Using unlabeled data to enhance fairness of medical AI.

AI models for tasks such as pathology and dermatology struggle to generalize to new patient groups or hospitals that they were not trained on; learning more robust features from unlabeled data could prevent overfitting to the training distribution and thereby increase fairness.