Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification
Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification
Variance in predictions across different trained models is a significant, under-explored source of error in fair binary classification. In practice, the variance on some data examples is so large that decisions can be effectively arbitrary. To investigate this problem, we take an experimental approach and make four overarching contributions. We: …