In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not consider multiple stakeholders or the broader social context. In this article, we present an auditing framework to guide the ethical assessment of an algorithm. The audit instrument itself is comprised of three elements: a list of possible interests of stakeholders affected by the algorithm, an assessment of metrics that describe key ethically salient features of the algorithm, and a relevancy matrix that connects the assessed metrics to stakeholder interests. The proposed audit instrument yields an ethical evaluation of an algorithm that could be used by regulators and others interested in doing due diligence, while paying careful attention to the complex societal context within which the algorithm is deployed.

近年来，对人工智能的道德影响已受到越来越多的审查，由于有偏见的结果，缺乏透明度和滥用数据而引起的公共丑闻不断出现。这导致对AI的不信任感日增，并要求对算法进行强制性的道德审核。当前对算法进行道德评估的建议要么太高，以至于无法在没有进一步指导的情况下付诸实践，要么将重点放在公平或透明的非常具体和技术性的概念上，而这些概念并未考虑多个利益相关者或更广泛的社会环境。在本文中，我们提出了一个审计框架来指导算法的道德评估。审核工具本身包含三个元素：受算法影响的利益相关者的潜在利益清单；评估指标，描述算法的关键道德显着特征，以及关联矩阵，将评估指标与利益相关者的利益联系起来。拟议的审计工具对一种算法进行了道德评估，监管者和其他有意进行尽职调查的人可以使用该算法，同时要特别注意该算法所处的复杂社会环境。