Explainable AI (XAI) refers to techniques and methods in artificial intelligence that aim to make the decisions and outputs of AI models understandable and interpretable by humans.
- Glossary > Letter: E
What does "Explainable AI (XAI)" mean?

Use Cases
Healthcare:
Explaining the reasons behind a medical diagnosis made by an AI model.
Finance:
Providing transparency in AI-driven decisions related to credit scoring or investment recommendations.
Legal:
Justifying AI recommendations in legal contexts, such as predicting case outcomes.

Importance
Transparency:
Builds trust by explaining how AI models arrive at decisions or recommendations.
Accountability:
Helps stakeholders understand and validate AI-driven decisions, reducing biases and errors.
Compliance:
Facilitates adherence to regulatory requirements that demand explanations for automated decisions.

Analogies
Explainable AI is like a detailed map that shows you the route taken by a navigation system. Instead of blindly following directions, you understand why certain turns are recommended, making you more confident in reaching your destination.
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