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

[Nathaniel Yazdani]

In another development, this seminar has been postponed to a later date. We
will re-announce once that date is confirmed.

We apologize for the confusion.

On Tue, Oct 29, 2019 at 6:48 PM Nathaniel Yazdani <yazdani.n at husky.neu.edu>
wrote:

> Please note that the seminar time has been changed to 1:30pm, due to a
> spurious double-booking of the room.
>
> On Tue, Oct 29, 2019 at 9:09 AM Nathaniel Yazdani <yazdani.n at husky.neu.edu>
> wrote:
>
>> NUPRL Seminar Presents
>>
>> Yuriy Brun
>> University of Massachusetts Amherst
>>
>> N/A
>> 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.
>>
>
-------------- next part --------------
HTML attachment scrubbed and removed