The vast majority of people, even if they worked for decades in accounting, can't learn to do numeric computation as fast and accurately as a mechanical calculator does.

The problems aren't even remotely comparable. A human is solving a much more complex problem - the inputs are in the form of visual or auditory signals which first need to be recognized and processed into symbolic numbers. The actual computation step is trivial and probably only involves a handful or even a single cycle.

I admit that I somewhat let you walk into this trap by not mentioning it earlier ... this example shows that the brain can learn near optimal (in terms of circuit depth or cycles) solutions for these simple arithmetic problems. The main limitation is that the brain's hardware is strongly suited to approximate inference problems, and not exact solutions, so any exact operators require memoization. This is actually a good thing, and any practical AGI will need to have a similar prior.