A Sociology of Artificial Intelligence: Inequalities, Power, and Data Justice
By Kelly Joyce and Taylor M. Cruz
Artificial intelligence is at the center of contemporary debates over the future of how we will live, learn, and work. AI applications ranging from predictive analytics to generative AI platforms such as ChatGPT are quickly being integrated into everyday life, provoking spirited discussions among professionals in law, business, and higher education. Media headlines generate public hype over AI’s promises and perils, yet significant uncertainty remains over the technology itself and its wider social consequences. What exactly is “AI”? Can AI be used for social good, or does it risk reinforcing forms of power and inequality? What is the role of sociology in building toward a more equitable future with AI?
The special collection “A Sociology of AI: Inequalities, Power, and Data Justice” in Socius showcases innovative research and scholarship from the emerging sociology of AI. This special collection builds on the U.S. Office of Science and Technology Policy’s (2022) “Blueprint for an AI Bill of Rights,” which was led by sociologist Alondra Nelson, and emphasizes issues of access, transparency, and public engagement. The collection integrates our original call for sociological research on AI (Hoffman et al. 2022; Joyce et al. 2021), and investigates what the discipline of sociology has to contribute to the study of AI. We highlight three contributions sociologists are poised to offer: (1) critical analysis of AI hype, promotion, and adoption; (2) empirical study of AI’s co-constitution with processes of social life; and (3) identification of avenues for structural change in creating equitable AI futures.
The articles draw on sociological foundations to study a range of topics associated with AI, such as machine learning (ML) health applications, sexual technologies, the creation of new scientific professions, and public policy. The articles collectively demonstrate the power of classical sociological methods such as ethnography, content analysis, and surveys to investigate AI as well as offer suggestions for how to integrate GenAI platforms into sociological research. The articles further examine AI as a tool for design, practice, and method; the special collection thus showcases the breadth of approaches sociologists may take in studying AI.
As we think about next steps, we conclude the collection with a call for additional research in this emerging area. First, we highlight the need to develop new ways of studying AI in practice. Because of the distributed nature of AI, in which multiple programmers may contribute to it at once or over time, our current methodological toolkit will need to expand to imagine novel ways of studying AI and consider new data sources (e.g., records from AI practitioner documentation of model building). Second, we encourage researchers to design future projects focused on issues of power, inequality, and social justice. Sociologists recognize that technical advances in data, algorithms, and AI cannot undo durable systems of entrenched inequality alone . Moving beyond critique, however, we also believe sociology has the tools needed to imagine more just and equitable futures with AI.
We hope this special collection on the sociology of AI moves us beyond headlines and hype, to spark innovative sociological work toward equity and justice.
Special Collection details
Sociology of Artificial Intelligence
Guest Editors: Kelly Joyce & Taylor M. Cruz
Socius: Sage Journals
About the Authors
