Léa Genuit is a data scientist at Fiddler AI, focusing her research on transparency in AI algorithms.
As more companies adopt AI, more people question the impact AI creates on society, especially on algorithmic fairness. However, most metrics that measure the fairness of AI algorithms today don’t capture the critical nuance of intersectionality. Instead, they hold a binary view of fairness, e.g., protected vs. unprotected groups. In this talk, we’ll discuss the latest research on intersectional group fairness using worst-case comparisons.
Key Takeaways: The importance of fairness in AI, why AI fairness is even more critical today, and why intersectional group fairness is critical to improving AI fairness