6 papers
Misaligned AI as a New Insider Risk
Matteo Pistillo, Charlotte Stix, Cameron Mohwinkle +1
In this policy memorandum, we explain why deployers of AI models in high-stakes contexts should treat those AI models as insider risk vectors. High-stakes contexts include AI model…
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…
The Loss of Control Playbook: Degrees, Dynamics, and Preparedness
Charlotte Stix, Annika Hallensleben, Alejandro Ortega +1
This research report addresses the absence of an actionable definition for Loss of Control (LoC) in AI systems by developing a novel taxonomy and preparedness framework. Despite in…
Assurance of Frontier AI Built for National Security
Matteo Pistillo, Charlotte Stix
This memorandum presents four recommendations aimed at strengthening the principles of AI model reliability and AI model governability, as DoW, ODNI, NIST, and CAISI refine AI assu…
AI Behind Closed Doors: a Primer on The Governance of Internal Deployment
Charlotte Stix, Matteo Pistillo, Girish Sastry +6
The most advanced future AI systems will first be deployed inside the frontier AI companies developing them. According to these companies and independent experts, AI systems may re…
Pre-Deployment Information Sharing: A Zoning Taxonomy for Precursory Capabilities
Matteo Pistillo, Charlotte Stix
High-impact and potentially dangerous capabilities can and should be broken down into early warning shots long before reaching red lines. Each of these early warning shots should c…