ARTIFICIAL INTELLIGENCE: UNDERSTANDING THE PRESENT AND ANTICIPATING THE FUTURE

Artificial intelligence is fundamentally transforming psychiatric practice across multiple domains, from accelerating drug discovery and development, to advancing digital therapeutics and enhancing clinical decision support systems. These technological advances hold unprecedented promise for improving diagnostic accuracy, personalizing treatment approaches, and expanding access to mental health care. However, these innovations bring significant challenges that must be carefully navigated, including algorithmic bias that may perpetuate health disparities, privacy vulnerabilities in sensitive mental health data, model hallucinations that could provide inaccurate clinical information, automation complacency among healthcare providers, performance drift as models encounter new populations, lack of transparency in algorithmic decision-making, and ambiguous accountability frameworks when AI systems influence patient care. This conference plenary session will feature three presentations followed by a panel of experts that explore the current landscape, emerging opportunities, and critical challenges facing AI implementation in psychiatry. The first speaker will provide a comprehensive overview of AI technologies currently being deployed in psychiatric settings, examining their applications across clinical research and practice while addressing both the technical capabilities and practical limitations of these systems. The second speaker will examine the rapidly emerging role of LLMs and AI chatbots in psychiatric care, exploring their therapeutic potential and clinical risks, while critically evaluating implementation considerations, including safety protocols, risk simulation, benchmarking, therapeutic boundaries, and integration with traditional care models. While the talk will primarily focus on chatbots for care purposes, the clinical role of LLMs and AI for diagnostic and clinical decision support will also be considered. The third speaker will present practical, real-world examples of AI applications in clinical trial analyses, demonstrating how machine learning algorithms, natural language processing, and predictive modeling are advancing psychiatric research methodologies, improving patient recruitment and retention, and accelerating the translation of research findings into clinical practice. The session will conclude with an expert panel discussion addressing regulatory considerations, ethical frameworks, and strategies for responsible AI implementation that prioritizes patient safety and therapeutic benefit while fostering continued innovation in psychiatric care.