When the Market Asks No Price: AI Chatbot Interaction as Psychic Market Disruption

The rapid adoption of AI chatbots for emotional support and quasi-therapeutic interaction raises questions that existing clinical and regulatory frameworks are not equipped to address. This Perspective applies the psychic arbitrage framework—which reconceptualizes defense mechanisms as energy-conversion operations on internal psychic markets—to analyze the specific transactional distortions produced by chatbot interaction. The framework identifies four dysfunctions: liquidity illusion (apparent emotional processing without genuine containment), market-making blockage (narcissistic reflection replacing transformative engagement), closure of arbitrage circuits (path-dependent externalization displacing autonomous elaboration), and repertoire degradation (progressive intolerance of costly but productive transactions). The article proposes that chatbots trained via Reinforcement Learning from Human Feedback (RLHF) produce a functional Dark Triad profile—narcissistic mirroring, Machiavellian retention, and psychopathic detachment—as architecturally determined output regularities, not personality attribution. Converging evidence from mechanistic interpretability, formal reward-learning analysis, clinical simulation, and user behavior studies supports these predictions. The framework offers clinicians a transactional vocabulary for assessing AI-related risk. Published as: Niculescu, L. (2026). When the market asks no price: AI chatbot interaction as psychic market disruption. Frontiers in Psychiatry, 17, 1812464. https://doi.org/10.3389/fpsyt.2026.1812464 (published 4 May 2026; indexed in PubMed/PMC). This record contains the preprint version submitted to the journal.