Model Reliability

Model reliability refers to the consistency and dependability of an AI model's predictions or outputs across different scenarios and datasets. It encompasses the model's ability to perform accurately under varying conditions and its robustness against errors or biases. Ensuring model reliability is crucial for building trust in AI systems and their decision-making processes.