I don't think that holds up if you reduce to simple examples that are easily analyzed. If a billiard ball is pushed, it is the contact of the thing that pushed it which caused its motion, an equal and opposite reaction by Newton's 3rd law. If you did statistical analysis you'd discover that the chances of a ball moving depend very highly on whether the last ball to end up in a net was matching suit (colored or striped). But that's not a causal connection in the same sense. There's a causality in this level of physics that works perfectly well. It's not a coincidental combination of multiple spontaneous conditions that the ball moved -- it moved because it got pushed, and if it hadn't been pushed it wouldn't have moved.
that seems to be the whole core of those discussions - statistics, as a science, operates only with correlations and has nothing to do with causation. As long as one stays inside the domain of statistics, one can never say whether something is causation or not. Causation is subject matter of other sciences which study specific machinery of various causations.
I would suggest reading up on Judea Pearl’s Caudality, which is a complete treatment of how to integrate a useful notion of causality into statistical analysis. It can be done; it’s just not common practice.
If there is no human there to blame do we then say that the cause is a coincidental combination of multiple spontaneous conditions, all necessary but not sufficient by themselves.