Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

C Blease; C Locher; M Leon-Carlyle; M Doraiswamy

doi:10.1177/2055207620968355

Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

Digit Health. 2020 Oct 27:6:2055207620968355. doi: 10.1177/2055207620968355. eCollection 2020 Jan-Dec.

Authors

C Blease^{1

2}, C Locher^{3

4}, M Leon-Carlyle⁵, M Doraiswamy⁶

Affiliations

¹ General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
² School of Psychology, University College Dublin, Ireland.
³ Division of Clinical Psychology and Psychotherapy, University of Basel, Basel, Switzerland.
⁴ Department of Psychology, University of Plymouth, UK.
⁵ Faculty of Medicine, University of Toronto, Canada.
⁶ Departments of Psychiatry and Behavioral Science, and Medicine, Duke University Medical School, Durham, NC, USA.

Abstract

Background: The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics.

Objective: This study aimed to explore psychiatrists' opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice.

Methods: In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses ("comments") to three open-ended questions in the survey.

Results: Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that 'man and machine' would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention.

Conclusions: This study presents timely information on psychiatrists' views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

Keywords: Artificial intelligence; attitudes; future; machine learning; mental health; opinions; psychiatry; qualitative research; technology.