Questão 39 — Amazon AIF-C01 Simulado | AWS Certified AI Practitioner Questões e Respostas

Explanation: The correct answer is A because model interpretability refers to the ability to understand and explain how an ML model arrives at a particular prediction or decision. From AWS documentation: "Model interpretability is the degree to which a human can understand the cause of a decision made by a machine learning model. Interpretability techniques help explain which features influenced a prediction and how much they contributed." This is essential in areas like financial services, healthcare, or compliance-heavy industries, where decision transparency is critical. Explanation of other options: B . Model training refers to the process of teaching a model from data and doesn't explain how predictions are made. C . Model interoperability refers to the ability of systems or models to work across different platforms or environments. D . Model performance refers to how accurate or effective the model is but doesn't relate to the explanation of its decisions. Referenced AWS AI/ML Documents and Study Guides: Amazon SageMaker Clarify Documentation Explainability and Bias Detection AWS Machine Learning Specialty Study Guide Responsible AI and Model Explainability