The Measure and Mismeasure of Fairness with Sharad Goel - #363

Sharad Goel, an Assistant Professor at Stanford, specializes in applying machine learning to public policy. He dives into his work on discriminatory policing, discussing the impact of practices like Stop and Frisk. Goel critiques traditional definitions of algorithmic fairness and emphasizes the ethical implications in high-stakes environments like law enforcement. He advocates for data transparency and community engagement to reform inequitable systems, highlighting the need for balanced approaches in criminal risk assessments.