When Machines Misread Science: Creating Guardrails for Human and AI Interpretation of Biomedical Research

August 24, 2026

Peoples N, Milne K, Luo B, Yan LL. npj Digital Medicine (2026).

As AI increasingly interprets and summarizes medical research, how can we prevent it from misrepresenting scientific findings? This article proposes two frameworks, SIMcard and FACTS, to help AI systems and human readers interpret biomedical research accurately, recognize limitations, and avoid drawing conclusions beyond what the evidence supports.

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Published Research from the HUMAI Faculty

Explore peer-reviewed research and scholarly contributions from HUMAI co-chair Dr. Ken Milne and colleagues, examining how artificial intelligence can be used responsibly in medicine and how to protect the integrity of evidence-based healthcare.