Critical Machine Learning Studies

Fabian Offert
Germanic and Slavic Studies
UC Santa Barbara

Rita Raley
UC Santa Barbara


Benjamin Bratton
Visual Arts
UC San Diego

Paul Dourish
UC Irvine

Jacob Gaboury
Film and Media
UC Berkeley

Lilly Irani
Communication and Science Studies
UC San Diego

Matteo Pasquinelli
Media Philosophy
University of Arts and Design, Karlsruhe

Kriss Ravetto
School of Theater, Film & Television
UC Los Angeles

This working group aims to articulate, from within the humanities, a technically specific and situated paradigm for engaging machine learning. Academic work on artificial intelligence seems now to be omnipresent, precisely because AI itself is such a rapidly developing field of research with widespread practical implementations lagging only slightly behind. The focus of many of these academic initiatives is genealogical, philosophical, and political. While we by no means eschew such perspectives, what we contribute is a framework that yokes the theoretical and the practical by focusing on specific machine learning architectures, rather than understanding artificial intelligence as a technically and ideologically homogeneous cultural technique. We leverage, in a collaborative and interdisciplinary way, the combined experience of UC faculty to design new approaches to describe, and critique in detail, contemporary machine learning systems. We focus on their individual (“ML studies”) rather than collective (“AI Studies”) properties, and on their architecture-specific rather than model-specific biases and shortcomings.