Machine learning can help somewhat in that you can modify your
  small assumptions about a number of potential outcomes, and let
  the software utilize the various "effects" (input data) to
  attempt to find pathways to the potential causes (the small
  assumptions). But I agree - the danger is in the assumptions.
  The expected results become the results, making a nice, neat,
  balanced, logical B-A... and potentially very wrong. So yes, the
  use of AI / machine learning _can_ be helpful in solving inverse
  problems but only if used very carefully.

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