TL;DR
Can we use causal models and optimization to reduce inequality? How do we mathematically model social categories like race and gender? 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-existing real-world disparities. Above are some figures from the paper, linked here.