“Optimize user experience”: optimization techniques and the simulation of life, from the model to the algorithm

ABSTRACT

This article takes up the issue of optimization to consider the relationship between predictive algorithms and platform user experience. Corporate data analytic practices increasingly rely on machine learning algorithms that apply models to user behaviors, producing “knowledge” about users that can be bought and sold. This article considers the opacity of algorithms today in relation to optimization. Using a conceptual apparatus that draws from the study of cultural techniques, the following argues that optimization—the task of finding a sufficient solution to a well-defined problem—makes use of models to simulate possible answers to problems around the incomputablity of behavior. Tracing a set of examples that deal with the problem of predicting behavior—the “minimum point” problem, John von Neumann's automata theory, and the Facebook pixel—optimization is characterized by a shift from statistical model making towards predictive and algorithmic techniques. This shift is seen within the context of the decline of Cold War rationality towards the embeddedness of “intelligent” algorithms across technoculture.

KEYWORDS:

• optimization
• artificial intelligence
• Cold War rationality
• Facebook
• platform capitalism

Acknowledgements

The author acknowledges the support of colleagues at Duke University, with whom the first versions of this article originated through conversation. It was subsequently improved via feedback from Jordan Sjol (Duke), Quran Karriem (Duke), Brett Zehner (Brown), and other authors included in this themed issue. The author is indebted to Fenwick McKelvey and Josh Neves for their support and comments throughout entire editorial process. Comments by the anonymous reviewers led to fruitful changes and opened up further avenues of research. Finally, the author would like to thank her committee—Mark Hansen, Luciana Parisi, and Mark Olson—for their support and encouragement, ongoing.

Notes

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3 Tarleton Gillespie, “The Relevance of Algorithms,” in Media Technologies: Essays on Communication, Materiality and Society, ed. Tarleton Gillespie, Pablo J. Boczkowski, and Kirsten A. Foot (Cambridge, MA: MIT Press, 2014), 167–93.

4 Craig Silverman and Ryan Mac, “Facebook Gets Paid,” BuzzFeed News, December 10, 2020, https://www.buzzfeednews.com/article/craigsilverman/facebook-ad-scams-revenue-china-tiktok-vietnam?ref=bfnsplash; “ASA Ruling on PLR Worldwide Sales Ltd t/a Playrix,” Advertising Standards Authority, September 30, 2020, https://www.asa.org.uk/rulings/plr-worldwide-sales-ltd-g20-1061644-plr-worldwide-sales-ltd.html; Margaret Hu, “Cambridge Analytica's Black Box,” Big Data & Society 7, no. 2 (2020): https://doi.org/10.1177/2053951720938091.

5 Trevor Paglen, “Invisible Images (Your Pictures Are Looking at You),” The New Inquiry, December 8, 2016, https://thenewinquiry.com/invisible-images-your-pictures-are-looking-at-you/; David M. Berry and Michael Dieter, eds., “Thinking Postdigital Aesthetics: Art, Computation and Design,” in Postdigital Aesthetics: Art, Computation and Design (Basingstoke, U.K.: Palgrave Macmillan, 2015), 1–11.

6 Jane Lytvynenko, “This Idaho Chiropractor Was Running Ads on Facebook Falsely Claiming Silver Prevents the Coronavirus,” BuzzFeed News, April 2, 2020, https://www.buzzfeednews.com/article/janelytvynenko/chiropractor-runnings-false-covid-ads.

7 Jean-Christophe Plantin, Carl Lagoze, Paul N. Edwards, and Christian Sandvig, “Infrastructure Studies Meet Platform Studies in the Age of Google and Facebook,” New Media & Society 20, no. 1 (2016): 293–310.

8 Palgen, “Invisible Images.”

9 Ibid.

10 Orit Halpern, Beautiful Data: A History of Vision and Reason Since 1945 (Durham, NC: Duke University Press, 2015).

11 Orit Halpern, Robert Mitchell, and Bernard Dionysius Geoghegan, “The Smartness Mandate: Notes Toward a Critique,” Grey Room 68 (Summer 2017): 106–29.

12 Paul Erickson et al., How Reason Almost Lost Its Mind: The Strange Career of Cold War Rationality (Chicago: University of Chicago Press, 2013).

13 Ibid., 2.

14 M. Beatrice Fazi, “Beyond Human: Deep Learning, Explainability and Representation,” Theory, Culture & Society (2020): https://doi.org/10.1177/0263276420966386.

15 Luciana Parisi and Ezekiel Dixon-Román, “Recursive Colonialism and Cosmo-Computation,” Social Text Periscope: “Control Societies @ 30: Technopolitical Forces and Ontologies of Difference” (November 2020): https://socialtextjournal.org/periscope_article/recursive-colonialism-and-cosmo-computation/.

16 Jean-Luc Chabert, ed., “Introduction,” in A History of Algorithms: From the Pebble to the Microchip (Berlin: Springer-Verlag, 1999), 1–7; Donald E. Knuth, The Art of Computer Programming Volume 3: Sorting and Searching, 2nd ed. (Boston: Addison-Wesley, 1998); Bernhard Siegert, Cultural Techniques: Grids, Filters, Doors, and Other Articulations of the Real, trans. Geoffrey Winthrop-Young (New York: Fordham University Press, 2015).

17 See Siegert, Cultural Techniques; Thomas Macho, “Second Order Animals: Cultural Techniques of Identity and Identification,” Theory, Culture & Society 30, no. 6 (2013): 30–47; Geoffrey Winthrop-Young, “Cultural Techniques: Preliminary Remarks,” Theory, Culture & Society 30, no. 6 (2013): 3–19.

18 Berhnard Rieder, Engines of Order: A Mechanology of Algorithmic Techniques (Amsterdam: Amsterdam University Press, 2020), 17.

19 Fenwick McKelvey, Internet Daemon: Digital Communications Possessed (Minneapolis: University of Minnesota Press, 2018).

20 Ding-Zhu Du, Panos M. Pardalos, and Weili Wu, “History of Optimization,” in Encyclopedia of Optimization, ed. Christodoulos A. Floudas and Panos M. Pardalos (Boston: Springer, 2008), 1539, https://doi.org/10.1007/978-0-387-74759-0_268.

21 Ibid., 1538.

22 Ibid., 1539.

23 Erickson et al., How Reason Almost Lost Its Mind.

24 Adrian Mackenzie, “Simulate, Optimise, Partition: Algorithmic Diagrams of Pattern Recognition from 1953 Onwards,” in Cold War Legacies: Systems, Theory, Aesthetics, ed. John Beck and Ryan Bishop (Edinburgh: Edinburgh University Press, 2016), 50–69.

25 Du, Pardalos, and Wu, “History of Optimization.”

26 Numberphile, “Inventing Game of Life (John Conway)—Numberphile,” YouTube, March 5, 2014, https://www.youtube.com/watch?v=R9Plq-D1gEk&ab_channel=Numberphile.

27 Ibid.

28 Arthur W. Burks, Von Neumann's Self-Reproducing Automata (Ann Arbor: University of Michigan Press, 1969), 10–12.

29 The field of automata studies was ill defined from its origins, according to the criticism of Claude Elwood Shannon and John McCarthy (Automata Studies [Princeton, NJ: Princeton University Press, 1956]). The volume focuses on the distinction between brain modeling and symbolic information processing within artificial intelligence, and later prompted the Dartmouth Summer Research Project on Artificial Intelligence (1956). See Ronald R. Kline, The Cybernetics Moment: Or Why We Call Our Age the Information Age (Baltimore, MD: Johns Hopkins University Press, 2015).

30 Arthur W. Burks, ed., “Preface,” in John von Neumann, Theory of Self-Reproducing Automata (Urbana: University of Illinois Press, 1966), xv–xix.

31 John von Neumann, “Fourth Lecture: The Role of High and of Extremely High Complication,” in Theory of Self-Reproducing Automata, ed. Arthur W. Burks (Urbana: University of Illinois Press, 1966), 65.

32 Barry McMullin, “John von Neumann and the Evolutionary Growth of Complexity: Looking Backward, Looking Forward,” Artificial Life 6, no. 4 (2000): 347–61.

33 Evelyn Fox Keller, Making Sense of Life: Explaining Biological Development with Models, Metaphors, and Machines (Cambridge, MA: Harvard University Press, 2002), 270.

34 von Neumann, “Fourth Lecture,” 76.

35 Philip Mirowski, Machine Dreams: Economics Becomes a Cyborg Science (Cambridge: Cambridge University Press, 2002).

36 von Neumann, “Fourth Lecture,” 72.

37 McMullin, “John von Neumann and the Evolutionary Growth of Complexity.”

38 Paul Erickson, “Game Theory without Rationality,” in The World the Game Theorists Made (Chicago: University of Chicago Press, 2015), 204–39.

39 Ibid.

40 Erickson et al., How Reason Almost Lost Its Mind.

41 Plantin, Lagoze, Edwards, and Sandvig, “Infrastructure Studies Meet Platform Studies in the Age of Google and Facebook.”

42 Nick Srnicek, Platform Capitalism (Cambridge: Polity, 2017).

43 Tania Bucher, “The Algorithmic Imaginary: Exploring the Ordinary Affects of Facebook Algorithms,” Information, Communication & Society 20, no. 1 (2017): 30–44; Gillespie, “The Relevance of Algorithms”; Robyn Caplan and Tarleton Gillespie, “Tiered Governance and Demonetization: The Shifting Terms of Labor and Compensation in the Platform Economy,” Social Media + Society 6, no. 2 (2020): 1–13, https://doi.org/10.1177/2056305120936636.

44 Julia Angwin, Terry Parris Jr., and Surya Mattu, “Breaking the Black Box: What Facebook Knows About You,” ProPublica, September 28, 2016, https://www.propublica.org/article/breaking-the-black-box-what-facebook-knows-about-you.

45 Fazi, “Beyond Human.”

46 Mackenzie, “Simulate, Optimise, Partition.”

47 “Facebook Pixel,” Facebook for Developers, https://developers.facebook.com/docs/facebook-pixel (accessed April 2020).

48 “The Facebook Pixel,” Facebook for Business, https://www.facebook.com/business/learn/facebook-ads-pixel (accessed September 2020).

49 “Custom Audience,” Facebook for Developers, https://developers.facebook.com/docs/marketing-api/audiences/guides/custom-audiences/ (accessed April 2020); “Facebook Pixel,” Facebook for Developers.

50 Shoshana Zuboff, The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power (New York: PublicAffairs, 2019).

51 See “General Data Protection Regulation” Facebook for Developers, https://developers.facebook.com/docs/facebook-pixel/implementation/gdpr/ (accessed September 2020).

52 This statistic was calculated on data available in 2020. Rishi Iyengar, “Here's How Big Facebook's Ad Business Really Is,” CNN Business, July 1, 2020, https://www.cnn.com/2020/06/30/tech/facebook-ad-business-boycott/index.html (accessed September 2020).

53 Steffen Böhm, Chris Land, and Armin Beverungen, “The Value of Marx: Free Labour, Rent and ‘Primitive’ Accumulation in Facebook,” Working Paper (University of Essex, 2012), 3, https://www.researchgate.net/publication/239735772 (accessed May 2019).

54 Christian Fuchs and Sebastian Sevignani, “What Is Digital Labour? What Is Digital Work? What's Their Difference? And Why Do These Questions Matter for Understanding Social Media?” TripleC: Communication, Capitalism & Critique 11, no. 2 (2013): 237–93.

55 Srnicek, Platform Capitalism.

56 Tung-Hui Hu, “Digital Lethargy” (video lecture, Rhetoric and Public Cultures Summer Institute, Northwestern University, Evanston, IL, 2020).

57 “Facebook Pixel,” Facebook for Developers.

58 “The Facebook Pixel,” Facebook for Business.

59 Facebook's expanded security preferences settings include information on Advertisers and Businesses that have uploaded and used a list containing users’ contact information, as well as information about interests that Facebook determines a user has based on their Facebook activity.

60 Clemens Apprich, “Data Paranoia: How to Make Sense of Pattern Discrimination,” in Pattern Discrimination, by Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl (Minneapolis: University of Minnesota Press and Lüneburg, Germany: meson press, 2018), 103.

61 Wendy Hui Kyong Chun, “Queering Homophily,” in Pattern Discrimination, by Clemens Apprich, Wendy Hui Kyong Chun, Florian Cramer, and Hito Steyerl (Minneapolis: University of Minnesota Press and Lüneburg, Germany: meson press, 2018), 76, 70.

62 David Kirkpatrick, The Facebook Effect: The Inside Story of the Company That Is Connecting the World (New York: Simon & Schuster, 2011), 157.

63 Ibid., 217.

64 The Graph API was scaled back and access limited after the Cambridge Analytica scandal in 2018. As a result, many applications that could be used to visualize the social graph—often used for quantitative social research—no longer work. See Bernhard Rieder, “Facebook's App Review and How Independent Research Just Got a Lot Harder,” The Politics of Systems, August 11, 2018, http://thepoliticsofsystems.net/2018/08/facebooks-app-review-and-how-independent-research-just-got-a-lot-harder/ (accessed September 2020).

65 Phillip E. Agre, “Surveillance and Capture: Two Models of Privacy,” The Information Society 10, no. 2 (1994): 101–27.

66 Andrea Fumagalli, Stefano Lucarelli, Elena Musolino, and Giulia Rocchi, “Digital Labour in the Platform Economy: The Case of Facebook,” Sustainability 10, no. 6, 1757 (2018): 9.

67 Louise Amoore, “Doubt and the Algorithm: On Partial Accounts of Machine Learning,” Theory, Culture & Society 36, no. 6 (2019): 148.

68 Mackenzie, “Simulate, Optimise, Partition.”

69 See Safiya Umoja Nobel, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: New York University Press, 2018).

70 “Breeder Animation,” Wikimedia Commons, posted November 29, 2008, https://commons.wikimedia.org/wiki/File:Conways_game_of_life_breeder_animation.gif.

71 Burks, Von Neumann's Self-Reproducing Automata, 66.