In this paper, we argue that AI ethics must move beyond the concepts of race-based representation and bias, and towards those that probe the deeper relations that impact how these systems are designed, developed, and deployed. Many recent discussions on ethical considerations of bias in AI systems have centered on racial bias. We contend that antiblackness in AI requires more of an examination of the ontological space that provides a foundation for the design, development, and deployment of AI systems. We examine what this contention means from the perspective of the sociocultural context in which AI systems are designed, developed, and deployed and focus on intersections with anti-Black racism (antiblackness). To bring these multiple perspectives together and show an example of antiblackness in the face of attempts at de-biasing, we discuss results from auditing an existing open-source semantic network (ConceptNet). We use this discussion to further contextualize antiblackness in design, development, and deployment of AI systems and suggest questions one may ask when attempting to combat antiblackness in AI systems.

翻译：在本文中,我们争论说,大赦国际的道德观念必须超越种族代表制和偏见的概念,而应转向那些探究影响这些体系的设计、发展和部署的更深层关系的概念。最近许多关于大赦国际体系中偏见的伦理考虑的讨论都以种族偏见为中心。我们争论说,大赦国际中的反黑人要求更多地审查为设计、开发和部署大赦国际体系奠定基础的本体空间。我们从设计、开发和部署大赦国际体系的社会文化背景的角度来审视这一论点意味着什么,并侧重于与反黑人种族主义(反黑人)的交叉点。为了将这些多重观点结合起来,并展示在试图消除偏见时反黑人的例子,我们讨论审计现有开放源的语义网络(ConceptNet)的结果。我们利用这一讨论进一步将大赦国际体系的设计、开发和部署中的反黑人联系联系到设计、开发和部署中,并提出在试图打击大赦国际体系中的反黑人时可能提出的问题。