Publications (5)
Fairness Transferability Subject to Bounded Distribution Shift
Yatong Chen, Reilly Raab, Jialu Wang +1
Given an algorithmic predictor that is "fair" on some source distribution, will it still be fair on an unknown target distribution that differs from the source within some bound? I…
Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processing
Reilly Raab, Mike Parker, Dan Nally +4
The advent of language models (LMs) has the potential to dramatically accelerate tasks that may be cast to text-processing; however, real-world adoption is hindered by concerns reg…
Conjugate Natural Selection
Reilly Raab, Luca de Alfaro, Yang Liu
We prove that Fisher-Rao natural gradient descent (FR-NGD) optimally approximates the continuous time replicator equation (an essential model of evolutionary dynamics), and term th…
Unintended Selection: Persistent Qualification Rate Disparities and Interventions
Reilly Raab, Yang Liu
Realistically -- and equitably -- modeling the dynamics of group-level disparities in machine learning remains an open problem. In particular, we desire models that do not suppose…
Long-Term Fairness with Unknown Dynamics
Tongxin Yin, Reilly Raab, Mingyan Liu +1
While machine learning can myopically reinforce social inequalities, it may also be used to dynamically seek equitable outcomes. In this paper, we formalize long-term fairness in t…