Sociological Contributions to Artificial Intelligence

Session Submission Type: Invited Session (90 minute)

Description

As artificial intelligence systems become central to many domains of social life — from healthcare to education to the workplace — this panel highlights the unique contributions sociology can make to cross-disciplinary conversations about AI. Responding to the conference’s call to put sociology to work for a more equitable society, we explore how sociological insights can sharpen critiques of AI and inform its design, deployment, evaluation, and governance. The panel asks: How can sociological concepts, theories, and methods enrich technical and normative debates on AI? How might community-engaged sociological research democratize AI development and foster more comprehensive evaluations? And what changes within our discipline could better support scholars working at these intersections? Bringing together scholars with diverse substantive and methodological perspectives, we aim to show how sociology’s theoretical richness and methodological range can be leveraged to shape AI systems in ways that bridge inequalities while advancing human wellbeing, creativity, and institutional accountability.

Sub Unit

• Thematic Session

Presider

• Simone Zhang, New York University

Panelists

• Karen Levy, Cornell University

• Mona Sloane, University of Virginia

• Marion Fourcade, University of California-Berkeley

• James A. Evans, University of Chicago

• Barbara Kiviat, Columbia University

• Robb Willer, Stanford Universty

Session Organizer

• Simone Zhang, New York University