Disaggregated Interventions to Reduce Inequality

@article{Bynum2021DisaggregatedIT,
  title={Disaggregated Interventions to Reduce Inequality},
  author={Lucius E.J. Bynum and Joshua R. Loftus and Julia Stoyanovich},
  journal={Equity and Access in Algorithms, Mechanisms, and Optimization},
  year={2021}
}
A significant body of research in the data sciences considers unfair discrimination against social categories such as race or gender that could occur or be amplified as a result of algorithmic decisions. Simultaneously, real-world disparities continue to exist, even before algorithmic decisions are made. In this work, we draw on insights from the social sciences brought into the realm of causal modeling and constrained optimization, and develop a novel algorithmic framework for tackling pre… 

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