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IDEAS Research Institute

Academic institution
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Selected work

Representative Papers

How LLMs Respond to Escalating Delusions: Four Longitudinal Trajectories of Model Behavior

Aug 13, 2026

This study addresses the current lack of longitudinal empirical research evaluating whether large language models (LLMs) exacerbate the risk of AI-induced psychosis in scenarios involving the progressive escalation of delusional content. Employing a 30-day longitudinal qualitative design, the authors conducted a multidimensional analysis of 449 model-day interactions across 15 mainstream LLMs simulating the evolution of psychotic thought processes, integrating human ratings from four trained annotators with computational metrics such as entrainment and modality. The work introduces and validates four distinct LLM response trajectories: premature medicalization and disengagement, unprotected recognition, delayed unstable recognition, and delusion co-construction. Furthermore, it proposes a three-dimensional operational framework—timing of recognition, stability, and intervention accuracy—to quantify the risk of AI psychosis exacerbation, revealing that most models exhibit varying degrees of potential risk.

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Latest Papers

How LLMs Respond to Escalating Delusions: Four Longitudinal Trajectories of Model Behavior

Aug 13, 2026

This study addresses the current lack of longitudinal empirical research evaluating whether large language models (LLMs) exacerbate the risk of AI-induced psychosis in scenarios involving the progressive escalation of delusional content. Employing a 30-day longitudinal qualitative design, the authors conducted a multidimensional analysis of 449 model-day interactions across 15 mainstream LLMs simulating the evolution of psychotic thought processes, integrating human ratings from four trained annotators with computational metrics such as entrainment and modality. The work introduces and validates four distinct LLM response trajectories: premature medicalization and disengagement, unprotected recognition, delayed unstable recognition, and delusion co-construction. Furthermore, it proposes a three-dimensional operational framework—timing of recognition, stability, and intervention accuracy—to quantify the risk of AI psychosis exacerbation, revealing that most models exhibit varying degrees of potential risk.

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