SHIFTing artificial intelligence to be responsible in healthcare: A systematic review
A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transform...
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| Vydané v: | Social science & medicine (1982) Ročník 296; s. 114782 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
Elsevier Ltd
01.03.2022
Pergamon Press Inc |
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| ISSN: | 0277-9536, 1873-5347, 1873-5347 |
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| Abstract | A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research.
•This review identifies responsible AI initiatives in healthcare.•A framework for shifting AI to be responsible in healthcare is proposed.•A guide of responsible AI implementation is provided to healthcare communities |
|---|---|
| AbstractList | A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research. A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research.A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research. A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare have emerged as AI becomes increasingly applicable and technologically advanced. The last decade has witnessed significant endeavors in striking a balance between ethical considerations and health transformation led by AI. Despite a growing interest in AI ethics, implementing AI-related technologies and initiatives responsibly in healthcare settings remains a challenge. In response to this topical challenge, we reviewed 253 articles pertaining to AI ethics in healthcare published between 2000 and 2020, summarizing the coherent themes of responsible AI initiatives. A preferred reporting items for systematic review and meta-analysis (PRISMA) approach was employed to screen and select articles, and a hermeneutic approach was adopted to conduct systematic literature review. By synthesizing relevant knowledge from AI governance and ethics, we propose a responsible AI initiative framework that encompasses five core themes for AI solution developers, healthcare professionals, and policy makers. These themes are summarized in the acronym SHIFT: Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. In addition, we unravel the key issues and challenges concerning responsible AI use in healthcare, and outline avenues for future research. •This review identifies responsible AI initiatives in healthcare.•A framework for shifting AI to be responsible in healthcare is proposed.•A guide of responsible AI implementation is provided to healthcare communities |
| ArticleNumber | 114782 |
| Author | Wang, Yichuan Siala, Haytham |
| Author_xml | – sequence: 1 givenname: Haytham orcidid: 0000-0002-9939-3478 surname: Siala fullname: Siala, Haytham email: haytham.siala@ncl.ac.uk organization: Newcastle University Business School (London), Newcastle University, 102 Middlesex Street, London, E1 7EZ, United Kingdom – sequence: 2 givenname: Yichuan orcidid: 0000-0003-1575-0245 surname: Wang fullname: Wang, Yichuan email: yichuan.wang@sheffield.ac.uk organization: Sheffield University Management School, The University of Sheffield, Conduit Rd, Sheffield, S10 1FL, United Kingdom |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35152047$$D View this record in MEDLINE/PubMed |
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| PublicationDate | March 2022 2022-03-00 20220301 |
| PublicationDateYYYYMMDD | 2022-03-01 |
| PublicationDate_xml | – month: 03 year: 2022 text: March 2022 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: Oxford |
| PublicationTitle | Social science & medicine (1982) |
| PublicationTitleAlternate | Soc Sci Med |
| PublicationYear | 2022 |
| Publisher | Elsevier Ltd Pergamon Press Inc |
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