Talk: Examining Validity of ML Systems in the Public Sphere by Rediet Abebe

On 24 May, Rediet Abebe will be visiting P1 to give a talk Examining Validity of Machine Learning Systems in the Public Sphere.  

Title:
Algorithms on the Bench: Examining Validity of Machine Learning Systems in the Public Sphere

Bio:
Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows and a 2022 Andrew Carnegie Fellow. Abebe’s research examines the interaction of algorithms and inequality, with a focus on contributing to the scientific foundations of this emerging research area. Abebe co-launched the ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), for which Abebe serves on the executive committee and was a program co-chair for the inaugural conference. Abebe’s work has received recognitions including the MIT Technology Reviews’ 35 Innovators Under 35, the Bloomberg 50 as a one to watch, the ACM SIGKDD Dissertation Award, and an honorable mention for the ACM SIGecom Dissertation Award. Abebe is on leave as an assistant professor of computer science at UC Berkeley. Abebe holds a Ph.D. in Computer Science from Cornell University and Master’s degrees in mathematics from both the University of Cambridge and Harvard University.

The talk is a part of “The Science of the Predicted Human” series, a collaboration with the Copenhagen Center for Social Data Science (SODAS)

Find more information here.