BIHE Monthly Seminar – Sequential Bias Mitigation and the Need for Causal Fairness
BIHE Monthly Seminar
October 19, 2022
12:00 PM - 1:00 PM
Presenter:
Lu Cheng, PhD
Assistant Professor
Computer Science
Abstract:
The increasing use of machine learning in high stakes domains such as healthcare and policing has brought the algorithmic fairness into the spotlight. The majority of research in fair machine learning has been focused on statistical-based measures that try to equalize the performance metrics (e.g., true positive rate) between different groups. Despite its simplicity, statistical fairness, which relies on correlation and passive observations, has its limitations, and it is essential to properly address causality in fairness.
Sponsored by the Office of the Vice Chancellor for Research, College of Medicine, and College of Applied Health Sciences.
Date posted
Sep 21, 2022
Date updated
Oct 3, 2022
Speakers
