Aequitas vs AI Explainability 360
A side-by-side comparison of two Explainability and Fairness AI agents — to help you pick the right one.
Aequitas
Aequitas is an open-source bias audit toolkit designed to evaluate machine learning models for discrimination and fairness. It provides statistical metrics and visualizations to assess disparities in model outcomes across demographic groups. The tool helps users identify and mitigate bias in predictive risk-assessment systems.
AI Explainability 360
AI Explainability 360 is an open-source toolkit that provides a comprehensive set of algorithms and metrics to interpret and explain machine learning model decisions. It supports multiple explanation techniques, including feature importance, rule-based explanations, and contrastive explanations, to improve transparency in AI systems.
| Aequitas | AI Explainability 360 | |
|---|---|---|
| Category | Explainability and Fairness | Explainability and Fairness |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Open Source |
Aequitas: what it solves
It detects and quantifies bias in machine learning models, enabling developers and policymakers to address unfair disparities in algorithmic decision-making.
AI Explainability 360: what it solves
It helps users understand and justify the predictions of machine learning models, reducing opacity and increasing trust in AI decision-making.