Interpretability

Browse all content tagged with Interpretability

Glossary

Explainability

AI Explainability refers to the ability to understand and interpret the decisions and predictions made by artificial intelligence systems. As AI models become more complex, explainability ensures transparency, trust, regulatory compliance, bias mitigation, and model optimization through techniques like LIME and SHAP.

AI Explainability Transparency +4
• 5 min read
Glossary

XAI (Explainable AI)

Explainable AI (XAI) is a suite of methods and processes designed to make the outputs of AI models understandable to humans, fostering transparency, interpretability, and accountability in complex machine learning systems.

AI Explainability Transparency +3
• 6 min read

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