I genuinely don't see how that would be a reasonable assumption.
>Will humans do worse in base-3 than base-9?
Why not? If you haven't learnt base 3 but you have base 9 you'll do poorer on it.
>That, IMO, is an indicator that something different is going on.
Whether something different is going on is about as relevant as the question of whether submarines swim or plans fly or cars run.
>I.e., humans are deriving principles to work from rather than just pattern recognition.
Not really. Nearly all your brain does with sense data is predict what it should be and adjust your perception to fit. You can mold these predictions implicitly with your experiences but you're not deriving anything from first principles.
>This is probably a clunky example, but I'll try. Suppose an autonomous vehicle is trained to recognize that when a ball rolls into the street, it needs to slow down or stop because a child may not be far behind. A human can infer that seeing a kite blow into the street may signal the same response, even though they've never witnessed a kite blow into the street. The question is: can the autonomous vehicle infer the same? (This shouldn't be conflated with the general case of "see object obstructing the street and slow down/stop." The case I'm drawing here specifically adjusts the risk by the nature of the object being a child's toy. So, can the AV not only recognize the object as a kite but also adjust the risk accordingly?) I think one of the possible pitfalls is that we solve a more simple problem like image/pattern recognition and conflate it to a more difficult problem set being solved.
Casual reasoning ? all evidence points to LLMs being more than capable of that https://arxiv.org/abs/2305.00050
