Intersectional Group Fairness in Machine Learning

At the ML Fairness Summit, we welcomed Fiddler Data Scientist, Léa Genuit to discuss intersectional group fairness. As more companies adopt AI, more people question the impact AI creates on society, especially on algorithmic fairness. Instead, they hold a binary view of fairness, e.g., protected vs. unprotected groups. In the below blog, Lea covers the latest research in research on intersectional group fairness. Before explaining why, the first question should be how do you detect and mitigate bias in European models to avoid a bad experience?