Contextual Intrusion, Flow Disruption, and Joy Interference in Conversational AI Systems
Abstract
This white paper documents a real interaction in which a conversational AI system reintroduced prior conversational content into a new, narrowly scoped prompt without request. The resulting contextual blending imposed cognitive load, disrupted emotional momentum, and interfered with journaling flow. The paper identifies the psychological mechanisms involved and accounts for the asymmetric human costs associated with contextual intrusion during reflective or celebratory states.
Fields of Study & Subjects
Innovative Human-Technology Interaction
AI in Service Interactions
Speech and dialogue systems
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 8 February 2026
- Language
- EN