The ethics of AI in health care: A mapping review

Morley, Jessica; Machado, Caio C. Vieira; Burr, Christopher; Cowls, Josh; Joshi, Indra; Taddeo, Mariarosaria; Floridi, Luciano

doi:10.1016/j.socscimed.2020.113172

Cited by 382 publications

(262 citation statements)

References 119 publications

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“…Consequently, the practical discussions about the ethics of particular AI Systems are realized primarily in relation to the field affected, such as AI in healthcare or AI in transportation [46,51,59]. In these discussions, the ethics concerning the AI system is applied and shaped to the field in which it will operate and not the other way around.…”

Section: The Failure Of Machine Ethics As An Applied Ethicmentioning

confidence: 99%

Perspectives about artificial moral agents

et al. 2021

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The pursuit of AMAs is complicated. Disputes about the development, design, moral agency, and future projections for these systems have been reported in the literature. This empirical study explores these controversial matters by surveying (AI) Ethics scholars with the aim of establishing a more coherent and informed debate. Using Q-methodology, we show the wide breadth of viewpoints and approaches to artificial morality. Five main perspectives about AMAs emerged from our data and were subsequently interpreted and discussed: (i) Machine Ethics: The Way Forward; (ii) Ethical Verification: Safe and Sufficient; (iii) Morally Uncertain Machines: Human Values to Avoid Moral Dystopia; (iv) Human Exceptionalism: Machines Cannot Moralize; and (v) Machine Objectivism: Machines as Superior Moral Agents. A potential source of these differing perspectives is the failure of Machine Ethics to be widely observed or explored as an applied ethic and more than a futuristic end. Our study helps improve the foundations for an informed debate about AMAs, where contrasting views and agreements are disclosed and appreciated. Such debate is crucial to realize an interdisciplinary approach to artificial morality, which allows us to gain insights into morality while also engaging practitioners.

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Section: The Failure Of Machine Ethics As An Applied Ethicmentioning

confidence: 99%

Perspectives about artificial moral agents

et al. 2021

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“…These broad ethical themes of privacy and security, accountability and responsibility, bias, and trust have also been revealed in other reviews. In a mapping review by Morley et al (110) on AI in healthcare, for instance, concerns of trust, 'traceability' (aligning with what we have labelled 'accountability'), and bias emerged. While privacy and security were explicitly excluded from their review (110), these very issues were a signi cant nding in a systematic review by Stahl et al (111), both with regard to data privacy and personal (or physical) privacy.…”

Section: Cross-cutting Themes and Asymmetriesmentioning

confidence: 99%

“…In a mapping review by Morley et al (110) on AI in healthcare, for instance, concerns of trust, 'traceability' (aligning with what we have labelled 'accountability'), and bias emerged. While privacy and security were explicitly excluded from their review (110), these very issues were a signi cant nding in a systematic review by Stahl et al (111), both with regard to data privacy and personal (or physical) privacy. Issues of the autonomy and agency of AI machines, the challenge of trusting algorithms (linked with their lack of transparency), as well as others that were more closely associated with non-AI computing technologies were also discussed (111).…”

Section: Cross-cutting Themes and Asymmetriesmentioning

confidence: 99%

Artificial Intelligence for Good Health: A Scoping Review of the Ethics Literature

Murphy

Ruggiero

Upshur

et al. 2021

Preprint

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Background: Artificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective? Methods: Eight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed. Results: Upon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs). Conclusions: The ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.

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“…In a mapping review by Morley et al. (106) on AI in healthcare, for instance, concerns of trust, 'traceability' (aligning with what we have labelled 'accountability'), and bias emerged. While privacy and security were explicitly excluded from their review (106), these very issues were a signi cant nding in a systematic review by Stahl et al (107), both with regard to data privacy and personal (or physical) privacy.…”

Section: Cross-cutting Themes and Asymmetriesmentioning

confidence: 99%

Artificial Intelligence for Good Health: A Scoping Review of the Ethics Literature

Murphy,

Ruggiero,

Upshur

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Artificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective? Methods: Eight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed. Results: Upon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs). Conclusions: The ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere.

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The ethics of AI in health care: A mapping review

Cited by 382 publications

References 119 publications

Perspectives about artificial moral agents

Perspectives about artificial moral agents

Artificial Intelligence for Good Health: A Scoping Review of the Ethics Literature

Artificial Intelligence for Good Health: A Scoping Review of the Ethics Literature

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