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Information technology — Artificial intelligence — Objectives and approaches for explainability and interpretability of machine learning (ML) models and artificial intelligence (AI) systems
信息技术 人工智能 机器学习(ML)模型和人工智能(AI)系统的可解释性和可解释性的目标和方法
本文档描述了可用于实现利益相关者在机器学习(ML)模型和人工智能(AI)系统的行为、输出和结果方面的可解释性目标的途径和方法。利益相关者包括但不限于学术界、工业界、政策制定者和最终用户。它提供了关于所描述的途径和方法在人工智能系统的整个生命周期中对已确定目标的适用性的指导,如ISO/IEC 22989中所定义的。
This document describes approaches and methods that can be used to achieve explainability objectives of stakeholders with regard to machine learning (ML) models and artificial intelligence (AI) systems’ behaviours, outputs and results. Stakeholders include but are not limited to, academia, industry, policy makers and end users. It provides guidance concerning the applicability of the described approaches and methods to the identified objectives throughout the AI system’s life cycle, as defined in ISO/IEC 22989.