[Pl-seminar] Seminar TOMORROW: Yuriy Brun: "Software Fairness"

[Nathaniel Yazdani]

NUPRL Seminar Presents

Yuriy Brun
University of Massachusetts Amherst

12:00pm to 1:30pm
Wednesday, October 30th, 2019
Room 366 WVH (http://www.ccs.neu.edu/home/wand/directions.html)

Software Fairness

Abstract

Modern software contributes to important societal decisions, and yet we
know very little about its fairness properties. Can software discriminate?
Evidence of software discrimination has been found in systems that
recommend criminal sentences, grant access to loans and other financial
products, transcribe YouTube videos, translate text, and perform facial
recognition. Systems that select what ads to show users can similarly
discriminate. For example, a professional social network site could,
hypothetically, learn stereotypes and only advertise stereotypically female
jobs to women and stereotypically male ones to men. Despite existing
evidence of software bias, and significant potential for negative
consequences, little technology exists to test software for such bias, to
enforce lack of bias, and to learn fair models from potentially biased
data. Even defining what it means for software to discriminate is a complex
task. I will present recent research that defines software fairness and
discrimination; develops a testing-based, causality-capturing method for
measuring if and how much software discriminates; and provides provable
formal guarantees on software fairness. I will also describe open problems
in software fairness and how recent advances in machine learning and
natural language modeling can help address them. Overall, I will argue that
enabling and ensuring software fairness requires solving research
challenges across computer science, including in machine learning, software
and systems engineering, human-computer interaction, and theoretical
computer science.

Bio

Yuriy Brun is an associate professor with the College of Information and
Computer Sciences at the University of Massachusetts Amherst. His research
interests include software engineering, software fairness and bias,
self-adaptive systems, and distributed systems. He received his PhD from
the University of Southern California in 2009 and was a Computing
Innovation postdoctoral fellow at the University of Washington until 2012.
Prof. Brun is a recipient of the NSF CAREER Award in 2015, the IEEE TCSC
Young Achiever in Scalable Computing Award in 2013, a Best Paper Award in
2017, two ACM SIGSOFT Distinguished Paper Awards in 2011 and 2017, a
Microsoft Research Software Engineering Innovation Foundation Award in
2014, a Google Faculty Research Award in 2015, a Lilly Fellowship for
Teaching Excellence in 2017, a College Outstanding Teacher Award in 2017,
and an ICSE 2015 Distinguished Reviewer Award.
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