UMD Center for Machine Learning Launches Fairness in AI Seminar Series

A weekly seminar series focused on fairness and bias in artificial intelligence (AI) and machine learning (ML) virtually kicks-off at the University of Maryland on Monday, March 8.

The hour-long talks—Mondays from 11 a.m. to noon—are sponsored by the University of Maryland Center for Machine Learning and technology and financial leader Capital One. 

The Fairness in AI seminar series will feature experts in AI, ML and theoretical computer science who will identify challenges—and seek input on solutions—to the plethora of questions regarding fairness and bias in software used for everything from judicial sentencing guidelines, to employment hiring, to loan applications, to organ donor exchanges.

Algorithms for these types of AI and ML applications normally use already-collected datasets, which can tend to include implicit social biases. 

“It’s imperative for machine learning researchers to take issues of fairness explicitly into account when designing these systems,” says Leonidas Tsepenekas, a fourth-year doctoral student in computer science who is organizing the seminar series. 

Tsepenekas says the Fairness in AI seminars are timely, as the topic is attracting great interest, both in the scientific community and in society. 

The inaugural speaker for the series is Aravind Srinivasan,  a Distinguished University Professor of computer science with an appointment in the University of Maryland Institute for Advanced Computer Studies. 

Srinivasan’s talk, “Fairness in AI and in Algorithms,” is designed for anyone wanting to learn more about this topic, assuming they’ve had only a general exposure to computer science and AI.

After outlining some general approaches to fairness, Srinivasan will discuss his research—particularly in the area of unsupervised learning.

Sign up here to receive updates on the Fairness in AI seminar series. 

—Story by Maria Herd

The University of Maryland Center for Machine Learning is one of six major centers in the University of Maryland Institute for Advanced Computer Studies (UMIACS).