Regulation, Policy, Governance
How policymakers can best regulate AI to balance innovation with public interests and human rights.
The AI Sovereignty Paradox: Should Countries Buy, Build, or Lease to Maintain Strategic Control of Their AI?
As nations invest billions to reduce reliance on foreign AI providers, a new Stanford HAI report surveys commercial sovereignty solutions and assesses the extent to which they meaningfully reduce dependencies on U.S. tech giants.
As nations invest billions to reduce reliance on foreign AI providers, a new Stanford HAI report surveys commercial sovereignty solutions and assesses the extent to which they meaningfully reduce dependencies on U.S. tech giants.
In January 2026, Utah announced a first-of-its kind pilot program allowing an autonomous artificial intelligence (AI) agent to renew prescriptions for consumers who request it. The state agreed not to enforce its unprofessional conduct laws against the developer, Doctronic, if the company adheres to a contract that includes safety and privacy protections. The pilot program includes 192 drugs for chronic conditions. Although physicians will initially validate the AI’s actions, the pilot program will swiftly become one of the first deployments at scale of an autonomous, agentic system in medicine. The announcement prompted concern from associations of physicians and pharmacists who opined that AI “should NOT be making care decisions.”
In January 2026, Utah announced a first-of-its kind pilot program allowing an autonomous artificial intelligence (AI) agent to renew prescriptions for consumers who request it. The state agreed not to enforce its unprofessional conduct laws against the developer, Doctronic, if the company adheres to a contract that includes safety and privacy protections. The pilot program includes 192 drugs for chronic conditions. Although physicians will initially validate the AI’s actions, the pilot program will swiftly become one of the first deployments at scale of an autonomous, agentic system in medicine. The announcement prompted concern from associations of physicians and pharmacists who opined that AI “should NOT be making care decisions.”
Policy Research Grants
We welcome proposals for research projects that tackle important challenges and opportunities in this space from either a technical or social science perspective, with findings that can generate policy insights and recommendations.
Policy Research Grants
We welcome proposals for research projects that tackle important challenges and opportunities in this space from either a technical or social science perspective, with findings that can generate policy insights and recommendations.
Operationalizing Real-Time Monitoring of Clinical AI
This brief demonstrates how real-time monitoring can address critical gaps in the oversight of radiological AI tools.
This brief demonstrates how real-time monitoring can address critical gaps in the oversight of radiological AI tools.
All Work Published on Regulation, Policy, Governance
The state of New York is working to overhaul their antiquated and problematic regulations using AI tools developed by HAI Associate Director Dan Ho.
The state of New York is working to overhaul their antiquated and problematic regulations using AI tools developed by HAI Associate Director Dan Ho.
The AI Arms Race In Health Insurance Utilization Review: Promises Of Efficiency And Risks Of Supercharged Flaws
Health insurers and health care provider organizations are increasingly using artificial intelligence (AI) tools in prior authorization and claims processes. AI offers many potential benefits, but its adoption has raised concerns about the role of the “humans in the loop,” users’ understanding of AI, opacity of algorithmic determinations, underperformance in certain tasks, automation bias, and unintended social consequences. To date, institutional governance by insurers and providers has not fully met the challenge of ensuring responsible use. However, several steps could be taken to help realize the benefits of AI use while minimizing risks. Drawing on empirical work on AI use and our own ethical assessments of provider-facing tools as part of the AI governance process at Stanford Health Care, we examine why utilization review has attracted so much AI innovation and why it is challenging to ensure responsible use of AI. We conclude with several steps that could be taken to help realize the benefits of AI use while minimizing risks.
Health insurers and health care provider organizations are increasingly using artificial intelligence (AI) tools in prior authorization and claims processes. AI offers many potential benefits, but its adoption has raised concerns about the role of the “humans in the loop,” users’ understanding of AI, opacity of algorithmic determinations, underperformance in certain tasks, automation bias, and unintended social consequences. To date, institutional governance by insurers and providers has not fully met the challenge of ensuring responsible use. However, several steps could be taken to help realize the benefits of AI use while minimizing risks. Drawing on empirical work on AI use and our own ethical assessments of provider-facing tools as part of the AI governance process at Stanford Health Care, we examine why utilization review has attracted so much AI innovation and why it is challenging to ensure responsible use of AI. We conclude with several steps that could be taken to help realize the benefits of AI use while minimizing risks.
Data Privacy and Foundation Models: Can We Have Both?
This brief examines the privacy risks foundation models pose to individuals and society, and governance mechanisms needed to address them.
This brief examines the privacy risks foundation models pose to individuals and society, and governance mechanisms needed to address them.
Daniel E. Ho
HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.
HAI Executive Director Russell Wald talks about the AI competition between the U.S. and China, and the advent of “world models” that predict what might happen in real-world environments.