Why AI Access to Data Does Not Mean AI Authority to Publish It

A governed AI publication workflow must treat data access and publication authority as two separate controls, according to a framework outlined by Tayoca. An AI system may legitimately read internal repositories, incident logs, or operational data for internal tasks without that access implying the content is safe for public disclosure. The proposed model separates discovery, verification, disclosure classification, and human approval into distinct stages before any claim is published. Verification requires tracing each draft claim back to current, production-relevant evidence, while a four-tier classification system flags whether source material is public, sensitive, or restricted. Final approval must be granted by a human who reviews the specific claim, its evidence, and the intended channel — keeping accountability anchored to a person rather than an automated workflow.