The Global Governance of Artificial Intelligence

Session Submission Type: Full Paper Panel

Session Description

The rapid advancement of artificial intelligence (AI) has ignited widespread debate about when, where, and how the technology should be regulated. These discussions are shaped by evolving public perceptions, corporate interests, and geopolitical considerations, leading to considerable variation in the regulatory outlook of individuals, firms, and governments across the globe. This panel brings attention to several themes that are likely to shape the literature on AI governance in the coming years. Using a variety of methodological approaches and new data sources, the papers investigate the nature of individual, state and non-state preferences over AI regulation, and how such preferences shape regulatory choices at national and international levels. This panel sheds light on the emerging landscape of AI regulation, drawing on a range of methodologies, including survey experiments, text analysis, and new cross-national datasets on AI policy initiatives.

The paper by Lake and Wong proposes a novel approach to AI regulation through professional associations, advocating for a model that combines technical expertise with ethical standards enforcement. Chapman, Nielson, and Li examine preferences of firm managers over international AI regulation, revealing insights through a conjoint survey experiment. Büthe provides a comparative analysis of AI use in algorithmic management, examining various governance attempts including the U.S. Executive Order on AI. Li’s paper examines trends in AI governance, utilizing OECD data to analyze national AI policies across 70 countries. Lastly, Geith, Lundgren, and Tallberg offer a quantitative analysis of the EU AI Act negotiations, using a preference attainment model to uncover the dynamics of bargaining success among EU member states.

Sub Unit

• Division 17: International Collaboration

Cosponsor

• Division 16: International Political Economy

Individual Presentations

• Why Not Regulate AI through Professional Associations? - David A. Lake, University of California, San Diego; Wendy H. Wong, University of British Columbia

• Firm Preferences over International AI Regulatory Governance - Terrence Chapman, University of Texas at Austin; Daniel L. Nielson, University of Texas at Austin; Huimin Li, University of Texas at Austin

• The Governance of Algorithmic Management: A Comparative Analysis - Tim Buthe, Technical University of Munich (TUM)

• AI Governance and Digital Rights Protection: Insights from the OECD Dataset - Huimin Li, University of Texas at Austin

• Governing Artificial Intelligence in Europe - Johannes Geith, Stockholm University; Magnus Lundgren, University of Gothenburg; Jonas Tallberg, Stockholm University

Chair

• Karl Orfeo Fioretos Temple University

Discussants

• Graeme Auld Carleton University

• Terrence Chapman University of Texas at Austin