RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems
This work targets AI practitioners in the EU needing clearer methods to comply with ethical guidelines, but it is incremental as it builds on existing literature without introducing new technical methods.
The paper addresses the lack of actionable instructions for operationalizing ethics in AI development under the EU AI Act, by analyzing inconsistencies in ethical guidelines and the absence of requirements engineering in frameworks, and proposes recommendations to improve trustworthy AI development.
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.