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Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review

BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development of new healthcare AI (HCAI) technologies. Whilst some of these technologies show promise for improving the patient experience, ethicists have warned that AI can introduce and exacerbate harms and wro...

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Autores principales: Frost, Emma Kellie, Bosward, Rebecca, Aquino, Yves Saint James, Braunack-Mayer, Annette, Carter, Stacy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288036/
https://www.ncbi.nlm.nih.gov/pubmed/35841073
http://dx.doi.org/10.1186/s13643-022-02012-4
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author Frost, Emma Kellie
Bosward, Rebecca
Aquino, Yves Saint James
Braunack-Mayer, Annette
Carter, Stacy M.
author_facet Frost, Emma Kellie
Bosward, Rebecca
Aquino, Yves Saint James
Braunack-Mayer, Annette
Carter, Stacy M.
author_sort Frost, Emma Kellie
collection PubMed
description BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development of new healthcare AI (HCAI) technologies. Whilst some of these technologies show promise for improving the patient experience, ethicists have warned that AI can introduce and exacerbate harms and wrongs in healthcare. It is important that HCAI reflects the values that are important to people. However, involving patients and publics in research about AI ethics remains challenging due to relatively limited awareness of HCAI technologies. This scoping review aims to map how the existing literature on publics’ views on HCAI addresses key issues in AI ethics and governance. METHODS: We developed a search query to conduct a comprehensive search of PubMed, Scopus, Web of Science, CINAHL, and Academic Search Complete from January 2010 onwards. We will include primary research studies which document publics’ or patients’ views on machine learning HCAI technologies. A coding framework has been designed and will be used capture qualitative and quantitative data from the articles. Two reviewers will code a proportion of the included articles and any discrepancies will be discussed amongst the team, with changes made to the coding framework accordingly. Final results will be reported quantitatively and qualitatively, examining how each AI ethics issue has been addressed by the included studies. DISCUSSION: Consulting publics and patients about the ethics of HCAI technologies and innovations can offer important insights to those seeking to implement HCAI ethically and legitimately. This review will explore how ethical issues are addressed in literature examining publics’ and patients’ views on HCAI, with the aim of determining the extent to which publics’ views on HCAI ethics have been addressed in existing research. This has the potential to support the development of implementation processes and regulation for HCAI that incorporates publics’ values and perspectives. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02012-4.
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spelling pubmed-92880362022-07-17 Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review Frost, Emma Kellie Bosward, Rebecca Aquino, Yves Saint James Braunack-Mayer, Annette Carter, Stacy M. Syst Rev Protocol BACKGROUND: In recent years, innovations in artificial intelligence (AI) have led to the development of new healthcare AI (HCAI) technologies. Whilst some of these technologies show promise for improving the patient experience, ethicists have warned that AI can introduce and exacerbate harms and wrongs in healthcare. It is important that HCAI reflects the values that are important to people. However, involving patients and publics in research about AI ethics remains challenging due to relatively limited awareness of HCAI technologies. This scoping review aims to map how the existing literature on publics’ views on HCAI addresses key issues in AI ethics and governance. METHODS: We developed a search query to conduct a comprehensive search of PubMed, Scopus, Web of Science, CINAHL, and Academic Search Complete from January 2010 onwards. We will include primary research studies which document publics’ or patients’ views on machine learning HCAI technologies. A coding framework has been designed and will be used capture qualitative and quantitative data from the articles. Two reviewers will code a proportion of the included articles and any discrepancies will be discussed amongst the team, with changes made to the coding framework accordingly. Final results will be reported quantitatively and qualitatively, examining how each AI ethics issue has been addressed by the included studies. DISCUSSION: Consulting publics and patients about the ethics of HCAI technologies and innovations can offer important insights to those seeking to implement HCAI ethically and legitimately. This review will explore how ethical issues are addressed in literature examining publics’ and patients’ views on HCAI, with the aim of determining the extent to which publics’ views on HCAI ethics have been addressed in existing research. This has the potential to support the development of implementation processes and regulation for HCAI that incorporates publics’ values and perspectives. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13643-022-02012-4. BioMed Central 2022-07-15 /pmc/articles/PMC9288036/ /pubmed/35841073 http://dx.doi.org/10.1186/s13643-022-02012-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Protocol
Frost, Emma Kellie
Bosward, Rebecca
Aquino, Yves Saint James
Braunack-Mayer, Annette
Carter, Stacy M.
Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title_full Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title_fullStr Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title_full_unstemmed Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title_short Public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
title_sort public views on ethical issues in healthcare artificial intelligence: protocol for a scoping review
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288036/
https://www.ncbi.nlm.nih.gov/pubmed/35841073
http://dx.doi.org/10.1186/s13643-022-02012-4
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