Custom Model Explainability Dashboards with AWS SageMaker Clarify and QuickSight

Modern machine learning models—especially black-box models like gradient-boosted trees or deep neural networks—often prioritize predictive accuracy over interpretability. Yet in domains like healthcare, finance, criminal justice, and hiring, stakeholders must understand how a model reaches its conclusions to ensure that decisions are not only effective but also fair, accountable, and legally compliant.