Does correlation vs causation have any meaning in Machine Learning?

In traditional statistics, it is hammered into us that correlation DOES NOT mean causation.

But I feel like that doesn't apply in something like a Neural Network seeing as we don't care if the input variable is causing the output variable or is merely correlated with it.

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