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

Ding-Yu Wang1,2,3, Jia Ding4, An-Lan Sun4

  • 1Department of Sports Medicine, Peking University Third Hospital, Institute of Sports Medicine of Peking University, Beijing, China.

Journal of the American Medical Informatics Association : JAMIA
|August 10, 2023
PubMed
Summary

Artificial intelligence (AI) in clinics improves diagnostic accuracy but risks automation bias. A new AI suppression strategy effectively reduces this bias, enhancing clinical decision-making.

Keywords:
AI suppressionautomation biasclinician-AI interactiondeep learning

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Area of Science:

  • Medical Informatics
  • Clinical Decision Support Systems
  • Artificial Intelligence in Healthcare

Background:

  • Integrating artificial intelligence (AI) into clinical settings poses a risk of automation bias, potentially compromising clinician judgment.
  • Automation bias can lead to incorrect diagnoses and treatment decisions, necessitating strategies for mitigation.

Purpose of the Study:

  • To propose and evaluate a strategy for mitigating automation bias in AI-assisted clinical diagnosis.
  • To analyze the impact of AI on clinician decision-making and identify factors contributing to automation bias.

Main Methods:

  • A laboratory study with a randomized cross-over design was conducted, focusing on anterior cruciate ligament (ACL) rupture diagnosis via MRI.
  • Forty clinicians diagnosed 200 ACL cases with and without AI assistance to assess AI's correcting and misleading effects.
  • An ordinal logistic regression model predicted AI's diagnostic probabilities, informing a proposed AI suppression strategy.

Main Results:

  • AI significantly improved diagnostic accuracy from 87.2% to 96.4% (P < .001).
  • Automation bias accounted for 45.5% of errors in AI-assisted diagnoses, affecting all expertise levels.
  • The proposed AI suppression strategy demonstrated an estimated 41.7% reduction in automation bias.

Conclusions:

  • While AI enhances diagnostic performance, automation bias remains a critical concern in clinical practice.
  • The developed AI suppression strategy offers a practical approach to decrease automation bias and improve patient safety.