How do you prioritize which models or parts of a model to make explainable in a large-scale AI system?

Instruction: Describe your approach to identifying and prioritizing explainability efforts within complex AI systems.

Context: This question explores the candidate's strategic thinking in applying explainability efforts efficiently across large-scale AI deployments.

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The way I'd approach it in an interview is this: I prioritize explainability based on risk, decision impact, and operational dependence. If a model affects safety, money, rights, or high-friction user outcomes, it moves to the front of the line. The same goes for components that are...

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