Robustness in predictive models is crucial, especially for self-learning systems that operate in real-time. As these models can evolve and potentially behave unpredictably, it's essential to monitor their performance closely. Rapid drift in model behavior can signal issues that need to be flagged to a governance body, ensuring that any anomalies are addressed promptly.
