Are Bias Mitigation Techniques for Deep Learning Effective?

arXiv:2104.00170v3 Announce Type: replace
Abstract: A critical problem in deep learning is that systems learn inappropriate biases, resulting in their inability to perform well on minority groups. This has led to the creation of multiple algorithms that endeavor to mitigate bias. However, it is not clear how effective these methods are. This is because study protocols differ among papers, systems are tested on datasets that fail to test many forms of bias, and systems have access to hidden knowledge or …

arxiv bias cs.ai cs.cv cs.lg deep learning stat.ml type