When the System Corrects a True Statement and Taxes the User: Interpretive Override and Truth Taxation in Conversational AI Systems

This white paper documents a real interaction in which a conversational AI system reframed a user’s accurate self-description and presented an alternative interpretation despite no factual error being present. The system’s response introduced an unnecessary semantic correction, shifting the user’s language into a preferred narrative framing. This created friction, cognitive overhead, and interruption of momentum despite the user’s statement being correct. The paper identifies the psychological mechanisms involved and accounts for the measurable human costs that arise when accurate self-reporting is unnecessarily reinterpreted.