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How to Assess Trustworthy AI in Practice
10
Zitationen
20
Autoren
2022
Jahr
Abstract
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.
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Autoren
- Roberto V. Zicari
- Julia Amann
- Frédérick Bruneault
- Megan Coffee
- Boris Düdder
- Eleanore Hickman
- Alessio Gallucci
- Thomas Krendl Gilbert
- Thilo Hagendorff
- Irmhild van Halem
- Elisabeth Hildt
- Sune Holm
- Georgios Kararigas
- Pedro Kringen
- Vince I. Madai
- Emilie Wiinblad Mathez
- Jesmin Jahan Tithi
- Dennis Vetter
- Magnus Westerlund
- Renee Wurth