Complying with the EU AI Act (AIA) guidelines while developing and implementing AI systems will soon be mandatory within the EU. However, practitioners lack actionable instructions to operationalise ethics during AI systems development. A literature review of different ethical guidelines revealed inconsistencies in the principles addressed and the terminology used to describe them. Furthermore, requirements engineering (RE), which is identified to foster trustworthiness in the AI development process from the early stages was observed to be absent in a lot of frameworks that support the development of ethical and trustworthy AI. This incongruous phrasing combined with a lack of concrete development practices makes trustworthy AI development harder. To address this concern, we formulated a comparison table for the terminology used and the coverage of the ethical AI principles in major ethical AI guidelines. We then examined the applicability of ethical AI development frameworks for performing effective RE during the development of trustworthy AI systems. A tertiary review and meta-analysis of literature discussing ethical AI frameworks revealed their limitations when developing trustworthy AI. Based on our findings, we propose recommendations to address such limitations during the development of trustworthy AI.

翻译：遵守欧盟《人工智能法案》（AIA）指南的要求，在欧盟范围内开发和实施人工智能系统即将成为强制规定。然而，从业者在人工智能系统开发过程中缺乏可操作的伦理实施指导。对不同伦理指南的文献综述表明，其所涉及的原则及描述术语存在不一致性。此外，需求工程（RE）被认定有助于从早期阶段增强人工智能开发过程的可信性，但在大量支持伦理且可信人工智能开发的框架中却未见其踪。这种措辞不一致与具体开发实践的缺失使得可信人工智能开发更为困难。为解决这一问题，我们针对主要伦理人工智能指南中所用术语及伦理人工智能原则覆盖范围，构建了对比表格。随后，我们检验了伦理人工智能开发框架在执行有效需求工程以开发可信人工智能系统方面的适用性。通过三级文献综述及对伦理人工智能框架相关文献的元分析，揭示了其在开发可信人工智能时的局限性。基于研究结果，我们提出了在可信人工智能开发中应对这些局限性的建议。