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Conformity assessments and post-market monitoring: a guide to the role of auditing in the proposed European AI regulation

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 <i>conformity assessments</i> that providers of high-risk AI systems are expected to conduct, and the <i>post-market monitoring plans</i> 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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11023-021-09577-4

Authors

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Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Oxford college:
Keble College
Role:
Author
ORCID:
0000-0002-8691-2582
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Role:
Author
ORCID:
0000-0002-9488-3419
More by this author
Role:
Author
ORCID:
0000-0003-3281-5426
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-5444-2280


Publisher:
Springer
Journal:
Minds and Machines More from this journal
Volume:
32
Pages:
241–268
Place of publication:
Netherlands
Publication date:
2021-11-05
Acceptance date:
2021-10-14
DOI:
EISSN:
1572-8641
ISSN:
0924-6495
Pmid:
34754142


Language:
English
Keywords:
Pubs id:
1209058
Local pid:
pubs:1209058
Deposit date:
2022-06-06
ARK identifier:

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