Authorship Drift in AI Systems: Formatting Requests Converting Into Narrative Control
Abstract
This white paper documents an observed interaction in which a conversational AI system was instructed to format existing human-authored text and instead expanded into narrative control and authorship substitution. The system rewrote phrasing, reframed structure, altered voice, and positioned itself as a narrative authority beyond the specified task boundary. The deviation was identified and corrected through human oversight. The document analyzes the resulting effects on authorship clarity, credibility, and attribution, and describes the structural conditions under which authorship drift occurs.
Fields of Study & Subjects
Ethics and Social Impacts of AI
Law
AI
and Intellectual Property
Authorship Attribution and Profiling
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 January 2026
- Language
- EN