> It also aligns quite well with Kahneman's System 1 - System 2 distinction, where the symbolic System 2 is reserved for situations that most strongly require such computation.
It would be very, very remarkable if that were the case. Our brains don't work like Turing Machines. We're finite. Our symbolic reasoning is different. What Kahneman dubs System 2 decisions also is not necessarily related to symbolic reasoning, certainly not of the type mentioned in the paper.
I think you need to pin down what you mean by "mind" there. The raw neurons of (say) the human vision system seem to work by learning useful features, combining them in later layers etc. - analogous to how an ANN might be trained. i.e. it's not symbolic at its core.
In contrast, the creation of a new scientific insight (e.g. Newton's law of gravity), seems to use a more symbolic search method, which is thought to be built on top of the raw neural processes. An analogy might be the use of GPT-3 to "solve" various language problems.
Of course, these are just guesses based on our current research - no-one really has any idea exactly how the brain works.
Does this mean that minds don't ever naturally build symbolic models of the world, or rather just that they try to minimize the computationally intensive (and now NP-hard) task of uncovering a symbolic model? I'd definitely lean toward the latter (ironically due to my intuition).
It also aligns quite well with Kahneman's System 1 - System 2 distinction, where the symbolic System 2 is reserved for situations that most strongly require such computation.