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MARLA framework proposed to aid EU AI Act regulatory learning

By PulseAugur Editorial · [1 sources] ·

A new conceptual framework called MARLA has been proposed to facilitate regulatory learning for the EU AI Act. MARLA, which stands for Map, Assess, Report, Learn, Adapt, aims to bridge the gap between those who generate evidence during AI implementation and those who use it for governance. The framework is designed to support consistent interpretation, effective oversight, and adaptation of AI regulations as technologies evolve, illustrated through piloted case studies. AI

IMPACT Provides a structured approach for adapting AI regulations to evolving technologies and ensuring consistent governance.

RANK_REASON The cluster describes a conceptual framework proposed in an academic paper for regulatory learning related to the EU AI Act. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

MARLA framework proposed to aid EU AI Act regulatory learning

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The cluster describes a conceptual framework proposed in an academic paper for regulatory learning related to the EU AI Act. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Alessio Buscemi, Tom Deckenbrunnen, Imane Hmiddou, Marco Billi, Livio Rubino, Silvia Rizzuto Ferruzza, Daniele Pagani, Antonino Rotolo ·

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

    arXiv:2609.04877v1 Announce Type: new Abstract: 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 translate…

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