Alexander Tolbert (University of Pennsylvania): "A Capabilities Approach to Causal Fairness in Machine Learning: Addressing Algorithmic Bias"

Feb 8, 2023, 4:30 pm6:00 pm
Laura Wooten Hall, Room 301 (Kerstetter Room)
Free and Open to the Public


Event Description

Ira W. DeCamp Bioethics Seminars

ABSTRACT: Two criticisms of data science have recently emerged. The first argues that seemingly objective machine-learning algorithms often reinforce a racist or unjust status quo. The second chastises data science for failing to develop a science of causal inference rather than a mere collection of techniques for exploiting associations. The first highlights an urgent social problem; the second seems like an internal methodological dispute. I argue the absence of causal methodology in favor of a purely predictive approach in data science aids in the racialization of algorithms analogous to the history of racialized statistics. I propose a novel capabilities model of causal fairness to redress these concerns.