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.
All events take place in the Calvin Lab auditorium.
Further details about this workshop will be posted in due course. Enquiries may be sent to the organizers workshop-fairness2 [at] lists [dot] simons [dot] berkeley [dot] edu (at this address).
Registration is required to attend this workshop. Space may be limited, and you are advised to register early. To submit your name for consideration, please register and await confirmation of your acceptance before booking your travel.
Yahav Bechavod (Hebrew University), Cynthia Dwork (Harvard University & Microsoft Research), Boriana Gjura (Harvard University), Sharad Goel (Stanford), Shafi Goldwasser (Simons Institute), Swati Gupta (Georgia Tech), 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), Neil Lutz (University of Pennsylvania), Charles Marx (Haverford College), Cristopher Moore (Santa Fe Institute), Jamie Morgenstern (University of Pennsylvania), Deirdre Mulligan (UC Berkeley), Toniann Pitassi (University of Toronto), Gireeja Ranade (UC Berkeley), Omer Reingold (Stanford University), Guy Rothblum (Weizmann Institute), Yonadav Shavit (Harvard University), Nathan Srebro Bartom (Toyota Technological Institute at Chicago), Pragya Sur (Stanford University), Yuanyuan (Chloe) Yang (Georgia Institute of Technology), Gal Yona (Weizmann Institute), Richard Zemel (University of Toronto), Haiyi Zhu (University of Minnesota), James Zou (Stanford University)