Modest_Witness in the Wire: Haraway, Predictive Algorithms, and Online Profiling

Abstract

Donna Haraway’s concepts of the cyborg and a modest witness have renewed salience in today’s digital world, as online profiling, big data, and predictive personality algorithms alter human subjectivities as part of an identity feedback loop. These evolutions in turn trouble theoretical life-writing constructs such as narration, authenticity, agency, automediality, and collaboration.

Disclosure Statement

No potential conflict of interest was reported by the author.

Notes

1 Haraway, The Haraway Reader, 322.

2 Haraway, The Haraway Reader, 8.

3 Haraway, The Haraway Reader.

4 Haraway, The Haraway Reader, 299.

5 Grebowicz and Merrick, Beyond the Cyborg, 18.

6 Haraway, The Haraway Reader, 13.

7 Haraway, The Haraway Reader, 20–21.

8 Haraway, The Haraway Reader, 39.

9 Haraway, The Haraway Reader, 246.

10 Schneider, Donna Haraway, 59.

11 See, for example, “Profile Pictures,” a study by Zheng et al. of gender and regional difference in the use of profile pictures to create virtual identities.

12 Chen, Chiang, and Storey, “Business Intelligence and Analytics,” 1169.

13 “What Is Big Data?”

14 Dewey, “98 Personal Data Points,”

15 See Hearn, “Verified” and Quercia et al., “Our Twitter Profiles.”

16 Cheney-Lippold defines algorithm categorization as follows: “A measurable type is a data template, a nexus of different datafied elements that construct a new, transcoded interpretation of the world. These templates are most often used to assign users an identity, an algorithmic identification that compares streams of new data to existing datafied models.” Cheney-Lippold, We Are Data, 47.

17 O’Neil, Weapons of Math Destruction, 3.

18 See Linguistic Inquiry Word Count at http://liwc.wpengine.com/

19 See Linguistic Inquiry Word Count at http://liwc.wpengine.com/

20 Cheney-Lippold, We Are Data, 50.

21 The quantification of emotional states and the use of linguistic tools to analyze social media output from users has been an active field of study since about 2010, including researchers beyond Kosinski and Stillwell and the Cambridge group behind Cambridge Analytica. For computational models of anger and unhappiness, see Tam, “Computation in Emotional Processing.” For the work of Kosinski and Stillwell at the Psychometrics Centre at the University of Cambridge, see Youyou, Kosinski, and Stillwell, “Computer-Based Personality Judgments”; Kosinski, Stillwell, and Graepel, “Private Traits”; Quercia et al., “Our Twitter Profiles”; and Markovikj et al., Mining Facebook Data. Golbeck and her associates at the Human-Computer Interaction Lab at the University of Maryland have published a number of scholarly articles on predictive personality algorithms. See Golbeck et al., “Predicting Personality from Twitter” and Golbeck, Robles, and Turner, “Predicting Personality.” For a study of commercial applications of “personality mining,” see Buettner, “Predicting User Behavior,” and for a similar study for Chinese social network users using the LIWC and the Big Five personality, see Gao et al., “Improving User Profile.” Chapsky also proposed a computational model for personality prediction based on Facebook data, including users’ preferences for Lady Gaga’s music. See Chapsky, “Leveraging Online Social Networks.”

22 Golbeck, Robles, and Turner, “Predicting Personality,” 254–255.

23 Golbeck, Robles, and Turner, “Predicting Personality,” 260.

24 Golbeck, Robles, and Turner, “Predicting Personality.”

25 Golbeck and Hansen, “A Method for Computing,” 184.

26 See Gonzales and Hancock, “Identity Shift”; Carr and Foreman, “Identity Shift III”; and Walther et al., “The Effect of Feedback.”

27 “Back of the Net.”

28 Youyou, Kosinski, and Stillwell, “Computer-Based Personality Judgments,” 1036.

29 Kosinski, Stillwell, and Graepel, “Private Traits,” 5802.

30 Youyou, Kosinski, and Stillwell, “Computer-Based Personality Judgments,” 1039.

31 Youyou, Kosinski, and Stillwell, “Computer-Based Personality Judgments.”

32 Grassegger and Krogerus, “The Data.”

33 Nix, “Cambridge Analytica.”

34 Grassegger and Krogerus, “The Data.”

35 Golbeck, “What Can Companies Predict?”

36 Smith and Watson, Reading Autobiography, 56.

37 Butler, 58.

38 Haraway, The Haraway Reader, 13, 38.

39 Haraway, The Haraway Reader, 39.

40 Floridi and Sanders, “On the Morality,” 351.

41 Bennett, Vibrant Matter, 31.

42 Herbrechter, “Posthumanism, Subjectivity, Autobiography,” 330, 334.

43 Schmitt, “Autobiographical Act,” 10.

44 Herbrechter, “Posthumanism, Subjectivity, Autobiography,” 340.

45 Cardell, Douglas, and Maguire, “Stories,” 158.

46 Whitlock and Poletti, “Self-Regarding Art,” xvi; McNeill and Zuern, “Online Lives 2.0,” xv–xvi.

47 Poletti and Rak, “Introduction,” 5.

48 Smith and Watson, Reading Autobiography, 168.

49 Bruns, Blogs, 1, 2.

50 McNeill and Zuern, “Online Lives 2.0,” xx.

51 Youyou, Kosinski, and Stillwell, “Computer-Based Personality Judgments.”

52 Poletti and Rak, “Introduction,” 5.

53 Morrison, “Facebook and Coaxed Affordances,” 117.

54 Smith and Watson, Reading Autobiography, 168; Poletti and Rak, “‘We’re All Born Naked”; Rak, “Life Writing versus Automedia,” 156, 172. On automedia, see also Kennedy and Maguire, “Texts and Subjects” and Nagel, “Alts and Automediality.”

55 Smith, “Presidential Address 2011,” 570.

56 Cheney-Lippold, We Are Data, 50.

57 Smith and Watson, Reading Autobiography, 16.

58 Schaffer and Smith, “E-witnessing,” 225–226.

59 McNeill, “There Is No ‘I,’” 68n.

60 Haraway, Modest_Witness, 24.

61 Haraway, Modest_Witness.

62 Haraway, Modest_Witness, 267–269.

63 Cheney-Lippold, We Are Data, 39–46.

64 Angwin et al., “Machine Bias.”

65 González “Seeing into Hearts,” 13–15.

66 Haraway, Modest_Witness, 41.