no code implementations • 27 Apr 2023 • Louis Hickman, Jason Kuruzovich, Vincent Ng, Kofi Arhin, Danielle Wilson
In this study, we systematically under- and oversampled minority (Black and Hispanic) applicants to manipulate adverse impact ratios in training data and investigated how training data adverse impact ratios affect ML model adverse impact and accuracy.
no code implementations • 7 Dec 2021 • Kofi Arhin, Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh
The use of machine learning (ML)-based language models (LMs) to monitor content online is on the rise.