Is there no intrinsic nondeterminism in any causal Bayesian network relevant to social science?
I doubt it
The intrinsic quantum nondeterminism probably mostly gets washed away due to enormous averages. Of course chaos theory means that it eventually gets relevant, but by the time it gets to relevant magnitudes, the standard epistemic uncertainty has already overwhelmed the picture. So I think in comparison to standard epistemic uncertainty, any intrinsic nondeterminism will be negligible in social science.
More importantly, the thing you can do with counterfactual models that you can’t do with “ordinary” causal Bayesian networks is you can condition on the results of an action and then change the action (called “abduction”; this is why it would be helpful to have a better explanation of the difference between the two!). This will usually leave a bunch of uncertainty about stuff, which may or may not be intrinsic.
I know and agree.
Do we need determinism to define counterfactuals?
No
[...]
You definitely don’t need determinism to do abduction, and I submit that our attitude towards the question of whether the leftover uncertainty is “intrinsic” should often be the same as our usual attitude toward this question: who cares?
I sort of have some problems with/objections to counterfactuals in the presence of intrinsic nondeterminism. E.g.YX=X might not be equal to Y (and per chaos theory, would under many cicumstances never be equal or even particularly close). But since intrinsic nondeterminism isn’t relevant for social science anyway, I just skipped past them.
The intrinsic quantum nondeterminism probably mostly gets washed away due to enormous averages. Of course chaos theory means that it eventually gets relevant, but by the time it gets to relevant magnitudes, the standard epistemic uncertainty has already overwhelmed the picture. So I think in comparison to standard epistemic uncertainty, any intrinsic nondeterminism will be negligible in social science.
I know and agree.
I sort of have some problems with/objections to counterfactuals in the presence of intrinsic nondeterminism. E.g.YX=X might not be equal to Y (and per chaos theory, would under many cicumstances never be equal or even particularly close). But since intrinsic nondeterminism isn’t relevant for social science anyway, I just skipped past them.
Does chaos theory apply at the micro-scale (quantum phenomena) or at the macro-scale?
Chaos theory applies at all scales. It turns micro-scale uncertainty into macro-scale uncertainty at an exponential rate.