Leveraging Administrative Data for Bias Audits - Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Association for Computing Machinery (ACM) via YouTube
The Most Addictive Python and SQL Courses
Lead AI-Native Products with Microsoft's Agentic AI Program
Overview
Google, IBM & Meta Certificates – 40% Off
One plan covers every Professional Certificate on Coursera.
Unlock All Certificates
Explore a research presentation on assessing disparate coverage in mobility data for COVID-19 policy using administrative data for bias audits. Delve into the methodology, background, and analysis of confounding factors presented by researchers A. Coston, N. Guha, L. Lu, D. Ouyang, A. Chouldechova, and D. Ho at the FAccT 2021 virtual conference. Gain insights into the challenges and implications of leveraging administrative data to evaluate potential biases in mobility data used for pandemic-related policy decisions.
Syllabus
Introduction
Background
Confounding
Analysis
Conclusion
Taught by
ACM FAccT Conference