This workshop will take place at the end of the cluster. It will examine the causes and consequences of bias in machine learning. It will cover recent results on statistical and individual notions of fairness in algorithmic decisions and examine the circumstances for which they are achievable or provably impossible. In particular, it will also examine more complex settings where multiple decisions are made in parallel or in a pipelined manner and examine appropriate notions of fairness in these settings. The aim is to bring together diverse researchers interested in a rigorous approach to the issues.

Steven Wu (University of Minnesota Twin Cities)
Invited Participants

Shera Avi-Yonah (Harvard University), Yahav Bechavod (Hebrew University), Joshua Blumenstock (U.C. Berkeley), Elisa Celis (Yale University), Kai-Wei Chang (UCLA), Bo Cowgill (Columbia Business School), Rachel Cummings (Georgia Institute of Technology), Frances Ding (Harvard University), Cynthia Dwork (Harvard University & Microsoft Research), Alex Frankel (Chicago Booth), Sorelle Friedler (Haverford College), Sumegha Garg (Princeton University), Boriana Gjura (Harvard University), Sharad Goel (Stanford), Shafi Goldwasser (Simons Institute), Swati Gupta (Georgia Tech), Moritz Hardt (UC Berkeley), Bernease Herman (Escience Institute), Cyrus Hettle (Georgia Institute of Technology), Lily Hu (Harvard University), Christina Ilvento (Harvard University), Christopher Jung (University of Pennsylvania), Sampath Kannan (University of Pennsylvania), Michael Kim (Stanford University), Jon Kleinberg (Cornell University), Min Kyung Lee (Carnegie Mellon University), Kristian Lum (HRDAG), Neil Lutz (University of Pennsylvania), Charlie Marx (Haverford College), Smitha Milli (UC Berkeley), Alan Mislove (Northeastern University), Cris Moore (Santa Fe Institute), Jamie Morgenstern (University of Pennsylvania), Deirdre Mulligan (UC Berkeley), Helen Nissenbaum (Cornell Tech), Toni Pitassi (University of Toronto), Gireeja Ranade (UC Berkeley), Omer Reingold (Stanford University), Aaron Roth (University of Pennsylvania), Guy Rothblum (Weizmann Institute), Yonadav Shavit (Harvard University), Nati Srebro Bartom (Toyota Technological Institute at Chicago), Pragya Sur (Stanford University), Chloe Yang (Georgia Institute of Technology), Gal Yona (Weizmann Institute), Richard Zemel (University of Toronto), Haiyi Zhu (University of Minnesota), James Zou (Stanford University)