AI Documentation: A path to accountability
AI Documentation: A path to accountability
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AI 文档：问责之路
DOI：
10.1016/j.jrt.2022.100043
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
S. Thalmann
中科院分区：
文献类型：
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作者：
Florian Königstorfer;S. Thalmann
人工智能（AI）为企业带来了巨大的潜力，但由于其黑箱特性，也有很大的缺点。在受监管的用例中，这是一个特别的挑战，在这些用例中，软件需要在部署之前进行认证或验证。传统的软件文档不足以为审计人员提供所需的证据，并且尚未提供AI特定的指南。因此，人工智能在受监管的用例中面临着重大的采用障碍，因为人工智能的问责制无法得到充分的保证。这项访谈研究旨在确定在受监管的用例中记录AI的当前状态。我们发现，AI用例的风险水平会影响AI的采用和AI文档的范围。此外，我们还讨论了人工智能目前是如何记录的，以及从业者在记录人工智能时面临哪些挑战。
Artificial Intelligence (AI) promises huge potential for businesses but due to its black-box character has also substantial drawbacks. This is a particular challenge in regulated use cases, where software needs to be certified or validated before deployment. Traditional software documentation is not sufficient to provide the required evidence to auditors and AI-specific guidelines are not available yet. Thus, AI faces significant adoption barriers in regulated use cases, since accountability of AI cannot be ensured to a sufficient extent. This interview study aims to determine the current state of documenting AI in regulated use cases. We found that the risk level of AI use cases has an impact on the AI adoption and the scope of AI documentation. Further, we discuss how AI is currently documented and which challenges practitioners face when documenting AI.