Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare

Open Access
Authors
Publication date 2025
Journal Proceedings of Machine Learning Research
Event 10th Machine Learning for Healthcare Conference
Volume | Issue number 298
Number of pages 28
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
  • Faculty of Economics and Business (FEB)
Abstract
Explainable AI (XAI) holds the promise of advancing the implementation and adoption of AI-based tools in practice, especially in high-stakes environments like healthcare. However, most of the current research lacks input from end users, and therefore their practical value is limited. To address this, we conducted semi-structured interviews with clinicians to discuss their thoughts, hopes, and concerns. Clinicians from our sample generally think positively about developing AI-based tools for clinical practice, but they have concerns about how these will fit into their workflow and how it will impact clinician-patient relations. We further identify training of clinicians on AI as a crucial factor for the success of AI in healthcare and highlight aspects clinicians are looking for in (X)AI-based tools. In contrast to other studies, we take on a holistic and exploratory perspective to identify general requirements for (X)AI products for healthcare before moving on to testing specific tools.
Document type Article
Note Proceedings of the 10th Machine Learning for Healthcare Conference : 15-16 August 2025, Mayo Clinic, Rochester, MN, USA
Language English
Published at https://proceedings.mlr.press/v298/rober25a.html
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