AINeutralarXiv – CS AI · 10h ago6/10
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Fairness of Explanations in Artificial Intelligence (AI): A Unifying Framework, Axioms, and Future Direction toward Responsible AI
Researchers present a unified framework addressing a critical gap between algorithmic fairness and explainable AI (XAI): models can produce fair outputs while employing biased reasoning processes. The study introduces the concept of 'procedural bias' and proposes a conditional invariance framework to formalize and audit explanation fairness, establishing the first comprehensive taxonomy and evaluation workflow for this emerging field.