Creativity, analysed: stats show Beethoven's influence
It's Beethoven's 250th birthday, and so we’re looking at how maths and computing can analyse his music. There’s no doubt that he has inspired generations of musicians; despite Chuck Berry telling him “to roll over”, you can hear his flourishes in the samples of the rapper Nas, and subjectively, his style in the instrumentals of bands like Yes and Pink Floyd. But objective statistical analyses can tell us even more, and suggest that he may - for a century or more - have been the most influential composer around. Phil Sansom heard from statistical physicist Juyong Park, who’s been mapping out the similarities and differences between the notes of different pieces of music, to try and pin down an abstract concept into maths…
Juyong - We're trying to find out who's the most creative composer. And of course in order to be creative, you actually have to have new elements that you introduce that have never been used before. But one of the problems with using only novelty as a measure of creativity is: it's actually pretty easy to try something new, just find something that hasn't been used before. So we actually have two measures, or two elements, of creativity. One is novelty, and the other is influence: how much you inspired others who have come after you.
Phil - This is sort of your model of creativity, then, is: how much new stuff you tried, and how much people liked it?
Juyong - Yes, you can say that. Of course, this doesn't really cover everything about creativity, but I think these two are very essential ones when we talk about how to model or how to measure creativity. We compared compositions by nineteen composers, all the way from the earlier ones from the Baroque era, like Haydn and Bach, to the late romantic ones like Rachmaninoff. And what we discovered was: Beethoven was the most influential composer on the evolution of music after his time.
Phil - How can you tell?
Juyong - We're actually looking at not just one note at a time, but one note and the one that follows it. Let's say you just play do re mi fa, then we're looking at "do-re", so one transition; "re-mi", one transition; and "mi-fa", one transition. And those transitions actually are like a fingerprint of that composer, and depending on how common those elements are, we can actually determine how similar the composers sound.
Phil - Were the same people both really novel and really influential, or who was what and who was the other?
Juyong - Novelty and influence don't necessarily correlate perfectly. Beethoven is actually not the most novel, but the new things that he actually tried were actually widely accepted by the others have followed him. And his influence remains number one for many decades after his death.
Phil - How much of creativity do you think that you've covered in this analysis? Because obviously it feels instinctively like it's quite a human concept that you can't translate into a computer.
Juyong - Yeah, words like 'creativity' actually bring up a lot of thoughts in people's minds and a lot of ideas, because it means a lot of things. Some people say, "okay, that is what makes our civilisation evolve". A good analogy would be energy. To me when I hear the word energy, I immediately think about, you know, half mass times velocity squared, for instance; but to many people energy actually does still mean 'life force', like, "hey, he's got a lot of energy". Because we were able to come up with a physical theory of energy, we were able to build those great things that actually help our civilisation. And I think creativity is in a very similar stage, where we're not trying to restrict the meaning of creativity, but actually we're trying to come up with a self-consistent useful framework for measuring creativity. And hopefully that will help us come up with new science and new technologies that actually help us be more creative.