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AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research

Artificial intelligence (AI) is set to transform healthcare. Key ethical issues to emerge with this transformation encompass the accountability and transparency of the decisions made by AI-based systems, the potential for group harms arising from algorithmic bias and the professional roles and integ...

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Autores principales: Lysaght, Tamra, Lim, Hannah Yeefen, Xafis, Vicki, Ngiam, Kee Yuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Singapore 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747260/
https://www.ncbi.nlm.nih.gov/pubmed/33717318
http://dx.doi.org/10.1007/s41649-019-00096-0
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author Lysaght, Tamra
Lim, Hannah Yeefen
Xafis, Vicki
Ngiam, Kee Yuan
author_facet Lysaght, Tamra
Lim, Hannah Yeefen
Xafis, Vicki
Ngiam, Kee Yuan
author_sort Lysaght, Tamra
collection PubMed
description Artificial intelligence (AI) is set to transform healthcare. Key ethical issues to emerge with this transformation encompass the accountability and transparency of the decisions made by AI-based systems, the potential for group harms arising from algorithmic bias and the professional roles and integrity of clinicians. These concerns must be balanced against the imperatives of generating public benefit with more efficient healthcare systems from the vastly higher and accurate computational power of AI. In weighing up these issues, this paper applies the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research (Xafis et al. 2019). The analysis applies relevant values identified from the framework to demonstrate how decision-makers can draw on them to develop and implement AI-assisted support systems into healthcare and clinical practice ethically and responsibly. Please refer to Xafis et al. (2019) in this special issue of the Asian Bioethics Review for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end of this paper.
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spelling pubmed-77472602021-03-12 AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research Lysaght, Tamra Lim, Hannah Yeefen Xafis, Vicki Ngiam, Kee Yuan Asian Bioeth Rev Original Paper Artificial intelligence (AI) is set to transform healthcare. Key ethical issues to emerge with this transformation encompass the accountability and transparency of the decisions made by AI-based systems, the potential for group harms arising from algorithmic bias and the professional roles and integrity of clinicians. These concerns must be balanced against the imperatives of generating public benefit with more efficient healthcare systems from the vastly higher and accurate computational power of AI. In weighing up these issues, this paper applies the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research (Xafis et al. 2019). The analysis applies relevant values identified from the framework to demonstrate how decision-makers can draw on them to develop and implement AI-assisted support systems into healthcare and clinical practice ethically and responsibly. Please refer to Xafis et al. (2019) in this special issue of the Asian Bioethics Review for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end of this paper. Springer Singapore 2019-09-12 /pmc/articles/PMC7747260/ /pubmed/33717318 http://dx.doi.org/10.1007/s41649-019-00096-0 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Paper
Lysaght, Tamra
Lim, Hannah Yeefen
Xafis, Vicki
Ngiam, Kee Yuan
AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title_full AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title_fullStr AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title_full_unstemmed AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title_short AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
title_sort ai-assisted decision-making in healthcare: the application of an ethics framework for big data in health and research
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747260/
https://www.ncbi.nlm.nih.gov/pubmed/33717318
http://dx.doi.org/10.1007/s41649-019-00096-0
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