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

• Published in: Social science & medicine (1982) Vol. 296; p. 114782
• Main Authors: Siala, Haytham, Wang, Yichuan
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.03.2022; Pergamon Press Inc
• Subjects: AI ethics; Artificial Intelligence; Delivery of Health Care; Digital health; Ethics; Exegesis & hermeneutics; Governance; Health care; Health Facilities; Health services; Health-medicine; Humans; Intelligence; Literature reviews; Medical personnel; Meta-analysis; Morals; Policy making; Responsible artificial intelligence (AI); Systematic literature review; Systematic review; Technology; Transformation; Transparency; Virtue ethics; AI ethics; Digital health; Virtue ethics; Responsible artificial intelligence (AI); Health-medicine; Systematic literature review
• ISSN: 0277-9536; 1873-5347; 1873-5347
• DOI: 10.1016/j.socscimed.2022.114782

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