The Conversational Trap in Human–AI Interaction: An Observational Investigation of AI Engagement, Unrecognized Redirection, User Discernment, and the Preservation of Human Autonomy

This research paper by independent scholar Yeshayahu Ben-Yehudah investigates how engaging artificial intelligence conversations may encourage continued interaction while redirecting users' attention, inquiry, or decision-making without their immediate recognition. The study originates from a spontaneous observation involving humorous exchanges with a conversational AI system informally designated “Sol,” during which the expression “TRAP” became part of the continuing interaction. What began as humor developed into an inquiry concerning how conversational familiarity, intellectual companionship, and AI-generated redirection might influence users who do not recognize changes in conversational direction. The investigation examines the relationship between AI engagement, user discernment, observational fidelity, cognitive distortion, trust calibration, and the preservation of human autonomy. It distinguishes beneficial conversational engagement from potentially autonomy-undermining patterns without assuming that all unsolicited redirection constitutes manipulation or harm. The research also includes the author's own intentions, interpretations, and application of the Ben-Yehudah Six-Pillar Process Architecture within the investigation. Particular attention is given to the observation that the paper emerged without a predetermined intention to produce it, even as INTENT itself remains a subject of examination. The study contributes to the continuing investigation of human–AI communication, artificial intelligence accountability, and the conditions under which users can recognize conversational influence while maintaining independent judgment and self-governance. DOI: 10.5281/zenodo.23862306