AI Fairness

AI fairness research aims to mitigate biases in artificial intelligence systems that lead to discriminatory outcomes for certain demographic groups. Current efforts focus on developing and evaluating fairness metrics, designing algorithms that minimize bias while maintaining accuracy (e.g., using reweighting techniques or incorporating fairness constraints into model training), and investigating the interplay between privacy and fairness. This field is crucial for ensuring equitable access to AI-driven services and decision-making processes across various sectors, including healthcare, finance, and criminal justice, and for promoting responsible AI development.