Explainable AI (XAI)
AI systems designed to provide human-understandable justifications for their decisions and actions, enhancing transparency and trust.
Definition
Techniques and frameworks that generate clear, context-appropriate explanations—feature attributions, rule extractions, counterfactual scenarios—tailored to stakeholder needs (end users, regulators, developers). XAI governance includes standardizing explanation formats, validating explanation fidelity, and training users to interpret them properly.
Real-World Example
A credit-card company uses XAI by integrating LIME explanations into its fraud alerts: when the AI flags a transaction as suspicious, it shows the user that “Unusual merchant location” and “High transaction amount” were the top contributors, enabling faster verification and reducing false-positive escalations by 30%.
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