What you need to know about a learning robot: Identifying the enabling architecture of complex systems

Nowadays, we are dealing more and more with robots and AI in everyday life. However, their behavior is not always apparent to most lay users, especially in error situations. As a result, there can be misconceptions about the behavior of the technologies in use. This, in turn, can lead to misuse and rejection by users. Explanation, for example, through transparency, can address these misconceptions. However, it would be confusing and overwhelming for users if the entire software or hardware was explained. Therefore, this paper looks at the énabling' architecture. It describes those aspects of a robotic system that might need to be explained to enable someone to use the technology effectively. Furthermore, this paper is concerned with the éxplanandum', which is the corresponding misunderstanding or missing concepts of the enabling architecture that needs to be clarified. We have thus developed and present an approach for determining this énabling' architecture and the resulting éxplanandum' of complex technologies.