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Artificial intelligence and the future of psychiatry: Insights from a global physician survey.

Publication ,  Journal Article
Doraiswamy, PM; Blease, C; Bodner, K
Published in: Artif Intell Med
January 2020

BACKGROUND: Futurists have predicted that new autonomous technologies, embedded with artificial intelligence (AI) and machine learning (ML), will lead to substantial job losses in many sectors disrupting many aspects of healthcare. Mental health appears ripe for such disruption given the global illness burden, stigma, and shortage of care providers. OBJECTIVE: To characterize the global psychiatrist community's opinion regarding the potential of future autonomous technology (referred to here as AI/ML) to replace key tasks carried out in mental health practice. DESIGN: Cross sectional, random stratified sample of psychiatrists registered with Sermo, a global networking platform open to verified and licensed physicians. MAIN OUTCOME MEASURES: We measured opinions about the likelihood that AI/ML tools would be able to fully replace - not just assist - the average psychiatrist in performing 10 key psychiatric tasks. Among those who considered replacement likely, we measured opinions about how many years from now such a capacity might emerge. We also measured psychiatrist's perceptions about whether benefits of AI/ML would outweigh the risks. RESULTS: Survey respondents were 791 psychiatrists from 22 countries representing North America, South America, Europe and Asia-Pacific. Only 3.8 % of respondents felt it was likely that future technology would make their jobs obsolete and only 17 % felt that future AI/ML was likely to replace a human clinician for providing empathetic care. Documenting and updating medical records (75 %) and synthesizing information (54 %) were the two tasks where a majority predicted that AI/ML could fully replace human psychiatrists. Female- and US-based doctors were more uncertain that the benefits of AI would outweigh risks than male- and non-US doctors, respectively. Around one in 2 psychiatrists did however predict that their jobs would be substantially changed by AI/ML. CONCLUSIONS: Our findings provide compelling insights into how physicians think about AI/ML which in turn may help us better integrate technology and reskill doctors to enhance mental health care.

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Published In

Artif Intell Med

DOI

EISSN

1873-2860

Publication Date

January 2020

Volume

102

Start / End Page

101753

Location

Netherlands

Related Subject Headings

  • Surveys and Questionnaires
  • Social Stigma
  • Referral and Consultation
  • Psychiatry
  • Physicians
  • Middle Aged
  • Medical Informatics
  • Male
  • Machine Learning
  • Humans
 

Citation

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ICMJE
MLA
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Doraiswamy, P. M., Blease, C., & Bodner, K. (2020). Artificial intelligence and the future of psychiatry: Insights from a global physician survey. Artif Intell Med, 102, 101753. https://doi.org/10.1016/j.artmed.2019.101753
Doraiswamy, P Murali, Charlotte Blease, and Kaylee Bodner. “Artificial intelligence and the future of psychiatry: Insights from a global physician survey.Artif Intell Med 102 (January 2020): 101753. https://doi.org/10.1016/j.artmed.2019.101753.
Doraiswamy PM, Blease C, Bodner K. Artificial intelligence and the future of psychiatry: Insights from a global physician survey. Artif Intell Med. 2020 Jan;102:101753.
Doraiswamy, P. Murali, et al. “Artificial intelligence and the future of psychiatry: Insights from a global physician survey.Artif Intell Med, vol. 102, Jan. 2020, p. 101753. Pubmed, doi:10.1016/j.artmed.2019.101753.
Doraiswamy PM, Blease C, Bodner K. Artificial intelligence and the future of psychiatry: Insights from a global physician survey. Artif Intell Med. 2020 Jan;102:101753.
Journal cover image

Published In

Artif Intell Med

DOI

EISSN

1873-2860

Publication Date

January 2020

Volume

102

Start / End Page

101753

Location

Netherlands

Related Subject Headings

  • Surveys and Questionnaires
  • Social Stigma
  • Referral and Consultation
  • Psychiatry
  • Physicians
  • Middle Aged
  • Medical Informatics
  • Male
  • Machine Learning
  • Humans