  Trustworthiness is a central requirement for the acceptance and success of
human-centered artificial intelligence (AI). To deem an AI system as
trustworthy, it is crucial to assess its behaviour and characteristics against
a gold standard of Trustworthy AI, consisting of guidelines, requirements, or
only expectations. While AI systems are highly complex, their implementations
are still based on software. The software engineering community has a
long-established toolbox for the assessment of software systems, especially in
the context of software testing. In this paper, we argue for the application of
software engineering and testing practices for the assessment of trustworthy
AI. We make the connection between the seven key requirements as defined by the
European Commission's AI high-level expert group and established procedures
from software engineering and raise questions for future work.
