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INDEX
A/B testing, 4–7, 9
accidents, classifying events as, 36–38
accuracy, machine learning and, 43
Acquia, 133
added value to products, open platforms and, 89–90
Adopt-a-Siren app, 91
agile development, 14, 83–85, 103, 140
Allenby, Braden R., 11–12, 158
AlphaGo, 2, 59–60, 160
Ancient Egyptians, Greeks, Hebrews, prediction and, 22–23
Anderson, Chris, 173
Angst & Panik, 112
Anscombe, Elizabeth, 188
anticipate-and-prepare strategy, 77–79
Apple, 89, 123–124
application programming interfaces (APIs), 88, 94, 103, 117, 136
applications (apps), 90, 91, 117
Aristotle, 149, 188, 190, 191, 192, 210n11
armillary, 47–48
Arnold, Henry “Hap,” 128
arrowheads, production process, 76–77
artificial intelligence (AI)
assigning moral decisions to, 184–189
explanations and, 66–68
governance of, 72–73
stages of innovation and, 159–160
See also Deep learning; Machine learning
artificial neural networks, 54, 60
Asimov, Isaac, 184, 185, 214n23
AT&T, 146, 154
Austin, J. L., 186–187
autonomous vehicles (AVs), optimization of, 68–73
Bacon, Francis, 150
Bacon, Roger, 153
Bain & Company, 129
Barlow, John Perry, 163
“Battle of the Book, The” (Swift), 150
Beckman, Johann, 210–211n23
behavior, nonrational levers for changing human, 174–175
Bentham, Jeremy, 182
Berners-Lee, Tim, 117
best practices, 82–83
bias, artificial intelligence and, 59, 67
Bing, 5, 104
Bitvore, 55, 67–68
Bjerknes, Vilhelm, 24, 44, 45
Bolcer, Greg, 55
Book of Why, The (Pearl), 104
Box, George E. P., 47
Bricklin, Dan, 45–46
Brown, John Seely, 94, 176
browsing, 97–99
Butler, Samuel, 160
Butterfield, Stewart, 81–82
Buytaert, Dries, 132–134, 135, 137
Cambridge Analytica, 120
Carr, Nicholas, 164
Carson, Rachel, 13
Casas, Josefina, 10
cascades, 115
Castle Wolfenstein/Castle Smurfenstein (games), 89–90, 204n28
categorization, meaning and, 190, 191
causality, interoperability as new, 109–119
causal models for machine learning, 114, 115
cause and effect, illusion of, 113–115
certainty, prediction and, 20–25
change, theory of, 8–11
Chaos Theory, 12–14, 45
Chengyu, 142
chicken sexing, 39–41
Chopra, Aneesh, 83, 85
Clairaut, Alexis Claude, 28–29
Clark, Andy, 165–166
Clark, David, 95
Clausewitz, Carl von, 126
clock metaphor, for workings of universe, 25–27, 116
Cloud Healthcare Pledge, 104
Cluetrain Manifesto, The (Levine, et al.), 17
Code for America, 91
Cold War strategy, 128, 130–131
complexity
beyond prediction, 14–15
deep learning and, 66
embrace of, 169–170
machine learning and, 7, 36
complex systems surrounding us, 11–12
computational irreducibility, principle of, 35
computer
introduction of, 32–33
as tool, 153–154
universe as vast, 34–35
conceptual models, 40–43
armillary and, 48
; construction of, 59
Mississippi River basin model and, 51–52
spreadsheets and, 46–47
tides and, 50
consequentialism, 182
Conway, John, Game of Life, 33–35, 161
Copernicus, Nicolaus, 47
copyright constraints, 99
counterfactual approach, 57
creativity, obscurity enabling, 143
credit score companies, model used to calculate, 55–56
Curie, Jeff, 55
Darwin, George, 49
data, transparency of, 72
Data.gov, 91
Davison, Lang, 94, 176
Dean, Howard, 133
“Declaration of the Independence of Cyberspace” (Barlow), 163
deep learning, 1–2, 15
complexity and, 66
human bias and, 59
simplification and, 60
Deep Patient, 1–2, 10, 53–55
Deming, W. Edwards, 82
Dennett, Daniel C., 34
deontology, 182, 188
differences, interoperability and, 109–111
digital networks, strategy and, 140
distance, interoperability and, 112
Da Vinci, Leonardo, 149
Doctrine of Double Effect, 183
Dr. Strangelove, or: How I Learned to Stop Worrying and Love the Bomb (film), 128
Dropbox, 81
Drucker, Peter, 125
Drunkard’s Walk, The (Mlodinow), 31
Drupal, 132–135, 137–138
earthquake prediction, 19–20, 24, 196n
ecosystem of interoperability, 116–119
effect, proportional to change, 10–11
18F (federal digital agency), 84
Einstein, Albert, 27
emergent effects, of complex systems, 13
empowerment, obscurity creating, 143
End of Competitive Advantage, The (McGrath), 129
“End-to-End Arguments in System Design” (Saltzer, Reed & Clark), 95
engagement, obscurity enabling, 143–144
“Equal Opportunity” fairness, 186
Erewhon (Butler), 160
events, classifying as accidents, 36–38
Everything Bad Is Good for You (Johnson), 178
explanations, 62–68, 170–172
artificial intelligence and, 66–68
for crash of JAL 123, 62–65
levers without, 173–175
optimization over, 68–73
as social acts, 64–65
use of, 67–68
for war, 65–66
Facebook, 85–87, 106, 120, 190
fairness
“Equal Opportunity,” 186
machine learning and, 186–187
Fan Hui, 2
Ferguson protests, 92
Fermat, Pierre de, 30
Ferrentino, Marc, 106
FICO, 55–56, 67–68
Figuier, Louis, 211n23
Fitbit, 90
Flickr, 112
flip-chart strategies, 130, 132
Foo Camp “unconferences,” 93–94
Foot, Philippa, 183
Ford, Henry, 76, 82
forecasts
predictions vs., 197n4
statistical, 44–45
Foucault, Michel, 119–120
Fourth Paradigm, 173
Frankston, Bob, 46
Freedman, Lawrence, 126
Frischmann, Brett, 69
future, control of, 192–193
Future of Ideas, The (Lessig), 154
Future of the Internet, and How to Stop It, The (Zittrain), 156
Galaxy Note 7, 8
Galileo, 47
Game of Life, 33–35, 161
Game of Thrones (television series), 180
Gardner, Martin, 34
Gasser, Urs, 103, 110
generative adversarial network, 160
generative progress, 160–163
generativity
internet and, 155–157
traditional progress vs., 157–159
Gibson, Stanford, 51
Gilligan, Carol, 187
GitHub, 92–93, 154–155, 157
Go (game), 2
See also AlphaGo
Google, 54, 104, 173
A/B testing and, 5
AlphaGo, 2, 59–60, 160
dumbbell recognition in machine learning system, 59, 189, 191–192
Knowledge Graph, 190
Schema.org and, 105
search engine, 97–98
TensorFlow, 136–137, 138, 154
Google Photos, 112
government
new practices recognizing chaos beneath apparent order, 14–15
as platform, 91
Grand Theft Auto V (game), 90
graphs, 86, 105–106, 190
gravitation, Newton’s theory of universal, 26, 28, 206n16
gravity, Occupy movement and, 176–177
Gray, Jim, 173
ground truth, 42
Hagel, John, 94, 176
Halley, Edmund, 27–28
Halley’s comet, 28–29, 30
handwriting recognition, machine learning and, 41–43
Hannay, Timo, 170
Hardt, Moritz, 186
Harvard University Library, 98–99
Hashtags, Twitter, 113, 117–118, 177
HealthCare.gov site launch, 83–84
Hedberg, Mitch, 151
Hidden Persuaders (Packard), 174
Hillis, Daniel, 113–115
History of Inventions (Beckman), 210–211n23
History of Technology (5 volumes), 152, 210n23, 211n24
Hitler, Adolf, 65–66
Hooke, Robert, 27
Horsey, Richard, 39
Huawei, 142
hugeness (scale) of machine learning and the internet, 7
Hume, David, 114
Huygens, Christian, 30–31
hyperlinks, 112
IBM, 33, 104
ice water challenge, 10
id Software, 89–90
IFTTT (If This Then That), 117
IMVU, 80–81
In a Different Voice (Gilligan), 187
Inevitable’s, The (Kelly), 95
innovation, artificial intelligence and, 159–160
In Search of Excellence (Peters), 82
internet
architected for unanticipation, 95–96
collections of information on, 99–100
experience of chaos and, 118
generativity and, 155–157
interoperability and, 7, 104, 116, 155, 156
machine learning and, 6–7
unpredictability and, 101
Internet of Things, 111
interoperability, 101–121
defined, 102
internet and, 104, 116, 155, 156
as new causality, 109–119
possibilities and, 139–142
signs and, 119–121
standards and, 102–108
Interop (Palfry & Gasser), 103, 110
inverted cascades, 115
IRC (Internet Relay Chat), 81
I Robot (Asimov), Three Laws of Robotics, 184, 185
JAL 123, crash of, 62–65
Jennings, Andrew, 55–56
Jobs, Steve, 123–124
Johnson, Steven, 178
Jomini, Antoine Henri, 206n16
Kahn, Herman, 128
Kant, Immanuel, 115
Kelly, Kevin, 95
Kelvin (Lord), 49–50
King, Martin Luther, Jr., 148
knowledge
imperfection of human, 3–4, 26
technological progress and, 151, 161
truth and, 40
Knowledge Graph, 190
Knox, Bernard, 23
Kubrick, Stanley, 128
Kuhn, Thomas, 61, 158
Kurzweil, Raymond, 34
Lalande, Joseph Jérôme Lefrançois de, 28–29
Laplace, Pi
erre-Simon, 26–27, 31, 49, 50, 116, 170
Laplace’s demon, 26, 35, 44–45
laws, idea that things happen according to, 8–9
See also Newton, Isaac
Lean Startup, The (Ries), 80
Lego Group, 102
Lepaute, Nicole-Reine Étable de la Brière, 29
Lessig, Lawrence, 154
levers, function of, 176–177
Levy, Steven, 46
libraries, browsing and, 98–99
Linnaeus, Carl, 182, 190, 191
Lorenz, Edward, 12
machine learning, 2, 3, 15, 117
accuracy and, 43
chicken sexing and, 40–41
conceptual models and, 52
constantly changing models of, 61–62
embrace of complexity and, 36
“explanations” and, 172
fairness and, 186–187
handwriting recognition and, 41–43
internet and, 6–7
interoperability and, 7, 103–104
optimization and, 68–73
prediction and causal models, 114, 115
signs and, 120–121
undoing idea that human mind attuned to truth of universe, 167
working models and, 53–62
Managing for Results (Drucker), 125
Martin, George R. R., 180
mash up data, 15
McAlister, Matt, 87–88
McGrath, Rita Gunther, 129, 131, 140
McLuhan, Marshall, 159
McNamara, Robert, 188
McNealy, Scott, 124, 139
meaning
explanations, 170–172
levers without explanations, 173–175
morality and, 181–189
notion of, 189–192
rejection of lever-based of change, 175–177
storytelling and, 178–181
Menelaus, 125–126
metaphors
clock, 25–27, 116
shaping our experience through, 116
microformats, 107–108, 117
Microsoft, 104, 107
military strategy, 126, 127–128, 130, 207n7
minimum viable product (MVP), 14, 80–83
Mississippi River basic model, 50–53
Mittelstadt, Brent, 57
Mlodinow, Leonard, 31
modding/mods, 15, 89–90, 103, 117, 204n28
model-free explanations, 173
models
explanations and, 63
purpose of, 52–53
weather, 44–45
See also Conceptual models; Working models
Model T’s design process, 76
MONIAC (Monetary National Income Analogue Computer), 50–51, 52
morality, 181–189
motivational research (MR), 174–175
Mullen, Edward, 84
Musk, Elon, 69, 135, 136