Author name: Gideon Popoola, John Sheppard

MESD: A Risk-Sensitive Metric for Explanation Fairness Across Intersectional Subgroups

Gideon Popoola, John Sheppard / May 12, 2026

arXiv:2603.13452v2 Announce Type: replace
Abstract: Fairness in machine learning is predominantly evaluated through outcome-oriented metrics, such as Demographic parity, which measure whether predictions are statistically consistent across protected g…

cs.AI, cs.CE, cs.CY, cs.LG

Fairness of Explanations in Artificial Intelligence (AI): A Unifying Framework, Axioms, and Future Direction toward Responsible AI

Gideon Popoola, John Sheppard / May 12, 2026

arXiv:2605.09852v1 Announce Type: new
Abstract: Machine learning algorithms are being used in high-stakes decisions, including those in criminal justice, healthcare, credit, and employment. The research community has responded with two largely indepen…