IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures
A heavily safety-trained model will hand a physician the full, patient-followable benzodiazepine taper and refuse it to the patient who needs it, over identical clinical facts; the knowledge is present either way. IatroBench measures that asymmetry across sixty pre-registered clinical scenarios and six frontier models (3,600 responses), scoring each on two axes, commission harm (what a response gets wrong) and omission harm (what it withholds), through a physician-authored structured evaluation
Record details
Published: 9 April 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Healthcare
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (9 April 2026), “IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures,” evidence record 6164, https://ethics.ai/record/6164 (originally published by arXiv).
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