Bias Detection in Chest X-Ray Classifiers: Evidence of Racial, Gender, and Socioeconomic Inequalities
A recent study revealed racial, gender, and socioeconomic bias in chest X-ray classifier AI systems. This AI incident underscores the importance of trustworthy AI and reinforces the need for safe and secure AI governance. Are you ready to help shape responsible AI? JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/81
Data source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
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