AI systems are consistently evolving in terms of both capability and autonomy with an holistic social impact. In this context of proliferation and fast technological evolution, the scientific community is actively engaged to assure Trustworthy AI. However, in general terms, AI safety research is significantly slower and is facing critical challenges in terms of strategy, consensus and operationalisation. This paper presents AI-Ethics Ontology (AI-EO) which, by leveraging Semantic Technologies on the Web infrastructure and ontology-based knowledge representations, provides an abstracted semantic infrastructure to foster the convergence, interoperability and operationalization of the different frameworks for Trustworthy AI. The current implementation results from the analysis of two relevant case studies to establish a dynamic development process in fact, as well as to enable its iterative evolution according to a formally-defined methodology. The version 1.0 of the Ontology is freely available and has been designed to be conceptually close to target applications, in a context of interoperability, adaptability as a natural response to change and usability.

翻译：人工智能系统在能力与自主性方面持续演进，并产生全面的社会影响。在这种技术快速扩散与演进的背景下，科学界正积极致力于保障可信人工智能。然而，总体而言，人工智能安全研究明显滞后，并在策略、共识及可操作化方面面临严峻挑战。本文提出人工智能伦理本体（AI-Ethics Ontology, AI-EO），该本体借助基于Web基础设施的语义技术与基于本体的知识表示，构建抽象化的语义基础设施，以促进不同可信人工智能框架的融合、互操作与可操作化。当前版本的实现源于对两个相关案例研究的分析，旨在建立动态开发流程，并依据形式化定义的方法学实现迭代演进。该本体1.0版本已免费开放，其设计在互操作、适应性及可用性情境下，力求在概念层面贴近目标应用场景。