Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Cynthia Dwork - Group Fairness and Individual Fairness - IPAM at UCLA

Institute for Pure & Applied Mathematics (IPAM) via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the concepts of group fairness and individual fairness in algorithmic decision-making through this lecture by Cynthia Dwork from Harvard University SEAS. Recorded at IPAM's Graduate Summer School on Algorithmic Fairness at UCLA, delve into the early literature on the theory of algorithmic fairness and examine the two main categories of fairness notions. Understand the requirements of group fairness, which focuses on similar statistics across demographic groups, and individual fairness, which emphasizes similar treatment for individuals who are alike in relation to scoring or classification tasks. Analyze the advantages and disadvantages of these fairness concepts and their implications for creating equitable algorithms. Gain valuable insights into the complexities of implementing fairness in algorithmic systems and the challenges faced in balancing different fairness criteria.

Syllabus

Cynthia Dwork - Group Fairness and Individual Fairness Pt. 1/2 - IPAM at UCLA

Taught by

Institute for Pure & Applied Mathematics (IPAM)

Reviews

Start your review of Cynthia Dwork - Group Fairness and Individual Fairness - IPAM at UCLA

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.