Page numbers listed correspond to the print edition of this book. You can use your device’s search function to locate particular terms in the text.
Abbott, Kathy, 55
accidents:
automotive, 7, 70, 91, 153, 154–55, 207, 208
plane, 43–45, 54, 55, 154, 169–70
accountants, accounting firms, 76–77
action, human, 85, 132, 147–51, 160, 210, 213–14, 215, 217, 218
hierarchy of, 65–66
Adams, Thomas, 191
adaptive automation, 165
Addiction by Design (Schüll), 179n
agriculture, 218, 222
Airbus A320 passenger jet, 50–52, 154
Airbus Industrie, 50–52, 168, 169–70
Air Force, U.S., 173
Air France Airbus A330, 45, 54, 169–70
airlines, 1, 43–46, 53–55, 59, 168–70, 172–73
air-traffic control, 170
Albaugh, James, 59
alert fatigue, 104
algorithms, 116–22
ethics and, 183–84, 186–87
predictive, 116–17, 123, 198
Amazon, 118, 195
American Health Information Community, 94
American Machinist, 34, 174
Andreessen, Marc, 40
Android, 153, 199
animals:
body-object blending in, 150–51
killing of, 183–84, 185
animal studies, 87–92, 133, 219
antiaircraft guns, 35–36, 37, 41
anxiety, 14, 16, 19, 59, 220
Aporta, Claudio, 126–27
Apple, 41, 118, 136, 203
apprenticeship, 109, 113, 147
apps, 12, 13, 17, 33, 40, 91, 133, 202
gamification and, 179n
see also specific apps
architects, architecture, 12, 69, 137–48, 167
“Are Human Beings Necessary?” (Russell), 39
Arendt, Hannah, 108, 227–28
Aristotle, 144, 224, 226
Army Air Forces, U.S., 49
Aronowitz, Stanley, 27–28
Arthur, W. Brian, 196–97
Arthur D. Little, 37
artificial intelligence, 111, 113, 118–20, 187
artistic skills, 10, 85
Asimov, Isaac, 184, 189, 257n
Asimov’s Rules of Robotics, 184, 257n
assembly lines, 34, 38, 39, 195
Associated Press, 29, 58
attention, 200, 219
attentional capacity, 90–91
attentional tunneling, 200–201, 202
attention deficit hyperactivity disorder, 220
automaticity, 81–85, 105–6
automatic transmission, 4, 5–6, 13–14
automation, 1–21, 30, 32–40, 59
attempts to rein in, 170–72
elements that characterize, 36
faith in, 65–66
fallacy about, 67
flight, 43–63, 100
in health care, 93–106
hierarchy of, 110–11
human- vs. technology-centered view of, 153–75
important and unsettling direction of, 193–99
invention and definition of word, 34–35, 237n
limits of, 10–11
tool-user bond weakened by, 223
Yerkes-Dodson law and, 90–91
see also specific topics
Automation (Illingworth cartoon), 19, 33
Automation and Management (Bright), 111–12
automation bias, 67–72, 122
automation complacency, 67–69, 71, 72, 74
Automation: Friend or Foe? (Macmillan), 19–20
automation paradox, 91
Automation Specialties, 174
“Automation Surprises” (Sarter, Woods, and Billings), 162
automatization (proceduralization), 81–85
autonomy, 38, 61, 106, 108, 128, 131
autopilot, 43–63, 153, 154
Autor, David, 32
aviation, 43–63, 91, 100, 137–38, 215, 223
technology- vs. human-centered automation in, 165–66, 168–70, 172–73
see also autopilot
Bainbridge, Lisanne, 157, 160
banks, banking, 115, 170–71
Baxter, Gordon, 77
behavior, changes in, 67, 97–100
being, 131, 133
Berardi, Franco, 118
Bhana, Hemant, 53
Bhidé, Amar, 77
bicycles, 51, 61
big data, 114
Big Data (Cukier and Myer-Schonberger), 122
Billings, Charles, 162
Bilton, Nick, 204
body, 11, 63, 132, 159, 162, 165, 213–14, 215–20, 222–23, 224
mind vs., 148–51, 215, 216
sketching and, 142–43
transport and, 132
Boeing, 27, 168–69, 170
Boeing 737, 56
Bombardier Q400 turboprop, 43–44
bombsight technology, 49
Bonin, Pierre-Cédric, 45, 168–70
boredom, 5, 14, 16
Boy’s Will, A (Frost), 212, 221
brain, 9–12, 20, 79–84, 148–51, 165, 169, 219
computer compared with, 119, 151
concentration and, 200
knowledge and, 9–10
navigation and, 129–33
of pilot, 57
technological, 36, 237n
Braverman, Harry, 109–10
Bright, James, 110–12, 115, 237n
Brillhart, Jacob, 147
Brin, Sergey, 199–201
Brooks, David, 128, 132
Brynjolfsson, Erik, 28–29, 30
Buffalo crash, 43–45, 154
Bush, George W., 93–94
business, 18, 28, 29, 30, 37, 38, 76, 112, 117, 168, 174–75, 196, 228
Buzsáki, György, 134–35
C-54 Skymaster transport plane, 49, 50
Cachin, Emil, 46–47, 232
California Polytechnic State University, 189
Campbell, Donald T., 122
cancer, 70–71
capital investments, 18, 28, 30, 31
capitalism, 21–22, 24, 28, 31, 109, 116, 160
Carlsen, Magnus, 82
cars and driving, 3–18, 34, 46
accidents, 7, 70, 91, 153, 154–55, 207, 208
author’s experience with, 3–6, 13–14, 80, 81
automation bias and, 69–70
GPS in, 128, 130, 136–37
luxury, 8
manual vs. automatic transmission in, 3–6
paper maps and, 130
self-driving, 6–8, 10, 12, 13, 120, 153–56, 183–87, 193, 204, 207, 208
while sleepy, 71–72
Cartesian dualism, 148–49
Cartlidge, John, 77
cartoons, 19, 33
Caruthers, Felix P., 174
cascading failures, 155
Centers for Disease Control, 220
Cerner Corporation, 96
Chabris, Christopher, 201
Chapanis, Alphonse, 158
Checklist Manifesto, The (Gawande), 104
Cheng, Britte Haugan, 73
chess playing, 12, 121
China, 31, 167
Churchill, Winston, 139
CIA, 120
Cisco, 195
City University London, 70
Clark, Andy, 149–51
Clarke, Arthur C., 197–98
cloud computing, 195, 202, 209
cognition, cognitive skills, 11–12, 56–58, 71–74, 81, 120, 121, 148–51, 165
of doctors, 105
embodied, 149–51, 213
cognitive map, 129–30, 135
cognitive psychologists, 72–76, 81, 129–30
Colgan Air, 45
communication, 36, 163, 198
doctor-patient, 103–6
Communist Manifesto (Marx and Engels), 225
computer-aided design (CAD), 138–42, 144, 145, 167, 219, 229–30
computer games, 75, 177–80, 219
computer programmers, 161, 162, 168
computers, 1, 2, 17, 33, 37, 38, 40, 159
architecture and design and, 138–47
automation and, 36, 43, 50–58, 62, 66–67, 69, 90, 91, 202–3
aviation and, 43, 46, 50–52, 54, 55, 57, 62, 153, 168, 170, 172–73
avocations and, 12
benefits of transferring work to, 17–18
boundary between humans and, 10–12
brain compared with, 119, 151
capabilities of, 8–9
in cars, 7, 8–9
costs of transferring work to, 18, 28, 30, 66–67
dependency on, 12–13
effects on workload of, 90, 91
ergonomics and, 164–68
expectation of aid of, 193–95
health care and, 93–106
human compared with, 153
as media devices, 219
memory experiment and, 79
mental processes and, 74
monitoring of, 17
oracle machine, 119–20
satellite-linked, 125–37
speed of, 118–22, 139, 156, 164, 173, 219
vocations and, 12
wearable, 12, 201
white-collar, 93–106
computer scientists, 156
computer simulation models, 93, 97
concentration, 200
Concours de la Sécurité en Aéroplane, 46
consciousness, 83, 119n, 121, 148–49, 150, 187
Continental Connection, 43–45, 54, 154
corporate auditors, 115
Cowen, Tyler, 31
craft workers, 23, 106, 109
Crawford, Kate, 122–23
Crawford, Matthew, 147–48
creativity, 10, 12, 14, 143, 144, 167, 206, 229
Cross, Nigel, 143–44
Csikszentmihalyi, Mihalyi, 14–16, 18, 85, 228–29
Cukier, Kenneth, 122
culture, 124, 131, 196, 198, 217, 220, 226
Curtiss C-2 biplane, 46–47
cutting grass, 215–16
Cybernetics, or Control and Communication in the Animal and the Machine (Wiener), 38–39
cyborgs, 2
dancing mice, 87–92
Dancing Mouse, The (Yerkes), 85–86
DARPA (Department of Defense laboratory), 165
Dassault, 140
data, 113, 114, 117, 119–22, 136, 167, 248n
data fundamentalism, 122–23
data processing, 17, 195
decision aids, automated, 113–15, 166
drawbacks to, 77
decision making, 160, 166, 168
decision trees, 113–14
declarative knowledge, 9, 10–11, 83
Deep Blue, 12
degeneration effect, 65–85
automation complacency and bias and, 67–72
Whitehead’s views and, 65–67
dementia, 135–37
dependency, 130, 133, 136, 146, 203, 225
depression, 220
Descartes, René, 148, 216
design, designers, 137–47
computer-aided (CAD), 138–42, 144, 145, 167, 219, 229–30
human- vs. technology-centered automation and, 158–62, 164–65, 167–70, 172
parametric, 140–41
system, 155–57
video games as model for, 178–82
Designerly Ways of Knowing (Cross), 143–44
desire, 15, 17, 20, 83, 161, 206–7, 210
to understand the world, 123–24
deskilling, 55, 100, 106–12, 115
Dewey, John, 148, 149, 220
diabetes, 245n–46n
diagnostic testing, 70–71, 99, 102
DiFazio, William, 27–28
Digital Apollo (Mindell), 60, 61
disease, 70–71, 113, 135–37, 245n–46n
dislocation, 133
Do, Ellen Yi-Luen, 167
Doctor Algorithm, 154, 155
doctors, 12, 32, 70, 93–106, 114–15, 120, 123, 147, 155, 166, 173, 219
evidence-based medicine (EBM) and, 114, 123
patient’s relationship with, 103–6
primary-care, 100–104, 154
document discovery, 116
Dodson, John Dillingham, 88–89
Dorsey, Jack, 203
Dorsey, Julie, 167–68
Dostrovsky, Jonathan, 133
dot-com bubble, 117, 194, 195
drawing and sketching, 142–47
Dreyfus, Hubert, 82
driving, see cars and driving
drone strikes, 188
drugs, prescription, 220–21
Drum, Kevin, 225
Dyer-Witheford, Nick, 24
Dyson, Freeman, 175
Dyson, George, 20, 113
Eagle, Alan, 176
Ebbatson, Matthew, 55–56, 58
ebook, 29
economic growth, 22, 27, 30
economic stability, 20
Economist, 225
economists, 9, 18, 22, 29, 30, 32–33, 109
economy, economics, 20, 25–33, 117
e-discovery, 116
education, 113, 120, 153
efficiency, 8, 17, 26, 58, 61, 114, 132, 139, 159, 173, 174, 176, 219
EMR and, 101, 102
factories and, 106–8
electric grid, 195–96
electronic medical records (EMR), 93–106, 114, 123, 245n–46n
embodied cognition, 149–51, 213
Emerson, Ralph Waldo, 16, 232
End of Work, The (Rifkin), 28
engagement, 14, 165
Engels, Friedrich, 225
Engineering a Safer World (Leveson), 155–56
engineers, 34, 36–37, 46, 49, 50, 54, 59, 69, 119, 120, 139, 157–60, 162, 164, 168, 174, 175, 194, 196
Enlightenment, 159–60
entorhinal cortex, 134, 135
equilibrium, of aircraft, 61–62
ergonomics (human-factors engineering), 54, 158–60, 164–68
Ericsson, K. Anders, 84
essay-grading algorithms, 206
ethical choices, 18, 61, 183–93, 221–22
killer robots and, 187–93, 204
self-driving cars and, 183–87, 193, 204
top-down vs. bottom-up approach to, 189–91
Ethics and Emergency Science Group, 189
European Aviation Safety Agency, 58
evidence-based medicine (EBM), 114, 123
evolution, 137
experience, 1, 23, 121, 123, 124, 150, 190, 218, 219, 226
Experience Music Project, 140
“experience sampling” study, 14–15, 18
expert systems, 76–77
explicit knowledge, 9, 10–11, 83
eyeglasses, computerized, 199–202
eyes, 143, 148, 201, 216, 223
retina, 149–50
Facebook, 181–82, 201, 203, 205–6
factories, 22–26, 28, 106–8, 112, 118, 159, 174, 195, 222
Farrell, Simon, 74
Federal Aviation Administration (FAA), 1, 55, 170
feedback, 36–37, 84, 85, 105, 114, 160, 165, 169
negative, 71–72
from video games, 178–79
finance, 115–16, 120, 170–71, 173
financial meltdown (2008), 77
Fitts, Paul, 158
Flight, 50, 59
flight automation, 1, 49–63
flight crews, 59
flight engineers, 59
flight simulators, 56, 200–201
flow, 84–85, 96, 179, 213
Flow (Csikszentmihalyi), 14–15
fly-by-wire controls, 51–52, 55, 154, 168
Forces of Production (Noble), 173–74
Ford Motor Company, 34, 35, 38, 39
Ford Pinto, 5
France, 36, 45, 46, 159, 171
Frankenstein, Julia, 129–30
Frankenstein monster, 26, 30
freedom, 17, 61, 207, 208, 226, 227, 228
freight shipment, 196–97
friction, 133, 181, 182
frictionlessness, 180, 220
frictionless sharing, 181–82
Frost, Robert, 211–16, 218, 221–22, 232
future, futurism, 226–28
Gallagher, Shaun, 150
gamification, 179n
Gates, Bill, 197
Gawande, Atul, 104
GE, 31, 175, 195
Gehry, Frank, 140
General Motors, 27
generation effect, 72–80, 84–85, 165
genetic traits, 82–83
Gensler, 167
German Ideology, The (Marx), 235n
Giedion, Sigfried, 237n
Gilbert, Daniel, 15
glass cockpits, 50, 55, 59, 168, 169
Goldberger, Paul, 141
Google, 6–8, 13, 78–80, 118, 176, 181, 182, 195
cars, 6–8, 10, 12, 13, 153, 154–55, 183, 207, 208
Google Glass, 136–37, 199–201, 203, 208
Google Maps, 132, 136, 204–5
Google Now, 199
Google Suggest, 181, 200
Google Ventures, 116
Gorman, James, 134
GPS, 52, 68–70, 126–37, 144
“GPS and the End of the Road” (Schulman), 133
Graves, Michael, 143, 145
Gray, J. Macfarlane, 36–37
Great Britain, 22–23, 35, 157
Great Depression, 25–26, 27, 29, 38
grid cells, 134
Groopman, Jerome, 97–98, 105
Gross, Mark, 167
Gundotra, Vic, 203
gunnery crews, 35–36, 41
guns, 35–38, 41, 185
habit formation, 88–89
Hambrick, David, 83
hands, 143, 144, 145, 216
happiness, 14–16, 137, 203
hardware, 7–8, 52, 118
Harris, Don, 52–53, 63
Hartzband, Pamela, 97–98
Harvard Psychological Laboratory, 87
Hayles, Katherine, 12–13
Health Affairs, 99
Health and Human Services Department, U.S., 94, 95
health care, 33, 173
computers and, 93–106, 113–15, 120, 123, 153–54, 155
costs of, 96, 99
diagnosis in, 10, 12, 70–71, 105, 113–15, 120, 123, 154, 155
see also doctors; hospitals
Health Information Technology Adoption Initiative, 93–94
Heidegger, Martin, 148
Hendren, Sara, 130–31
Heyns, Christof, 188–89, 192
hippocampus, 133–37
Hippocrates, 158
history, 124, 127, 159–60, 174, 227
Hoff, Timothy, 100–102
Hoover, Herbert, 26
hospitals, 94–98, 102, 123, 155, 173
How Doctors Think (Groopman), 105
How We Think (Hayles), 13
Hughes, Thomas, 172, 196
human beings:
boundaries between computers and, 10–12
change and, 39, 40
killing of, 184
need for, 153–57
robots as replications of, 36
technology-first automation vs., 153–76
Human Condition, The (Arendt), 108, 227–28
humanism, 159–61, 164, 165
Human Use of Human Beings, The (Wiener), 37, 38
Huth, John Edward, 216–17
iBeacon, 136
IBM, 27, 118–20, 195
IBM Systems Journal, 194–95
identity, 205–6
IEX, 171
Illingworth, Leslie, 19, 33
imagination, 25, 121, 124, 142, 143, 215
inattentional blindness, 130
industrial planners, 37
Industrial Revolution, 21, 24, 28, 32, 36, 106, 159, 195
Infiniti, 8
information, 68–74, 76–80, 166
automation complacency and bias and, 68–72
health, 93–106, 113
information overload, 90–92
information underload, 90–91
information workers, 117–18
infrastructure, 195–99
Ingold, Tim, 132
integrated development environments (IDEs), 78
Intel, 203
intelligence, 137, 151
automation of, 118–20
human vs. artificial, 11, 118–20
interdependent networks, 155
internet, 12–13, 33n, 176, 188
internet of things, 195
Introduction to Mathematics, An, (Whitehead), 65
intuition, 105–6, 120
Inuit hunters, 125–27, 131, 217–20
invention, 161, 174, 214
iPads, 136, 153, 203
iPhones, 13, 136
Ironstone Group, 116
“Is Drawing Dead?” (symposium), 144
Jacquard loom, 36
Jainism, 185
Jefferson, Thomas, 160, 222
Jeopardy! (quiz show), 118–19, 121
Jobless Future, The (Aronowitz and DiFazio), 27–28
jobs, 14–17, 27–33, 85, 193
automation’s altering of, 67, 112–20
blue-collar, 28, 109
creating, 31, 32, 33
growth of, 28, 30, 32
loss of, 20, 21, 25, 27, 28, 30, 31, 40, 59, 115–18, 227
middle class, 27, 31, 32, 33n
white-collar, 28, 30, 32, 40, 109
Jobs, Steve, 194
Jones, Michael, 132, 136–37, 151
Kasparov, Garry, 12
Katsuyama, Brad, 171
Kay, Rory, 58
Kelly, Kevin, 153, 225, 226
Kennedy, John, 27, 33
Kessler, Andy, 153
Keynes, John Maynard, 26–27, 66, 224, 227
Khosla, Vinod, 153–54
killing, robots and, 184, 185, 187–93
“Kitty Hawk” (Frost), 215
Klein, Gary, 123
Knight Capital Group, 156
know-how, 74, 76, 115, 122–23
knowledge, 74, 76, 77, 79, 80–81, 84, 85, 111, 121, 123, 131, 148, 153, 206, 214, 215
design, 144
explicit (declarative), 9, 10–11, 83
geographic, 128
medicine and, 100, 113, 123
tacit (procedural), 9–11, 83, 105, 113, 144
knowledge workers, 17, 148
Kool, Richard, 228–29
Korzybski, Alfred, 220
Kroft, Steve, 29
Krueger, Alan, 30–31
Krugman, Paul, 32–33
Kurzweil, Ray, 181, 200
labor, 227
abridging of, 23–25, 28–31, 37, 96
costs of, 18, 20, 31, 175
deskilling of, 106–12
division of, 106–7, 165
intellectualization of, 118
in “Mowing,” 211–14
strife, 37, 175
see also jobs; work
Labor and Monopoly Capital (Braverman), 109–10
Labor Department, U.S., 66
labor unions, 25, 37, 59
Langewiesche, William, 50–51, 170
language, 82, 121, 150
Latour, Bruno, 204, 208
lawn mowers, robotic, 185
lawyers, law, 12, 116–17, 120, 123, 166
learning, 72–73, 77, 82, 84, 88–90, 175
animal studies and, 88–89
medical, 100–102
Lee, John, 163–64, 166, 169
LeFevre, Judith, 14, 15, 18
leisure, 16, 25, 27, 227
work vs., 14–16, 18
lethal autonomous robots (LARs), 188–93
Levasseur, Émile, 24–25
Leveson, Nancy, 155–56
Levesque, Hector, 121
Levinson, Stephen, 101
Levy, Frank, 9, 10
Lewandowsky, Stephan, 74
Lex Machina, 116–17
Licklider, J. C. R., 223
Lieberman, Matthew, 149
Lindbergh, Charles, 223
Lown, Beth, 103, 105
Luddites, 23, 106, 108, 231
Ludlam, Ned, 23
MacCormac, Richard, 142–43
Machine Age, 25
machine-breaking, 22–23
machine-centered viewpoint, 162–63
machine learning, 113–14, 190
machines, mechanization, 17–18, 20–41, 107–8, 110–12, 159, 161, 223, 237n
economy of, 31
as emancipators, 24–25
at Ford, 34
long history of ambivalence to, 21–41
love for, 20
planes and, 51, 52
ugliness of, 21
machine tool industry, 174
Macmillan, Robert Hugh, 19–20, 21, 39
mammograms, 70–71, 100
management, 37, 38, 76, 108, 166, 175
“Man-Computer Symbiosis” (Licklider), 223
manual transmission, 3–6, 13, 80
manufacturing, 5, 22, 30, 31, 37, 38, 106–7, 139, 195
plane, 46, 52, 168–70
Manzey, Dietrich, 71
maps, 127, 151, 204–5, 219, 220
cognitive, 129–30, 135
paper vs. computer, 129–30
Marcantonio, Dino, 141
“March of the Machines” (TV segment), 29
Marcus, Gary, 81, 83, 184
Marx, Karl, 20, 23–24, 66, 224, 225, 235n
Marx, Leo, 160
master-slave metaphor, 224–26
materiality, 142–43, 145, 146
mathematicians, 119, 156
Mayer-Schönberger, Viktor, 122
McAfee, Andrew, 28–29, 30
Meade, E. J., 146–47, 229–30
meaning, 123, 220
medical diagnosis, 10, 12, 70–71, 105, 113–15, 120, 123, 154, 155
Medicare, 97
Mehta, Mayank, 219–20
Meinz, Elizabeth, 83
Meister, David, 159
memory, 72–75, 77–80, 84, 151
drawing and, 143
navigation and, 129–30, 133–37
Men and Machines, 26
mental models, 57
Mercedes-Benz, 8, 136–37, 183
Mercury astronauts, 58
Merholz, Peter, 180
Merleau-Ponty, Maurice, 216, 217–18, 220
metalworkers, 111
mice, dancing, 87–92
microchips, 8, 114
microlocation tracking, 136
Microsoft, 195
military, 35–37, 47, 49, 158, 159, 166, 174
robots and, 187–93
mind, 63, 121–24, 201, 213–14, 216
body vs., 48–51, 215, 216
computer as metaphor and model for, 119
drawing and, 143, 144
imaginative work of, 25
unconscious, 83–84
Mindell, David, 60, 61
Missionaries and Cannibals, 75, 180
miswanting, 15, 228
MIT, 174, 175
Mitchell, William J., 138
mobile phones, 132–33
Moore’s Law, 40
Morozov, Evgeny, 205, 225
Moser, Edvard, 134–35
Moser, May-Britt, 134
motivation, 14, 17, 124
“Mowing” (Frost), 211–16, 218, 221–22
Murnane, Richard, 9, 10
Musk, Elon, 8
Nadin, Mihai, 80
NASA, 50, 55, 58
National Safety Council, 208
National Transportation Safety Board (NTSB), 44
natural language processing, 113
nature, 217, 220
Nature, 155
Nature Neuroscience, 134–35
navigation systems, 59, 68–71, 217
see also GPS
Navy, U.S., 189
Nazi Germany, 35, 157
nervous system, 9–10, 36, 220–21
Networks of Power (Hughes), 196
neural networks, 113–14
neural processing, 119n
neuroergonomic systems, 165
neurological studies, 9
neuromorphic microchips, 114, 119n
neurons, 57, 133–34, 150, 219
neuroscience, neuroscientists, 74, 133–37, 140, 149
New Division of Labor, The (Levy and Murnane), 9
Nimwegen, Christof van, 75–76, 180
Noble, David, 173–74
Norman, Donald, 161
Noyes, Jan, 54–55
NSA, 120, 198
numerical control, 174–75
Oakeshott, Michael, 124
Obama, Barack, 94
Observer, 78–79
Oculus Rift, 201
Office of the Inspector General, 99
offices, 28, 108–9, 112, 222
automation complacency and, 69
Ofri, Danielle, 102
O’Keefe, John, 133–34
Old Dominion University, 91
“On Things Relating to the Surgery” (Hippocrates), 158
oracle machine, 119–20
“Outsourced Brain, The” (Brooks), 128
Pallasmaa, Juhani, 145
Parameswaran, Ashwin, 115
Parameters, 191
parametric design, 140–41
parametricism, 140–41
“Parametricism Manifesto” (Schumacher), 141
Parasuraman, Raja, 54, 67, 71, 166, 176
Parry, William Edward, 125
pattern recognition, 57, 58, 81, 83, 113
Pavlov, Ivan, 88
Pebble, 201
Pediatrics, 97
perception, 8, 121, 130, 131, 132, 133, 144, 148–51, 201, 214–18, 220, 226, 230
performance, Yerkes-Dodson law and, 96
Phenomenology of Perception (Merleau-Ponty), 216
philosophers, 119, 143, 144, 148–51, 186, 224
photography, film vs. digital, 230
Piano, Renzo, 138, 141–42
pilots, 1, 2, 32, 43–63, 91, 153
attentional tunneling and, 200–201
capability of the plane vs., 60–61, 154
death of, 53
erosion of expertise of, 54–58, 62–63
human- vs. technology-centered automation and, 168–70, 172–73
income of, 59–60
see also autopilot
place, 131–34, 137, 251n
place cells, 133–34, 136, 219
Plato, 148
Player Piano (Vonnegut), 39
poetry, 211–16, 218, 221–22
Poirier, Richard, 214, 215
Politics (Aristotle), 224
Popular Science, 48
Post, Wiley, 48, 50, 53, 57, 62, 82, 169
power, 21, 37, 65, 151, 175, 204, 217
practice, 82–83
Predator drone, 188
premature fixation, 145
presence, power of, 200
Priestley, Joseph, 160
Prius, 6, 13, 154–55
privacy, 206
probability, 113–24
procedural (tacit) knowledge, 9–11, 83, 105, 113, 144
productivity, 18, 22, 29, 30, 37, 106, 160, 173, 175, 181, 218
professional work, incursion of computers into, 115
profit motive, 17
profits, 18, 22, 28, 30, 33, 95, 159, 171, 172–73, 175
progress, 21, 26, 29, 37, 40, 65, 196, 214
acceleration of, 26
scientific, 31, 123
social, 159–60, 228
progress (continued)
technological, 29, 31, 34, 35, 48–49, 108–9, 159, 160, 161, 173, 174, 222, 223–24, 226, 228, 230
utopian vision of, 25, 26
prosperity, 20, 21, 107
proximal cues, 219–20
psychologists, psychology, 9, 11, 15, 54, 103, 119, 149, 158–59
animal studies, 87–92
cognitive, 72–76, 81, 129–30
psychomotor skills, 56, 57–58, 81, 120
quality of experience, 14–15
Race against the Machine (Brynjolfsson and McAfee), 28–29
RAND Corporation, 93–98
“Rationalism in Politics” (Oakeshott), 124
Rattner, Justin, 203
reading, learning of, 82
Reaper drone, 188
reasoning, reason, 120, 121, 124, 151
recession, 27, 28, 30, 32
Red Dead Redemption, 177–78
“Relation of Strength of Stimulus to Rapidity of Habit-Formation, The” (Yerkes and Dodson), 89
Renslow, Marvin, 43–44
Revit, 146, 147
Rifkin, Jeremy, 28
Robert, David, 45, 169–70
Robert Frost (Poirier), 214
Roberts, J. O., 62
robotics, robots, 2, 6, 13, 19–20, 29, 30, 33, 39–41, 118, 153, 156, 219, 225, 227, 257n
capabilities of, 8, 9
essence of, 36
ethical questions about, 183–93, 204
killer, 187–93, 198, 204
speed of, 186
Rodriguez, Dayron, 103
Roomba, 185
Royal Air Force, 49
Royal Bank of Canada (RBC), 170–71
Royal Majesty (ship), 68
Rubin, Charles, 186
Russell, Bertrand, 21, 39
Rybczynski, Witold, 142
safety, 46, 53–59, 61, 91, 154, 169, 170, 184, 207
safety alert for operators (SAFO), 1, 170
Saint-Exupéry, Antoine de, 51, 53
Sarter, Nadine, 162
satisfaction, 14, 16, 17, 85, 132
Scerbo, Mark, 91
Schön, Donald, 143, 144
Schüll, Natasha Dow, 179n
Schulman, Ari, 133
Schumacher, Patrik, 141
Science, 73, 79, 219
scientific management (Taylorism), 107, 114, 158, 207
scientists, science, 46, 151, 155, 159, 160, 214, 217
scythe, 218–19, 221, 222, 224
search engines, 78–80, 206–7
self, 132, 161, 205–6, 216–17, 220
self-consciousness, jail of, 16
self-fulfillment, 24, 85, 157, 161
self-interest, 59–60
self-renewal, 132
senses, 8, 69, 83, 131, 134, 149–51, 201, 217, 219
sensors, sensing mechanism, 8, 36, 38, 46, 52
Shanghai Tower, 167
Shaw, Rebecca, 43–44
ships, 36–37, 68
Shop Class as Soulcraft (Crawford), 147–48
Shushwap tribe, 228–29, 232
Silicon Valley, 7, 33, 133, 194, 226, 227
Simons, Daniel, 201
simplicity, 180, 181
Singhal, Amit, 78–79
60 Minutes (TV show), 29
Sketchpad, 138
SketchUp, 146
Skidelsky, Robert, 31–32
Skiles, Jeffrey, 154
skill fade, 58
skills, 80–85, 161, 216–17, 218, 219
degradation of, 106–12, 125–31, 157
see also specific skills
skill tunneling, 202
Skinner, B. F., 179n
Slamecka, Norman, 72–73, 74
slavery, slaves, 20, 21, 25, 26, 224–26
slot machines, 179n
Small, Willard, 88
smartphones, 12–13, 33, 91, 136, 199–202
smartwatch, 201, 202
Smith, Adam, 21–22, 106–7
social decision-making, 122
social networks, 181–82
society, 159–60, 161, 172, 173, 176
automation’s changing of nature of, 193–99, 202
trade-offs made by, 207–8
sociologists, 109, 158–59
software, 1, 7–8, 12, 27, 28, 30, 33, 40, 52, 66, 67, 90, 108, 114–16, 119, 136, 151–52
architecture and design, 135, 138–47, 167, 229–30
cognitive processes and, 74–77, 80
compelling urgency of, 194
decision support, 70–71
ergonomics and, 164
ethics and, 184, 204
hidden assumptions of, 206
human- vs. technology-centered, 156, 160, 172–76
limits of, 9, 205
medical, 97–100, 114–15
planes and, 52, 54, 57, 168
social adaptations to, 202–8
trust in, 69
video games as model for design of, 178–82
software programmers, 157, 159, 174, 175
space, 129–30, 133–36, 205
Specialmatic, 174–75
speed, 17, 20, 35, 38, 51, 88, 159, 181, 207
of computers, 118–22, 139, 156, 164, 173, 219
of robots, 186
spell checkers, 180–81
Spence, Michael, 30
Sperry, Elmer A., 47
Sperry, Lawrence, 46–47, 50, 53, 232
Sperry autopilot, 47–49
Sperry Corporation, 49, 58
Spinoza, Baruch, 216
spy agencies, 120
Stanton, Neville, 90–91
Star Trek, 232
steamships, 36–37
stick shift, 3–6, 13
Street View, 136
substitution myth, 67, 97, 98, 129, 193
Sullenberger, Chesley, 154, 170
supersystem, development of, 196
Sutherland, Ivan, 138
tablets, 153, 199, 202
tacit (procedural) knowledge, 9–11, 83, 105, 113, 144
talents, 12, 27, 61, 74, 83, 85, 112, 216, 217, 219
of doctors, 105
human, limits to replication of, 9
Talisse, Robert, 85
Tango (mapping technology), 136
Taylor, Frederick Winslow, 107, 108, 114, 158, 207
teachers, teaching, 10, 12, 32, 153
technical arrogance, 175
technological momentum, 172–75, 196
technological unemployment, 26, 27, 198
technology, 1–2, 150–51, 215–32
health information, 93–106
invisibility of, 203–4, 208–10
labor-saving, 17, 20, 28, 67
long history of ambivalence to, 21–41
master-slave metaphor and, 224–26
progress and, see progress, technological
TED conference (2013), 199–201
Tesla Motors, 8
tests, medical, 70–71, 99, 102, 245n–46n
Thiel, Peter, 227
thinking, thought, 65, 67, 147–51
artificial intelligence and, 119
drawing as, 142–43, 144
Thinking Hand, The (Pallasmaa), 145
Thomis, Malcolm, 23
THOR (software program), 171
Thrun, Sebastian, 6, 207
tools, 150–51, 158, 174, 185, 195, 215–19, 221–26
To Save Everything, Click Here (Morozov), 225
traders, trading, 77, 115, 171
Tranel, Ben, 167
transport, 48, 49, 132, 173
“Tuft of Flowers, The” (Frost), 221
Turing, Alan, 119–20
Turkle, Sherry, 69
unconscious mind, 121, 148–49
unemployment, 20, 25–29, 38
technological, 26, 27, 198
United Kingdom, 95
University College London, 133
UPS, 117
U.S. Airways, 154
Utah, University of, 130
venture capitalism, 116
Veterans Administration, 103
video games, 177–80, 219
virtualization, 118
visual cortex, 82
vocabulary, generation effect and, 72–73
vocations, computers and, 12
Voltaire, 160
Volvo, 8
Vonnegut, Kurt, 39
Voss, Bill, 53
wages and income, 26, 31, 33
increase in, 22, 24, 30, 37
of pilots, 59–60
Wall Street, 77, 115, 156, 171
Wall Street Journal, 60, 153
warfare, 19, 35–36, 41, 48, 49
killer robots and, 187–93, 198, 204
Washington, University of, 102
Watson (supercomputer), 118–20
Watt, James, 36
wayfinding performance, 130
wayfinding skills, automation of, 122–37
wealth, 22, 26, 29, 32, 33, 117, 226–27
Wealth of Nations, The (Smith), 22–23, 106–7
weaving, weavers, 23, 36, 66
Weed, Lawrence, 123, 248n
Weiser, Mark, 194–95
Weizenbaum, Joseph, 194
well-being, 15, 17, 137, 208
Wells, Thomas J., 49
Westinghouse, 175
Whitehead, Alfred North, 65–67, 83, 84
Wiener, Norbert, 37–40, 117, 158, 161
WifiSlam, 136
Wilde, Oscar, 25, 66, 224, 225
Williams, Serena, 82
Williams, William Carlos, xi
Wilson, Timothy, 15
Winner, Langdon, 209, 224
Wired, 136, 153, 225
Woods, David, 162
word-processing programs, 101
Wordsworth, William, 137
work, 14–27, 213–14
paradox of, 14–16
standardization of, 107–8, 114
transfer of, 17–18, 66
see also jobs; labor
world, 121, 123–24, 133, 216–20, 232
World War I, 58
World War II, 35–36, 41, 49, 157, 158, 174
Wright, Orville, 61, 168, 215
Wright, Wilbur, 60, 61, 168, 215
Xerox, 117
Xerox PARC, 194, 195, 202
x-rays, 70, 99
Yerkes, Robert M., 87–88
Yerkes-Dodson law and curve, 89–91, 165
Young, Mark, 90–91
Zaha Hadid, 141
Ziegler, Bernard, 170
Zuckerberg, Mark, 181, 203, 206