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The computational and ethical ramifications of automated decision-making in society
Automated decision-making — the use of predictive tools to assist in decision-making — is no longer the future. It's used to decide what your school districts might look like, where you go to college, whether you get loans for purchases, or even a job. Automated decision-making is used to decide whether police are deployed to your neighborhood, whether you're released on bail or not, what sentence you receive for a conviction, and whether you're released on parole.
We're now seeing the effects of automated decision-making at scale, and we're realizing that predictive methods, much like us humans, can be both accurate and wildly discriminatory. They mirror and amplify some of our biases while correcting for others. And they're far less transparent, especially when we use sophisticated tools from machine learning.
In this talk I'll lay out a fast growing research landscape in the area of fairness, accountabiltiy and transparency in decision-making. I'll also situate this discussion in a larger framework of philosophy, ethics and justice that affects and is affected by decision-by-algorithm.
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 Computing Coommunity Consortium Council of the CRA, a member of the board of the ACLU in Utah, and a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council.
Host: Professor Seny Kamara
Computer Science at Brown University
Providence, Rhode Island 02912 USA
Phone: 401-863-7600
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