It’s interesting to compare the first two points: novel math derivations and remixing old artwork can seem like disparate paths to greater understanding. Yet often, ‘novel’ math derivations are more like the artistic remixes, or pastiches. Gian-Carlo Rota, MIT math & philosophy prof, referenced two ways to come across as genius: either keep a bag of tricks and apply them to new problems, or keep a bag of problems and apply them to new tricks.
Eliezer’s discussion about his work was interesting too, I hadn’t seen that before. Rota also spoke of scientific popularization as your mentioned, saying you’re more likely to be remembered for expository work than for original contributions:
Allow me to digress with a personal reminiscence. I sometimes publish in a branch of philosophy called phenomenology. After publishing my first paper in this subject, I felt deeply hurt when, at a meeting of the Society for Phenomenology and Existential Philosophy, I was rudely told in no uncertain terms that everything I wrote in my paper was well known. This scenario occurred more than once, and I was eventually forced to reconsider my publishing standards in phenomenology.
It so happens that the fundamental treatises of phenomenology are written in thick, heavy philosophical German. Tradition demands that no examples ever be given of what one is talking about. One day I decided, not without serious misgivings, to publish a paper that was essentially an updating of some paragraphs from a book by Edmund Husserl, with a few examples added. While I was waiting for the worst at the next meeting of the Society for Phenomenology and Existential Philosophy, a prominent phenomenologist rushed towards me with a smile on his face. He was full of praise for my paper, and he strongly encouraged me to further develop the novel and original ideas presented in it.
Here’s the source from which I found Rota’s speech—and the fact that I wouldn’t have known of those ideas otherwise—validates the usefulness of repackaging good ideas again! And you’re right that choosing what to curate is a form of originality; choosing the best out of several AI text generations is you applying your taste and sense of relevance, or in other words, bits of selection pressure. So both human contribution and human selectivity can indicate originality. But the same could go for sampling past human work too, in art, math, or otherwise.
If strong ideas that face friction come out stronger, then why would you need to insulate them behind locked doors from external stimuli? Shouldn’t they easily vanquish external stimuli and validate themselves? Unless the point is to recognize the strength of timeless ideas. But even if an idea worked well the first 999 times, it doesn’t mean it will also do so the 1,000th time—you shouldn’t strive to crystallize tried-and-true ideas into static heuristical husks: Heuristics that almost always work can still critically fail, with black swan moments.
‘Always run faster’ can make you stumble down a hill and break your ankle. ‘Always deploy capital prudently’ can make your business miss out on bold plays, as ChristianKl commented. Since even your best ideas are fallible, the goal should be to discern which part of the idea was wheat, and which was chaff. “Run fast, but not if it’ll overexert yourself, here’s an explanation to assess when that’s about to happen.” “Deploy capital prudently, but make allowance for calculated risks, and here’s an explanation for how to assess those opportunities.”
These distinctions require active criticism ‘in the arena,’ even if—especially if, rather—it’s at the risk of swaying under new information in the ephemeral territory of the immediate. It requires a willingness to suspend an idea’s universality if a better explanation carves an edge case where it doesn’t apply, or even subverts the whole paradigm (slow and steady wins the race!). But that only happens if you’re willing to part with even your best ideas, instead of jailing them behind thick walls and padlocks—which insulates them, yes, in an echochamber.