6 papers
The science and practice of proportionality in AI risk evaluations
Carlos Mougan, Lauritz Morlock, Jair Aguirre +19
A global challenge in artificial intelligence (AI) regulation lies in achieving effective risk management without compromising innovation and technical progress. The European Union…
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…
A Methodology for Quantitative AI Risk Modeling
Malcolm Murray, Steve Barrett, Henry Papadatos +5
Although general-purpose AI systems offer transformational opportunities in science and industry, they simultaneously raise critical concerns about safety, misuse, and potential lo…
The Role of Risk Modeling in Advanced AI Risk Management
Chloé Touzet, Henry Papadatos, Malcolm Murray +6
Rapidly advancing artificial intelligence (AI) systems introduce novel, uncertain, and potentially catastrophic risks. Managing these risks requires a mature risk-management infras…
Mapping AI Benchmark Data to Quantitative Risk Estimates Through Expert Elicitation
Malcolm Murray, Henry Papadatos, Otter Quarks +2
The literature and multiple experts point to many potential risks from large language models (LLMs), but there are still very few direct measurements of the actual harms posed. AI…
A Frontier AI Risk Management Framework: Bridging the Gap Between Current AI Practices and Established Risk Management
Simeon Campos, Henry Papadatos, Fabien Roger +3
The recent development of powerful AI systems has highlighted the need for robust risk management frameworks in the AI industry. Although companies have begun to implement safety f…