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

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 ps...

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Autores principales: Blease, C, Locher, C, Leon-Carlyle, M, Doraiswamy, M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597571/
https://www.ncbi.nlm.nih.gov/pubmed/33194219
http://dx.doi.org/10.1177/2055207620968355
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author Blease, C
Locher, C
Leon-Carlyle, M
Doraiswamy, M
author_facet Blease, C
Locher, C
Leon-Carlyle, M
Doraiswamy, M
author_sort Blease, C
collection PubMed
description 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.
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spelling pubmed-75975712020-11-12 Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey Blease, C Locher, C Leon-Carlyle, M Doraiswamy, M Digit Health Original Research 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. SAGE Publications 2020-10-27 /pmc/articles/PMC7597571/ /pubmed/33194219 http://dx.doi.org/10.1177/2055207620968355 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Blease, C
Locher, C
Leon-Carlyle, M
Doraiswamy, M
Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title_full Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title_fullStr Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title_full_unstemmed Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title_short Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey
title_sort artificial intelligence and the future of psychiatry: qualitative findings from a global physician survey
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597571/
https://www.ncbi.nlm.nih.gov/pubmed/33194219
http://dx.doi.org/10.1177/2055207620968355
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