Journal article
Ethics review of AI research: an approach to reviewing and revising existing governance structures
- Abstract:
-
The recent advancements in artificial intelligence (AI), and data science more broadly, have led to a proliferation of new methods and tools, such as machine learning (ML), that are used in all kinds of scientific research, from biomedical research through to environmental and education research. Research ethics review bodies are increasingly required to review AI research protocols that cover these different fields of enquiry. Questions have been raised regarding the appropriateness of existing ethics governance principles, practices, and processes to deal with the ethical challenges that AI and data science are introducing to research. Universities and research institutions across the world are trying to understand how to translate and practically implement broad AI ethical principles into research ethics governance guidelines and processes. In this article, we report on an expert stakeholders’ workshop organised at the University of Oxford as part of the process of reviewing its ethics governance for AI research. We describe the workshop and present the reflections and recommendations that emerged from it. The aim of the article is to share the approach taken by the University of Oxford CUREC in reviewing its ethics governance processes, and the insights gained with the broader research community, as a way of contributing to this scarce body of literature, facilitating further dialogue, promoting debate and collaboration on this important issue.
- Publication status:
- Accepted
Actions
Authors
- Publisher:
- SAGE Publications
- Journal:
- Research Ethics More from this journal
- Acceptance date:
- 2025-11-25
- EISSN:
-
2047-6094
- ISSN:
-
1747-0161
- Language:
-
English
- Keywords:
- Pubs id:
-
2342621
- Local pid:
-
pubs:2342621
- Deposit date:
-
2025-12-02
Terms of use
- Rights statement:
- This article is protected by copyright. All rights reserved.
- Notes:
- The author accepted manuscript (AAM) of this paper has been made available under the University of Oxford's Open Access Publications Policy, and a CC BY public copyright licence has been applied.
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record