If studies like this one are taken as evidence of a statistical mind, then non-statistical behavior has to be taken as evidence of a non-statistical mind. Otherwise we have a non-falsifiable theory.
Experiment shows mind behaving statistically: "mind is statistical."
Experiment shows mind behaving non-statistically: "mind is statistical, but this scenario exceeds its capabilities."
> which suggests that they might be employing an existing system consciously to get the bugs out.
I should clarify -- I have nothing against the idea that our minds employ statistical methods. In fact I'm sure they must.
I'm opposed to taking that kernel of truth and pushing a reductionist understanding of something extremely complex (the brain).
Though... I think I agree that this weakens the claim sufficiently to not be a notable claim anymore.
The way to reconcile those claims is to say that many of our statistical/estimation patterns are very bad. Mostly, they were good once, but are completely unequipped to deal with the modern world. I know "we're optimized for the savannah" is a laugh-line at this point, but it doesn't seem absurd to claim that we're using statistical techniques that are easy but inflexible. Flawless Bayesian updating is basically unachievable, and a lot of our biases seem like once-useful heuristics that screw us a lot in the modern world.
Tetlock's Superforcasting seems like a good reference here: it's a study of people who are uncommonly good at estimating future probabilities. These are people who estimate near-future events to better than half a percent (as in, rounding from .1% to .5% reliably lowers their accuracy). Most of them claim to use a lot of numerical probability estimates, which suggests that they might be employing an existing system consciously to get the bugs out.
None of this means I buy the study, but I'm not willing to reject the hypothesis, either. Given that we're running on neural nets, I wouldn't be surprised if we deal in actually probabilities and are just exceedingly bad at it.