Explainable AI
A field of artificial intelligence focused on developing tools and techniques that allow humans to understand exactly how and why a model makes its predictions.
Think of It Like This
Like having an interpreter translate a highly technical medical diagnosis into simple language so the patient can fully understand the reasoning behind it.
Explainable AI (XAI) seeks to break open the black-box nature of deep learning algorithms. It encompasses methods like SHAP, LIME, and Integrated Gradients that assign importance scores to input features. By providing transparency, XAI helps developers debug models, ensure fairness, and comply with strict regulatory requirements regarding algorithmic decisions.