It's particularly challenging in areas where as a human, you actually can't evaluate the model output. For example, if the model is just evaluating the classifying images, that's fine for humans to post-process and check. But if you're relying on machine learning to do something a bit superhuman, maybe make some prediction, well, the whole point is that you as a human shouldn't really be overriding the model. And so there you really want the gold standard model not a cheaper approximation.

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