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Governance of High-Risk AI Systems in Healthcare and Credit Scoring

Author

Listed:
  • Sebastian Bartsch

    (Technical University of Darmstadt)

  • Oliver Behn

    (University of Marburg)

  • Alexander Benlian

    (Technical University of Darmstadt)

  • Roger Brownsword

    (Somerset House East Wing)

  • Sebastian Bücker

    (Technical University of Darmstadt)

  • Marcus Düwell

    (Technical University of Darmstadt)

  • Nico Formánek

    (University of Stuttgart)

  • Marc Jungtäubl

    (Hessian University of Applied Sciences for Public Management and Security)

  • Michael Leyer

    (University of Marburg
    Queensland University of Technology)

  • Alexander Richter

    (Victoria University of Wellington)

  • Jan-Hendrik Schmidt

    (Technical University of Darmstadt)

  • Mascha Will-Zocholl

    (Hessian University of Applied Sciences for Public Management and Security)

Abstract

No abstract is available for this item.

Suggested Citation

  • Sebastian Bartsch & Oliver Behn & Alexander Benlian & Roger Brownsword & Sebastian Bücker & Marcus Düwell & Nico Formánek & Marc Jungtäubl & Michael Leyer & Alexander Richter & Jan-Hendrik Schmidt & M, 2025. "Governance of High-Risk AI Systems in Healthcare and Credit Scoring," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(4), pages 563-581, August.
    • Handle: RePEc:spr:binfse:v:67:y:2025:i:4:d:10.1007_s12599-025-00944-4
    DOI: 10.1007/s12599-025-00944-4
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    References listed on IDEAS

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    1. Christopher Robertson & Andrew Woods & Kelly Bergstrand & Jess Findley & Cayley Balser & Marvin J Slepian, 2023. "Diverse patients’ attitudes towards Artificial Intelligence (AI) in diagnosis," PLOS Digital Health, Public Library of Science, vol. 2(5), pages 1-16, May.
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    4. Sarah Lebovitz & Hila Lifshitz-Assaf & Natalia Levina, 2022. "To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis," Organization Science, INFORMS, vol. 33(1), pages 126-148, January.
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