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AI, matematica, insegnamento, e quelle cose lì

  Sono momenti di grande fermento, nella comunità matematica. L'annuncio che un'AI (Artificial Intelligence) avrebbe risolto un importante problema matematico relativo alle equazioni di Navier-Stokes ha scatenato fiumi di parole (cit.) e guerre di opinione sulle possibili ricadute di una tale ingerenza artificiale in ambiti tradizionalmente riservati al pensiero umano. Non voglio farla lunga, ci sono dozzine di testi pronti all'uso, per supportare o confutare qualsiasi opinione personale. Mi limito qui ad un modello banalissimo, ma altrettanto concreto: l'insegnamento. Anzi: l'insegnamento che da alcuni anni tengo al primo anno della laurea triennale in matematica. Ho studiato decine di libri, ne ho scritti tre, e umilmente sento di avere ormai una visione abbastanza concreta della materia che insegno. Quest'anno ho voluto fare un esperimento: ho selezionato qualche libro e qualche articolo particolarmente pertinente con il programma del mio corso, ho scelto una...

We are more or less the same

This post is a funny tribute to a sentence I heard from my friend Alessio Pomponio. We were PhD students at SISSA, and we were working together on some problem. One day, he said that most mathematicians always write the same paper, up to minor changes.

I won't spend much time claiming that this is false, that we always publish original and brand-new papers, etc etc. Indeed, sometimes I agree with Alessio. I'd rather comment on a feeling that, I'm sure, every (young) scientist is familiar with: it is rather easy to guess the content of a talk, once you know the speaker. By this I mean that Prof. Smith usually speaks about, say, the beauty of pets in medieval France; Prof. Doe speaks about the p-laplace operator; prof. Black speaks about the influence of the spanish flu on the development of commutative rings. Well, this is quite obvious, since contemporary science is so specialized that a chemist can't know enough mathematics to publish a mathematical paper (this is just an example). I heard that in a very recent book this problem of specialization is deeply discussed and criticized. I have not read that book, yet.

Of course, there are exceptions. I personally know a few mathematicians that publicly speak about different topics (though in the same general field of mathematics) and the audience is always fascinated by their deep understanding. And yet they are the exceptions.

In 2010 I was kindly invited to speak during a summer school, and a small group of colleagues was quietly discussing about the program. One of them sayd, more or less: Simone Secchi is from Italy, and therefore he will speak about Nonlinear Schroedinger Equations. Well, of course he/she was right! Sometimes I feel like I first find the solution and then I find the problem solved by my solution. If you browse the collection of scientific journals in a library, you will remark that this happens quite often. A lot of research papers are published because nothing better could be done by the authors. A friend of mine said: you work for some months on your problem, and you can't solve it. However. you can still publish all the computations you have done and promise to solve the problem in a future paper. Sad but true.

Ok, now I must go: I want to find a problem I can solve!

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