Math concepts can often be derived in a myriad different ways, and many derivations and explanations shed new lights on the concept and deepen your understanding.
In art, a popular saying is that everything is a remix, so complaining about lack of originality, or that A is just B in a different guise, seems a bit besides the point.
Popularisation of science is, to a significant extent, also about repackaging existing knowledge in a more comprehensible structure with better imagery and metaphors. And this is an immensely valuable endeavour.
Richard Dawkins’ books on biology and evolution come to mind.
As does a significant chunk of the original LW Sequences. See this Yudkowsky comment on which fraction of the ideas in the LW Sequences he considers to be wholly original rather than re-explanation of existing ideas (15%), and what that implies (namely that academic papers often have a similar fraction of original ideas, and that furthermore deciding what to curate is also a kind of originality).
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.
Other examples:
Math concepts can often be derived in a myriad different ways, and many derivations and explanations shed new lights on the concept and deepen your understanding.
In art, a popular saying is that everything is a remix, so complaining about lack of originality, or that A is just B in a different guise, seems a bit besides the point.
Popularisation of science is, to a significant extent, also about repackaging existing knowledge in a more comprehensible structure with better imagery and metaphors. And this is an immensely valuable endeavour.
Richard Dawkins’ books on biology and evolution come to mind.
As does a significant chunk of the original LW Sequences. See this Yudkowsky comment on which fraction of the ideas in the LW Sequences he considers to be wholly original rather than re-explanation of existing ideas (15%), and what that implies (namely that academic papers often have a similar fraction of original ideas, and that furthermore deciding what to curate is also a kind of originality).
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:
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.