The authors conduct a comprehensive survey of existing studies on fairness testing in ML software, focusing on the testing workflow and components. They aim to identify trends, research focus, and potential directions in the field.
Unfaire Verhaltensweisen von Machine Learning-Software haben zu wachsender Besorgnis geführt, was zu umfangreichen Forschungen im Bereich der Fairness-Tests geführt hat.