AI engineering glossary · AI ethics law product
What is XAI (Explainable AI)?
Explainable AI (also called XAI): The set of methods and design practices that let people understand why an AI system produced a particular output. It supports debugging, trust, regulatory compliance and appeals by affected people, and ranges from simple interpretable models to techniques that explain black-box predictions after the fact.
Explainable AI: an example
A bank shows a rejected applicant that 'low credit history length and high existing debt' were the main reasons for the decision.
Related terms
More AI ethics law product terms
- Explicit feedback
- Fair use
- Fairlearn
- Fairness impossibility theorem
- Fairness metric
- Fairness through unawareness
- Fallback behavior
- Federated learning
Where you learn it
Explainable AI is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.