  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 'enabling' 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 'explanandum', 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 'enabling' architecture and the resulting
'explanandum' of complex technologies.
