Label bias and proxy features drive algorithmic unfairness more than underrepresentation of protected groups in training data, and a new Data Bias Profile quantifies these risks.
Towards a standard for identifying and managing bias in artificial intelligence
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Underrepresentation, Label Bias, and Proxies: Towards Data Bias Profiles for the EU AI Act and Beyond
Label bias and proxy features drive algorithmic unfairness more than underrepresentation of protected groups in training data, and a new Data Bias Profile quantifies these risks.