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English(EN) MARLA: A Conceptual Scaffold for Regulatory Learning under the EU AI Act

MARLA框架被提出以辅助欧盟人工智能法案监管学习

一个名为MARLA的新概念框架被提出,旨在促进欧盟人工智能法案的监管学习。MARLA代表映射(Map)、评估(Assess)、报告(Report)、学习(Learn)、适应(Adapt),旨在弥合人工智能实施过程中证据生成者与用于治理的证据使用者之间的差距。该框架旨在支持人工智能法规的一致性解释、有效监督以及随着技术发展而进行的适应,并通过试点案例研究进行了说明。 AI

影响 为适应不断发展的技术和确保一致的治理,提供了一种结构化的方法来调整人工智能法规。

排序理由 该集群描述了在学术论文中提出的一个概念框架,用于与欧盟人工智能法案相关的监管学习。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.AI 阅读 →

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MARLA框架被提出以辅助欧盟人工智能法案监管学习

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该集群描述了在学术论文中提出的一个概念框架,用于与欧盟人工智能法案相关的监管学习。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [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:欧盟人工智能法案下监管学习的概念性脚手架

    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…