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InInterpretability4
Interpretability
Understanding the black box
validationRow 4: Emergingadvanced4 hoursRequires: Lg
Overview
Interpretability research aims to understand how AI models make decisions and what they've learned internally.
What is it?
Techniques for understanding what happens inside AI models.
Why it matters
Trust requires understanding. Interpretability helps us verify AI is learning the right things and making decisions for the right reasons.
How it works
Analyze attention patterns, probe internal representations, study how specific inputs affect outputs, and map concepts to neurons.
Real-World Examples
Attention Visualization
Seeing what the model focuses on
Feature Attribution
Which inputs influenced the output
Mechanistic Interpretability
Reverse-engineering model circuits
Tools & Libraries
TransformerLenslibrary
Mechanistic interpretability
Captumlibrary
Model interpretability for PyTorch
SHAPlibrary
Feature importance explanations