January 19, 2017 - January 20, 2017
12:00 PM - 5:30 PM
Co-sponsored by the Penn Fels Policy Research Initiative and the Warren Center for Network and Data Sciences.
Organized by Sampath Kannan, Jamie Morgenstern, Mallesh Pai, Aaron Roth, and Rakesh Vohra.
A large part of our digital infrastructure is designed to automate decision making, and ideally should improve economic efficiency. Automated decisions now govern, among many other things, whether we are approved for credit cards, what advertisements we are shown, and what search results we see. Algorithms determine the government’s perception of an individual’s risk (e.g. at airport security) or trustworthiness (e.g. in evaluating recidivism risk for parole decisions). The aim of the workshop is to better understand issues surrounding “unfairness” associated with the use of machine learning and automated decision making. This includes the frictions that are the cause of such inadvertent unfairness, and novel technical solutions to solve these problems.
Thursday, January 19th:
12:00 – 1:30 pm: Lunch (by invitation only)
2:00 – 3:00 pm: Cynthia Dwork (Harvard) with discussant Cary Coglianese (Penn Law)
3:00 – 3:30 pm: Coffee
3:30 – 4:30 pm: Jamie Morgenstern (Penn CIS) with discussant Solon Barocas (Microsoft Research)
4:30 – 5:00 pm: Coffee
5:00 – 6:00 pm: Nicola Persico (Kellogg/ Northwestern) with discussant Richard Berk (Penn Statistics)
Friday, January 20th:
8:30 – 9:30 am: Breakfast
9:30 – 10:30 am: Mortiz Hardt (Google) with discussant Suresh Venkatsubramanian (Utah)
10:30 – 11:00 am: Coffee
11:00 – 12:00 pm: James Zou (Stanford) with discussant Glen Weyl(Microsoft Research)
12:00 – 1:30 pm: Lunch
1:30 – 2:30 pm: Sorelle Friedler (Haverford) with discussant Danah Boyd (Microsoft Research)
2:30 – 3:00 pm: Coffee
3:00 – 4:00 pm: Jon Kleinberg (Cornell) with discussant Sandra Mayson (Penn Law)
4:00 – 4:30 pm: Coffee
4:30 – 5:30 pm: Panel Discussion with Cary Coglianese, Cynthia Dwork, Jon Kleinberg, Hanna Wallach, and Glen Weyl