no code implementations • 9 Mar 2024 • Dalia Gala, Milo Phillips-Brown, Naman Goel, Carinal Prunkl, Laura Alvarez Jubete, Medb Corcoran, Ray Eitel-Porter
Machine learning requires defining one's target variable for predictions or decisions, a process that can have profound implications on fairness: biases are often encoded in target variable definition itself, before any data collection or training.
no code implementations • 20 Jul 2022 • Arash Bateni, Matthew C. Chan, Ray Eitel-Porter
This paper summarizes and evaluates various approaches, methods, and techniques for pursuing fairness in artificial intelligence (AI) systems.