How to be fair? A study of label and selection bias

arXiv:2403.14282v1 Announce Type: new
Abstract: It is widely accepted that biased data leads to biased and thus potentially unfair models. Therefore, several measures for bias in data and model predictions have been proposed, as well as bias mitigation techniques whose aim is to learn models that are fair by design. Despite the myriad of mitigation techniques developed in the past decade, however, it is still poorly understood under what circumstances which methods work. Recently, Wick et al. showed, with experiments …

abstract aim arxiv bias biased data cs.ai cs.cy cs.lg data fair leads learn predictions study type