All Work Published on Regulation, Policy, Governance
Empowering Policymakers: Stanford HAI Trains Public Sector at Every Level
Stanford HAI has built a major portfolio of education opportunities for state, federal, and international policy leaders to strengthen AI governance.
Stanford HAI has built a major portfolio of education opportunities for state, federal, and international policy leaders to strengthen AI governance.
In this paper, a multi-disciplinary group of Stanford students and contributors led by HAI Policy Fellow Marietje Schaake share policy recommendations with the EU Commission regarding a European approach to regulating AI, as laid out in its White Paper on AI.
In this paper, a multi-disciplinary group of Stanford students and contributors led by HAI Policy Fellow Marietje Schaake share policy recommendations with the EU Commission regarding a European approach to regulating AI, as laid out in its White Paper on AI.
Making AI Work for Health Care: Stanford’s Framework Evaluates Impact
As hospitals rapidly adopt artificial intelligence technologies, open-source guardrails can help better determine whether a tool is ethical, useful, and realistic for their systems.
As hospitals rapidly adopt artificial intelligence technologies, open-source guardrails can help better determine whether a tool is ethical, useful, and realistic for their systems.
A Plan To Democratize Access To Powerful AI Tools Gets A Last-Ditch Push In Congress
HAI Executive Director Russell Wald speaks about the importance of passing the CREATE AI Act, born from Stanford HAI's National AI Research Resource.
HAI Executive Director Russell Wald speaks about the importance of passing the CREATE AI Act, born from Stanford HAI's National AI Research Resource.
This bipartisan effort promises transformative benefits for AI research—but only if Congress acts now.
This bipartisan effort promises transformative benefits for AI research—but only if Congress acts now.
At a recent Stanford-MIT-Princeton workshop, experts highlight the need for legal protections, standardized evaluation practices, and better terminology to support third-party AI evaluations.
At a recent Stanford-MIT-Princeton workshop, experts highlight the need for legal protections, standardized evaluation practices, and better terminology to support third-party AI evaluations.
