How to Assess Trustworthy AI in Practice
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Abstract (arXiv)
This report is a methodological reflection on Z-Inspection^smallcircledR. Z-Inspection^smallcircledR 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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jun 2022.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 1.
4 papers.
- 2023Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulationcited by 61
- 2024Auditing of AI: Legal, Ethical and Technical Approachescited by 10
- 2024Explainable AI needs formalizationcited by 5
- 2026Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Studycited by 0
- 2026Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study13 Sep 2026
- 2024Explainable AI needs formalization22 Sep 2024
- 2024Auditing of AI: Legal, Ethical and Technical Approaches7 Jul 2024
- 2023Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation2 May 2023