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SHIFTing artificial intelligence to be responsible in healthcare: A systematic review

Lookup NU author(s): Dr Haytham Siala

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).

Abstract

© 2022 Elsevier Ltd. 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.

Publication metadata

Author(s): Siala H, Wang Y

Publication type: Article

Publication status: Published

Journal: Social Science and Medicine

Year: 2022

Volume: 296

Print publication date: 01/03/2022

Online publication date: 04/02/2022

Acceptance date: 03/02/2022

Date deposited: 13/04/2022

ISSN (print): 0277-9536

ISSN (electronic): 1873-5347

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.socscimed.2022.114782

DOI: 10.1016/j.socscimed.2022.114782

ePrints DOI: 10.57711/gx11-0f04

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