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Collaborative study finds women set high standards for the use of AI in breast screening

A study published this month in Digital Health, led by Professor Stacy Carter Director of University of Wollongong’s Australian Centre for Health Engagement, Evidence and Values in collaboration with the Daffodil Centre’s Professor Nehmat Houssami and researchers from several other institutions, found that women support using AI to read mammograms, so long as certain conditions are met.

Professor Nehmat Houssami
Professor Nehmat Houssami

Professor Carter said research on what consumers want from AI in healthcare is fairly new and that “We uncovered important conditions that women said need to be met before AI was used in breast screening and some well-founded intuitions that women had about the weaknesses of AI. There are also some valid, complex concerns about equity in AI use in breast screening”.

The study ran eight online discussion groups with 50 women who participate in breast screening to understand women’s attitudes and values regarding the use of AI to read mammograms.  The study found that although women were positive about the potential of breast screening AI, their trust was contingent on two caveats: Women argued strongly that humans must remain as central actors in breast screening systems. They felt strongly that breast screening should retain the valued expertise of professionals who read mammograms. This expertise was perceived to include skills that machines lack, including intuitive, holistic interpretive capabilities and the ability to deal with unusual decision-making challenges.

The other requirement women insisted on was excellent performance. Women said quality assurance was critical, and AI systems should perform better than the status quo. The main benefits women hoped for were greater accuracy—especially better cancer detection rates—and greater speed and efficiency in returning results.

Professor Houssami said that research into women’s expectations of AI for breast screening is essential to guide potential application of AI and complements work we have reported earlier this year on the performance of AI in mammography screen-reading.


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