SOURCE-LINKED INTELLIGENCE

MARLA: A Conceptual Scaffold for Regulatory Learning under the EU AI Act

arXiv · AI, language, vision and robotics · article · Sep 4, 2026 · UTC

The EU AI Act positions regulation as part of the infrastructure for safe, trustworthy and market-ready innovation. Realising this ambition requires regulatory learning: the evidence generated during implementation must be translated into governance and legal knowledge that supports consistent interpretation, effective oversight, and adaptation as technologies evolve. Yet the actors who produce this evidence and those who rely on it operate in different professional worlds. This paper proposes MARLA (Map, Assess, Report, Learn, Adapt), a conceptual scaffold organising regulatory learning as a

Read original source ↗ Open in workspace

recordType

paper

region

Global