Model Interpretability Trend 2026

Model interpretability reveals how machine learning models reach decisions, making their inner logic transparent and trustworthy. It helps data scientists debug predictions, regulators ensure fairness, and business leaders validate outcomes. By clarifying why a model says "yes" or "no," it builds confidence and accountability in AI systems across industries.