[user_235711]

Insofar as the algorithms in the machine are adjusted to overcome past inaccuracies (whether they are adjusted by the machine itself or by the machine programmers) we are merely witnessing a new tool for use when developing scientific theories.

Whether or not we understand everything that the ML systems are doing, we can still observe if events corroborate their predictions, and will be forced to debug or reprogram them if they are not learning well.

Also, I am guessing that many if not most of these ML systems do not start learning from zero, but have some pre-ML naming, sorting, and classification scheme baked into their algorithms. If that is the case, increasing the accuracy of the scheme - refining the concepts of the theory - should only increase the accuracy of the systems' predictions.