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cs.AI2026
MESD: A Risk-Sensitive Metric for Explanation Fairness Across Intersectional Subgroups
Gideon Popoola, John Sheppard
Fairness in machine learning is predominantly evaluated through outcome-oriented metrics, such as Demographic parity, which measure whether predictions are statistically consistent…
cs.AI2026
Fairness of Explanations in Artificial Intelligence (AI): A Unifying Framework, Axioms, and Future Direction toward Responsible AI
Gideon Popoola, John Sheppard
Machine learning algorithms are being used in high-stakes decisions, including those in criminal justice, healthcare, credit, and employment. The research community has responded w…