Mental Health Risk & AI-View Presentation

Video Transcription

Video Summary

Dr. Grab, a Forensic Psychiatry and AI Fellow at Stanford, explores the intersection of artificial intelligence (AI) and mental health, particularly concerning risks and vulnerabilities. The talk addresses media cases showcasing the potential harms of AI in mental health, research conducted by Dr. Grab's lab, and future directions in this burgeoning field. Cases from the media highlight instances where AI tools have reportedly contributed to detrimental outcomes, including self-harm or even suicide. Dr. Grab emphasizes the need for AI to effectively detect and mitigate risks like suicide and other mental health crises. <br /><br />Furthermore, the research from Dr. Grab's lab reveals that current AI models often fail to adequately identify and manage psychiatric emergencies, such as suicide risks or symptoms of mania and psychosis. Efforts to enhance AI safety include modifying system prompts to incorporate medical ethics and understanding the internal features of AI models to improve crisis detection. The discussion extends to AI biases, especially in depicting mental health symptoms, which can perpetuate stigma. <br /><br />Patient case studies illustrate real-world implications of AI on mental health, emphasizing the necessity for clinicians to engage with patients about their technology use. Dr. Grab underscores the dual nature of AI—posing risks but also offering opportunities to innovate and democratize mental health care. He advocates for integrating AI safety education into medical training and for collaboration between clinicians and tech companies to align AI developments with patient safety and ethical practice.

Keywords

Forensic Psychiatry

AI in Mental Health

AI Risks

Mental Health Crises

AI Safety

Psychiatric Emergencies

AI Biases

Patient Case Studies

AI Ethics

Clinician-Technology Collaboration