Abstract：
Race is directly or indirectly incorporated into many AI systems. These systems, which automate typically human tasks, are used across various domains such as predictive policing, disease detection, government resource allocation, and loan approvals. However, these tools have been criticized for handling race insensitively or inaccurately. Despite the prevalent use of race in these AI systems, it is often not properly defined. It is treated as an obvious concept and represented as fixed categories, which fail to fully incorporate the social meaning surrounding race. Thus, in this review article, we define race and discuss how it is represented in AI systems. We also explore the consequences of such representations and offer recommendations on how to incorporate race more appropriately in these systems.
摘要：
种族直接或间接地整合到许多AI系统中。这些系统,通常自动执行人工任务，在各个领域使用，如预测性警务，疾病检测，政府资源配置,和贷款批准。然而,这些工具因不敏感或不准确地处理种族而受到批评。尽管在这些人工智能系统中普遍使用种族，它通常没有正确定义。它被视为一个明显的概念，并被表示为固定的类别，未能充分融入围绕种族的社会意义。因此，在这篇评论文章中，我们定义种族并讨论它在AI系统中的表现。我们还探讨了这种表示的后果，并就如何在这些系统中更适当地纳入种族提供了建议。
