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Transforming Subjects into Objects

Fri, September 6, 9:45 to 11:15am, Sheraton New Orleans Hotel, Floor: Eight, Zulu

Abstract

This panel explores the way statistical modeling and algorithmic mediation transform subjects into objects. In his paper, John Cheney-Lippold argues that algorithmic accidents produce new knowledges not through difference or disruption, but through sameness. This argument exmained three examples, from statistical analysis disproving the authenticity signatures, to essentialist, and thus homogenizing, statistical analyses used to prove the guilt of an interracial couple, and to the physical accident of an algorithmically-driven car. In her paper, Angela Xiao Wu examines the use of sentiment analysis, or the automatic recognition of emotion in texts, in China’s fast growing “online public opinion analytics” industry that converts and aggregates individual online expressions into pie charts of categorical affect, which are further circulated and interpreted as public opinion in government and media discourses. In her paper, Kira Lussier examnines the entanglement of psychology, statistics, subjectivity, and computation at stake in the Implicit Association Test (IAT), a popular online psychological test that purports to measure implicit racial biases. She shows how IAT has created a massive data-gathering infrastructure and become a powerful truth-telling technology, generating “data doubles” by which people encounter their own attitudes towards race and racial differences. In his paper, Patrick Keilty focuses on PornHub insights to examine the uses to which PornHub’s vast surveillance network turns bodies over into the service of capital by softly persuading viewers to continue searching for an imagined perfect image and to enable repetitive and recursive browsing. Natasha Dow Schull will act as a discussant for the panel.

Discussant

Individual Presentations

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