The use of artificial intelligence (AI) in psychiatry holds promise for diagnosis, therapy, and the categorization of mental disorders. At the same time, it raises significant theoretical and ethical concerns. The debate appears polarized, with proponents and critics seemingly irreconcilably opposed. On the one hand, AI is heralded as a transformative force poised to revolutionize psychiatric research and practice. On the other hand, it is depicted as a harbinger of dehumanization. To better understand this dichotomy, it is essential to identify and critically examine the underlying arguments. To what extent does the use of AI challenge the theoretical assumptions of psychiatric diagnostics? What implications does it have for patient care, and how does it influence the professional self-concept of psychiatrists?

To explore these questions, we conducted 15 semi-structured interviews with experts from psychiatry, computer science, and philosophy. The findings were analyzed using a structuring qualitative content analysis.

The analysis focuses on the significance of AI for psychiatric diagnosis and care, as well as on its implications for the identity of psychiatry. We identified different lines of argument suggesting that expert views on AI in psychiatry hinge on the types of data considered relevant and on whether core human capacities in diagnosis and treatment are viewed as replicable by AI.

The results provide a mapping of diverse perspectives, offering a basis for more detailed analysis of theoretical and ethical issues of AI in psychiatry, as well as for the adaptation of psychiatric education.