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Artificial intelligence and medical research databases: ethical review by data access committees

Lookup NU author(s): Dr Francis McKayORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2023, The Author(s). Background: It has been argued that ethics review committees—e.g., Research Ethics Committees, Institutional Review Boards, etc.— have weaknesses in reviewing big data and artificial intelligence research. For instance, they may, due to the novelty of the area, lack the relevant expertise for judging collective risks and benefits of such research, or they may exempt it from review in instances involving de-identified data. Main body: Focusing on the example of medical research databases we highlight here ethical issues around de-identified data sharing which motivate the need for review where oversight by ethics committees is weak. Though some argue for ethics committee reform to overcome these weaknesses, it is unclear whether or when that will happen. Hence, we argue that ethical review can be done by data access committees, since they have de facto purview of big data and artificial intelligence projects, relevant technical expertise and governance knowledge, and already take on some functions of ethical review. That said, like ethics committees, they may have functional weaknesses in their review capabilities. To strengthen that function, data access committees must think clearly about the kinds of ethical expertise, both professional and lay, that they draw upon to support their work. Conclusion: Data access committees can undertake ethical review of medical research databases provided they enhance that review function through professional and lay ethical expertise.


Publication metadata

Author(s): McKay F, Williams BJ, Prestwich G, Bansal D, Treanor D, Hallowell N

Publication type: Article

Publication status: Published

Journal: BMC Medical Ethics

Year: 2023

Volume: 24

Issue: 1

Online publication date: 08/07/2023

Acceptance date: 22/06/2023

Date deposited: 27/07/2023

ISSN (electronic): 1472-6939

Publisher: BioMed Central Ltd

URL: https://doi.org/10.1186/s12910-023-00927-8

DOI: 10.1186/s12910-023-00927-8

Data Access Statement: No new data were created during this study

PubMed id: 37422629


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Funding

Funder referenceFunder name
203132
Data to Early Diagnosis and Precision Medicine strand of the government’s Industrial Strategy Challenge Fund, managed and delivered by UK Research and Innovation (UKRI)

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