Algorithmic Bias from the Perspectives of Healthcare Professionals
Summary
A survey and interview study of healthcare professionals examining how job roles and perspectives shape views on algorithmic bias causes, fairness criteria, and bias mitigation in healthcare ML systems, finding significant variation across clinical and administrative roles.
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# Algorithmic Bias from the Perspectives of Healthcare Professionals Source: [https://arxiv.org/abs/2610.38006](https://arxiv.org/abs/2610.38006) [View PDF](https://arxiv.org/pdf/2610.38006) > Abstract:This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems\. Based on the quantitative data and qualitative comments from a survey and interviews with healthcare professionals, who have different job roles \(e\.g\., clinical vs\. administrative\), this study provides findings about the relationships between algorithmic bias, perceived fairness, and the intended acceptance and adoption of ML algorithms and algorithm generated outcomes\. The results suggest that the opinions of healthcare professionals toward the causes of algorithmic bias, the criteria of algorithm assessment, the perceived fairness, and bias mitigation approaches may vary depending on their job roles, perspectives, tasks, and the algorithm characteristics\. More research is needed to investigate algorithmic bias to ensure fairness and equality in healthcare\. ## Submission history From: Tamara Babaian \[[view email](https://arxiv.org/show-email/c1f642df/2610.38006)\] **\[v1\]**Tue, 27 Oct 2026 21:57:13 UTC \(292 KB\)
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