2 citations · 3 across the 6 of their papers we have counts for
6 papers
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…
Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts
Alexander K. Saeri, Jess Graham, Michael Noetel +185
Artificial intelligence poses many risks, ranging from familiar present-day harms to unprecedented and potentially catastrophic ones. Effective risk management requires prioritizat…
Toward Risk Thresholds for AI-Enabled Cyber Threats: Enhancing Decision-Making Under Uncertainty with Bayesian Networks
Krystal Jackson, Deepika Raman, Jessica Newman +3
Artificial intelligence (AI) is increasingly being used to augment and automate cyber operations, altering the scale, speed, and accessibility of malicious activity. These shifts r…
CALMA: A Process for Deriving Context-aligned Axes for Language Model Alignment
Prajna Soni, Deepika Raman, Dylan Hadfield-Menell
Datasets play a central role in AI governance by enabling both evaluation (measuring capabilities) and alignment (enforcing values) along axes such as helpfulness, harmlessness, to…
AI Risk-Management Standards Profile for General-Purpose AI (GPAI) and Foundation Models
Anthony M. Barrett, Jessica Newman, Brandie Nonnecke +5
Increasingly multi-purpose AI models, such as cutting-edge large language models or other 'general-purpose AI' (GPAI) models, 'foundation models,' generative AI models, and 'fronti…
Intolerable Risk Threshold Recommendations for Artificial Intelligence
Deepika Raman, Nada Madkour, Evan R. Murphy +2
Frontier AI models -- highly capable foundation models at the cutting edge of AI development -- may pose severe risks to public safety, human rights, economic stability, and societ…