Artificial intelligence suppression as a strategy to mitigate artificial intelligence automation bias.

ABSTRACT:

Background

Incorporating artificial intelligence (AI) into clinics brings the risk of automation bias, which potentially misleads the clinician's decision-making. The purpose of this study was to propose a potential strategy to mitigate automation bias.

Methods

This was a laboratory study with a randomized cross-over design. The diagnosis of anterior cruciate ligament (ACL) rupture, a common injury, on magnetic resonance imaging (MRI) was used as an example. Forty clinicians were invited to diagnose 200 ACLs with and without AI assistance. The AI's correcting and misleading (automation bias) effects on the clinicians' decision-making processes were analyzed. An ordinal logistic regression model was employed to predict the correcting and misleading probabilities of the AI. We

SUBMITTER: Wang DY 

PROVIDER: S-EPMC10531198 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature