I like the Kronecker quote, "Natural numbers were created by god, everything else is the work of men" (translated). I figure that (like programming) it turns out that putting our problems and solutions into precise reusable generalizable language helps us use and reuse them better, and that (like programming language evolution) we're always finding new ways to express problems precisely. Reusability of ideas and solutions is great, but sometimes the "language" gets in the way, whether that's a programming language or a particular shape of the formal expression of something.

You don’t really have to believe Wittgenstein; any logician will tell you that if your proof is not logically equivalent to 1=1 then it’s not a proof.

In my view mathematics builds tools that help solve problems in science.

More like 1 = 0 + 1.

Read about Lisp, the Computational Beauty of Nature, 64k Lisp from https://t3x.org and how all numbers can be composed of counting nested lists all down.

List of a single item:

     (cons '1 nil)

[ 1 | nil ]

List of three items:

    (cons '1 (cons 2 (cons 3 nil)))

    (list '1 '2 '3)

[ 1 | --> [ 2 | -> [ 3 | nil ]

A function is a list, it applies the operation over the rest of the items:

     (plus '1 '2 3') 

Which is like saying:

  (eval '(+ '1 '2 '3))

Eval will just apply the '+' operation to the rest of the list, recursively.

Whis is the the default for every list written in parentheses without the leading ' .

    (+ 1 (+ 2 3))

    (+ '1 '(+ '2 '3)) 

How arithmetic is made from 'nothing':

https://t3x.org/lisp64k/numbers.html

Table of contents:

https://t3x.org/lisp64k/toc.html

Logic, too:

https://t3x.org/lisp64k/logic.html

I do not think this parallel works, because I think you would struggle to find a discipline for which this is not the case. It is trivial to enumerate all the possible scientific or historical hypothesis, or all the possible building blueprints, or all the possible programs, or all the possible recipes, or legal arguments…

The fact that the domain of study is countable and computable is obvious because humans can’t really study uncountable or uncomputable things. The process of doing anything at all can always be thought of as narrowing down a large space, but this doesn’t provide more insight than the view that it’s building things up.

I don't think that's true. Often, to come up with a proof of a particular theorem of interest, it's necessary to invent a whole new branch of mathematics that is interesting in its own right e.g. Galois theory for finding roots of polynomials. If the proof is automated then it might not be decomposed in a way that makes some new theory apparent. That's not true of a simple calculation.

There are areas of mathematics where the standard proofs are very interesting and require insight, often new statements and definitions and theorems for their sake, but the theorems and definitions are banal. For an extreme example, consider Fermat's Last Theorem.

Note on the other hand that proving standard properties of many computer programs are frequently just tedious and should be automated.

First of all, I think your comment is against HN guidelines.

And I expect GP has actually a lot of experience in mathematics - there are exactly right and this is how professional mathematicians see math (at least most of them, including ones I interact with).

Material implication was not the default implication historically; it came as a useful hack by people who hoped that by enforcing it they could formalize the whole math and knowledge and have a sort of a "single source of truth" for any statement, and evaluate all statements purely syntactically. This proved to be futile as incompleteness theorem showed, and which material implication directly enabled by allowing self-referential non-sense as valid statements. There were many attempts to reconcile this with different logics but they all ended up weaker and unable to formalize all statements. We are now entering the next phase of this attempt, by using hugely complex reasoning function approximators as our "single source of truth" in the form of AI/LLMs.

I used to do a lot of proofs coming all the way from Peano arithmetics, successor operators and first-order tableaux method.