"The Future is Knocking: How Artificial Intelligence Will Fundamentally Change Psychiatry"

by Brunn, Matthias; Diefenbacher, Albert; Courtet, Philippe; Genieys, William (2020)

Abstract

Artificial intelligence (AI) is inducing a profound transformation of both the practice and structure of medicine. This implies changes in tasks, where certain processes may be taken over by AI applications, as well as novel ways of collaborating and integrating information. Consider a recent example where AI is used to avoid suicide attempts by using smartphones’ native sensors and signal processing techniques [1]. This new suicide prevention technique requires the psychiatrist to acquire new skills (handling and interpreting continuous patient data sent by a dedicated application) and interact with new actors (programmers, data managers, etc.). Further, the abundance of individual patient data may contribute to a shift in conceptualizing care—from the traditional identification of general risk factors towards more tailored prevention strategies in the sense of personalized medicine [1]. Thus, unlike past technologies, AI has the potential to not only enhance medical capacity but also change the way health professionals are organized and embedded into the broader medical context. In particular, the implementation of AI applications is leading to a redistribution and renegotiation of responsibilities—and thus power—both within medicine and in relation with other stakeholders. This article discusses the future impact of AI on psychiatry, highlights the challenges for research, and outlines perspectives for the next generation of psychiatrists.

Key Passage

Given their specific skillset— including, notably, complex social skills—it seems likely that psychiatrists may actually be relatively well sheltered from job displacement. Indeed, psychiatry requires greater integration of cultural and psychosocial factors than other, more patternbased disciplines. Hence, in a perspective where competencies that are complementary to machine prediction will become more valuable in the future while competencies that are substitutes for machine prediction will become less valuable, psychiatrists could capitalize on the potential benefits of AI in psychiatric practice (p.462)

Keywords

Artificial Intelligence, Machine Learning, Deep Learning, Psychiatry, Mental Health, Mental Health Work, Medicine

Themes

AI and Counselling

Links to Reference

• http://dx.doi.org/10.1007/s40596-020-01243-8
• https://www.ncbi.nlm.nih.gov/pubmed/32424706
• https://dx.doi.org/10.1007/s40596-020-01243-8
• https://hal.archives-ouvertes.fr/hal-02615164/

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