This report is a methodological reflection on Z-Inspection®. Z-Inspection® 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.
@article{arxiv.2206.09887,
title = {How to Assess Trustworthy AI in Practice},
author = {Roberto V. Zicari and Julia Amann and Frédérick Bruneault and Megan Coffee and Boris Düdder and Eleanore Hickman and Alessio Gallucci and Thomas Krendl Gilbert and Thilo Hagendorff and Irmhild van Halem and Elisabeth Hildt and Sune Holm and Georgios Kararigas and Pedro Kringen and Vince I. Madai and Emilie Wiinblad Mathez and Jesmin Jahan Tithi and Dennis Vetter and Magnus Westerlund and Renee Wurth},
journal= {arXiv preprint arXiv:2206.09887},
year = {2024}
}
Comments
On behalf of the Z-Inspection$^{\small{\circledR}}$ initiative (2022)