RT Journal Article
T1 Operationalizing Explainable AI in the EU Regulatory Ecosystem
A1 Nannini, Luca
A1 Alonso Moral, José María
A1 Catalá Bolós, Alejandro
A1 Lama Penín, Manuel
A1 Barro Ameneiro, Senén
K1 Artificial intelligence
K1 Law
K1 Regulation
K1 Intelligent systems
K1 Ecosystems
K1 Stakeholders
K1 Explainable AI
K1 Sociotechnical systems
K1 Europe
AB The European Union’s (EU’s) regulatory ecosystem presents challenges with balancing legal and sociotechnical drivers for explainable artificial intelligence (XAI) systems. Core tensions emerge on dimensions of oversight, user needs, and litigation. This article maps provisions on algorithmic transparency and explainability across major EU data, AI, and platform policies using qualitative analysis. We characterize the involved stakeholders and organizational implementation targets. Constraints become visible between useful transparency for accountability and confidentiality protections. Through an AI hiring system example, we explore the complications with operationalizing explainability. Customization is required to satisfy explainability desires within confidentiality and proportionality bounds. The findings advise technologists on prudent XAI technique selection given multidimensional tensions. The outcomes recommend that policy makers balance worthy transparency goals with cohesive legislation, enabling equitable dispute resolution.
PB IEEE
YR 2024
FD 2024
LK http://hdl.handle.net/10347/34596
UL http://hdl.handle.net/10347/34596
LA eng
NO L. Nannini, J. M. Alonso-Moral, A. Catalá, M. Lama and S. Barro, "Operationalizing Explainable Artificial Intelligence in the European Union Regulatory Ecosystem," in IEEE Intelligent Systems, vol. 39, no. 4, pp. 37-48, July-Aug. 2024, doi: 10.1109/MIS.2024.3383155
DS Minerva
RD 23 abr 2026