3 citations · 3 across the 5 of their papers we have counts for
4 papers · 1 filter
Open Problems in AI Risk Modeling: Insights from a Workshop on the Technical Foundations of AI Risk Modeling
Krystal Jackson, Deepika Raman, Jakub Kryś +8
We investigate the design of robust risk models to assess societal risks posed by advanced AI systems, an emerging area in AI governance. Many regulatory proposals increasingly req…
Exploring Systems-Thinking Approaches to Loss of Control Risk
Aurelio Carlucci, Sean P. Fillingham, James Walpole +1
Internal deployment of agentic AI systems for coding and research creates a sociotechnical control problem that extends beyond model behaviour. We treat internal-deployment Loss of…
Toward Quantitative Modeling of Cybersecurity Risks Due to AI Misuse
Steve Barrett, Malcolm Murray, Otter Quarks +17
Advanced AI systems offer substantial benefits but also introduce risks. In 2025, AI-enabled cyber offense has emerged as a concrete example. This technical report applies a quanti…
Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape
Jakub Kryś, Yashvardhan Sharma, Janet Egan
Advances in low-communication training algorithms are enabling a shift from centralised model training to compute setups that are either distributed across multiple clusters or dec…