Extended Empirical Validation of the Explainability Solution Space

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Authors: Antoni Mestre, Manoli Albert, Míriam Gil, Vicente Pelechano
Cited by: 0
References: 1

Abstract

This technical report provides an extended validation of the Explainability Solution Space (ESS) through cross-domain evaluation. While initial validation focused on employee attrition prediction, this study introduces a heterogeneous intelligent urban resource allocation system to demonstrate the generality and domain-independence of the ESS framework. The second case study integrates tabular, temporal, and geospatial data under multi-stakeholder governance conditions. Explicit quantitative positioning of representative XAI families is provided for both contexts. Results confirm that ESS rankings are not domain-specific but adapt systematically to governance roles, risk profiles, and stakeholder configurations. The findings reinforce ESS as a generalizable operational decision-support instrument for explainable AI strategy design across socio-technical systems.

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) Ethics and Social Impacts of AI E-Government and Public Services

Publication details

Journal / source
arXiv (Cornell University)
Publication date
1 March 2026
Language
EN
Document type
Preprint