This systematic literature review synthesizes the conceptualizations of ethical principles in AI auditing literature and the knowledge contributions to the stakeholders of AI auditing. We explain how the literature discusses fairness, transparency, non-maleficence, responsibility, privacy, trust, beneficence, and freedom/autonomy. Conceptualizations vary along social/technical- and process/outcome-oriented dimensions. The main stakeholders of ethics-based AI auditing are system developers and deployers, the wider public, researchers, auditors, AI system users, and regulators. AI auditing provides three types of knowledge contributions to stakeholders: 1) guidance; 2) methods, tools, and frameworks; and 3) awareness and empowerment.

中文翻译：

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基于道德的人工智能审计：关于道德原则概念化和对利益相关者的知识贡献的系统文献综述


这篇系统的文献综述综合了人工智能审计文献中道德原则的概念以及对人工智能审计利益相关者的知识贡献。我们解释文献如何讨论公平、透明、非恶意、责任、隐私、信任、仁慈和自由/自治。概念化随着社会/技术和过程/结果导向的维度而变化。基于道德的人工智能审计的主要利益相关者是系统开发者和部署者、广大公众、研究人员、审计员、人工智能系统用户和监管者。人工智能审计为利益相关者提供三种类型的知识贡献：1）指导； 2）方法、工具和框架； 3）意识和赋权。