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Engineering Explainable AI Systems for GDPR-Aligned Decision Transparency: A Modular Framework for Continuous Compliance

2026-01-21

Abstract excerpt

Explainability is increasingly expected to support not only interpretation, but also accountability, human oversight, and auditability in high-risk Artificial Intelligence (AI) systems. However, in many deployments, explanations are generated as isolated technical reports, remaining weakly connected to decision provenance, governance actions, audit logs, and regulatory documentation. This short communication intro...

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Literature Corpus work
3f2d644f-71da-531d-9d20-852e0f4cb837
DOI
10.20944/preprints202601.1610.v1
Open publication

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