Your question is Assess Model Robustness and Reliability. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You've shipped a model that looks strong on validation, but the team is not convinced it will hold up once it is used by real users. You are asked to explain how you would judge whether the model is reliable enough to trust.
How do you ensure that your machine learning models are robust and reliable?