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> I thought the reason we were encouraging people to go into STEM, and providing clever people with large salaries, was that mathematical results were of practi
by curt15 13d ago
> I thought the reason we were encouraging people to go into STEM, and providing clever people with large salaries, was that mathematical results were of practical value to the wider human race. In which case, it’s surely very good news that AI can get those results.
The impact of mathematics on other disciplines goes much further than specific results. Just as important, if not even more so, are the language and ways of thinking that typically come out of the process of establishing those results. Results without the accompanying conceptual understanding are about as useful as a mere oracle for math theorems.
Another point that seems to be frequently missed or mischaracterized is that mathematicians are not opposed to computational tools as a matter of principle and in fact do use them when they help their research. The current controversy is not about a hypothetical future where mathematicians have easy access to open-source, open-weight, auditable natural-language assistants to help them internalize a new result or search for counterexamples. It's primarily about the recent behavior of certain for-profit companies suddenly trying to disrupt mathematics by caricaturing it in the public eye as a game they can "solve" or "beat" for headlines and valuation.
- dash2 12d ago> The impact of mathematics on other disciplines goes much further than specific results. Just as important, if not even more so, are the language and ways of thinking that typically come out of the process of establishing those results What makes you think so? I can think of lots of specific results that helped e.g. economists - convex optimization or supermodularity, say - but I don’t think the broader way of thinking of mathematicians has had any input into economics for the past fifty years, and arguably nor should it - the discipline can think for itself. Similarly, sociologists can use linear regression, or geneticists can partition variance, without having to think like mathematicians.