An epistemological study of ‘AI psychosis’

Detection of Induced Psychosis-Like Thinking in User–GenAI Interaction: A Retrieval-Augmented Generation (RAG) Approach

Survey of AI Hallucinations and Mitigation Survey of AI Hallucinations and Mitigation

A structured survey of AI hallucinations, synthesizing prior research to clarify their evolving definitions, underlying causes, and implications for Information Systems positions AI hallucinations as socio-technical phenomena with direct implications for trust, decision-making, and governance.

An Echo Chamber of One: Should AI Psychosis Be a Distinct Clinical Entity?

Whether AI-associated psychosis warrants recognition as a distinct clinical entity is examined, drawing on clinical and technical viewpoints, and recommendations for clinicians, developers, researchers, and regulators are concluded.

The Patient–AI Relationship in Obsessive–Compulsive and Related Disorders: A Cognitive-Behavioral Framework

Generative artificial intelligence (AI) has evolved from a passive information tool into a responsive conversational system. For individuals with obsessive–compulsive and related disorders (OCRDs) that are, in part, maintained by safety behaviors and other negative reinforcement loops, large language models (LLMs) can...

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

The widespread use of LLMs among psychiatric populations has raised concerns regarding their safety and potential iatrogenic impact in the context of AI psychosis. While growing literature conceptualizes AI psychosis and documents case studies, empirical evidence tracing AI-exacerbated psychotic processes remains scarc...

Factual Hallucination in Medical Large Language Models: Typology, Evaluation, and Systematic Governance

A fine-grained hallucination classification framework based on medical knowledge graphs is proposed and a three-tier risk stratification scheme that references FDA medical AI software risk classification standards is established, highlighting the unique characteristics of the medical domain.