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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 inerror situations. As a result, there can be misconceptions about the behaviorof the technologies in use. This, in turn, can lead to misuse and rejection byusers. Explanation, for example, through transparency, can address thesemisconceptions. However, it would be confusing and overwhelming for users ifthe entire software or hardware was explained. Therefore, this paper looks atthe 'enabling' architecture. It describes those aspects of a robotic systemthat might need to be explained to enable someone to use the technologyeffectively. Furthermore, this paper is concerned with the 'explanandum', whichis the corresponding misunderstanding or missing concepts of the enablingarchitecture that needs to be clarified. We have thus developed and present anapproach for determining this 'enabling' architecture and the resulting'explanandum' of complex technologies.

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