responsible-ai-toolbox

Overview of responsible-ai-toolbox

What it is

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. It is developed by Microsoft and is available as an open-source project under the MIT license.

Key features

• Responsible AI dashboard: a single pane of glass integrating error analysis, fairness assessment, model interpretability, counterfactual analysis, causal analysis, and data balance.
• Error Analysis dashboard: identifies model errors and discovers cohorts of data for which the model underperforms.
• Interpretability dashboard: powered by InterpretML, helps understand model predictions.
• Fairness dashboard: powered by Fairlearn, helps understand model's fairness issues using group-fairness metrics across sensitive features and cohorts.
• GenBit library: helps measure gender bias in NLP datasets.
• Mitigations Library: offers mitigation techniques for improving model performance and data balance analysis.

Use cases

Model debugging and decision-making workflows, such as identifying model errors and diagnosing them through data exploration, assessing fairness issues, performing counterfactual analysis to understand individual prediction changes, and exploring causal relationships for data-driven decisions.

Getting started

pip install raiwidgetsIf running in Jupyter, restart the kernel after installing.

License and pricing

Licensed under the MIT license. The project is open source and free to use.

Based on the project's public README and repository metadata.