The Glass Cage: Automation and Us (40 page)

BOOK: The Glass Cage: Automation and Us
2.97Mb size Format: txt, pdf, ePub
ads

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, 179
n

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), 235
n

Giedion, Sigfried, 237
n

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, 33
n
, 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, 33
n

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, 237
n

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, 235
n

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, 119
n

neuroergonomic systems, 165

neurological studies, 9

neuromorphic microchips, 114, 119
n

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, 251
n

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 (
continue
d
)

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

BOOK: The Glass Cage: Automation and Us
2.97Mb size Format: txt, pdf, ePub
ads

Other books

Planeswalker by Lynn Abbey
A Motive For Murder by Katy Munger
Dragon Frost by Kelvia-Lee Johnson
Trouble by Jamie Campbell
Green Girl by Sara Seale
The Ideas Pirates by Hazel Edwards
What the River Knows by Katherine Pritchett