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The Challenge of Bias Mitigation in Clinical AI Decision Support:A Balance Between Decision Efficiency and Quality

Year: 2023

Type: article

Abstract: An increasing number of intelligent data-driven health systems seek to support patients and clinicians in decision making tasks. However, the recommendations provided by such systems can negatively impact the reasoning abilities of its users, giving rise to cognitive biases. Such mental processes can subsequently harm the quality of the user's decision. While decision support systems are typically designed to increase user efficiency, known approaches to mitigate such biases primarily rely on slowing down the decision making process---offsetting any efficiency benefits. This position paper calls attention to the efficiency--quality trade-off in bias mitigation and outlines a future research direction for bias mitigation in AI decision support.

Source: VBN Forskningsportal (Aalborg Universitet)

Authors: van Berkel, Niels; id_orcid 0000-0001-5106-7692, de Jong, Sander; id_orcid 0000-0002-2591-3805, Wester, Joel; id_orcid 0000-0001-6332-9493, Als, Naja Kathrine Kollerup

Institution: Aalborg University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4412343708

FWCI:

Cites: 4

Cited by:

Related to: 10