Colloq & CSE 600: Suresh Venkatasubramanian, Univ. of Utah

Event Type: 
CSE 600
Thursday, January 25, 2018 - 14:30 to 16:00
Room 120 (105 Seats)

Algorithmic Fairness: Doing good (or at least doing no harm) with automated decision-making 

In the span of a few years, we've gone from a world where machine learning is a curiosity that makes hilariously bad recommendations to one where learned models makes increasingly intrusive decisions about all aspects of our daily lives.

The very way in which we think about how decisions are made, what it means to be fair and unbiased, and what (or who) is accountable for these decisions, is undergoing a radical shift, driven by computational metaphors that are only now entering mainstream discussions in society at large.

This shift presents challenges: how do we adapt the way we design models to adapt to the larger issues of discrimination and bias in society, and how can we instrument our models to provide more clarity about their inner workings? But it also presents opportunities: can we use concepts from data science to build better tools for decision-making?

In this talk I'll present examples of these challenges and opportunities in my own work. I'll discuss the problem of defining fairness  mathematically, and how we might build fair models and inspect them. I'll also talk about new work in predictive policing that abstracts the problem of feedback in decision systems and uses ideas from reinforcement learning to fix it.

Bio: Suresh Venkatasubramanian is a professor at the University of Utah. His background is in algorithms and computational geometry, as well as data mining and machine learning. His current research interests lie in algorithmic fairness, and more generally the problem of understanding and explaining the results of black box decision procedures. Suresh was the John and Marva Warnock Assistant Professor at the U, and has received a CAREER award from the NSF for his work in the geometry of probability, as well as a test-of-time award at ICDE 2017 for his work in privacy. His research on algorithmic fairness has received press coverage across North America and Europe, including NPR’s Science Friday, NBC, and CNN, as well as in other media outlets. He is a member of the board of the ACLU in Utah, and is a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council.


(hosted by IACS)

Hosted By: 
Steve Skiena
Computed Event Type: 
Event Title: 
Colloq & CSE 600: Suresh Venkatasubramanian, Univ. of Utah