[Thoughts on what to do if there is an ontological mismatch between one’s thinking and a tool]
When I saw Jacob present a version of the OP in person, the discussion focused on cases where the correct response is to use a different tool, ideally one that matches the natural ontology of ones thinking. E.g. when using a whiteboard rather than a Google doc to express thoughts most naturally expressed as a mind map.
But I think it’s important that there are other cases where it can actually beneficial to ‘learn how to think in a different ontology’. I think this is quite common in pure maths, but also shows up in more everyday situations: e.g. initially I found it quite counterintuitive to use, say, Emacs org mode or LaTeX, but after I had payed the fixed cost of adapting to the ontologies imposed by them I actually think that it made me more efficient at some tasks.
Similarly, I think it’s useful to be able to translate between different ontologies. To learn this, it can be useful to deliberately expose oneself to ontologies that seem unnatural/bad/cumbersome initially.
As a fellow former mathematician, I share your sense that “mathematics as poetry” seems like the most likely outcome, at least for pure maths and barring more fundamental AI-driven changes to the human condition (e.g., extinction, or humans being replaced by very different kinds of minds).
Some of your discussion reminded me of Field Medalist Bill Thurston’s 1994 note “On Proof and Progress in Mathematics”:
Similarly, Thurston wrote on MathOverflow:
To be clear, I do think that AI comes with bigger challenges for, and will have bigger impacts on, the maths community than the kind of ‘automatic computation’ or ‘computer code’ Thurston mentions in these quotes because LLMs can do a much wider range of maths tasks, including communicating about maths in many of the ways human mathematicians do, and so their use likely won’t be limited to narrow use cases outside an exclusively human-driven core activity of generating and transmitting ‘understanding’ to each other. And so in particular I agree with the broad picture you outline where AI use is a pervasive feature of a “mathematics as poetry” world.