Measuring racial disparities is challenging, especially when demographic labels are unavailable. Recently, some researchers and advocates have argued that companies should infer race and other demographic factors to help them understand and address discrimination. Others have been more skeptical, emphasizing the inaccuracy of racial inferences, critiquing the conceptualization of demographic categories themselves, and arguing that the use of demographic data might encourage algorithmic tweaks where more radical interventions are needed.
We conducted a novel empirical analysis that informs this debate, using a dataset of self-reported demographic information provided by users of the ride-hailing service Uber who consented to share this information for research purposes.
We presented this paper at the 2022 FAccT Conference.