Department Seminar: The Material Political Economy of Prediction

About the lecture
Automated, machine-learning prediction is central to the digital economy, via platforms prominent in everyday life and what the paper will describe as the data “icebergs” that platforms accumulate. Access difficulties, however, make direct interview-based or observational research on these platforms close to impossible. The research reported
in this paper circumvents those difficulties in two ways. First, it examines platforms “obliquely,” via the experiences/practices of those who advertise on them. Second, it takes advantage of material practices of prediction having been rendered more visible by a major disruption of them: Apple’s 2021 App Tracking Transparency changes to iPhones. In the aftermath of those changes, the paper argues, two different formsof material configuration are implicitly vying for a key role in underpinning the everydaydigital economy: Apple’s and (soon) Google’s partially de-individualized “crowd anonymity” arrangements; and other market participants’ efforts to rebuild individualization.

All members of the department and research staff from across the faculty are invited to attend. Please navigate the calendar on the Department and Sociology's website to find upcoming Department Seminars.