Summer 2018

Summer Cluster: Algorithmic Fairness

Jul. 2Aug. 10, 2018

As algorithms reach ever more deeply into our daily lives, determining our online experiences, credit offerings, and educational opportunities, and contributing to decisions on eligibility for bail and parole, there is increasing concern that they be “fair”. But what does “fair” mean? How can fairness be ensured? When can we conclude that a system composed of pieces that are fair in isolation is fair in toto? The exploration of these questions is giving rise to the emerging theory of algorithmic fairness. This cluster brings together architects of this new area and researchers in machine learning of fair representations.


Cynthia Dwork (Harvard University & Microsoft Research), Guy Rothblum (Weizmann Institute)

Long-Term Participants (including Organizers):

Cynthia Dwork (Harvard University & Microsoft Research), Sampath Kannan (University of Pennsylvania), Moni Naor (Weizmann Institute), Omer Reingold (Stanford University), Guy Rothblum (Weizmann Institute)

Visiting Graduate Students and Postdocs:

Zhun Deng (Harvard University), Sumegha Garg (Princeton University), Christina Ilvento (Harvard University), Christopher Jung (University of Pennsylvania), Himabindu Lakkaraju (Stanford University), Neil Lutz (University of Pennsylvania), Gal Yona (Weizmann Institute)