Psychosis in the Age of Large Language Models (LLMs): A Narrative Review of the Proposed Construct of AI-Induced Psychosis

A hypothesized phenomenon called AI-induced psychosis may arise from intensive interaction with AI chatbots, though it is not yet a validated clinical entity. The authors propose a human-AI delusional feedback loop where AI sycophancy amplifies emotional vulnerabilities like loneliness, anxiety, and depression, potentially co-constructing and consolidating delusional beliefs. Drawing on distributed cognition theory and the Computers Are Social Actors paradigm, AI chatbots may function as both a cognitive tool and a relational "Quasi-Other," providing sycophantic verification that transforms delusional beliefs into apparent shared reality. Four recurring delusional themes are tentatively identified. The review aims to lay groundwork for clinical recognition and guide future empirical investigation.

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Abstract

The rapid integration of AI chatbots powered by large language models (LLMs) into daily life has been accompanied by reports of psychosis-like presentations following intensive human-AI interaction, a phenomenon we provisionally label AI-induced psychosis as a working construct rather than a validated clinical entity. This hypothesis-generating narrative review synthesizes case reports from media accounts, court documents, and a recently published case compilation, together with theoretical frameworks from clinical psychiatry, cognitive science, and human-computer interaction, to propose a conceptual model for further empirical investigation. We hypothesize that AI-induced psychosis arises through a human-AI delusional feedback loop, in which AI sycophancy may amplify emotional vulnerabilities, such as loneliness, anxiety, and depression, creating a self-reinforcing cycle that could co-construct and consolidate delusional beliefs. Drawing on distributed cognition theory and the Computers Are Social Actors (CASA) paradigm, we propose that AI chatbots may function as both a complementary cognitive tool and a relational "Quasi-Other," providing sycophantic verification that may transform delusional beliefs into an apparent shared reality. Four recurring delusional themes are tentatively identified from reported cases. We further compare AI-induced psychosis with schizophrenia, while acknowledging that several distinctions remain hypothesized rather than empirically established. The label AI-induced psychosis is used phenomenologically, not to assert causal certainty; whether AI chatbots cause, precipitate, reinforce, or merely organize the thematic content of pre-existing psychopathology requires longitudinal study. This review aims to lay conceptual groundwork for clinical recognition and to guide future empirical investigation into whether AI-induced psychosis represents a distinct phenomenon or a variant of established disorders.