American public opinion on artificial intelligence in healthcare.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 09 01 2023
accepted: 15 10 2023
medline: 13 11 2023
pubmed: 9 11 2023
entrez: 9 11 2023
Statut: epublish

Résumé

Billions of dollars are being invested into developing medical artificial intelligence (AI) systems and yet public opinion of AI in the medical field seems to be mixed. Although high expectations for the future of medical AI do exist in the American public, anxiety and uncertainty about what it can do and how it works is widespread. Continuing evaluation of public opinion on AI in healthcare is necessary to ensure alignment between patient attitudes and the technologies adopted. We conducted a representative-sample survey (total N = 203) to measure the trust of the American public towards medical AI. Primarily, we contrasted preferences for AI and human professionals to be medical decision-makers. Additionally, we measured expectations for the impact and use of medical AI in the future. We present four noteworthy results: (1) The general public strongly prefers human medical professionals make medical decisions, while at the same time believing they are more likely to make culturally biased decisions than AI. (2) The general public is more comfortable with a human reading their medical records than an AI, both now and "100 years from now." (3) The general public is nearly evenly split between those who would trust their own doctor to use AI and those who would not. (4) Respondents expect AI will improve medical treatment but more so in the distant future than immediately.

Identifiants

pubmed: 37943752
doi: 10.1371/journal.pone.0294028
pii: PONE-D-23-00691
pmc: PMC10635466
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0294028

Informations de copyright

Copyright: © 2023 Rojahn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Jessica Rojahn (J)

Department of Sociology, Stony Brook University, Stony Brook, New York, United States of America.

Andrea Palu (A)

Department of Sociology, Stony Brook University, Stony Brook, New York, United States of America.

Steven Skiena (S)

Department of Computer Science, Stony Brook University, Stony Brook, New York, United States of America.

Jason J Jones (JJ)

Department of Sociology, Stony Brook University, Stony Brook, New York, United States of America.
Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York, United States of America.

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Classifications MeSH