The Formula_How Algorithms Solve All Our Problems... and Create More
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Adams, Douglas 2
Adorno, Theodor 179, 205
Adventures in the Screen Trade (Goldman) 161
Affectiva 193
Against Autonomy (Conly) 138–39
Agrippa (Gibson) 238n
Akrich, Madeline 136n
algorithms:
and Amazon’s “fulfilment associates” 44
and astronaut selection 24
and black-boxing 151–52, 227–28, 235–36
and call centers 21–22, 24–25, 49–50
cars driven by 141–42
in CCTV cameras 145–46
and death 96–98
and differential pricing 50–53
and differentiated search results 47–48
and discriminatory practices 53–54
for divorce 130–31
for drunk-driving detection 131–33
and early computer dating 82
and emotion sniffing 51–52
and equity market 210–11
and exclusive highways 48–49
explained 1–6
for finding love and sex 61–95 passim, 98–105; see also ALikeWise; BeautifulPeople; Bedpost; eHarmony; FindYourFaceMate; FitnessSingles; Internet: dating; Kari; LargeAndLovely; love and sex; “Match”; Match .com; OKCupid; PlentyOfFish; SeaCaptainDate; Serendipity; TrekPassions; UniformDating; VeggieDate
Flu Trends 238–39
to forecast crime 119–24; see also Berk, Richard; law and law enforcement
and gaming technology 32–34
“genetic” 203–4
growing role of 210
Iamus 206–7
inferences of, and conceptions of self 36–38
and Kari 98–103; see also love and sex
and legal documents 129–30
and London Symphony Orchestra 206
and “The Match,” see “Match”
measuring students’ progress with 39–41
and medic 211
and money laundering 18–19
and offence 224–27
and police work, public policy and judicial system, see law and law enforcement
and recruitment 25–31
and same-sex couples 147
and student grades 208, 212
and terrorism 149–50, 153
as “tricks” 221–23
and “truths” in art 182–83; see also art and entertainment
TruthTeller 237
and Twitter 35–36, 38
upward mobility programmed into 46–47
why we trust 149–51
ALikeWise 79
Amabot 214–15
Amazon 85, 188, 198
and disappearing gay-friendly books 232
e-books sold by 179–80
“fulfilment associates” at 44–45
how algorithms work with 1–2
and Solid Gold Bomb 224–25
two departments of 213–15
work practices at 44–46
Ambient Law 131–33, 137, 143–44
Amscreen 20
Anderson, Chris 56, 191n, 223
Angela (Quantified Self devotee) 14
see also Quantified Self movement
Aniston, Jennifer 69
Anomo 89–90
Apple 133
Apple v. Samsung 127–28
Apprentice, The (US) 89
Aquinas, Thomas 183
Aron, Arthur 101
art and entertainment 161–207
and dehumanisation 203–4
and films via Internet 179–80
and mass market 175–77
and Salganik–Dodds–Watts study 172–73
and “superstar” markets 173 see also Epagogix; individual participants; individual titles
artificial intelligence 126, 217
AT&T 29
Atlantic 11
Avatar 163, 172, 205
Avaya 49
Balloon Brigade 33
Barefoot Into Cyberspace (Hogge) 44
Barrymore, Drew 167
Barthes, Roland 186
Bauman, Zygmunt 81–82
BeautifulPeople 78
beauty map 31–32
Beck, Charlie 106–7
Bedpost 13, 93–95
Bedwood, David 97
Beethoven, Ludwig 202
Bellos, David 215
Benjamin, Walter 178–79
Bense, Max 182n
Bentham, Jeremy 55, 118
Berk, Richard 120–24, 236
Bezos, Jeff 190
Bianculli, David 189
Bieber, Justin 202–3
Blackstone Electronic Discovery 127–28
Blink (Gladwell) 211
blogging 30
and owners’ personalities 38–39
and word choice 38–39
body-hacking 13–14
BodyMedia 94
books, see art and entertainment
Bowden, B. V. 184
Bowden, Mark 11
Boyce, Vincent Dean 15–16
Bratton, William 108–10, 113
Brazier, David 70
Breathalyzer 143–44
Brownsword, Roger 138
Brynjolfsson, Erik 217
Burberry 52
Busa, Roberto 183
California Institute for Telecommunications and Information Technology 7
call centers 21–22, 24, 49
CalWIN 159
Cameron, David 113
Cameron, James 162–63
Carter, Steve 74–76
Casablanca 86
Catherine, Duchess of Cambridge 68
CBS 126
CCTV 145–46
CCTV Today 146
celebrity marriages, predicting breakup of 67–69
chatterbot 99
Cheney-Lippold, John 58–59
Chivers, Tom 135
Christensen, Clayton 129
Churchill, Winston 45
Cisco 49
Citron, Danielle 150, 153–54
Claburn, Thomas 239
Clarke, Arthur C. 221
Clegg, Nick 225
Click: What We Do Online and Why It Matters (Tancer) 3, 233–34
Clinical vs. Statistical Prediction (Meehl) 208
Coetzee, J. M. 203
cogito ergo sum (I think, therefore I am) 12
Colorado public-benefits system, errors in 153–54
Community 196
Comte, Auguste 114–16
Conboy, Kevin 13, 92–95
Conly, Sarah 138–39
cookies 17
Coughlan, Alexandra 201
Coupland, Douglas 16
CourseSmart 39–41
crime, see law and law enforcement
Crohn’s disease 10
Crosby, Michelle 131
Crowded Room 89
Cruise, Tom 68–69, 118
Csikszentmihalyi, Mihaly 100
Cuckoo’s Calling, The (Galbraith) 187
Culture of Public Problems, The (Gusfield) 142–43
“cyberbole” 210
origin of 4
DARPA 213
Darwin, Charles 31, 118
data-mining 10, 41, 67–68, 106, 126, 134–35, 150, 156, 158–60, 183, 187, 223
dating sim 103–4
Dawkins, Richard 129
de Botton, Alain 87
“De-Scription of Technical Objects, The” (Akrich) 136n
DeadSocial 96
death, apps concerning 96–98
decimated-reality aggregators 45–47
Deep Blue 29
deferred acceptance 63
see also “Match”
Deleuze, Gilles 54–55, 60
demassification 21
DeRose, Steven 194
Descartes, René 12
deviantART 37
Dialectic of Enlightenment (Adorno, Horkheimer) 179
Dick, Philip K. 118, 226
Die Walküre 70
differential pricing 50–52
digital humanities 3
“Digital Panopticon, The” (Poole) 55–56
“Digitizing the Racialized Body” (Hansen) 53
Disney 181
“dividuals” 54
divorce:
algorithm for 129
rate of 67, 71–72
“Do Artifacts Have Politics?” (Winner) 134
Dodds, Peter 172–76
Dominguez, Jade 25
Dostoyevsky, Fyodor 118
Dourish, Paul 231
Dow Jones 219
drunk driving 142–44
Eagle, Nathan 85
Ecker, David 206–7, 219
eHarmony 71, 74–77, 88
see also Internet; love and sex; Warren, Neil Clark
Eisenstein, Sergei 178
Electric Dreams 103
Ellul, Jacques 5, 56
EMD Serono 58
emotion sniffing 51–52
Emotional Optimisation 200–201
Enchanted Loom, The (Jastrow) 96
entertainment, see art and entertainment
Epagogix 165–68, 170–72, 176, 179, 191, 203, 205
Eric Berne Memorial Scientific Award 23
Essay on the Moral Statistics of France (Guerry) 117
“Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market” 173
Facebook 232, 241
and Facedeals 20
and facial recognition 215
how algorithms work with 2
jobs at 27
profiles, and people’s success 30–31
profiles, traits inferred from 37–38
Timeline feature on 38–39
and YouAreWhatYouLike 37
Facedeals 20
facial recognition and analysis 20, 33, 91, 146, 151, 193, 215
and Internet dating 78
Failing Law Schools (Tamanha) 216
Family Guy 196
Farewell to the Working Class (Gorz) 217–18
Fast Company 3, 35, 128, 220
on Amazon 44–5
Faster Than Thought (Bowden) 184
Faulkner, William 187
Feldman, Konrad 18–19
films, see art and entertainment
Filter Bubble, The (Pariser) 47
Fincher, David 189
Find the Love of Your Life (Warren) 73
FindYourFaceMate 78
Fitbit 13
FitnessSingles 78
Flash Crash 219
flexitime 43
Food Stamp Act (US) 154–55
Ford, Henry 44
Foucault, Michel 101
Fourastie, Jean 219
Freud, Sigmund 11
Friedman, Milton 218
Galbraith, Robert 187
Gale, David 62–63, 66
Galton, Francis 31–32
gaming technology 32–33
Gass, John 148
Gates, Bill 182
Geek Logik (Sundem) 67–68
gender reassignment 26
GenePartner 77–78
Generation X (Coupland) 16
Gibson, William 194n
Gild 25–26, 29–30
Gillespie, Tarleton 233
Gladwell, Malcolm 211
Goldman, William 161, 173
Good Morning America 67
Google 201–2
and auto-complete 225–27
claimed objectivity of 220–21
differentiated results from 46–48
dynamic-pricing patent granted to 50; see also differential pricing
employment practices of 41–42
and facial recognition 215
Flu Trends algorithm of 238–39
how algorithms work with 2
and inadvertent racism 151
and Lake Wobegone Strategy 27–29
Levy’s study of 41
and news-outlet decline 225–27
People Analytics Group within 41–42; see also web analytics
and self-driving cars 143, 213
Slate article on 41
and UAL 229
Google Earth 135
Google Glass 14, 26
Google Maps 16, 134–35
Google Street View 227
Google Translate 215, 221
Gorz, André 217
Gottschall, Jonathan 186
Gould, Stephen Jay 33–34
Graf, Daniel 135
graph theory 182
Grindr 89, 152
Guardian 84
Guattari, Félix 48, 54
Guerry, André-Michel 114–18
Gusfield, Joseph 142–43
Halfteck, Guy 32–34
Hansen, Mark 53
Hanson, Curtis 167
Heaven’s Gate 167
Henry VI (Shakespeare) 125–26
Her 103
Hitchcock, Alfred 17
Hogge, Becky 44
Holmes, Katie 68–69
Holmes, Oliver Wendell Jr. 158
Horkheimer, Max 179, 205
House of Cards 188–89
House of Commons, rebuilding of 45
How the Mind Works (Pinker) 80
Human Dynamics (at MIT) 85
Hume, David 199–200
Hunch 37, 234
Hunger Games, The 169
Hutcheson, Joseph C. Jr. 157
Iamus 206–7
IfIDie 96
In The Plex (Levy) 41
Industrial Revolution 21, 40
info-aesthetics 182
Information Age, coming of 21
Instagram 216
Interactive Telecommunications Program 15
Internet:
and cookies 17
dating 71, 75–79, 81; see also eHarmony; FindYourFaceMate; GenePartner; love and sex
growing access to 76–77
and scavenger-class customers 49–50
shopping via 16–17, 20; see also Amazon
tracking of user movements on 18
as transactional machine 46
and web analytics 18–19, 41; see also Google
iPhone 36
Is That a Fish in Your Ear? (Bellos) 215
Isaacson, Walter 36
Islendiga-App 88–89
Jackson, Joe 70
James, Henry 70
James, William 17
Jastrow, Robert 96
Jeopardy! 158
Jobs, Steve 36, 87
John Carter 163, 172
Jolie, Angelina 69
Jonze, Spike 103
JPod (Coupland) 16
judges 156–58
judicial behavior, predicting 156–59
and automated judges 160
jurimetrics 139–40, 158
Kahler Communications 24–25
Kahler, Dr. Taibi 22–24
Kardashian, Khloe 68
Kari 99–103, 105
Kasparov, Garry 29
Keillor, Garrison 28
Kelly, John 127–29
Kelly, Kevin 12
Kelvin, Lord 31
Kerckhoff,
Alan 77
Kindle 180, 197–98, 203
Kinect 132
Kipman, Alex 132
Kirke, Alexis 190–92, 194, 197
Knack 32–34
Knowledge Acquiring and Response Intelligence 99
Kodak 129, 216
Koppleman, Lee 134
Kranzberg, Melvin 151, 222
lactoferrin 10
Lake Wobegone Strategy 28–29
Lanier, Jaron 90–91, 199, 216, 239
LargeAndLovely 78
Lasswell, Harold 5
Late Age of Print, The (Stiphas) 221
Latour, Bruno 136, 235–36
law and law enforcement 106–33, 137–60
and age and gender 121–23
and Ambient Law 132, 137, 143–44
and automated judges 160
and bail and parole 119–21
and crime hotspots 110–112
and drunk-driving detection 131–33
and legal discovery 125–28
and “PreCrime” 118–19, 123–25
and predicting judicial behavior 155–60
and predictive policing 107–9, 119
and PredPol 113
and “RealCog” 120–21
and relative poverty 117
and rules vs. standards 141–43
and school students 125
Lawrence, Jennifer 169
LegalZoom 130
Leibniz, Gottfried 139–40
Lessig, Lawrence 139
Levitt, Theodore 217
Levy, David 104–5
Levy, Frank 212–13
Levy, Steven 41
Lewis, Sinclair 186–87
Li, Jiwei 35
Life & Times of Michael K (Coetzee) 203
Life on Screen (Turkle) 57
LinkedIn 27
Liquid Love (Bauman) 82
Liu, Benjamin 89
LivesOn 96–97
London Symphony Orchestra 206
Long Tail, The (Anderson) 56, 191n
Lorenz, Edward 171
Love in the Time of Algorithms (Slater) 81
love and sex:
algorithms and technology for 61–95 passim, 98–105, 239; see also ALikeWise; BeautifulPeople; Bedpost; eHarmony; FindYourFaceMate; FitnessSingles; Kari; LargeAndLovely; love and sex; “Match”; Match.com; OKCupid; SeaCaptainDate; Serendipity; UniformDating; VeggieDate
and celebrity marriages, see celebrity marriages, predicting breakup of
genetic matching for 77–78
Warren’s researches into 72–74
and wearable tech 94–5
see also divorce; “Match”; PlentyOfFish
Love and Sex with Robots (Levy) 104–5
Lovegety 87–88
Lucky You 167–68
Lust in Space 100
McAfee, Andrew 217
Macbeth (Shakespeare) 191
McBride, Joseph 164n
MacCormick, John 212, 222
McCue, Colleen 106–7
McLuhan, Marshall 88
Malinowski, Sean 107–14
Manovich, Lev 177–78