A Reusable Semantic Web Framework for Evidence-Grounded Fundamental Rights Impact Assessments under the EU AI Act

2026-09-30

AI Summary

This study addresses the fragmentation of evidence for fundamental rights impact assessments of high-risk systems under the EU AI Act by proposing a Semantic Web-based evidence reuse framework. The approach integrates SPARQL, RDF, LLM-assisted annotation, and hybrid classification techniques to construct a unified architecture that consolidates multi-source heterogeneous evidence from the employment and public service domains into a queryable knowledge graph. The project achieves coverage of 103 records and open-sources all artifacts to support compliance assessments by regulatory authorities and small-to-medium enterprises. Furthermore, the research reveals significant limitations of LLMs in automatically retrieving fairness-related evidence within the employment domain (κ=0.045), thereby offering a novel paradigm for evidence-driven assessment in AI governance.

Abstract

The EU AI Act (Art. 27) requires deployers of high-risk AI systems to conduct Fundamental Rights Impact Assessments (FRIAs) before deployment, yet the evidence needed for credible assessments is fragmented across incompatible incident repositories, risk vocabularies, and legal texts. We present a reusable Semantic Web-based framework that consolidates this evidence for two high-risk public sector categories: employment and worker management (Annex III(4)) and access to essential public services (Annex III(5)(a)). A curated 150-record corpus is annotated along four axes using keyword, LLM, and hybrid methods and serialised as a SPARQL-queryable knowledge graph of 1,351 RDF triples. Five FRIA demonstration scenarios surface 103 records (68.7% coverage). Evaluation against a 69-record gold standard reveals that LLM-assisted classification of the employment domain achieves only $κ= 0.045$, a cautionary result for automated fairness-related evidence retrieval in this domain. All artefacts are released openly to support adoption by regulators, national authorities, and SMEs.

Problem

• Fundamental Rights Impact Assessment
• EU AI Act
• evidence fragmentation
• high-risk AI systems
• Semantic Web

Innovation

• Semantic Web
• Knowledge Graph
• Fundamental Rights Impact Assessment
• Large Language Models
• EU AI Act