Manifesto, The (Stallman), 6

Goodhart’s Law, 239

Good Jobs Strategy (Ton), 197

Goodman, George, 278

Google, 103

        algorithmic curation of information, 89

        Android phones, 52, 101

        and cloud computing, 113

        continuous improvement process, 119

        corpus for language researchers, 155–56

        discovery of hidden intelligence in web links, 39

        economic impact of, 290–91

        and fake news, 202–7, 215–17

        importance of, 51–52

        Knowledge Graph, 158

        on Linux operating system, 24

        and machine learning, 335

        Moto X phone, 82–83

        as native web application, 30–31

        as network of people and advertisers, 64

        NSF grant for, 132

        and online mapping dominance, 127–28

        pay-per-click ad auction, 161–62

        and public sentiment about privacy, 82

        Site Reliability Engineering/DevOps, 123

        stock-based compensation, 280, 289–90

        Street View cars collecting data, 33, 34–35

Google AlphaGo, x

Google Book Search, 170–71

Google Finance, 126

Google Glass, xviii–xix, 344–45

Google Maps, xiii, 127–28

Google Photos, 166

Google Search, 34, 43–44, 156–59, 165

Gordon, Robert, 243

Gov 2.0 Summit and Expo (2009 and 2010), Washington DC, 128–31

government, 187–89, 249–50, 269, 270–73. See also regulations

government as a platform, 133–35, 149–50

        Code for America, 138–44, 147, 148–49, 187, 222

        and elites understanding technology, 146

        federal government, 147

        Gov 2.0 Summit and Expo, 128–31

        healthcare.gov crisis, 118–19, 146

        local governments, 138–42

        need for reinvention of applications, 143

        NSF Digital Library Program, 132

        R&D grants, 132

        requirements for, 135–37

“Government Data and the Invisible Hand” (Robinson, et. al), 130

Government Digital Service, United Kingdom (UK GDS), 144–45, 168–69

GPL (GNU Public License), 25

GPS, 83–84, 131, 176–77

Gray, Mary, 166

“greed is good” choice in 1980s, xxv

Green, Hank, 289, 316

Green, Logan, 77, 183

Green Bay Packers, 244

Green Mars (Robinson), 96

Griffith, Saul, 66, 326–27, 363–64

Grossman, Nick, 189

Guardian, 214

Guarino, Dave, 141–43

Hagel, John, III, 341

Hagiu, Andrei, 196

Ha-Joon Chang, 134

Haldane, Andrew, 175

Halevy, Alon, 155–56

Hammerbacher, Jeff, 156, 169

Hanauer, Nick, 196, 250, 257, 264–65, 267, 268, 300, 368–69

Hanrahan, Jim, 43

Haque, Umair, 248–49

“Hardware, Software, and Infoware” (O’Reilly), 9–11, 13–14

“Harnessing Collective Intelligence” vector, 37–40

Harvard Business Review, 24, 156, 196, 204

Hassabis, Demis, 167, 234

healthcare.gov, 118–19, 146

Hedlund, Mark, 287

Herbert, Frank, 76

Hewlett-Packard (HP), 79

Hickey, Dave, 313

Hidden Figures (film), 301

Hill, Steven, 184, 196

Hillaker, Harry, 209

Hillis, Danny, 44

HITs (Human Intelligence Tasks), 166

Hoffman, Reid, 36

Hoffman’s Law, 36–37

Honor, 332–33

Hooke’s Law, 327

Hotwired (online magazine), 81

household debt, xxi

Howard, Jeremy, 168

Hsiang, Mina, 148

Huber, Jeff, 353–54

Hugo, Victor, 355

Humans of New York (Stanton), 370–71

Human Spectrogram, 222

Huxley, Thomas Henry, 44

Hwang, Tim, 332

hybrid artificial intelligence, 234–36

IBM, 11–12, 136

idea meritocracy, 223

Ignorance (Firestein), 340

Immelt, Jeff, 303

independent contractors, 190–92

indie.vc model, 286

industrial revolution, xxiv

Inequality for All (documentary film), 265

inflation, 239

information, 66–67, 89. See also data

Information, The (tech report), 287

innovation waves, xxiii, 46–47, 339

Innovator’s Dilemma, The (Christensen), 351

Instagram, 96–97, 102

Intel, 12–13, 33

Internet

        and business organization changes, 123–24

        commercializing process, 79–81

        communications role, 90

        cybercrime, 208–9

        economic value of, 97

        file sharing between users, 25–26

        freedom leads to growth, 100–101

        free software people and, 15

        and GNN, 28–29, 38–39, 79–81, 89, 276

        as neutral platform, 202–3

        open source infrastructure, 19, 20

        as operating system, 27–28, 35, 41

        packet switching, 106–7

        peer-to-peer file sharing, 26–27

        programmers work from inside the application, 120–24

        proprietary applications running on open source software, 25

        SETI@home project, 26

        survey of users, 81

        TCP/IP development, 107–8

        web spidering, 110

        See also World Wide Web

Internet Creators Guild, 289

Internet in a Box, 81

invention obvious in retrospect, 71–75

invisible hand theory, 262–70

iPhone, xiii, 32, 128, 136

iPhone App Store, 101, 128, 136

issue-tracking systems, 118–19

“It’s Still Day 1” (Bezos), 124

iTunes, 31

Jacobsen, Mark, 285

Janeway, Bill, 104–5, 115, 238, 247, 263, 274, 277–78, 284

Jefferson, Thomas, 130

Jensen, Michael, 240–41

jobs, xxvi, 301–3, 308, 320–21

        and AI, xx–xxi, 91–92, 232–33

        caring and sharing aspects, 308–11, 323–24, 332–33

        creativity-based, 312–19

        displacement and transformation of, 94

        and education/training, 303, 304

        independent contractor status at Uber and Lyft, 59

        labor globalization, 67

        and new technology, xvii

        optimism about the future, 298–302

        reducing work hours, 304, 308–11

        replacing with higher-value tasks, 94–95

        universal basic income for, 305–6, 307–11

        See also augmented workers; employees

Jobs, Steve, 70, 313

Johnson, Bryan, 330

Johnson, Clay, 149

Johnson, Samuel, 313

Johri, Akhil, 256

Just for Fun (Torvalds), 14

Kahn, Bob, 107

Kalanick, Travis, 54, 69, 75

Kaplan, Esther, 193

Kasriel, Stephane, 333–34

Katsuyama, Brad, 237–38

Kernighan, Brian, 105–6

Kettl, Donald, 129

Keynes, John Maynard, 271–72, 298

Kickstarter, 291–92

Kilpi, Esko, 89–90

Kim, Gene, 122–23

Klein, Ezra, 143

knowledge, sharing vs. hoarding, 296–97, 323–25

Korea, 134

Korzybski, Alfred, 20, 195, 211, 314

Kressel, Henry, 284

Krol, Ed, 28

Kromhout, Peter, 116–17

Kwak, James, 258

labor globalization, 67

labor movement, 262–63

Lang, David, 183

language, 20–21, 323–24

language translation, 155–56, 165–66

Lanier, Jaron, 96

laser eye surgery, xvii

Launchbury, John, 209

LaVecchia, Olivia, 103

Law of Conservation of Attractive Profits (Christensen), 24–25, 33–34, 331

Lazonick, William, 245, 247

Learning by Doing (Bessen), 345–47

LeCun, Yann, 164–65, 167, 234, 297

leisure time, 309–10, 314

Lessig, Larry, 130–31

Lessin, Jessica, 287

Lessin, Sam, 331

Levi, Margaret, 60

Levie, Aaron, 85–86

Lewis, Michael, 237

Lincoln, Abraham, 150, 323

Linux Kongress, Würzburg, Germany, 8–11

Linux operating system, xii, 7, 8, 23, 24

Long Now Foundation, 355–56

Loosemore, Tom, 186–87

“Looting” (Akerlof and Romer), 249

Lopez, Nadia, 371

Loukides, Mike, 38

Lucovsky, Mark, 119

Lyft, 47, 54–55, 58, 70, 77, 94, 183, 262, 318. See also Uber for topics that apply to both

machine learning, 155, 163–69, 235–36, 334–36

MACRA (2015), 147–48

magical user experiences, 70, 83–86, 322

Magoulas, Roger, 155

Make (magazine), 337, 341

Makers and Takers (Foroohar), 251–52

Malamud, Carl, 125–26, 129, 130–31

Malaney, Pia, 263

management, xxi, 153–54, 247, 279–80

Managing UUCP and Usenet (O’Reilly), 38

Manber, Udi, 158

manufacturing technique advances, 327–28

manufacturing workers and offshoring, 349–50

Manyika, James, xxiii, 290

MapReduce, 325

maps, 3–5, 19–20, 35

        of business models, 48–51, 57–61, 62–70

        of energy sources and uses in the US economy, 363–64

        the future of management, 153–54

        Google Maps, xiii

        language as, 20–21

        meme maps, 51–53

        new maps, 75, 128–31, 203

        scenario planning, 361

        stock prices as a bad map, 243–45

        and territory it claims to describe, 211–14, 268

        user failure, 170–71

        watching trends unfold, 345

Marder, Michael P., 217

marketplace at critical mass, 102–5

Markey, Edward J., 125

Markle Foundation Rework America task force, 320–21, 342–43

Marriage of Heaven and Hell (Blake), 265

mashups, 127, 128

Masiello, Betsy, 64

Mattison, John, 224

Maudslay, Henry, 324

Mazzucato, Mariana, 296

McAfee, Andy, xxii–xxiii

McChrystal, Stanley, 116–17

McCloskey, Mike, 368

McCool, Rob, 81

McGovern, Pat, 344

McKusick, Kirk, 16

McLaughlin, David, 340–41

Meckling, William, 240–41

MediaLive International, 29

Medium, 89, 143, 183, 196, 226–27

Megill, Colin, 200, 221

meme maps, 51–53

memes (self-replicating ideas), 44, 205

Merchant of Venice, The (Shakespeare), 171

Messina, Chris, 42

Metaweb, 158

Microsoft, 5

        Active/X, 10

        barriers to entry against competitors, 13

        and cloud computing, 113

        and HITs, 166–67

        HoloLens, 344, 345

        and IBM, 12

        investments in AI and “cognitive services,” 53

        missing the Internet wave, 360

        monopoly position, 33, 102–4

        and open source software, 24

        operating systems, 7

        and World Wide Web, 99–100

Microsoft Network (MSN), 100

minimum wage, 264–68

Misérables, Les (Hugo), 355

Mitchell, Stacy, 103

MIT’s X Window System for Unix and Linux, 16

Molano Vega, Diego, 174

Money:Tech conference, 104

monopoly status, 33, 102–4

Monsanto, 326

Moonves, Leslie, 228

Moore’s Law, 36, 149

Morin, Brin, 341–42

Mosseri, Adam, 224, 226

Mother Night (Vonnegut), 357–58

Moto X phone (Google), 82–83

Mundie, Craig, 131

Muñoz, Cecilia, 148

Musk, Elon, xvi, 302, 329, 363

Nadella, Satya, 353

Napster, 25

narrow AI, 232–33

National Highway Traffic Safety Administration, 188–89

National Science Foundation (NSF), 80, 132

navigation, 83–84, 131, 176–77

Nest, 82

Netscape, 15

networks, xxiv, 90–91

        centralization and decentralization, 105–8

        hosting data centers, 121

        insight vs. blinded by the familiar, 95–98

        marketplace at critical mass, 102–5

        networked marketplace platforms, 67

        network effects, 34

        platforms for physical world services, 92–95

        thick marketplaces, 98–105, 128, 133

        See also platforms

Neuralink Brain-Machine interface, 329

neurotech interfaces, 328–32

NewMark, Craig, 101

news media, 18–19, 200–201, 201–8, 210–14, 225–28

Next:Economy Summit, 267, 303, 309, 369–70

Nielsen, Michael, 43

No Ordinary Disruption (Dobbs, Manykia, and Woetzel), xxiii

Nordhaus, William, 296

Norvig, Peter, 33, 155–56

Norway, 305–6

O’Brien, Chris, 225

Occupy Wall Street movement, 229–31, 255

Oculus, 291

“Of the 1%, by the 1%, for the 1%” (Stiglitz), 255

Omidyar, Pierre, 357

on-demand blood-delivery drones, 370

on-demand education, 341–45

on-demand services, x, xxiii, xxiv, 67–68, 89, 92–95, 302, 309–10. See also Airbnb; Lyft; Uber

on-demand talent and resources, 67–68

on-demand technology, 310

O’Neil, Cathy, 167–68

Open Source Initiative, 18

“Open Source Paradigm Shift, The” (O’Reilly), 23, 29

open source software, 5–7, 8–9, 15

        collaborative model, 35

        evolution vs. design, 13–14

        Freeware Summit, 15–16

        innovation related to, 127

        learning by doing, 339

        MapReduce, 325

        naming decision, 16–19

        and next generation of applications, 23–24

        reason for making Perl free, 16–17

Open Source Summit, 19

Open Systems Interconnect (OSI) model, 108

operating systems, 24, 27–28, 35, 41. See also individual operating systems

“Operations: The New Secret Sauce” (O’Reilly), 121

Oram, Andy, 25–26

Orbitz, 178

O’Reilly, Tim, ix, xvii, 20, 71–75

O’Reilly AlphaTech Ventures, 50, 285–88

O’Reilly Media

        acquisition procedure, 279

        and Amazon, 110–13

        core strategic positioning, 48–50

        ebook publishing venture, 28–29, 50

        evaluating new industries, xi–xii

        googling name, 159–60

        as startup, 274–75, 284–85

        tracking trends to identify vectors, 37–40

Organisation for Economic Co-operation and Development (OECD), 170

Oringer, Jon, 283

Overton Window, 268–69

Overture, 161

“Owner’s Manifesto” (Dougherty), 337

Pacific Railroad Surveys, 4

Page, Larry, 132, 157, 160, 289–90

Pahlka, Jennifer “Jen,” 129, 137–38, 144–46, 318, 319

Paine, Thomas, 306

parental leave, 310–11

Pariser, Eli, 199–200

Park, Todd, 144, 146–47

Pascal’s Wager, 361–62

Patacconi, Andrea, 246

Patil, D. J., 156

Patreon, 316–17

pattern recognition systems, 164–65

Paul, Sunil, 75–76, 82, 283–84

payment collection methods, 77–79, 84

pay-per-click vs. pay-per-impression ads, 161–62

Peek, Jerry, 38

Peers, Inc. (Chase), 84–85

Peer-to-Peer and Web Services Conference (2001), 27

peer-to-peer file sharing, 26–27

Pelosi, Nancy, 188

“People, Not Data” (Solomon), 143

Pereira, Fernando, 155–56

Perez, Carlota, 277

Perez, Tom, 194

Perl, 10–11, 15, 16–17, 120–21

personal agents, xiii, xiv–xvi, 82, 232, 233

Peterson, Christine, 17–18

Philadelphia, Pennsylvania, 138–40

Phoenix Project, The (Kim, Behr, and Spafford), 122

physical assets with digital footprint, 66–67

Pike, Rob, 105–6

Piketty, Thomas, 246, 272, 291

platforms, xxiv, 90–91

        algorithmic curation of information, 89

        Amazon’s development into, 111–13

        digital platforms and the real economy, 288–89

        evolution of, 91–92

        networked platforms, 67, 92–95

        and reputation systems, 181–90

        search engines, 39, 92, 157–59, 207, 288

        thick marketplace requirement, 95–105, 128, 133

        Uber as, 59–61

        See also Amazon; Google; government as a platform; networks

platform strategies, 109–10

        employees work inside the application, 119–24

        platform vs. application, 110–13

        promise-centered organizations, 113–19

pol.is, 200, 221–22

politics

        barriers to fresh thinking, 268–69

        and corporate malfeasance, 249–50

Power of Pull, The (Hagel, Brown, and Davison), 341

Practice of Management (Drucker), 250

principal component analysis (PCA), 221–22

privacy bullies, 178–79

profits and open source software, 24

Programming Perl (Wall), 10

promise-centered organizations, 113–19

promise theory, 115–19

public benefit corporations, 292

Putnam, Robert, 218–19, 320

QVC, 162–63

Rachmeler, Kim, 115–16, 117

racism, 21

Rackspace, 350

Rademacher, Paul, 127–28

Rand, Ayn, 69

RankBrain (Google), 165

Rasselas (Johnson), 313

Raw Deal (Hill), 184

Rawls, John, 181

Raymond, Eric, 8–9, 15–16, 17–18

RCA, 351

reality vs. abstraction, 21–22

redlining data, 178–79

RegTech, 175

regulations, 171–72

        defining the desired outcome, 173–75

        financial market speed vs., 172–73

        and government technology, 187–89

        improving outcomes, 175–76

        of labor, 190–98

        reputation systems in design of online platforms, 181–90

        role of sensors, 176–77

        and surveillance data, 177–81

        value of, 181–90

        and workers’ continuous partial employment, 190–98

regulatory capture, 187–88

REI, 244

Reinventing Discovery (Nielsen), 43

Remix, 140

repairs vs. sealed hardware, 337–38

reputation systems, 181–90

Resnick, Paul, 182

Reuther, Walter, 357

rhyming patterns, 5, 8, 13

Ries, Eric, 186

right to work laws, 262–63

Rilke, Rainer Maria, 353

Rinaudo, Keller, 370, 372

Rise and Fall of American Growth (Gordon), 243

Rise of the Robots, The (Ford), 269

Robbins, Jesse, 121

Roberts, Bruce, 285–88

Robinson, David, 130

Robinson, Kim Stanley, 96

robots and robotics

        competitive advantage of human touch, 311, 315, 330–31

        fears about, ix, 300

        filling the gap of not enough workers, 310

        and jobs, xx–xxi

        and laser eye surgery, xvii–xviii

        and people, at Amazon, 95

        the Robot Lawyer, 332

        robot tax proposal, 307

Rolf, David, 196, 262

Roman empire, xix

Romer, Paul, 249

Rosencrantz & Guildenstern Are Dead (Stoppard), xii

Rossman, John, 117

Roth, Alvin E., 98

Rothman, Simon, 196

Rushkoff, Douglas, 251

Rwanda, 370

Safari service for ebooks, 50, 344

Sanders, Bernie, 255

Saudi Arabia, 305–6

scenario planning, 358–67

Scheifler, Bob, 16

Schlossberg, Edwin, 3

Schmidt, Eric, 126, 129, 137

Schneier, Bruce, 177

Schrage, Michael, xiv, 58

Schulman, Andrew, 10

Schumpeterian profits, 296

Schumpeterian waste, 277–78

Schwartz, Peter, 359

Science and Sanity (Korzybski), 20

Scoble, Robert, 39

Search, The (Battelle), 161

search engine optimization, 160–61

search engines, 39, 92, 157–59, 207, 288. See also Google

Seattle, Washington, 138–40

Second Machine Age (McAfee), xxii–xxiii

secular stagnation, 271

Securities and Exchange Commission (SEC), 125–26

security on platforms, 135–36

self-driving vehicles, 232–33

        data collection for, 32–33, 34–35

        jobs resulting from, 94–95

        as manifestation of the global brain, 46

        National Highway Traffic Safety Administration regulations, 188–89

        for Uber and Lyft, x, 62–64

self-service marketplaces, 91

sensors, xviii–xix, 33, 34–35, 40, 41, 85, 176–77, 326

SETI@home project, 26

sewing as WTF? technology, 322–23

Shakespeare, 171

shareholder capitalism, 240–41, 245–51, 256, 263–68, 292

Shareholder Value Myth, The (Stout), 292

Shirky, Clay, 27, 91

Sidecar, 54–55, 77

Silicon Valley. See economy and Silicon Valley

Simon, George, 20

Site Reliability Engineering (SRE), 123, 146–47

Skynet moment, 241. See also financial markets

Slaughter, Anne-Marie, 309

Sloan Management Review, MIT, 153

Sloss, Benjamin Treynor, 123

Smart Disclosure and smart contracts, 180

smartphones, xiii, 76, 128

        Android operating system, 52

        difficulty doing repairs, 338

        iPhone, xiii, 32, 101, 128, 136

        navigation/location tracking, 83–84

        and sensors, 40, 41, 85

        thick marketplace for, 133

Smith, Adam, 262

Smith, Jeff, 349

SNAP (Supplemental Nutrition Assistance Program), 140–42, 266

social capital, 345–50

social infrastructure

        AI as part of, 353–54

        business intent to make money vs., 240–41

        corporate control of media content vs., 226–28

        fighting fake news with, 218–20

        Ponzi scheme elements, 355–56

        tools for building, 220–24

social media, 96–97, 207. See also individual platforms

“Social Responsibility of Business Is to Increase Its Profits” (Friedman), 240

software, 15, 35

        continuous improvement process, 30, 119–21, 122

        and DevOps, 121–23

        generative design, 327–28

        MapReduce, 325

        as organizational structure, 113–19

        Perl, 10–11, 15, 16–17, 120–21

        programmers as managers of, 153–54

        RegTech, 175

        for scheduling employees or ICs, 193

        See also Microsoft; open source software

“Software Above the Level of a Single Device” (O’Reilly), 31

solar energy, 326–27

Solomon, Jake, 141–43

Sony, 351

Soros, George, 210, 236

South by Southwest conference, 148–49

Southwest Airlines, 48–49

Spafford, George, 122

Spence, Michael, 67

sports and rewriting rules, 266–67

Spotify, 116

“Spy Who Fired Me, The” (Kaplan), 193

SRE (Site Reliability Engineer), 123, 146–47

Stallman, Richard, 6, 71, 72

stand-up meetings, 118

Stanton, Brandon, 370–71, 372

startups, 41, 186, 247, 275, 279, 282–85, 316

Steinberg, Tom, 146

Stern, Andy, 305

Sternberg, Seth, 332–33

“Stevey’s Platform Rent” (Yegge), 111–13

Stiglitz, Joseph, 255, 261, 266, 272–73

stock buybacks, 242–44, 245, 256

stock options, 247, 279–80

Stoppard, Tom, xii

Stout, Lynn, 292

Strickler, Yancey, 292

Strine, Leo, 292

structural literacy, 343–44

success as a by-product, 353. See also achievement

Sullenberger, “Sully,” 43

Sullivan, Danny, 157–58, 214

Summers, Larry, 271

Summit on Technology and Opportunity, 269–70

Sun Microsystems, 125, 126

sun-tracking system for solar farms, 326–27

supermoney, 276–79, 280–84, 289

Supplemental Nutrition Assistance Program (SNAP), 140–42, 266

Surely You’re Joking, Mr. Feynman (Feynman), 22, 340

surveillance, 177–81

Systemantics (Gall), 106

Taiwan, 221, 222–23

Taobao, 294

TaskRabbit, 67–68, 69

Taxicab, Limousine & Paratransit Association (TLPA), 93

taxi industry, 55–56, 60, 61–62, 183–86

Taxi Magic, 55–56

TCP/IP development, 107–8

technology, ix–xi, xviii, xxiii–xiv, 50–51, 124

        available ideas and tech limitations, 75–77, 79, 83

        available tech and ideas, 83–86, 96–98

        available tech and knowledge limitations, 79–80, 81–82

        disruptive technology, 351–52

        education system lagging behind, 335–36

        electronic devices for everyday use, ix, xiii

        and evolution of job skills, 347–50

        future of the economy scenario, 364–67

        innovation driving opportunity, 136

        innovation waves, xxiii, 46–47, 339

        learning by doing, 337–41, 345–50

        on-demand technology, 310

        pace of evolution, 336

        for reimagining the world, 86, 94–95

        rethinking how the world works vs., 322

        See also AI

Tesla, 33, 34–35, 63–64

Thain, John, 238

“Theory of the Firm” (Jensen and Meckling), 240–41

thick marketplaces, 98–105, 128, 133

“Thinking in Promises” (Burgess), 114

thinking in vectors, 35–36

thin value, 248–49

Thomas, Gibu, 177–78

Thompson, Clive, 347

Thrun, Sebastian, 163

Tiemann, Michael, 15–16, 17

Time Warner, 276

Tmall, 294

Tocqueville, Alexis de, 272–73

Tohuku earthquake and tsunami, Japan, 43

Ton, Zeynep, 197

Torvalds, Linus, 7, 14, 15–16

Transparent Society, The (Brin), 177

Trump, Donald, 149, 205, 255, 257, 269

trust, 181–90, 224–28

trusting strangers, 181–90

truth, 210–14, 220–24

Tsai, Jaclyn, 221, 222–23

Tucker, Eric, 206–7

Tumblr, 229–31

Turbeville, Wallace, 246

Turrings Cathedral (Dyson), 45

Twain, Mark, 5

Twilio, 84

Twitter, 42–47, 102, 206–7

Tyson, Laura, 67, 245

Uber (and Lyft), xi, 31, 46–47, 54–57, 85–86

        augmented drivers, 58–59, 69–70, 332

        background checks on drivers, 184

        building both sides of marketplace, 102

        business model maps, 57–61, 62–64, 65–70

        capitalization as startups, 77, 102, 284

        dispatch and branding services, 93–94

        driver employment status, 190–92

        driver incentives in new markets, 60–61

        driver rating system, 59–60, 183–84

        driver turnover problem, 61, 261

        economic impact report, 293–94

        as genrealized urban logistics system, 95

        market liquidity, 60–61

        paying for service automatically, 77, 84

        and pol.is in Taiwan, 221, 222–23

        and regulations, 62, 189–90

        and self-driving vehicles, x, 62–64

        sensor-based data collection, 33, 34–35, 41

        taxi companies’ response to, 61–62

        trip pricing algorithms, 60, 259–62

Udell, John, 26

UK GDS (Government Digital Service, United Kingdom), 144–45, 168–69

Unfinished Business (Slaughter), 309

unicorns, xi, xii–xviii. See also AI

United States, xxiii, xxv, 199–201, 255, 266, 267

United States Digital Service (USDS), 146–50

United Technologies, 256

universal basic income (UBI), 305–6, 307–11

Unix operating system, 6–7, 16, 338–39

Unix Power Tools (O’Reilly, Peek, and Loukides), 38

Unix Programming Environment, The (Kernighan and Pike), 105–6

Unix-to-Unix Copy Program (UUCP), 38

“Unreasonable Effectiveness of Data, The” (Halevy, Norvig, and Pereira), 155–56

Upwork, 68, 333–34

Usenet, 38

value creation, 17, 104, 246, 249–50, 291–92, 296–97, 354–55

value creation measures, 289–97

Vanguard, 244

Varian, Hal, xviii, 90, 122, 261, 290, 307–8, 314

vectors, 35–41

vehicles

        eliminating the safety-related weight, 66–67

        peer-to-peer car sharing, 76–77, 84–85

        See also self-driving vehicles

Velocity Conference, 121–22

vending machine government model, 129–30

venture capital, 247, 275, 279, 282–88

viruses, 45

Vogels, Werner, 113

Volcker, Paul, 239–40

von Kempelen’s Mechanical Turk, 119–20

Vonnegut, Kurt, 357–58

Wall, Larry, 10, 15–16

Wall Street Journal Blue Feed/Red Feed, 200

Walmart, 90, 265–68

Washington, DC, 138–40, 144

Watson, Thomas, Sr., 27

wealth inequality, 263–65

Wealth of Humans, The (Avent), 304

wealth of nations, 134

Weapons of Math Destruction (O’Neil), 167–68

Web 2.0, 28–31, 40

web spam, 160

Weil, David, 194

Welch, Jack, 241, 249, 251

welfare economics, 263, 266, 307

Weston, Graham, 350

WhatsApp, 102

Where 2.0 conference, 127

Whitehouse, Sheldon, 36

Who Do You Want Your Customers to Become? (Schrage), xiv, 58

Whole Internet User’s Guide & Catalog (Krol), 28

“Who’s Got the Monkey?” (Harvard Business Review), 204

Wikipedia, 43

Williams, Alan, 141–43

Williams, Evan “Ev,” 226–27

Woetzel, Jonathan, xxiii

Wolff, Steve, 79–81

World Wars I and II, results compared, xxv

World Wide Web, xii–xiii, 14, 26

        Apache server, 99

        as collective intelligence of users, 32–35

        data collection implications, 40

        evolution of webmaster position, 348

        as global brain developing a body, 45–47, 158, 235

        HTML as a learning by doing software, 339

        and Microsoft, 100

        services vs. applications, 30–31

        Web 2.0, 28–31, 40

        See also Internet

Yahoo!, 89, 285

Yahoo! Finance, 126

Y Combinator, 98, 306

Yegge, Steve, 111–13

yellow journalism, 208

Yiannopoulos, Milo, 205

Young, Bob, 24

YouTube, 102, 288–89, 316, 342

Zarsky, Tal, 181

Zeckhauser, Richard, 182

Zimmer, John, 77

Zimride, 77

Zipcar, 84–85

Zipline’s on-demand blood-delivery drones, 370

Zuckerberg, Mark, 187, 199, 201–2, 206, 218, 219–20, 302–3

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