SSC Virtual Seminar Series: Luke Stark, Faculty of Information & Media Studies, University of Western Ontario

Luke Stark
Luke Stark

Artificial Intelligence, Prediction, and the Conjectural Sciences

Wednesday, March 2, 2022

12:30 – 2:00 pm

*We will send the seminar link and password to registered participants.

Please RSVP to Joan Sharpe.


In this paper I argue ML-driven science involving certain categories of data is fundamentally “conjectural.” Such “conjectural science” produces conclusions reliant on post-facto interpretation: partial inductive insights misinterpreted as widely applicable deductive truths. Elaborating on the notion of “conjectural science” as developed by Italian historian Carlo Ginzburg, I apply the history of the “conjectural sciences” to their contemporary instantiations in machine learning research and aiming to clarify some of the ways in which the use of ML systems is appropriate or inappropriate, not only practically but also conceptually. The appeal of AI-driven predictive statistical analyses, paired as they are with very large data sets to be analyzed, is that the conclusions drawn from that data about individual humans can be understood as measurable and repeatable through sheer quantity of data. However, I argue that AI techniques, when applied to data about humans and the social world, are conjectural science raised to its most acute form. Though AI analysis of human behaviors and societies aspire to the epistemological norms of “natural” science, in many cases, AI does not support such science as commonly understood.

About the speaker:

Luke Stark is an Assistant Professor in the Faculty of Information and Media Studies at Western University in London, ON. His work interrogating the historical, social, and ethical impacts of computing and AI technologies has appeared in journals including The Information Society, Social Studies of Science, and New Media & Society, and in popular venues like Slate, The Globe and Mail, and The Boston Globe. Luke was previously a Postdoctoral Researcher in AI ethics at Microsoft Research, and a Postdoctoral Fellow in Sociology at Dartmouth College; he holds a PhD from the Department of Media, Culture, and Communication at New York University.

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