Extended Empirical Validation of the Explainability Solution Space
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