Explainable AI (XAI)
Explainable AI is a set of methods that make an AI system's outputs understandable to people, explaining why it reached a particular result.
What is Explainable AI (XAI)?
Explanations help users trust and challenge decisions and help developers find errors. Data protection law gives people rights to meaningful information about automated decisions, and the EU AI Act gives a right to an explanation of certain high-risk AI decisions.
How it works
Techniques include feature-importance methods such as SHAP, counterfactual explanations and using inherently interpretable models.
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