  This report is a methodological reflection on
Z-Inspection$^{\small{\circledR}}$. Z-Inspection$^{\small{\circledR}}$ is a
holistic process used to evaluate the trustworthiness of AI-based technologies
at different stages of the AI lifecycle. It focuses, in particular, on the
identification and discussion of ethical issues and tensions through the
elaboration of socio-technical scenarios. It uses the general European Union's
High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI. This report
illustrates for both AI researchers and AI practitioners how the EU HLEG
guidelines for trustworthy AI can be applied in practice. We share the lessons
learned from conducting a series of independent assessments to evaluate the
trustworthiness of AI systems in healthcare. We also share key recommendations
and practical suggestions on how to ensure a rigorous trustworthy AI assessment
throughout the life-cycle of an AI system.
