Journal article
The permissibility of biased AI in a biased world: an ethical analysis of AI for screening and referrals for diabetic retinopathy in Singapore
- Abstract:
- A significant and important ethical tension in resource allocation and public health ethics is between utility and equity. We explore this tension between utility and equity in the context of health AI through an examination of a diagnostic AI screening tool for diabetic retinopathy developed by a team of researchers at Duke-NUS in Singapore. While this tool was found to be effective, it was not equally effective across every ethnic group in Singapore, being less effective for the minority Malay population than for the Chinese majority. We discuss the problematic normative nature of bias in health AI and explore the ways in which bias can interact with various forms of social inequalities. From there, we examine the specifics of the diabetic retinopathy case and weigh up specific trade-offs between utility and equity. Ultimately, we conclude that it is ethically permissible to prioritise utility over equity where certain criteria hold. Given that any medical AI is more likely than not to have lingering bias due to bias in the training data that may reflect other social inequalities, we argue that it is permissible to implement an AI tool with residual bias where: (1) its introduction reduces the influence of biases (even if overall inequality is worsened), and/or (2) where the utility gained is significant enough and shared across groups (even if unevenly).
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, pdf, 677.3KB, Terms of use)
-
- Publisher copy:
- 10.1007/s41649-024-00315-3
Authors
+ National Medical Research Council
More from this funder
- Funder identifier:
- https://ror.org/04x3cxs03
- Publisher:
- Springer Nature
- Journal:
- Asian Bioethics Review More from this journal
- Volume:
- 17
- Issue:
- 1
- Pages:
- 167–185
- Publication date:
- 2024-10-31
- Acceptance date:
- 2024-07-28
- DOI:
- EISSN:
-
1793-9453
- ISSN:
-
1793-8759
- Language:
-
English
- Keywords:
- Pubs id:
-
2062757
- Local pid:
-
pubs:2062757
- Deposit date:
-
2024-11-26
Terms of use
- Copyright holder:
- Muyskens et al
- Copyright date:
- 2024
- Rights statement:
- © The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- 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