7 papers
Silent Updates: Measuring and Closing the Post-Deployment Disclosure Gap
Sophia Abraham, Ben Bucknall
Deployed foundation models are often not static systems, with providers able to modify system behavior through fine-tuning, classifier updates, system prompt revisions, retrieval c…
Underwriting the Agent Economy: The Blueprint for an AI Insurance Stack
Cristian Trout, Sanmi Koyejo, Sasha Romanosky +34
The paper proposes a comprehensive AI insurance framework to price and manage risks from the emerging AI agent economy, outlining an eight‑component stack for data collection, mode…
The 2026 Singapore Consensus on Global AI Safety Research Priorities
Stephen Casper, Oskar Galeev, Yoshua Bengio +117
Frontier AI capabilities and autonomy are advancing rapidly. A growing number of real-world incidents make a trusted AI ecosystem essential to embracing AI with confidence. The 202…
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…
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…
Emerging Practices in Frontier AI Safety Frameworks
Marie Davidsen Buhl, Ben Bucknall, Tammy Masterson
As part of the Frontier AI Safety Commitments agreed to at the 2024 AI Seoul Summit, many AI developers agreed to publish a safety framework outlining how they will manage potentia…