Explainable AI: Making Machine Learning Decisions Transparent with SHAP and LIME
As machine learning models increasingly influence decisions affecting people’s lives—loan approvals, medical diagnoses, criminal justice recommendations, hiring decisions—the demand for explainability has grown urgent. Black-box models that produce predictions without rationale raise concerns about fairness, accountability, and trust. Explainable AI (XAI) addresses these concerns by providing methods to understand how models reach their conclusions. This