FairXAI - A Taxonomy and Framework for Fairness and Explainability Synergy in Machine Learning.

Summary: Artificial Intelligence (AI) is used today to make big decisions in areas like healthcare, criminal justice, and online recommendations. Because these decisions affect real people, we need to make sure AI is fair and that we can understand how it makes its choices. Until now, making AI "fair" and making it "explainable" were treated as two completely different goals. This paper looks at how to combine them into one powerful idea called "FairXAI." The authors reviewed past research and created a new guide, including a "FairXAI Wheel" with four main rules. This guide will help computer scientists build AI systems that are not only smart, but also fair, transparent, and easy for everyone to trust.