Fairness Tree for Policymakers

Abstract

We expand on previous work at Aequitas, and build upon existing works on designing worksheet and checklist for stakeholders of algorithmic systems, by developing a checklist for policymakers to map their notion of fairness onto metrics that are commonly used. We use the checklist as a conversational tool to workshop and examine where the understandings of fairness diverge across different human services domains and stakeholders (community member vs policymakers). Advised by Prof. Rayid Ghani.

Lingwei Cheng

PhD Candidate in Public Policy and Management

My research interests include the socio-economic impact of algorithm and algorithmic fairness in public policy.