期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2019
卷号：42
期号：3
页码：24-35
出版社：IEEE Computer Society
摘要：Fairness is increasingly recognized as a critical component of machine learning systems. However, it isthe underlying data on which these systems are trained that often reflects discrimination, suggesting adata management problem. In this paper, we first make a distinction between associational and causaldefinitions of fairness in the literature and argue that the concept of fairness requires causal reasoning.We then review existing works and identify future opportunities for applying data management techniquesto causal algorithmic fairness..
