Tailoring Requirements Engineering for Responsible AI
This addresses the issue of AI acceptance post-deployment in domains like medical and automotive, but it is incremental as it builds on existing RE concepts.
The paper tackles the problem of ensuring Responsible AI systems by proposing that Requirements Engineering (RE) needs to be tailored specifically for this purpose, highlighting challenges in research and practice without presenting concrete results or numbers.
Requirements Engineering (RE) is the discipline for identifying, analyzing, as well as ensuring the implementation and delivery of user, technical, and societal requirements. Recently reported issues concerning the acceptance of Artificial Intelligence (AI) solutions after deployment, e.g. in the medical, automotive, or scientific domains, stress the importance of RE for designing and delivering Responsible AI systems. In this paper, we argue that RE should not only be carefully conducted but also tailored for Responsible AI. We outline related challenges for research and practice.