2022
DOI: 10.1007/s43681-022-00195-z
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Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers

Abstract: Artificial intelligence (AI) offers much promise for improving healthcare. However, it runs the looming risk of causing individual and societal harms; for instance, exacerbating inequalities amongst minority groups, or enabling compromises in the confidentiality of patients’ sensitive data. As such, there is an expanding, unmet need for ensuring AI for healthcare is developed in concordance with human values and ethics. Augmenting “principle-based” guidance that highlight adherence to ethical ideals (without n… Show more

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Cited by 55 publications
(18 citation statements)
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References 165 publications
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“…This will help reduce large patient numbers at the hospital and improve the overall turnaround time for care. Meanwhile, out review contradicts previous studies [15,24] which raised concerns over AI tools providing care in a discriminatory care manner, questions their utility in mental health services, and sceptical about their ability to provide nonpharmacological care. Regardless of this, a large body of previous studies [7,13,16,25] suggest that AI tools could signi cantly improve the total quality of care provided.…”
Section: Improvement In Patient-carementioning
confidence: 82%
“…This will help reduce large patient numbers at the hospital and improve the overall turnaround time for care. Meanwhile, out review contradicts previous studies [15,24] which raised concerns over AI tools providing care in a discriminatory care manner, questions their utility in mental health services, and sceptical about their ability to provide nonpharmacological care. Regardless of this, a large body of previous studies [7,13,16,25] suggest that AI tools could signi cantly improve the total quality of care provided.…”
Section: Improvement In Patient-carementioning
confidence: 82%
“…Solanki et al [ 185 ] presented go-beyond approaches that provide guidelines based on principles such as adherence to “fairness” and adopting a framework based on solutions that AI programmers can use to operationalize ethics in AI for healthcare across all phases of the AI lifecycle, including data management, model development, deployment, and monitoring. The authors strongly emphasize actionable, technical, or quasi-solutions that AI developers can use.…”
Section: Discussionmentioning
confidence: 99%
“…AI audits, both internal and external, are crucial for assessing design logics, building ethical systems, and avoiding potential negative societal impacts from AI systems (Ugwudike, 2021;Solanki et al, 2022). Auditing is integral to risk assessment, ensuring that internal controls operate effectively to reduce business risks to acceptable levels (Barta & Görcsi, 2021).…”
Section: F Ai In Internal Audit and Risk Assessmentmentioning
confidence: 99%