Explorations in Critical Studies of Advertising by James F. Hamilton Robert Bodle Ezequiel Korin

Author:James F. Hamilton, Robert Bodle, Ezequiel Korin [James F. Hamilton, Robert Bodle, Ezequiel Korin]
Language: eng
Format: epub
Tags: Nonfiction, Reference & Language, Language Arts, Communication, Business & Finance, Marketing & Sales, Advertising & Promotion, Social & Cultural Studies, Social Science
ISBN: 9781317232971
Publisher: Taylor and Francis
Published: 2016-10-26T04:00:00+00:00

The Political Economy of Algorithmic Power

A better understanding of the political economy of algorithmic power can help inform user participation and agency. Although Web 2.0 rhetoric celebrates an era of disintermediation, predictive algorithms have been interposed as society’s new gatekeepers, information filters, social shapers, and causal agents (Mayer-Schönberger & Cukier, 2013). Algorithms are not neutral or “a-political” prediction engines, suggests McStay (2011, 138). Seemingly neutral and inscrutable machine processes have political effects that reveal corporate agendas (Bucher 2012; Gillespie 2011). They are “codified politics” (McStay 2011, 138), “ideological formulations about social relations embodied in code, insulated from political debate, about which most people are unaware” (Bucher 2012, 1171). Algorithms infer, filter, and correlate big data for a wide range of purposes: discriminate people for targeted ads (Turow 2011), regulate incivility on news sites (Morozov 2013), shape social behavior by rewarding sharing online (Bucher, 2012), guide public opinion (Sunstein 2009), and act as an ideological filter (Pariser 2011). Surveillance and algorithmic control over user data reveals power asymmetries, “The seemingly abundant existence of data does in no way mean that it is available” (Ulbricht and von Grafenstein 2016). Although people generate surplus value for social media sites from their online participation, they have very little access, control, ownership, understanding, or awareness of the instrumental use of their data that may account for social inequality, discrimination, censorship, and other potential abuses.

Insights into the operational logics of Facebook’s algorithm reinforce an understanding of the company’s underlying business model that is predicated on tracking users and amassing data tied to fixed identities. Close examination of Facebook’s data-driven personalization practices reveals the fundamental inequality among members, advertisers, and the Internet company. Recognizing Facebook’s asymmetrical algorithmic power can provide insights into the implications of personalization for informational privacy, personal autonomy, critical thinking, and civic engagement.

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