Optimal Medical Liability for AI -- by Alex Chan

2026-06-11 · Source: National Bureau of Economic Research Working Papers · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Advanced, quick

Summary

The National Bureau of Economic Research (NBER) serves as a leading non-profit organization dedicated to promoting economic research, offering a vast repository of working papers, periodicals, and data. Its extensive research agenda spans diverse fields including economics of health, law, industrial organization, and public economics. Among its recent working papers is "Optimal Medical Liability for AI" by Alex Chan, which explores the critical intersection of artificial intelligence in healthcare and the associated legal frameworks for accountability. This paper's inclusion highlights NBER's engagement with emerging policy challenges driven by technological advancements. NBER also supports various programs, projects, and conferences, fostering collaboration among researchers on topics from aging and health to entrepreneurship and international finance.

Key takeaway

For legal professionals and policymakers developing regulations for AI in healthcare, "Optimal Medical Liability for AI" by Alex Chan signals a critical area of emerging legal and economic analysis. You should consider how existing liability frameworks apply to AI-driven medical decisions and explore new models that balance innovation with patient safety and accountability. This research suggests the need for proactive engagement with evolving technological risks.

Key insights

The paper explores optimal liability frameworks for AI in medical applications.

Topics

• Artificial Intelligence
• Medical Liability
• Healthcare Policy
• Economic Research
• Legal Frameworks
• NBER

Best for: Legal Professional, Policy Maker, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by National Bureau of Economic Research Working Papers.