Response to OSTP’s Request for Information on the Development of an AI Action Plan
In this response to a request for information issued by the National Science Foundation’s Networking and Information Technology Research and Development National Coordination Office (on behalf of the Office of Science and Technology Policy), scholars from Stanford HAI, CRFM, and RegLab urge policymakers to prioritize four areas of policy action in their AI Action Plan: 1) Promote open innovation as a strategic advantage for U.S. competitiveness; 2) Maintain U.S. AI leadership by promoting scientific innovation; 3) Craft evidence-based AI policy that protects Americans without stifling innovation; 4) Empower government leaders with resources and technical expertise to ensure a “whole-of-government” approach to AI governance.
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Safeguarding Third-Party AI Research
This brief examines the barriers to independent AI evaluation and proposes safe harbors to protect good-faith third-party research.
This brief examines the barriers to independent AI evaluation and proposes safe harbors to protect good-faith third-party research.
This white paper assesses federal efforts to advance leadership on AI innovation and governance through recent executive actions and emphasizes the need for senior-level leadership to achieve a whole-of-government approach.
This white paper assesses federal efforts to advance leadership on AI innovation and governance through recent executive actions and emphasizes the need for senior-level leadership to achieve a whole-of-government approach.
In this response to the U.S. AI Safety Institute’s (US AISI) request for comment on its draft guidelines for managing the misuse risk for dual-use foundation models, scholars from Stanford HAI, the Center for Research on Foundation Models (CRFM), and the Regulation, Evaluation, and Governance Lab (RegLab) urge the US AISI to strengthen its guidance on reproducible evaluations and third- party evaluations, as well as clarify guidance on post-deployment monitoring. They also encourage the institute to develop similar guidance for other actors in the foundation model supply chain and for non-misuse risks, while ensuring the continued open release of foundation models absent evidence of marginal risk.
In this response to the U.S. AI Safety Institute’s (US AISI) request for comment on its draft guidelines for managing the misuse risk for dual-use foundation models, scholars from Stanford HAI, the Center for Research on Foundation Models (CRFM), and the Regulation, Evaluation, and Governance Lab (RegLab) urge the US AISI to strengthen its guidance on reproducible evaluations and third- party evaluations, as well as clarify guidance on post-deployment monitoring. They also encourage the institute to develop similar guidance for other actors in the foundation model supply chain and for non-misuse risks, while ensuring the continued open release of foundation models absent evidence of marginal risk.
Leading policymakers, academics, healthcare providers, AI developers, and patient advocates discuss the path forward for healthcare AI policy at closed-door workshop.
Leading policymakers, academics, healthcare providers, AI developers, and patient advocates discuss the path forward for healthcare AI policy at closed-door workshop.