What are some techniques for explainable AI?

What are some techniques for explainable AI?

There are several techniques for explainable AI, including LIME, SHAP, and model-agnostic methods.

Can you explain how LIME works?

LIME, or Local Interpretable Model-agnostic Explanations, works by approximating the model locally with an interpretable model.

What is SHAP and how is it different from LIME?

SHAP, or SHapley Additive exPlanations, provides a unified measure of feature importance based on cooperative game theory.

Are there any challenges in implementing these techniques?

Yes, challenges include computational cost, model complexity, and ensuring the explanations are meaningful to users.