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Discrimination and Equality in Algorithmic Decision-making

Algorithms are often used to supplement or make decisions in a way that “optimizes’’ some objective; often, these decisions are made under limited resource constraints specific to the given domain. The MD4SG group on Discrimination and Equity in Algorithmic Decision-making focuses on understanding how these optimization choices, constraints, and mechanisms impact different stakeholders of algorithmic systems. This group has larger biweekly meetings, as well as smaller project subgroups focusing on different research areas such as understanding the impacts of ranking problems and design of resource allocation mechanisms. Larger biweekly group meetings will discuss topics including, but not limited to, long-term effects and feedback loops, impacts of resource constraints, implications of discrimination metrics, and contextualization across different domains such as education, hiring, and the gig economy.

Projects #

Working Group Organizers #

Richard Lanas PhillipsPh.D. Student in Computer ScienceCornell University
Samuel GallerSocial Sector Consultant for Major Foundations and NonprofitsRedstone Strategy Group

Working Group Members #

Shubham SinghUniversity of Illinois at Chicago
Savannah ThaisPrinceton University
Kate DonahueCornell University
Sandro RadovanovićUniversity of Belgrade
Soham MukherjeePurdue University
Jose M. AlvarezUniversity of Pisa
Alejandro BelloginUniversidad Autónoma de Madrid, Spain
Sakina HansenGraduate Data Scientist Office for National Statistics
Violet (Xinying) ChenCarnegie Mellon University
Elie AlhajjarUSMA
Corinna HertweckUniversity of Zurich and Zurich University of Applied Sciences
Carlos MouganUniversity of Southampton
Jakob SchoefferKarlsruhe Institute of Technology