Tag
This paper presents a computational audit of representational bias in ClinicalBERT, finding that demographic associations are amplified by the model itself rather than inherited from training data.
This study demonstrates that large language models inherit and amplify biases from stigmatizing language in clinical notes, leading to less aggressive patient management, and that current mitigation strategies are insufficient.