Tracing Class and Capital in Critical AI Research

Keywords: artifical intelligence, machine learning, digital capitalism, distant reading, critical studies


This article explores the rapidly developing field of Critical AI Studies and its relation to issues of class and capitalism through a hybrid approach based on distant reading of a newly collected corpus of 300 full-text scientific articles, the creation of which is itself a first attempt at properly delineating the field. We find that words related to issues of class are predominantly but not exclusively confined to a set of studies that make up their own distinct subfield of Critical AI Studies, in contrast to, e.g., issues of race and gender, which are more broadly present in the corpus.

Author Biographies

Petter Ericson, Umeå University

Petter Ericson is a postdoctoral research fellow in the research group for Responsible AI at the Department of Computing Science at Umeå University, Sweden. His research is focused on the political implications of technology, and on exploring alternative technological and computational paradigms with the potential to distribute, rather than accumulate, power. He is also interested in facilitating clear and honest communication between seemingly distant groups of people interacting with the same socio-technical systems, and in clarifying issues of common interest, as well as of conflict, between them.

Roel Dobbe, Technische Universiteit Delft

Roel Dobbe is an assistant professor in the Information and Communication Technology section of the Faculty of Technology, Policy, and Management at Delft University of Technology. His research embraces system safety as a lens to understand how harm arises in data-driven, algorithmic and artificial intelligence systems, leaning on the history of complex systems subject to software-based automation. Roel has a PhD in Electrical Engineering and Computer Sciences from the University of California Berkeley (2018) and a MSc in Systems and Control from Delft University of Technology (2010). He is an active contributor to the establishment of governance practices for algorithmic and AI systems in public organizations, including in public administration, energy systems and healthcare. He also serves as a board member to Foundation PublicSpaces, a Dutch coalition of public organisations in public media, cultural heritage, festivals, museums and education working together to reclaim the internet as a force for the common good and advocating for and building a new internet that strengthens the public domain.

Simon Lindgren, Umeå University

Simon Lindgren is Professor of Sociology at Umeå University. He is also the director of DIGSUM, an interdisciplinary research centre studying the social dimensions of digital technology, and the editor-in-chief of the Journal of Digital Social Research. His research is about the transformative role of digital communication technologies (internet and social media), and the consequences of datafication and algorithms, with a particular focus on politics and power relations. He uses combinations of methods from computational social science and network science, and analytical frameworks from interpretive sociology and critical theory. Lindgren’s books include “Critical Theory of AI” (2023). “Data Theory” (2020), “Digital Media and Society” (2017; 2022), and “New Noise” (2013).

Critical Perspectives on Digital Capitalism 2: Digital Labour and Class