1 citations · 1 across the 6 of their papers we have counts for
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Embedded Assessments for Frontier AI
Jacob Charnock, Sophie Williams, Zaheed Kara +5
Third-party evaluations for frontier AI have mostly tested models through external interfaces before deployment. But the risks from frontier AI models depend on how their developer…
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…
Open Technical Problems in Open-Weight AI Model Risk Management
Stephen Casper, Kyle O'Brien, Shayne Longpre +19
Frontier AI models with openly available weights are steadily becoming more powerful and widely adopted. However, compared to proprietary models, open-weight models pose different…
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…
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…
Expanding External Access To Frontier AI Models For Dangerous Capability Evaluations
Jacob Charnock, Alejandro Tlaie, Kyle O'Brien +2
Frontier AI companies increasingly rely on external evaluations to assess risks from dangerous capabilities before deployment. However, external evaluators often receive limited mo…