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Tech Ethics & Policy Summer Fellowships

HAI is offering a fully funded summer fellowship for graduate students to gain hands-on experience in AI policy in  Washington D.C. and California applying their technical expertise to shape responsible technology policy. 

AI Policy Working Group

A unique opportunity for Stanford graduate students and researchers to bridge the gap between cutting-edge AI research and pressing public policy challenges.

Emerging Technology Policy Writing Competition

The competition sought innovative policy analysis and solutions to help policymakers map out a human-centric approach to the safe, responsible development and deployment of emerging technologies.

Recent Policy Publications

Testimony

Russ Altman’s Testimony Before the U.S. Senate Committee on Health, Education, Labor, and Pensions

Russ Altman
HealthcareRegulation, Policy, GovernanceSciences (Social, Health, Biological, Physical)Quick ReadOct 09

In this testimony presented to the U.S. Senate Committee on Health, Education, Labor, and Pensions hearing titled “AI’s Potential to Support Patients, Workers, Children, and Families,” Russ Altman highlights opportunities for congressional support to make AI applications for patient care and drug discovery stronger, safer, and human-centered.

Policy Brief

Validating Claims About AI: A Policymaker’s Guide

Olawale Salaudeen, Anka Reuel, Angelina Wang, Sanmi Koyejo
Foundation ModelsPrivacy, Safety, SecurityQuick ReadSep 24

This brief proposes a practical validation framework to help policymakers separate legitimate claims about AI systems from unsupported claims.

Testimony

Yejin Choi’s Briefing to the United Nations Security Council

Yejin Choi
International Affairs, International Security, International DevelopmentQuick ReadSep 24

In this address, presented to the United Nations Security Council meeting on "Maintenance of International Peace and Security," Yejin Choi calls on the global scientific and policy communities to expand the AI frontier for all by pursuing intelligence that is not only powerful, but also accessible, robust, and efficient. She stresses the need to rethink our dependence on massive-scale data and computing resources from the outset, and design methods that do more with less — by building AI that is smaller and serves all communities.