A survey on datasets for fairness-aware machine learning. (arXiv:2110.00530v3 [cs.LG] UPDATED)

As decision-making increasingly relies on Machine Learning (ML) and (big)
data, the issue of fairness in data-driven Artificial Intelligence (AI) systems
is receiving increasing attention from both research and industry. A large
variety of fairness-aware machine learning solutions have been proposed which
involve fairness-related interventions in the data, learning algorithms and/or
model outputs. However, a vital part of proposing new approaches is evaluating
them empirically on benchmark datasets that represent realistic and diverse
settings. Therefore, in this paper, we overview …

arxiv datasets fairness learning machine machine learning survey