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20242026
most citedInternational AI Safety Report 2026

2 citations · 7 across the 13 of their papers we have counts for

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11 papers · 1 filter

cs.CY2026

Underwriting the Agent Economy: The Blueprint for an AI Insurance Stack

Cristian Trout, Sanmi Koyejo, Sasha Romanosky +34

From maritime trade to commercial nuclear power, insurance has been the enabler of major economic and technological developments by pricing risk, limiting downside, and spreading b…

cs.CY2026

Measuring Biological Capabilities and Risks of AI Agents

Patricia Paskov, Jeffrey Lee, Kyle Brady +1

This paper addresses a rapidly emerging policy challenge: how to generate and interpret credible evidence about the biological capabilities and risks of AI scientists, or agentic A…

cs.CY2026

Open Weight AI Models Require Proportional Evaluation Approaches

Patricia Paskov, Christopher Rodriguez, Sunishchal Dev +1

Open-weight AI models (OWMs), or models released with publicly-available weights, are distributing rapidly and approaching the performance levels of leading closed-weight AI models…

cs.CY2026

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…

cs.CY2026

RCTs for Frontier AI Governance: Methodological Challenges and Solutions for Human Uplift Studies

Patricia Paskov, Kevin Wei, Shen Zhou Hong +7

Human uplift studies, or studies that measure the effects of AI access on human performance via randomized controlled trials (RCT) or similar methodologies, increasingly inform fro…

cs.CY2026★ 2 cited

International AI Safety Report 2026

Yoshua Bengio, Stephen Clare, Carina Prunkl +89

The International AI Safety Report 2026 synthesises the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report series…

cs.CY2026★ 2 cited

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…

cs.CY2026★ 1 cited

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…

cs.CY2025

Preliminary suggestions for rigorous GPAI model evaluations

Patricia Paskov, Michael J. Byun, Kevin Wei +1

This document presents a preliminary compilation of general-purpose AI (GPAI) evaluation practices that may promote internal validity, external validity and reproducibility. It inc…

cs.CY2025

In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?

Ben Bucknall, Saad Siddiqui, Lara Thurnherr +19

International cooperation is common in AI research, including between geopolitical rivals. While many experts advocate for greater international cooperation on AI safety to address…

cs.CY2024★ 2 cited

GPAI Evaluations Standards Taskforce: Towards Effective AI Governance

Patricia Paskov, Lukas Berglund, Everett Smith +1

General-purpose AI evaluations have been proposed as a promising way of identifying and mitigating systemic risks posed by AI development and deployment. While GPAI evaluations pla…