Sustainability and Sovereignty in AI Governance

Session Submission Type: Panel

Abstract

As artificial intelligence (AI) becomes increasingly embedded in public systems and global infrastructures, questions of sustainability and sovereignty are emerging as central challenges for governance. While existing approaches often address these dimensions in isolation, there remains limited integration across the socio-ecological, institutional, and political dynamics that shape AI’s development, deployment, and long-term societal impacts. This fragmentation presents a critical challenge for policymakers, who must simultaneously navigate environmental constraints, jurisdictional complexity, uneven technological capacity, and the growing influence of private sector actors.

This panel brings together three complementary perspectives to examine how sustainability and sovereignty intersect across multiple layers of AI governance. The first paper develops a policy-oriented framework for understanding the socio-ecological impacts of AI across interconnected system layers, offering a structured approach to diagnosing cumulative effects and informing context-sensitive sustainability pathways under varying infrastructural and institutional conditions. The second paper examines AI governance in cross-jurisdictional settings, focusing on U.S. tribal emergency management. It demonstrates how collaborative co-design processes—particularly transparency—shape perceptions of tribal sovereignty and influence the legitimacy of governance in contexts marked by asymmetrical authority and complex intergovernmental relationships. The third paper addresses the expanding role of private sector actors, introducing a typology of corporate quasi-sovereignty to analyze how AI firms shape governance outcomes through both infrastructural capacity and political engagement.


Together, these papers highlight the multi-level and contested nature of AI governance, in which sustainability goals, jurisdictional authority, and private-sector power must be negotiated simultaneously. The panel advances a more integrated understanding of AI governance by bridging these domains and identifying the structural tensions, trade-offs, and governance gaps that emerge across them. In doing so, it provides policymakers and researchers with conceptual and empirical tools to design governance frameworks that are not only technologically responsive but also environmentally sustainable, institutionally legitimate, and attentive to the equitable distribution of power in AI-driven societies.

Policy Area

• Innovations in Science and Technology

Chair

• DORCAS U ATTAH, Workforce Intelligence Institute

Discussants

• Kaylyn Jackson Schiff, Purdue University

• Yanfang Su, University of Washington

Organizer

• DORCAS U ATTAH, Workforce Intelligence Institute

Individual Presentations

• Sustainable AI Development Pathways - Presenting Author: Hye In Chung, University of California, Berkeley

• Beyond Technological Benefits and Risks: Governance Conditions and Perceived Tribal Sovereignty in AI Co-Design - Presenting Author: Sukwon Choi, University of Nebraska-Omaha

• Operationalizing Corporate Quasi-Sovereignty in AI Governance: A Multi-Stream Typology and Methodological Framework - Presenting Author: Chee Hae Chung, Harvard University

• Mapping the landscape of AI-related legislation in the U.S. - Presenting Author: Tomo Lazovich, Brown University; Non-Presenting Co-Author: Juliet King, Brown University; Non-Presenting Co-Author: Emily Li Hong, Brown University