Discrimination

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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.

Ongoing Projects

 

• Bridging Mechanism Design and Machine Learning towards Algorithmic Fairness
  

Working Group Organizers

Faidra Monachou	Ph.D. Student in Management Science & Engineering	Stanford University
Jessica Finocchiaro	Ph.D. Student in Computer Science	University of Colorado - Boulder