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Domesticating AI in medical diagnosis

Author

Listed:
  • Williams, Robin
  • Anderson, Stuart
  • Cresswell, Kathrin
  • Kannelønning, Mari Serine
  • Mozaffar, Hajar
  • Yang, Xiao

Abstract

We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. We examine how seemingly compelling claims are tested as AI tools move into real-world settings and discuss how analysts can develop effective understandings in novel and rapidly changing settings.

Suggested Citation

  • Williams, Robin & Anderson, Stuart & Cresswell, Kathrin & Kannelønning, Mari Serine & Mozaffar, Hajar & Yang, Xiao, 2024. "Domesticating AI in medical diagnosis," Technology in Society, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:teinso:v:76:y:2024:i:c:s0160791x24000174
    DOI: 10.1016/j.techsoc.2024.102469
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    References listed on IDEAS

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    1. Ho, Manh-Tung & Le, Ngoc-Thang B. & Mantello, Peter & Ho, Manh-Toan & Ghotbi, Nader, 2023. "Understanding the acceptance of emotional artificial intelligence in Japanese healthcare system: A cross-sectional survey of clinic visitors’ attitude," Technology in Society, Elsevier, vol. 72(C).
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    4. Ekaterina Jussupow & Kai Spohrer & Armin Heinzl, 2022. "Radiologists’ Usage of Diagnostic AI Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(3), pages 293-309, June.
    5. Cresswell, Kathrin & Rigby, Michael & Magrabi, Farah & Scott, Philip & Brender, Jytte & Craven, Catherine K. & Wong, Zoie Shui-Yee & Kukhareva, Polina & Ammenwerth, Elske & Georgiou, Andrew & Medlock,, 2023. "The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision," Health Policy, Elsevier, vol. 136(C).
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