Cargando…

Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review

BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI...

Descripción completa

Detalles Bibliográficos
Autores principales: Beets, Becca, Newman, Todd P, Howell, Emily L, Bao, Luye, Yang, Shiyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131909/
https://www.ncbi.nlm.nih.gov/pubmed/37014676
http://dx.doi.org/10.2196/40337
_version_ 1785031282504237056
author Beets, Becca
Newman, Todd P
Howell, Emily L
Bao, Luye
Yang, Shiyu
author_facet Beets, Becca
Newman, Todd P
Howell, Emily L
Bao, Luye
Yang, Shiyu
author_sort Beets, Becca
collection PubMed
description BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public. OBJECTIVE: This study reviews the existing survey research on the United States’ public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings. METHODS: We conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups. RESULTS: This review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use. CONCLUSIONS: Americans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information.
format Online
Article
Text
id pubmed-10131909
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-101319092023-04-27 Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review Beets, Becca Newman, Todd P Howell, Emily L Bao, Luye Yang, Shiyu J Med Internet Res Review BACKGROUND: This paper reviews nationally representative public opinion surveys on artificial intelligence (AI) in the United States, with a focus on areas related to health care. The potential health applications of AI continue to gain attention owing to their promise as well as challenges. For AI to fulfill its potential, it must not only be adopted by physicians and health providers but also by patients and other members of the public. OBJECTIVE: This study reviews the existing survey research on the United States’ public attitudes toward AI in health care and reveals the challenges and opportunities for more effective and inclusive engagement on the use of AI in health settings. METHODS: We conducted a systematic review of public opinion surveys, reports, and peer-reviewed journal articles published on Web of Science, PubMed, and Roper iPoll between January 2010 and January 2022. We include studies that are nationally representative US public opinion surveys and include at least one or more questions about attitudes toward AI in health care contexts. Two members of the research team independently screened the included studies. The reviewers screened study titles, abstracts, and methods for Web of Science and PubMed search results. For the Roper iPoll search results, individual survey items were assessed for relevance to the AI health focus, and survey details were screened to determine a nationally representative US sample. We reported the descriptive statistics available for the relevant survey questions. In addition, we performed secondary analyses on 4 data sets to further explore the findings on attitudes across different demographic groups. RESULTS: This review includes 11 nationally representative surveys. The search identified 175 records, 39 of which were assessed for inclusion. Surveys include questions related to familiarity and experience with AI; applications, benefits, and risks of AI in health care settings; the use of AI in disease diagnosis, treatment, and robotic caregiving; and related issues of data privacy and surveillance. Although most Americans have heard of AI, they are less aware of its specific health applications. Americans anticipate that medicine is likely to benefit from advances in AI; however, the anticipated benefits vary depending on the type of application. Specific application goals, such as disease prediction, diagnosis, and treatment, matter for the attitudes toward AI in health care among Americans. Most Americans reported wanting control over their personal health data. The willingness to share personal health information largely depends on the institutional actor collecting the data and the intended use. CONCLUSIONS: Americans in general report seeing health care as an area in which AI applications could be particularly beneficial. However, they have substantial levels of concern regarding specific applications, especially those in which AI is involved in decision-making and regarding the privacy of health information. JMIR Publications 2023-04-04 /pmc/articles/PMC10131909/ /pubmed/37014676 http://dx.doi.org/10.2196/40337 Text en ©Becca Beets, Todd P Newman, Emily L Howell, Luye Bao, Shiyu Yang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 04.04.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Beets, Becca
Newman, Todd P
Howell, Emily L
Bao, Luye
Yang, Shiyu
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title_full Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title_fullStr Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title_full_unstemmed Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title_short Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
title_sort surveying public perceptions of artificial intelligence in health care in the united states: systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131909/
https://www.ncbi.nlm.nih.gov/pubmed/37014676
http://dx.doi.org/10.2196/40337
work_keys_str_mv AT beetsbecca surveyingpublicperceptionsofartificialintelligenceinhealthcareintheunitedstatessystematicreview
AT newmantoddp surveyingpublicperceptionsofartificialintelligenceinhealthcareintheunitedstatessystematicreview
AT howellemilyl surveyingpublicperceptionsofartificialintelligenceinhealthcareintheunitedstatessystematicreview
AT baoluye surveyingpublicperceptionsofartificialintelligenceinhealthcareintheunitedstatessystematicreview
AT yangshiyu surveyingpublicperceptionsofartificialintelligenceinhealthcareintheunitedstatessystematicreview