Think about the stakeholders first! Toward an algorithmic transparency playbook for regulatory compliance

Think about the stakeholders first! Toward an algorithmic transparency playbook for regulatory compliance
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DOI:
10.1017/dap.2023.8
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发表时间:
2023
期刊:
Data & Policy
影响因子:
--
通讯作者:
Stoyanovich, Julia
Stoyanovich, Julia
中科院分区:
--
文献类型:
--
作者:
Bell, Andrew;Nov, Oded;Stoyanovich, Julia

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世界各国政府越来越多地提出和通过法律,以规范公共和私营部门实施的人工智能(AI)系统。其中许多法规都涉及人工智能系统的透明度,以及相关的公民意识问题,例如允许个人有权解释人工智能系统如何做出影响他们的决定。然而,到目前为止,几乎所有的人工智能治理文件都有一个显著的缺点:它们都专注于在使人工智能系统透明方面应该做什么(或不应该做什么),但却把工作的主要任务留给了技术人员来弄清楚如何构建透明的系统。我们通过提出一种以技术人员为先的方法来填补这一空白,这种方法可以帮助技术人员设计透明、符合法规的系统。我们还描述了一个现实世界的案例研究,说明了这种方法可以在实践中使用。
Increasingly, laws are being proposed and passed by governments around the world to regulate artificial intelligence (AI) systems implemented into the public and private sectors. Many of these regulations address the transparency of AI systems, and related citizen-aware issues like allowing individuals to have the right to an explanation about how an AI system makes a decision that impacts them. Yet, almost all AI governance documents to date have a significant drawback: they have focused on what to do (or what not to do) with respect to making AI systems transparent, but have left the brunt of the work to technologists to figure out how to build transparent systems. We fill this gap by proposing a stakeholder-first approach that assists technologists in designing transparent, regulatory-compliant systems. We also describe a real-world case study that illustrates how this approach can be used in practice.
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