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Influential Machines: The Rhetoric of Computational Performance: Index

Influential Machines: The Rhetoric of Computational Performance
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Notes

table of contents
  1. Cover Page
  2. Title Page
  3. Copyright
  4. Dedication
  5. Contents
  6. List of Tables and Figures
  7. Acknowledgments
  8. Introduction: Locating the Energies of Computational Performance
    1. The Rhetorical Energies of Computing Machines
    2. Beyond the Front and the Back Ends of Computing and Toward the Deep End
    3. Thickening Procedurality with the Rhetorical Energies of Computational Performance
  9. Chapter 1: Manufactured Processing, Ritual, and Expert Systems
    1. Automation as Ritual of Science
    2. Knowledge-Based Systems and Looking to Machines for Answers about Health
    3. The Manufactured Processing of Vaccine Calculator
    4. The Energetic Movements of “Experts” and Science Communication
  10. Chapter 2: Processual Magnitude, the Sublime, and Computational Poiesis
    1. The Aesthetics of Vast Computing
    2. The Sublime Energies of @censusAmericans
    3. Attuning to the Angst of @censusAmericans
    4. Doing More with Computational Performance
  11. Chapter 3: Processual Signaling, Compulsion, and Neural Networks
    1. Persuasion, Indication, and Affective Compulsion
    2. The “Grooves” of Neural Networks
    3. The Machinic Parody of @DeepDrumpf
    4. The Critique of Processual Signaling
  12. Chapter 4: Designing Computational Performances to Actively Contribute Positive Energies
    1. Moral Luck and the Machine Question
    2. First- and Second-Order Agency
    3. Hedging Against Moral (Un)Luckiness and the Limits of Avoidance
    4. Computational Performance and an Ethic of (Distributed) Responsibility
    5. Pushing on the Precautionary Principle and the Paradox of Machinic Intervention
    6. Doing Good Instead of Avoiding Wrong with Alexa
    7. Good Machines, Speaking Well
  13. Chapter 5: Leveraging the Rhetorical Energies of Machines
    1. The Informational and Persuasive Labors of Machine Communicators During the Pandemic
    2. Going “Deeper” Toward Anthropomechanation
    3. Enlivening Human–Machine Communication with Rhetorical Energies
    4. Enlivening Inoculations Against Misinformation with Machinic Rhetorical Energies
  14. Notes
  15. Works Cited
  16. Index

Page 157 →Index

Italicized page numbers indicate illustrations.

A

  • Abbate, Janet, 74
  • Adams, Douglas, 24
  • affective compulsion, 64, 65–74, 86–87; and human reactions to machines, 72–73
  • Akerkar, Rajendra A., 28
  • Alexa (Amazon), 105–7; contrasted with Oracle of Delphia, 119; health apps during COVID-19 pandemic, 115–16; rhetorical energies of, 119–20, 123
  • algorithms, 48–49, 94
  • Amazon’s Alexa. See Alexa (Amazon)
  • Ambient Rhetoric (Rickert), 15, 59
  • Ames, Morgan, 48
  • Amoore, Louise, 92
  • analytic reasoning, 42
  • Anderson, Wayne, 82
  • angst, 57–59
  • anthropomechanation, 116–17
  • anthropomorphism, 33
  • Antonelli, Kay McNulty Mauchly, 74
  • archival magnitude, 46–47, 82
  • Aristotle, 10, 46, 81
  • artificial intelligence (AI): symbolic vs. connectionist, 28–29; writing by, 64–65
  • attunements, 15–17, 20, 54, 58–59, 85
  • AutoSpeech-Easy, 7–8

B

  • Baldwin, Alec, 68, 81
  • Banas, John A., 122
  • Banks, Jaime, 117
  • Barad, Karen, 12
  • Barnett, Scot, 4
  • Bartik, Jean Jennings, 74
  • Bilas, Frances (Spence), 74
  • bird populations, 60–61
  • Bogost, Ian, 18
  • Bollinger, Lee C., 106
  • Bowden, Bertram Vivian, 75–76
  • Boyle, Casey, 4, 11, 20
  • Bradshaw, Jonathan, 47
  • Brock, Kevin, 19, 60
  • Brown, James J., 11, 17, 18–19, 22, 99
  • Brunner, Elizabeth, 95
  • Burroughs, William S., 70
  • Burtynsky, Edward, 55
  • Bush, Vannevar, 75

C

  • Capek, Karel, 88
  • carbon footprint software, 19–20, 21
  • Carey, James W., 48
  • Carey, Tamika L., 107
  • Catch-Up Vaccine Scheduler, 29–33, 31, 34;
  • comparison with Vaccine Calculator, 35. See also Vaccine Calculator
  • Ceccarelli, Leah, 7, 23
  • @censusAmericans, 45, 48, 49–61, 110
  • Ceraso, Steph, 11
  • Chaput, Catherine, 6, 17, 79
  • Page 158 →chatbots, 12–13; medical applications, 113–114; and moral luck, 91; and moral programming, 95–96
  • Christ of the Abyss (Galletti), 45
  • citizen science, 44
  • Cloud Ethics (Amoore), 92
  • coherentization, 47
  • Coleman, E. Gabriella, 86
  • Colombini, Crystal Broch, 6, 79
  • communication, human-machine. See human-machine communication
  • “compulsion” contrasted with “impulse,” 66. See also affective compulsion
  • Computational Culture ( journal), 17
  • computing machines: as active agents, 1–2; agency of, 11–12; deep end, realm of, 13–18, 20, 67, 72–74, 86–87, 110–113; and energies, positive and negative, 92–93; ethics of responsibility, 98–102; first- and second-order agency, 93–95; front end contrasted with back end, 13–15, 110; information processing and storage, 13; and moral agency, 107–9; moral praise and blame, 88–89, 90–93; performative energy, 13–18; procedural rhetoric, 18–23, 21; rhetorical energies of, 5–13; and science communication, 24–27, 39; user interface, 13
  • connectionist artificial intelligence, 28–29
  • conspiracy theories, 40, 121
  • constraints, 23, 53
  • COVID-19 pandemic: and health apps, 115–16; “infodemic,” 112–16
  • Crick, Nathan, 66
  • Critique of the Power of Judgement (Kant), 47

D

  • @DeepDrumpf, 66, 82, 83, 85, 111; analysis of, 79–86; model, structural, 77–78
  • de Graaf, Maartje, 117
  • Deleuze, Giles, 55
  • Dewey, John, 66
  • digital computing, history of, 74–75
  • Digital Ethics (Reyman & Sparby), 98
  • distributed morality, 100–102
  • Dorin, Alan, 49–50, 53, 54, 56
  • “double rainbow” video, 62–63
  • Dunning, David, 41
  • Dunning-Kruger effect, 40–41
  • dynamical sublime, 53–54

E

  • Edwards, Autumn P., 5
  • Edwards, Chad, 118
  • ELIZA effect (ELIZA chatbot), 32, 73
  • emergence, concept of, 50
  • emotion contrasted with logic, 15–17
  • ethics: ethic of responsibility, 98–102; rules-based approaches, 103, 104
  • expert advice and science communication, 42–44
  • expert systems, 27–28

F

  • feminine personae of voice-based assistants, 106
  • first-order agency, 93
  • Fisher, Walter, 70
  • Floridi, Luciano, 100–101
  • Fortunati, Leopoldina, 5

G

  • Gallagher, Victoria J., 68
  • Galletti, Guido, 45
  • Geometry Theorem Prover, 76
  • Gillespie, Tarleton, 98
  • GitHub, 51
  • Gonzatti, Dario, 45
  • GPT-3, 64–65
  • “grooves” of culture, 68–69; and neural networks, 74–79
  • Gross, Daniel, 16
  • Gunkel, David J., 14, 91, 94, 97
  • Guzman, Andrea L., 112

H

  • “habit” and computational performance, 67
  • hate speech, 89 “hateware,” 99–100
  • Page 159 →Hawhee, Debra, 10, 16, 57, 68–69
  • Hawk, Byron, 17
  • Hayes, Bradley, 79–80
  • Heidegger, Martin, 15–17
  • Hennis, Gregory, 99
  • Henriques, Julian, 68
  • The Hitchhiker’s Guide to the Galaxy (Adams), 24
  • Hodges, Sara D., 58
  • Holberton, Betty Snyder, 74
  • Holmes, Steve, 67
  • Homer, 57–58
  • “A Hoot in the Dark” (Kennedy), 2, 19
  • Horner, David S., 96
  • human-machine communication, 5–6, 112–13, 132n28; persuasive roles for machines, 114–115; and rhetorical energies, 117–21. See also chatbots
  • Human-Machine Communication ( journal), 5
  • human-nature interface, 68

I

  • Illiad (Homer), 57
  • images, physical responses to, 70
  • “impulse” contrasted with “compulsion,” 66
  • infinity: “at work,” 46, 53, 56, 57, 58, 59–60, 110; concept of, 53–54, 56
  • Ingraham, Chris, 6
  • inoculation theory, 121–24
  • interface archaeology, 26–27

J

  • Jennings, Jean (Bartik), 74
  • Jones, Hillary A., 41
  • joy, experience of, 62–63

K

  • Kane, Carolyn, 55, 57
  • Kang, Minsoo, 56
  • Kant, Immanuel, 47;
  • Kantian frameworks, 53;
  • Kant’s sublime, 54–55
  • Kazemi, Darius, 57
  • Kennedy, George, 2–3, 6–7, 10, 19
  • Kennedy, Krista, 9–10, 12
  • King, Preston, 106
  • knowledge-based systems, 27–34
  • Kocaballi, A. Baki, 115
  • Kruger, Justin, 41

L

  • language, kinetic energy, and metaphor, 10–11
  • Laranjo, Liliana, 115
  • Larson, Stephanie, 47
  • Lawrence, Heidi Yoston, 40
  • Lewis, Seth C., 112
  • Lichterman, Ruth (Teitelbaum), 74
  • limits of avoidance, 95–98
  • logic contrasted with emotion, 16–17
  • logistical media, 71
  • Lokapannati, 1
  • Longinus, 57–58

M

  • machine-learning, probability contrasted with deduction, 76–77
  • machinic intervention, paradox of, 102–5
  • MacIntyre, Alasdair, 70
  • magical thinking, 69–70
  • magnitude: archival magnitude, 46–47, 82; processual magnitude, 46, 59–61, 111
  • manufactured processing as tactic, 24–27
  • Massumi, Brian, 40 mathematical sublime, 53–54
  • mathematics and rhetoric, 76–79
  • mattering contrasted with matter, 12
  • Mayo Clinic, 115–16
  • McCormack, Jon, 49–50, 53, 54, 56
  • McNulty, Kay (Mauchly Antonelli), 74
  • Meltzer, Marlyn Wescoff, 74
  • meta-ignorance, 41
  • metaphor and kinetic energy, 10–11
  • #MeToo hashtag, 47
  • Microsoft’s Taybot (chatbot), 89, 97–98
  • Miller, Carolyn R., 7–9, 81
  • Miner, Adam S., 115
  • misinformation, 113–16, 121–24
  • Mitchell, William J. T., 69–70
  • Page 160 →Moon, Youngme, 32–33
  • moral luck, 90–93; and Amazon’s Alexa, 105–7; and limits of avoidance, 95–98
  • Mosco, Vincent, 48
  • Muckelbaurer, John, 4
  • Myers, Michael W., 58

N

  • Nass, Clifford, 32–33
  • natural phenomena, reactions to, 62–65, 72, 87. See also affective compulsion neural networks, 66, 74–79
  • Nietzsche, Friedrich, 66
  • Norman, Don, 71
  • Nye, David, 48

O

  • Oliver, John, 80
  • On the Sublime (Hawhee), 57
  • Operto, Fiorella, 103
  • Oracle of Delphi, 113, 117, 118–19

P

  • parody, 80. See also @DeepDrumpf
  • Parrish, Allison, 51
  • Peirce, Charles S., 69
  • Persuasive Games (Bogost), 18
  • Peters, John Durham, 70–71
  • poiesis, 50, 53, 56–57
  • precautionary principle, 102–5
  • procedural enthymemes, 19
  • procedural habits, 67
  • procedural rhetorics, 3–4, 18–23, 21
  • processual magnitude, 46, 59–61, 111
  • processual signaling, 64, 111; critique of, 86–87
  • prophetic ethos, 26
  • Pythia, 118

Q

  • Quinn, Zoe, 97
  • Quintilian, 107
  • Quirk, John J., 48

R

  • racism, tolerance for, 106–7
  • Rains, Stephen A., 122
  • Rambot, 9
  • Ramsey, Derek, 9
  • Ratcliffe, Matthew, 58
  • Recoding Gender (Abbate), 74
  • reiteration, rhetoric of, 81–82
  • resonance, 17, 72, 73
  • responsibility, ethic of distributed, 98–102
  • Reyes, Mitchell, 78
  • Reyman, Jessica, 98, 100, 108
  • rheme (unit of measure), 3
  • rhetoric: definitions of, 107; expansion of,4; and mathematics, 76–79; procedural
  • rhetoric, 18–23, 21
  • Rhetoric (Aristotle), 10
  • Rhetoric, Through Everyday Things (Barnett & Boyle), 4
  • Rhetorica Ad Herennium, 53
  • rhetorical energies, 2–3; of computing machines, 5–13; and misinformation, 121–24; traditional vs. computational performances, 7–9, 8
  • Rhetorical Machines: Writing, Code, and Computational Ethics ( Jones & Hirsu), 22
  • Rhetoric in Tooth and Claw (Hawhee), 10
  • rhythm and vibration, 68–69
  • Rice, Jenny, 46, 82
  • Rickert, Thomas, 14–15, 17, 59
  • robot speech, perceptions of, 116–17
  • Rossum’s Universal Robots (Capek), 88
  • Roundtree, Aimee K., 43
  • Rudschies, Catharina, 108

S

  • Sajja, Priti Srinivas, 28
  • Schneider, Ingrid, 108
  • science: citizen science, 44; expert advice and science communication, 42–44;
  • “signaling” and science communication, 24–27, 39
  • science denial, 46–47
  • Scientists as Prophets (Walsh), 26
  • second-order agency, 93–94
  • sensation and language, 10, 16–17, 125n7
  • Shepherd, Dawn, 19
  • Page 161 →Simon, Judith, 108
  • Snyder, Betty (Holberton), 74
  • social media platforms, 41–42; custodian metaphor, 99
  • spaces of attention, 68
  • Sparby, Erika M., 98, 100, 108
  • species loss, 60–61
  • Spence, Frances Bilas, 74
  • Spinuzzi, Clay, 26
  • Stein, Jill, 84, 85
  • “Stimmung” (Heidegger), 15–17
  • storytelling, importance of, 70–71
  • Strategic Computing Initiative, 76
  • Sublime Dreams of Living Machines (Kang), 56
  • sublimity, 45–61
  • Sullivan, Dale, 84
  • symbolic artificial intelligence, 28–29
  • symbolic associations, 69–70
  • symbolic interaction, 5–6
  • System 2 reasoning, 42

T

  • Tal, Aner, 25–26
  • Taybot (chatbot), 89, 97–98, 135n10
  • Taylor, Tom, 121
  • Teitelbaum, Ruth Lichterman, 74
  • Tiainen, Milla, 68
  • tolerance and free speech, 106–7
  • transduction, metaphor of, 11
  • Trump, Donald, 79–80; speaking style, 84. See also @DeepDrumpf
  • Twitter, bot culture, 2, 7, 22, 49, 51–52, 131n57. see also @censusAmericans; @DeepDrumpf

V

  • Vaccine Calculator, 29, 34–44, 36, 37, 86, 110, 120
  • Väliaho, Pasi, 68
  • Vasquez, Paul “Bear,” 62–63
  • Vee, Annette, 14, 17
  • Veruggio, Gianmarco, 103
  • vibration and rhythm, 68–69
  • video games, 18

W

  • Walker, Jeffrey, 20
  • Walsh, Lynda, 26
  • Walton, Douglas, 81
  • Wansink, Brian, 25–26
  • Wardrip-Fruin, Noah, 32
  • Watson Assistant for Citizens (IBM), 114
  • Weizenbaum, Joseph, 73
  • Wescoff, Marlyn (Meltzer), 74
  • Wikipedia articles, 9–10, 78, 119, 124
  • Woods, Heather Suzanne, 106
  • writing process, 9–10
  • wrongdoing: avoidance of deliberate, 102; communicative by machinic agents, 103; by machines, 89, 91, 94, 95–97, 101–2
  • Wynn, James, 44

X

  • X-ray sublime, 55, 56, 59

Y

  • Yasuoka, Koichi, 71 Yasuoka, Motoko, 71

Z

  • Zagacki, Kenneth S., 68
  • Zhang, Jia, 49, 51–53, 57, 60
  • Zo (chatbot), 89

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