Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation.

IF 4.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Minds and Machines Pub Date : 2022-01-01 Epub Date: 2021-11-05 DOI:10.1007/s11023-021-09577-4
Jakob Mökander, Maria Axente, Federico Casolari, Luciano Floridi
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引用次数: 38

Abstract

The proposed European Artificial Intelligence Act (AIA) is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can (and should) be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the conformity assessments that providers of high-risk AI systems are expected to conduct, and the post-market monitoring plans that providers must establish to document the performance of high-risk AI systems throughout their lifetimes. We argue that the AIA can be interpreted as a proposal to establish a Europe-wide ecosystem for conducting AI auditing, albeit in other words. Our analysis offers two main contributions. First, by describing the enforcement mechanisms included in the AIA in terminology borrowed from existing literature on AI auditing, we help providers of AI systems understand how they can prove adherence to the requirements set out in the AIA in practice. Second, by examining the AIA from an auditing perspective, we seek to provide transferable lessons from previous research about how to refine further the regulatory approach outlined in the AIA. We conclude by highlighting seven aspects of the AIA where amendments (or simply clarifications) would be helpful. These include, above all, the need to translate vague concepts into verifiable criteria and to strengthen the institutional safeguards concerning conformity assessments based on internal checks.

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合格评定和上市后监测:审计在拟议的欧洲人工智能法规中的作用指南。
拟议中的《欧洲人工智能法案》(AIA)是全球主要经济体首次尝试为人工智能制定总体法律框架。因此,在关于如何监管人工智能系统的更广泛讨论中,AIA可能会成为一个参考点。在本文中,我们描述并讨论了AIA中提出的两种主要执行机制:高风险人工智能系统供应商应进行的符合性评估,以及供应商必须建立的上市后监测计划,以记录高风险人工智能系统在其整个生命周期中的性能。我们认为,AIA可以被解释为建立一个全欧洲范围内进行人工智能审计的生态系统的提议,尽管换句话说。我们的分析提供了两个主要贡献。首先,通过借用现有人工智能审计文献中的术语描述AIA中包含的执行机制,我们帮助人工智能系统提供商了解他们如何在实践中证明遵守AIA中规定的要求。其次,通过从审计的角度审视AIA,我们试图从先前的研究中提供可转移的经验教训,以进一步完善AIA中概述的监管方法。最后,我们强调了AIA的七个方面,其中修订(或简单澄清)将有所帮助。这些首先包括需要将模糊的概念转化为可核查的标准,并加强基于内部检查的合格评定方面的体制保障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Minds and Machines
Minds and Machines 工程技术-计算机:人工智能
CiteScore
12.60
自引率
2.70%
发文量
30
审稿时长
>12 weeks
期刊介绍: Minds and Machines, affiliated with the Society for Machines and Mentality, serves as a platform for fostering critical dialogue between the AI and philosophical communities. With a focus on problems of shared interest, the journal actively encourages discussions on the philosophical aspects of computer science. Offering a global forum, Minds and Machines provides a space to debate and explore important and contentious issues within its editorial focus. The journal presents special editions dedicated to specific topics, invites critical responses to previously published works, and features review essays addressing current problem scenarios. By facilitating a diverse range of perspectives, Minds and Machines encourages a reevaluation of the status quo and the development of new insights. Through this collaborative approach, the journal aims to bridge the gap between AI and philosophy, fostering a tradition of critique and ensuring these fields remain connected and relevant.
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