AI in Mental Health: A Review of Technological Advancements and Ethical Issues in Psychiatry.

Abstract

Artificial intelligence (AI) is transforming digital health, its influence is expanding across multiple sectors, with mental health and psychiatric care emerging as key areas of transformation. While significant advancements have been made in medical AI, there remains a need to better understand how these technologies are integrated into clinical practice and what challenges they introduce. We examine the use of AI in identifying and treating mental health disorders, highlighting its impact on screening, diagnosis, and intervention strategies. Technologies such as natural language processing (NLP), machine learning (ML), and computer-delivered cognitive behavioral therapy (CBT) are discussed in the context of enhancing Clinical Decision Support Systems (CDSS). While these innovations promise increased efficiency and accessibility in psychiatric care, they also introduce ethical challenges, including concerns over privacy, bias, and reduced human interaction. Through a critical evaluation, we find that greater transparency, unbiased model development and unbiased AI systems that work hand in hand with human-led care should be encouraged. Our findings underscore the importance of continued research and regulation to ensure the responsible and effective deployment of medical AI services.