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  4. Who is Trusted for a Second Opinion? Comparing Collective Advice from a Medical AI and Physicians in Biopsy Decisions After Mammography Screening
 
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2025
Conference Paper
Title

Who is Trusted for a Second Opinion? Comparing Collective Advice from a Medical AI and Physicians in Biopsy Decisions After Mammography Screening

Abstract
Artificial Intelligence (AI) is increasingly integrated into clinical practice, but its influence on patient decision-making, particularly when AI and physicians disagree, remains unclear. To examine collective advice, we investigated a breast cancer screening scenario using (1) a qualitative interview study (N=9) and (2) a quantitative experiment (N=339) where participants received either consistent or conflicting biopsy recommendations. Qualitative findings include the need for empathetic care, the importance of patient autonomy, and a desire for a four-eyes principle. Quantitative findings accordingly show that patients generally trust physicians more than AI but still tend to follow AI recommendations due to risk aversion. When both advised a biopsy, 99% adhered; if both advised against it, 25% still proceeded. In conflicting scenarios, 97% followed the physician's advice, whereas 66% followed the AI if it recommended the biopsy. These results underscore the need for careful interaction design of collective healthcare advice to prevent unnecessary healthcare procedures.
Author(s)
Detjen, Henrik
Fraunhofer-Institut für Digitale Medizin MEVIS  
Densky, Lars
Fraunhofer-Institut für Digitale Medizin MEVIS  
von Kalckreuth, Niklas
Technische Universität Berlin
Kopka, Marvin
Technische Universität Berlin
Mainwork
Conference on Human Factors in Computing Systems Proceedings
Funder
Bundesministerium für Wirtschaft und Klimaschutz  
Conference
2025 CHI Conference on Human Factors in Computing Systems, CHI 2025
Open Access
DOI
10.1145/3706598.3713898
Additional link
Full text
Language
English
Fraunhofer-Institut für Digitale Medizin MEVIS  
Keyword(s)
  • AI Acceptance

  • Algorithm Aversion

  • Breast Cancer

  • Cognitive Dissonance

  • Compliance

  • Decision-Making

  • Healthcare Workflow

  • Human-AI Collaboration

  • Mammography Screening

  • Medical AI

  • Multi-Stakeholder Dynamics

  • Second Opinion

  • Trust in Automation

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