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The ethics of AI in health care: A mapping review

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

Abstract

This article presents a mapping review of the literature concerning the ethics of artificial intelligence (AI) in health care. The goal of this review is to summarise current debates and identify open questions for future research. Five literature databases were searched to support the following research question: how can the primary ethical risks presented by AI-health be categorised, and what issues must policymakers, regulators and developers consider in order to be ‘ethically mindful? A series of screening stages were carried out—for example, removing articles that focused on digital health in general (e.g. data sharing, data access, data privacy, surveillance/nudging, consent, ownership of health data, evidence of efficacy)—yielding a total of 156 papers that were included in the review.

Suggested Citation

  • Morley, Jessica & Machado, Caio C.V. & Burr, Christopher & Cowls, Josh & Joshi, Indra & Taddeo, Mariarosaria & Floridi, Luciano, 2020. "The ethics of AI in health care: A mapping review," Social Science & Medicine, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:socmed:v:260:y:2020:i:c:s0277953620303919
    DOI: 10.1016/j.socscimed.2020.113172
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    References listed on IDEAS

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    1. Emma Rich & Andy Miah, 2014. "Understanding Digital Health as Public Pedagogy: A Critical Framework," Societies, MDPI, vol. 4(2), pages 1-20, June.
    2. Effy Vayena & Alessandro Blasimme & I Glenn Cohen, 2018. "Machine learning in medicine: Addressing ethical challenges," PLOS Medicine, Public Library of Science, vol. 15(11), pages 1-4, November.
    3. Fred S. Lu & Mohammad W. Hattab & Cesar Leonardo Clemente & Matthew Biggerstaff & Mauricio Santillana, 2019. "Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    4. Nic Fleming, 2018. "How artificial intelligence is changing drug discovery," Nature, Nature, vol. 557(7707), pages 55-57, May.
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    Cited by:

    1. Siala, Haytham & Wang, Yichuan, 2022. "SHIFTing artificial intelligence to be responsible in healthcare: A systematic review," Social Science & Medicine, Elsevier, vol. 296(C).
    2. Kusta, Olsi & Bearman, Margaret & Gorur, Radhika & Risør, Torsten & Brodersen, John Brandt & Hoeyer, Klaus, 2024. "Speed, accuracy, and efficiency: The promises and practices of digitization in pathology," Social Science & Medicine, Elsevier, vol. 345(C).
    3. Castonguay, Alexandre & Wagner, Gerit & Motulsky, Aude & Paré, Guy, 2024. "AI maturity in health care: An overview of 10 OECD countries," Health Policy, Elsevier, vol. 140(C).
    4. Alexandra Brintrup & George Baryannis & Ashutosh Tiwari & Svetan Ratchev & Giovanna Martinez-Arellano & Jatinder Singh, 2023. "Trustworthy, responsible, ethical AI in manufacturing and supply chains: synthesis and emerging research questions," Papers 2305.11581, arXiv.org.
    5. Markov, Iliya & Guglielmetti, Rafael & Laumanns, Marco & Fernández-Antolín, Anna & de Souza, Ravin, 2021. "Simulation-based design and analysis of on-demand mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 170-205.
    6. Wang, Weisha & Wang, Yichuan & Chen, Long & Ma, Rui & Zhang, Minhao, 2024. "Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals," Social Science & Medicine, Elsevier, vol. 347(C).
    7. Hamid Reza Saeidnia & Seyed Ghasem Hashemi Fotami & Brady Lund & Nasrin Ghiasi, 2024. "Ethical Considerations in Artificial Intelligence Interventions for Mental Health and Well-Being: Ensuring Responsible Implementation and Impact," Social Sciences, MDPI, vol. 13(7), pages 1-15, July.
    8. Clement A. Adebamowo & Shawneequa Callier & Simisola Akintola & Oluchi Maduka & Ayodele Jegede & Christopher Arima & Temidayo Ogundiran & Sally N. Adebamowo, 2023. "The promise of data science for health research in Africa," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    9. Bennett, Jeffrey A. & Simpson, Juliet G. & Qin, Chao & Fittro, Roger & Koenig, Gary M. & Clarens, Andres F. & Loth, Eric, 2021. "Techno-economic analysis of offshore isothermal compressed air energy storage in saline aquifers co-located with wind power," Applied Energy, Elsevier, vol. 303(C).

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