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Shaping the future of AI in healthcare through ethics and governance

Author

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  • Rabaï Bouderhem

    (Prince Mohammad Bin Fahd University
    Research Associate CREDIMI (FRE 2003) CNRS - University of Burgundy)

Abstract

The purpose of this research is to identify and evaluate the technical, ethical and regulatory challenges related to the use of Artificial Intelligence (AI) in healthcare. The potential applications of AI in healthcare seem limitless and vary in their nature and scope, ranging from privacy, research, informed consent, patient autonomy, accountability, health equity, fairness, AI-based diagnostic algorithms to care management through automation for specific manual activities to reduce paperwork and human error. The main challenges faced by states in regulating the use of AI in healthcare were identified, especially the legal voids and complexities for adequate regulation and better transparency. A few recommendations were made to protect health data, mitigate risks and regulate more efficiently the use of AI in healthcare through international cooperation and the adoption of harmonized standards under the World Health Organization (WHO) in line with its constitutional mandate to regulate digital and public health. European Union (EU) law can serve as a model and guidance for the WHO for a reform of the International Health Regulations (IHR).

Suggested Citation

  • Rabaï Bouderhem, 2024. "Shaping the future of AI in healthcare through ethics and governance," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02894-w
    DOI: 10.1057/s41599-024-02894-w
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    References listed on IDEAS

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    1. Winter, Jenifer Sunrise & Davidson, Elizabeth, 2022. "Harmonizing regulatory regimes for the governance of patient-generated health data," Telecommunications Policy, Elsevier, vol. 46(5).
    2. Elizabeth Gibney, 2024. "What the EU’s tough AI law means for research and ChatGPT," Nature, Nature, vol. 626(8001), pages 938-939, February.
    3. Nenad Tomašev & Xavier Glorot & Jack W. Rae & Michal Zielinski & Harry Askham & Andre Saraiva & Anne Mottram & Clemens Meyer & Suman Ravuri & Ivan Protsyuk & Alistair Connell & Cían O. Hughes & Alan K, 2019. "A clinically applicable approach to continuous prediction of future acute kidney injury," Nature, Nature, vol. 572(7767), pages 116-119, August.
    4. Jarrahi, Mohammad Hossein & Askay, David & Eshraghi, Ali & Smith, Preston, 2023. "Artificial intelligence and knowledge management: A partnership between human and AI," Business Horizons, Elsevier, vol. 66(1), pages 87-99.
    5. Wu, Chao, 2024. "Data privacy: From transparency to fairness," Technology in Society, Elsevier, vol. 76(C).
    6. Marina Johnson & Abdullah Albizri & Serhat Simsek, 2022. "Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis," Annals of Operations Research, Springer, vol. 308(1), pages 275-305, January.
    Full references (including those not matched with items on IDEAS)

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