How to regulate algorithmic decision-making: A framework of regulatory requirements for different applications
How to regulate algorithmic decision-making: A framework of regulatory requirements for different applications
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DOI：
10.1111/rego.12369
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发表时间：
2020-10-20
影响因子：
3
通讯作者：
Koenig, Pascal D.
中科院分区：
文献类型：
--
作者：
Krafft, Tobias D.;Zweig, Katharina A.;Koenig, Pascal D.
在许多领域，人工决策（ADM）系统已经开始支持、抢先或替代人类的决策，对个人的生活产生潜在的重大影响。实现透明度和问责制已被确定为使用这些系统的总目标。然而，具体的应用程序在风险程度和它们对数据主体造成的问责问题方面差别很大。本文件解决了这种变化，并提出了一个框架，区分一系列ADM系统用途的监管要求。它借鉴代理理论，从数据主体的角度对问责制挑战进行概念化，目的是使保障算法问责制的工具系统化。此外，本文还展示了如何将这些工具与基于风险矩阵的ADM应用程序相匹配。由此产生的综合框架可以指导ADM系统的评估和选择合适的监管规定。
Algorithmic decision-making (ADM) systems have come to support, pre-empt or substitute for human decisions in manifold areas, with potentially significant impacts on individuals' lives. Achieving transparency and accountability has been formulated as a general goal regarding the use of these systems. However, concrete applications differ widely in the degree of risk and the accountability problems they entail for data subjects. The present paper addresses this variation and presents a framework that differentiates regulatory requirements for a range of ADM system uses. It draws on agency theory to conceptualize accountability challenges from the point of view of data subjects with the purpose to systematize instruments for safeguarding algorithmic accountability. The paper furthermore shows how such instruments can be matched to applications of ADM based on a risk matrix. The resulting comprehensive framework can guide the evaluation of ADM systems and the choice of suitable regulatory provisions.