Feature-Wise Bias Amplification
@article{Leino2018FeatureWiseBA, title={Feature-Wise Bias Amplification}, author={Klas Leino and Matt Fredrikson and Emily Black and Shayak Sen and Anupam Datta}, journal={ArXiv}, year={2018}, volume={abs/1812.08999} }
We study the phenomenon of bias amplification in classifiers, wherein a machine learning model learns to predict classes with a greater disparity than the underlying ground truth. We demonstrate that bias amplification can arise via an inductive bias in gradient descent methods that results in the overestimation of the importance of moderately-predictive "weak" features if insufficient training data is available. This overestimation gives rise to feature-wise bias amplification -- a previously…
27 Citations
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