Rethinking the Role of AI with Physicians in Oncology

Revealing Perspectives from Clinical and Research Workflows

Conference Paper (2023)
Author(s)

H. Verma (TU Delft - Human-Centred Artificial Intelligence)

Jakub Mlynar (HES-SO))

Roger Schaer (HES-SO))

Julien Reichenbach (HES-SO))

Mario Jreige (University of Lausanne)

John Prior (University of Lausanne)

Florian Evéquoz (HES-SO))

Adrien Depeursinge (HES-SO))

Research Group
Human-Centred Artificial Intelligence
Copyright
© 2023 H. Verma, Jakub Mlynar, Roger Schaer, Julien Reichenbach, Mario Jreige, John Prior, Florian Evéquoz, Adrien Depeursinge
DOI related publication
https://doi.org/10.1145/3544548.3581506
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 H. Verma, Jakub Mlynar, Roger Schaer, Julien Reichenbach, Mario Jreige, John Prior, Florian Evéquoz, Adrien Depeursinge
Research Group
Human-Centred Artificial Intelligence
ISBN (electronic)
978-1-4503-9421-5
Reuse Rights

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Abstract

Significant and rapid advancements in cancer research have been attributed to Artificial Intelligence (AI). However, AI’s role and impact on the clinical side has been limited. This discrepancy manifests due to the overlooked, yet profound, differences in the clinical and research practices in oncology. Our contribution seeks to scrutinize physicians' engagement with AI by interviewing 7 medical-imaging experts and disentangle its future alignment across the clinical and research workflows, diverging from the existing "one-size-fits-all" paradigm within Human-Centered AI discourses. Our analysis revealed that physicians' trust in AI is less dependent on their general acceptance of AI, but more on their contestable experiences with AI. Contestability, in clinical workflows, underpins the need for personal supervision of AI outcomes and processes, i.e., clinician-in-the-loop. Finally, we discuss tensions in the desired attributes of AI, such as explainability and control, contextualizing them within the divergent intentionality and scope of clinical and research workflows.