  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.
