76 citations · 154 across the 14 of their papers we have counts for
11 papers · 1 filter
Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies
Miles Brundage, Noemi Dreksler, Aidan Homewood +45
We outline a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers' safety and security claims, and evaluation of their sy…
The Future of the AI Summit Series
Lucia Velasco, Charles Martinet, Henry de Zoete +27
This policy memo examines the evolution of the international AI Summit series, initiated at Bletchley Park in 2023 and continued through Seoul in 2024 and Paris in 2025, as a forum…
Position: Ensuring mutual privacy is necessary for effective external evaluation of proprietary AI systems
Ben Bucknall, Robert F. Trager, Michael A. Osborne
The external evaluation of AI systems is increasingly recognised as a crucial approach for understanding their potential risks. However, facilitating external evaluation in practic…
Who Should Run Advanced AI Evaluations -- AISIs?
Merlin Stein, Milan Gandhi, Theresa Kriecherbauer +2
Artificial Intelligence (AI) Safety Institutes and governments worldwide are deciding whether they evaluate advanced AI themselves, support a private evaluation ecosystem or do bot…
Open Problems in Technical AI Governance
Anka Reuel, Ben Bucknall, Stephen Casper +30
AI progress is creating a growing range of risks and opportunities, but it is often unclear how they should be navigated. In many cases, the barriers and uncertainties faced are at…
Governing Through the Cloud: The Intermediary Role of Compute Providers in AI Regulation
Lennart Heim, Tim Fist, Janet Egan +5
As jurisdictions around the world take their first steps toward regulating the most powerful AI systems, such as the EU AI Act and the US Executive Order 14110, there is a growing…
Computing Power and the Governance of Artificial Intelligence
Girish Sastry, Lennart Heim, Haydn Belfield +16
Computing power, or "compute," is crucial for the development and deployment of artificial intelligence (AI) capabilities. As a result, governments and companies have started to le…
Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework
Markus Anderljung, Everett Thornton Smith, Joe O'Brien +7
With the increasing integration of frontier large language models (LLMs) into society and the economy, decisions related to their training, deployment, and use have far-reaching im…
Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings
Sarah Shoker, Andrew Reddie, Sarah Barrington +20
Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapon…
International Institutions for Advanced AI
Lewis Ho, Joslyn Barnhart, Robert Trager +8
International institutions may have an important role to play in ensuring advanced AI systems benefit humanity. International collaborations can unlock AI's ability to further sust…
Frontier AI Regulation: Managing Emerging Risks to Public Safety
Markus Anderljung, Joslyn Barnhart, Anton Korinek +21
Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "fr…