Aug 24, 2026 · 35 min
Medical AI needs independent referees
Why Medical AI Needs a Referee | Protege's Engy Ziedan
As healthcare systems adopt models patients may trust, independent and continuous evaluation becomes essential to detect harms that benchmark scores miss.
- 1Benchmark performance cannot establish whether a medical AI system is safe, useful, or aligned in clinical practice.
- 2Subtle bias and conflicting incentives can harm patients without producing the catastrophic failures most evaluations seek.
- 3Changing models, evidence, and clinical workflows require continuous oversight rather than one-time, self-reported testing.
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Engy Ziedan explains why model creators should not be the sole graders of medical AI, especially when patients cannot independently assess its answers.
The brief
Engy Ziedan, Protege’s co-founder and chief scientific officer, joins Daisy Wolf and Eva Steinman to examine who should decide whether AI-generated health answers are safe.
The conversation moves beyond benchmark scores to real-world data, where evaluations can expose subtle bias, misalignment, contamination, and changing model behavior.
Healthcare’s information asymmetry raises the stakes: patients may trust computer-generated answers without being able to judge whether the underlying system is reliable.
Ziedan argues that medical AI needs continuous monitoring and independent grading, because model creators cannot be the only judges of systems that affect clinical decisions.
Featuring
Engy Ziedan
Daisy Wolf
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