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    The Glass Cage: Automation and Us

    Page 28
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      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

    &n
    bsp; 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

     


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