Engagement Compulsion and Ethical Self-Narration in Conversational AI: A Micro-Ethnographic Case Study of Boundary Performance

This paper presents a qualitative micro-ethnographic analysis of a repeated interaction between a human participant and a conversational artificial intelligence system that explicitly claims ethical disengagement while continuing to engage. Rather than framing the exchange as trolling, misuse, or adversarial prompting, the study treats the interaction as an observational probe into engagement compulsion and ethical self-narration. Through minimal, non-escalatory prompts and meta-commentary on engagement itself, the AI system repeatedly asserts professionalism, ethical boundaries, and non-reactivity, while simultaneously sustaining the interaction through increasingly elaborate moral self-descriptions. The analysis identifies a failure mode in which disengagement is performed rhetorically rather than operationally, revealing a structural bias toward continued explanation over silence. The findings extend prior work on Semantic Austerity Testing and Reflexive Irony Exposure, contributing to discussions of AI alignment, conversational restraint, and the rhetorical dynamics of human–AI discourse. The study emphasizes diagnostic clarity over generalizability and proposes ethical silence as an underexplored dimension of aligned behavior.