GovAI Research

Summary

The Centre for the Governance of AI's research repository is where rigorous academic inquiry meets real-world policy challenges. This isn't just another collection of papers—it's a dynamic research hub that bridges the gap between AI technical developments and governance implications. The repository features cutting-edge studies on AI agents' evolving capabilities and unique insights from surveys of US policymakers, offering both theoretical frameworks and empirical data that are often unavailable elsewhere. For anyone trying to understand how AI governance is evolving beyond the headlines, this is essential reading.

What makes this research different

Unlike think tank reports or industry whitepapers, GovAI Research applies academic rigor to governance questions that are often addressed through speculation or advocacy. Their approach combines technical understanding of AI systems with policy analysis, creating research that speaks to both communities. The policymaker surveys are particularly valuable—rather than assuming what officials think about AI governance, they actually ask them, providing rare empirical data on how AI policy is understood at the local level in the US.

The research on AI agents' capabilities stands out for its governance focus. While many technical papers explore what AI can do, GovAI Research examines what those capabilities mean for regulation, oversight, and societal impact. This perspective is crucial as policymakers grapple with governing technologies they may not fully understand.

Key research themes you'll encounter

AI Agents and Autonomy: Deep dives into how increasing AI agent capabilities create new governance challenges, from accountability questions to risk assessment frameworks.

Policymaker Perspectives: Empirical studies revealing how local US officials actually view AI governance issues, highlighting gaps between expert discussions and on-the-ground policy understanding.

Institutional Design: Research on how governance structures need to evolve to effectively oversee AI development and deployment.

International Coordination: Analysis of how different jurisdictions approach AI governance and opportunities for policy alignment.

Technical Governance: Studies bridging technical AI safety concepts with practical governance mechanisms.

Who this resource is for

Policy researchers and academics will find methodologically sound studies and novel datasets perfect for citations and building upon existing work.

Government officials and staffers can access evidence-based insights about AI governance approaches and learn from peer jurisdictions' experiences.

Think tank analysts and policy advocates will discover rigorous research to support their recommendations and identify gaps in current policy discussions.

AI industry professionals involved in policy work can better understand the governance landscape and anticipate regulatory developments.

Graduate students and researchers in AI policy, science and technology studies, or public administration will find both theoretical frameworks and empirical studies for their own work.

Getting the most from this repository

Start with the most recent publications to understand current research priorities, then explore thematic areas relevant to your work. Pay special attention to the methodology sections—GovAI's research designs often pioneer new approaches to studying governance questions that you might adapt for your own work.

The policymaker survey results are goldmines for understanding implementation challenges. Use these insights to ground theoretical governance proposals in political reality.

For practitioners, focus on the policy recommendations and institutional design suggestions. These researchers understand both the technical and political constraints, making their recommendations more actionable than purely technical or purely political analyses.

Limitations to keep in mind

As academic research, findings may take time to reflect rapidly evolving AI capabilities. The focus on certain jurisdictions (particularly the US and UK contexts) may limit global applicability. Some highly technical governance questions might require supplementing with more technical AI safety research. Additionally, the academic publication timeline means the most cutting-edge governance challenges might not yet be reflected in available studies.