All Work Published on Regulation, Policy, Governance
Biden-era AI safety promises aren't holding up, and Apple's the weakest link
Rishi Bommasani, Society Lead at Stanford Center for Research on Foundation Models, speaks about a new analysis: "Do AI Companies Make Good on Voluntary Commitments to the White House?"
Rishi Bommasani, Society Lead at Stanford Center for Research on Foundation Models, speaks about a new analysis: "Do AI Companies Make Good on Voluntary Commitments to the White House?"
This brief sheds light on the “regulatory misalignment” problem by considering the technical and institutional feasibility of four commonly proposed AI regulatory regimes.
This brief sheds light on the “regulatory misalignment” problem by considering the technical and institutional feasibility of four commonly proposed AI regulatory regimes.
Erik Brynjolfsson, HAI Senior Fellow and Director of the Stanford Digital Economy Lab, speaks about AI's policymakers' roles in preparing for AI impacts on the labor markets.
Erik Brynjolfsson, HAI Senior Fellow and Director of the Stanford Digital Economy Lab, speaks about AI's policymakers' roles in preparing for AI impacts on the labor markets.
Foundation Models and Copyright Questions
This brief warns that fair use may not fully shield U.S. foundation models trained on copyrighted data and calls for combined legal and technical safeguards to protect creators.
This brief warns that fair use may not fully shield U.S. foundation models trained on copyrighted data and calls for combined legal and technical safeguards to protect creators.
Experts from Stanford HAI and top universities urge policymakers to prioritize scientific understanding to govern frontier AI.
Experts from Stanford HAI and top universities urge policymakers to prioritize scientific understanding to govern frontier AI.
The Privacy-Bias Trade-Off
This brief examines the “regulatory misalignment” of existing regulatory proposals for AI and urges policymakers to first consider feasibility, trade-offs, and unintended consequences before rushing into regulation.
This brief examines the “regulatory misalignment” of existing regulatory proposals for AI and urges policymakers to first consider feasibility, trade-offs, and unintended consequences before rushing into regulation.
