Learn more about fairness and bias mitigation concepts, terminology, and tools before you begin. Step through the process of checking and remediating bias in an interactive web demo that …

AI Fairness 360, an LF AI incubation project, is an extensible open source toolkit that can help users examine, report, and mitigate discrimination and bias in machine learning models …

The AI Fairness 360 interactive demo provides a gentle introduction to the concepts and capabilities. The tutorials and other notebooks offer a deeper, data scientist-oriented introduction.

This article introduces a new open-source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360), released under an Apache v2.0 license (https://github.com/ibm/aif360).

We have provided three sample datasets that you can use to explore bias checking and mitigation. Each dataset contains attributes that should be protected to avoid bias. Predict a …

The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models …

AI Fairness 360 - This extensible open-source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle.

Jul 30, 2024 · IBM’s AI Fairness 360 (AIF360) toolkit helps developers detect and mitigate bias in machine learning models. In this series, we will explore AIF360, its importance, and how to …

This extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle.

Getting Started Contributing to AIF360 Modules Algorithms Datasets Explainers Fairness Metrics scikit-learn -Compatible API Reference