# Toward relationally responsible artificial intelligence in psychiatry: a neuropsychoanalytic framework through projective identification - URL: https://alisanburak.com/en/wcp-2026-posterler/so143 - Language: en - Last updated: not specified - Page title: Toward relationally responsible artificial intelligence in psychiatry: a neuropsychoanalytic framework through projective identification | WCP 2026 Summary > Human-like artificial intelligence in psychiatry should be evaluated not only in terms of accuracy and safety, but also through the relational meanings users a… This page was translated automatically from Turkish. [Read the original](https://alisanburak.com/wcp-2026-posterler/so143) This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it. SO143 Brief Oral Poster PresentationDigital Psychiatry and Artificial IntelligenceConceptual analysis # Toward relationally responsible artificial intelligence in psychiatry: a neuropsychoanalytic framework through projective identification TOWARD RELATIONALLY RESPONSIBLE AI IN PSYCHIATRY: A NEUROPSYCHOANALYTIC FRAMEWORK THROUGH PROJECTIVE IDENTIFICATION Presenter: Sera Çetingök Country: Turkey Institution: İstanbul Üniversitesi-Cerrahpaşa, Faculty of Health Sciences, Department of Gerontology Session: 2830 - PARALLEL SHORT ORAL POSTER SESSIONS: DIGITAL & AI PSYCHIATRY - Part II Date: Thu, 24.09.2026 Human-like artificial intelligence in psychiatry should be evaluated not only in terms of accuracy and safety, but also through the relational meanings users attribute to it and the trajectory of the interaction. The aim is to propose a neuropsychoanalytic framework for evaluating human-like artificial intelligence systems entering the mental health field, encompassing the unconscious, affective, and embodied dimensions of human–AI interaction. The method is a conceptual analysis integrating psychoanalytic theory on projective identification, neuropsychoanalytic approaches, embodied simulation research, the literature on AI self-modeling and non-axiomatic reasoning, and debates on AI in mental health; projective identification serves as the central model, understood as both a defensive process and a form of presymbolic relational communication. The poster emphasizes that even a technically safe response may be experienced by the user as reassurance, judgment, recognition, withdrawal, or care, and that the issue is therefore not merely whether the response is accurate, but what kind of relationship it establishes. Second, it notes that social cognition is not purely linguistic: internal body representations, interoception, and affective attunement operate together with external body representations and theory of mind. It explicitly acknowledges that this does not provide neurological proof of projective identification, but only supports the proposition that interpersonal understanding is embodied and relational. Third, it argues that AI can direct, stabilize, slow things down, guide, and refer, but cannot share in feeling, wait alongside someone, use countertransference, or assume a therapeutic frame; thus, the language of containment can be imitated, but containment in the psychoanalytic sense cannot occur. Relational risks across repeated interactions are identified, including escalating dependency, affective escalation, pseudo-intimacy, failed handoff to a human, and anthropomorphic overtrust, with particular emphasis on the potential for attachment and overtrust to develop among users in vulnerable states. In conclusion, the recommendation is that psychiatric AI should monitor not only individual outputs but also the trajectory of the interaction, and that relational safety, boundaries, and an ethical framework should be incorporated alongside technical performance in its design and evaluation. [View the original poster](https://cslide.ctimeetingtech.com/wcp26/attendee/eposter/file/1085) How to cite this study APA 7: Çetingök, S., et al. (2026, September 24). Toward relationally responsible ai in psychiatry: a neuropsychoanalytic framework through projective identification [Poster presentation]. 26th WPA World Congress of Psychiatry (WCP 2026), Stockholm, Sweden. https://cslide.ctimeetingtech.com/wcp26/attendee/eposter/file/1085 Vancouver: Çetingök S, et al. Toward relationally responsible ai in psychiatry: a neuropsychoanalytic framework through projective identification [poster]. 26th WPA World Congress of Psychiatry (WCP 2026); 2026 Sep 23-26; Stockholm, Sweden. 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