INDEX
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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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