Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits

no code implementations • 13 May 2022 • Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee, Jatinder Singh, Zhiwei Steven Wu, Kenneth Holstein, Haiyi Zhu

Recent years have seen the development of many open-source ML fairness toolkits aimed at helping ML practitioners assess and address unfairness in their systems.

BIG-bench Machine Learning Fairness

A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms

no code implementations • 21 Apr 2022 • Nil-Jana Akpinar, Manish Nagireddy, Logan Stapleton, Hao-Fei Cheng, Haiyi Zhu, Steven Wu, Hoda Heidari

This stylized setup offers the distinct capability of testing fairness interventions beyond observational data and against an unbiased benchmark.

Fairness