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Michelle Mello | Stanford HAI

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peopleFaculty

Michelle Mello

Professor of Law, Stanford Law School; Professor of Health Policy, Department of Health Policy, Stanford University School of Medicine

External Bio

Michelle Mello is Professor of Law at Stanford Law School and Professor of Health Policy in the Department of Health Policy at Stanford University School of Medicine.  She conducts empirical research into issues at the intersection of law, ethics, and health policy.  She is the author of more than 250 articles on medical liability, public health law, the public health response to COVID-19, pharmaceuticals and vaccines, data ethics and privacy, research ethics and governance, artificial intelligence, and other topics.

The recipient of a number of awards for her research, Dr. Mello was elected to the National Academy of Medicine at the age of 40. From 2000 to 2014, she was a professor at the Harvard School of Public Health, where she directed the School’s Program in Law and Public Health. 

Dr. Mello teaches in the areas of torts, public health law, and health policy. She holds a J.D. from the Yale Law School, a Ph.D. in Health Policy and Administration from the University of North Carolina at Chapel Hill, an M.Phil. from Oxford University, where she was a Marshall Scholar, and a B.A. from Stanford University. 

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Latest Related to Michelle Mello

Research
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The AI Arms Race In Health Insurance Utilization Review: Promises Of Efficiency And Risks Of Supercharged Flaws

Michelle Mello, Artem Trotsyuk, Abdoul Jalil Djiberou Mahamadou, Danton Char
HealthcareRegulation, Policy, GovernanceQuick ReadJan 06

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.

Research
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AI, Health, and Health Care Today and Tomorrow: The JAMA Summit Report on Artificial Intelligence

Tina Hernandez-Boussard, Michelle Mello, Nigam Shah, Co-authored by 50+ experts
HealthcareRegulation, Policy, GovernanceDeep DiveOct 13
testimony

Michelle M. Mello's Testimony Before the U.S. House Committee on Energy and Commerce Health Subcommittee

Michelle Mello
HealthcareRegulation, Policy, GovernanceQuick ReadSep 02

In this testimony presented to the U.S. House Committee on Energy and Commerce’s Subcommittee on Health hearing titled “Examining Opportunities to Advance American Health Care through the Use of Artificial Intelligence Technologies,” Michelle M. Mello calls for policy changes that will promote effective integration of AI tools into healthcare by strengthening trust.

All Related

Ethical Obligations to Inform Patients About Use of AI Tools
Michelle Mello, Danton Char, Sonnet H. Xu
Deep DiveJul 21, 2025
Research
Your browser does not support the video tag.

Permeation of artificial intelligence (AI) tools into health care tests traditional understandings of what patients should be told about their care. Despite the general importance of informed consent, decision support tools (eg, automatic electrocardiogram readers, rule-based risk classifiers, and UpToDate summaries) are not usually discussed with patients even though they affect treatment decisions. Should AI tools be treated similarly? The legal doctrine of informed consent requires disclosing information that is material to a reasonable patient’s decision to accept a health care service, and evidence suggests that many patients would think differently about care if they knew it was guided by AI. In recent surveys, 60% of US adults said they would be uncomfortable with their physician relying on AI,1 70% to 80% had low expectations AI would improve important aspects of their care,2 only one-third trusted health care systems to use AI responsibly,3 and 63% said it was very true that they would want to be notified about use of AI in their care.

Ethical Obligations to Inform Patients About Use of AI Tools

Michelle Mello, Danton Char, Sonnet H. Xu
Deep DiveJul 21, 2025

Permeation of artificial intelligence (AI) tools into health care tests traditional understandings of what patients should be told about their care. Despite the general importance of informed consent, decision support tools (eg, automatic electrocardiogram readers, rule-based risk classifiers, and UpToDate summaries) are not usually discussed with patients even though they affect treatment decisions. Should AI tools be treated similarly? The legal doctrine of informed consent requires disclosing information that is material to a reasonable patient’s decision to accept a health care service, and evidence suggests that many patients would think differently about care if they knew it was guided by AI. In recent surveys, 60% of US adults said they would be uncomfortable with their physician relying on AI,1 70% to 80% had low expectations AI would improve important aspects of their care,2 only one-third trusted health care systems to use AI responsibly,3 and 63% said it was very true that they would want to be notified about use of AI in their care.

Healthcare
Regulation, Policy, Governance
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Research
Michelle M. Mello's Testimony Before the U.S. Senate Committee on Finance
Michelle Mello
Quick ReadFeb 08, 2024
testimony

In this testimony presented to the U.S. Senate Committee on Finance, Michelle M. Mello provides recommendations on how Congress can support healthcare organizations and health insurers navigating the uncharted territory of AI tools by imposing some guardrails while allowing the rules to evolve with the technology.

Michelle M. Mello's Testimony Before the U.S. Senate Committee on Finance

Michelle Mello
Quick ReadFeb 08, 2024

In this testimony presented to the U.S. Senate Committee on Finance, Michelle M. Mello provides recommendations on how Congress can support healthcare organizations and health insurers navigating the uncharted territory of AI tools by imposing some guardrails while allowing the rules to evolve with the technology.

Regulation, Policy, Governance
Healthcare
testimony
Understanding Liability Risk from Healthcare AI
Neel Guha, Michelle Mello
Quick ReadFeb 08, 2024
policy brief

This brief explores the legal liability risks of healthcare AI tools by analyzing the challenges courts face in dealing with patient injury caused by defects in AI or software systems.

Understanding Liability Risk from Healthcare AI

Neel Guha, Michelle Mello
Quick ReadFeb 08, 2024

This brief explores the legal liability risks of healthcare AI tools by analyzing the challenges courts face in dealing with patient injury caused by defects in AI or software systems.

Healthcare
Regulation, Policy, Governance
policy brief
Michelle Mello | Understanding Liability Risk from Healthcare AI Tools
seminarJan 24, 202412:00 PM - 1:30 PM
January
24
2024

When use of a healthcare AI tool harms patients, who is responsible? This session will examine how courts are grappling with the challenges of adjudicating liability for software-related injuries and how health systems and clinicians can assess and manage AI liability risk. 

January
24
2024

Michelle Mello | Understanding Liability Risk from Healthcare AI Tools

Jan 24, 202412:00 PM - 1:30 PM

When use of a healthcare AI tool harms patients, who is responsible? This session will examine how courts are grappling with the challenges of adjudicating liability for software-related injuries and how health systems and clinicians can assess and manage AI liability risk. 

Healthcare