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Can we have platform capitalism without computational politics? 

Notes for week 2 of the CPGJ Platform Capitalism reading group 

Both readings for this week treat utopian hopes of the internet bolstering democracy as anachronistic relics, looking in different ways to the murky reality of the politics which platform capitalism is giving rise to. Tufekci accepts some of the claims made about the affordances of digital technology while stressing the new inequalities which come with these developments, as we operate within a “data–analytic environment that favors the powerful, data–rich incumbents, and the technologically adept”. This is what Mark Andrejevic has elsewhere described as the ‘big-data divide‘. New strategies take advantage of this divide, entrenching it in the process through the collection of data and the development of techniques, giving rise to “more effective — and less transparent — “engineering of consent” (Bernays, 1947) in the public sphere”. This is neatly conceptualised by Tufekci as  computational politics:

As a normative (but contested) ideal, the public sphere is envisioned by Habermas (1989) as the location and place in which rational arguments about matters concerning the public, especially regarding issues of governance and the civics can take place, freed from constraints of status and identity. The public sphere should be considered at once a “normative ideal” as well as an institutional analysis of historical practice (Calhoun, 1993). As actual practice, the public sphere pertains to “places” — intersections and commons — where these civic interactions take place, and which are increasingly online. This shift to a partially online public sphere, which has brought about the ability to observe, surveil and collect these interactions in large datasets, has given rise to computational politics, the focus of this paper.

Computational politics refers applying computational methods to large datasets derived from online and off–line data sources for conducting outreach, persuasion and mobilization in the service of electing, furthering or opposing a candidate, a policy or legislation. Computational politics is informed by behavioral sciences and refined using experimental approaches, including online experiments, and is often used to profile people, sometimes in the aggregate but especially at the individual level, and to develop methods of persuasion and mobilization which, too, can be individualized. Thus, computational politics is a set of practices the rise of which depends on, but is not solely defined by, the existence of big data and accompanying analytic tools and is defined by the significant information asymmetry — those holding the data know a lot about individuals while people don’t know what the data practitioners know about them (U.S. Federal Trade Commission, 2014).

Tufekci is careful to note that the use of ‘big data’ for politics and marketing predates the internet. But her concern is digital data facilitates “significantly more individualized profiling and modeling, much greater data depth, and can be collected in an invisible, latent manner and delivered individually”. The possibilities for interacting individually, privately and asymmetrically increase enormously, leading to a qualitative change in how public the public sphere will tend to be. Engineering consent is not a new ambition but the tools now available to undertake this are radically different to what has come before:

  1. availability of big data
  2. shift to individual targeting
  3. the potential and opacity of modeling
  4. the rise of behavioral science in the service of persuasion
  5. dynamic experimentation
  6. and the growth of new power brokers on the Internet who control the data and algorithms

I suggested Kate Crawford’s essay for this week because it highlights public understanding of computational politics. What happens when there is direct and indirect awareness of this? We might hope this will take the form of organised political action but her suggestion we will see cultural response is deeply plausible. What other reactions can we imagine? How might recent revelations about Cambridge Analytica contribute to this? I haven’t got time to write proper notes about her essay now but I’ve written about it in the past, albeit briefly.

  1. Will computational politics necessarily erode the public sphere? What action can we take to prevent this? Will technocratic solutions to problems defined as ‘fake news’ and ‘computational propaganda’ help the situation or make the problem worse?  Is there any way to put computational politics back in the box? Can we have platform capitalism without computational politics?
  2. Tufekci wrote in 2014 that “there has been fairly little conceptual theory–building especially about the political and civic consequences of big data” and mainstream media “rarely goes beyond exploring big data as a hot, new topic and an exciting new tool, and rarely consider issues of power”. Is this still the case? What would such work look like? Is it ‘remastering’ existing concepts to make them digitally adequate or developing new ones?
  3. Is a coherent public understanding of computational politics taking shape? What are the consequences of this? What’s the relationship between cultural responses to computational politics and political responses to it?

Categories: Archive Pre 2020 reading notes

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