University of Wollongong
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Australian women's judgements about using artificial intelligence to read mammograms in breast cancer screening

journal contribution
posted on 2024-11-17, 13:48 authored by Stacy M Carter, Lucy Carolan, Yves Saint James Aquino, Helen Frazer, Wendy A Rogers, Julie Hall, Chris Degeling, Annette Braunack-Mayer, Nehmat Houssami
Objective: Mammographic screening for breast cancer is an early use case for artificial intelligence (AI) in healthcare. This is an active area of research, mostly focused on the development and evaluation of individual algorithms. A growing normative literature argues that AI systems should reflect human values, but it is unclear what this requires in specific AI implementation scenarios. Our objective was to understand women's values regarding the use of AI to read mammograms in breast cancer screening. Methods: We ran eight online discussion groups with a total of 50 women, focused on their expectations and normative judgements regarding the use of AI in breast screening. Results: Although women were positive about the potential of breast screening AI, they argued strongly that humans must remain as central actors in breast screening systems and consistently expressed high expectations of the performance of breast screening AI. Women expected clear lines of responsibility for decision-making, to be able to contest decisions, and for AI to perform equally well for all programme participants. Women often imagined both that AI might replace radiographers and that AI implementation might allow more women to be screened: screening programmes will need to communicate carefully about these issues. Conclusions: To meet women's expectations, screening programmes should delay implementation until there is strong evidence that the use of AI systems improves screening performance, should ensure that human expertise and responsibility remain central in screening programmes, and should avoid using AI in ways that exacerbate inequities.

Funding

National Health and Medical Research Council (1181960)

History

Journal title

Digital Health

Volume

9

Language

English

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