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.
翻译:本报告从方法上思考了Z-检查$ 小型和半圆形的美元。Z-检查$ 小型和半圆形的美元是一个整体过程,用来评价AI生命周期不同阶段基于AI的技术的可信度,尤其侧重于通过拟订社会-技术设想方案查明和讨论伦理问题和紧张状况,用欧洲联盟高级别专家组(欧盟高专组)的一般准则来说明值得信赖的AI。本报告向大赦国际研究人员和执业工作者说明了欧盟关于可信赖的AI准则如何在实践中得到应用。我们分享了在进行一系列独立评估以评估AI系统在卫生保健方面可信度方面的经验教训。我们还就如何确保在AI系统整个生命周期内进行严格的可信赖的AI评估提出重要建议和实用建议。