A survey on datasets for fairness-aware machine learning

Understand

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 real-world datasets used for fairness-aware machine learning.