On the Interplay of Explainability and Fairness in AI: A Survey
Algorithmic fairness and explainability are foundational pillars of responsible AI. Although often studied independently, their interplay is increasingly recognized as crucial for diagnosing and mitigating bias in machine learning systems. We first introduce two systematic taxonomies: one for algorithmic fairness and o...
Christos Fragkathoulas, Vasiliki Papanikou, Danae Pla Karidi et al.
· IEEE Transactions on Knowled... · 0 citations