These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
explainX/explainx
explainX/explainx is a Python toolkit for generating explanations and debugging insights for black-box machine learning models. It produces explanation outputs for model predictions or behavior, supporting the Explainability and Transparency trustworthiness objectives. Practitioners such as ML developers, model auditors, and researchers can use it to better understand how a model is making decisions and to identify issues affecting model reliability.
Auto-discovered on 2026-09-03 by OECD Catalogue Automation
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