interviewer has no idea what's going on lol

So how would you explain a black box model's decision to a compliance team? Question: How to explain a black box model's decision to a compliance team? Answer: A black box model is one where the internal workings are not easily interpretable or transparent, such as complex machine learning models. To explain its decision to a compliance team, focus on interpretable outputs and impact rather than technical details. Use model-agnostic explanation tools like LIME or SHAP that highlight which features influenced the decision most. Provide clear, non-technical summaries of the decision rationale, emphasizing fairness, consistency, and compliance with regulations. Illustrate with examples or scenarios showing how the model behaves in typical cases. Highlight any validation and testing done to ensure the model meets compliance standards. Emphasize ongoing monitoring and audit processes to detect and address any biases or errors. This approach bridges the gap between complex technical models and the compliance biases or errors. So how would you explain a black box model's decision to a compliance team? I would focus on interpretable outputs and impact rather than technical details.