Skip to main content

The Creativity Code - Marcus du Sautoy *****

At first glance this might just be another 'What AI is good at and not so good at' title. And in a way, it is. But, wow, what a brilliant book! Marcus du Sautoy takes us on a tour of what artificial intelligence has achieved (and possibly can in the future achieve) in a range of fields from his own of mathematics, through game playing, music, art and more.

After a little discussion of what creativity is, we start off with the now very familiar story of DeepMind's AlphaGo and its astonishing ability to take on the hugely challenging game of Go. Even though I've read about this many times before, du Sautoy, as a Go player and mathematician, gives a real feel for why this was such a triumph - and so shocking. Not surprisingly he is also wonderful on what mathematicians actually do, how computers have helped them to date and how they have the potential to do far more in the future. After all, mathematics is by far the closest science to game playing, as it has strict rules established beforehand, where with most other sciences we really don't know what the rules are and have to try to work them out as we go along.

My only slight moan about the mathematical aspect of the content is that there are so many references to the mathematical discipline of symmetry and group theory that it would have been nice to have had an a little backgrounder on these to put what is being talked about into context. Having said that, though, given the inevitably slightly scary aspect of AI potentially taking over some of the roles of mathematicians, du Sautoy gives us an excellently balanced and fair assessment of how some mathematical AI projects really do very little to advance the field, while others really do eat into the mathematician's work.

Perhaps my favourite chapters of all were those on music. There is, of course, a distinctly algorithmic feel to composition theory, and du Sautoy really makes his exploration of this delightful. I'm familiar with a lot of Bach's work, but not The Musical Offering - which du Sautoy argues well was a particularly algorithmic feat. Apparently, Bach was asked if he could improvise a fugue from a very tricky 'tune' dreamed up as a challenge by Frederick the Great - not only did Bach manage a three part version on the spot, he went on to compose 11 variants using all sorts of remarkable modifications. A particular bonus was being able to summon up The Musical Offering on Spotify (itself an algorithmic marvel on a good day) and listen to it as I read the book.

I wasn't quite as taken with the sections on art. With modern art it's arguable that it's pretty much impossible to define what good art is (du Sautoy points out how difficult it is to fake a Jackson Pollack if you know technically what to look for... but I still find his paintings a visual mess that I wouldn't hang in the toilet, so I don't really care that it's hard to reproduce). With such an arbitrary borderline between creativity and randomness, it's hard to worry too much about what an AI can do - it all seems to be a matter of fashion anyway. These chapters were still interesting, just less significant for me. My interest revived, though, when he got onto approaches to writing, even if there was nothing there that seemed likely to displace human work any time soon.

All in all, a great crossover title between computing, mathematics and creativity, presented with du Sautoy's usual charm and clarity. Excellent.
Hardback 

Kindle 
Using these links earns us commission at no cost to you
Review by Brian Clegg

Comments

Popular posts from this blog

It's On You - Nick Chater and George Loewenstein *****

Going on the cover you might think this was a political polemic - and admittedly there's an element of that - but the reason it's so good is quite different. It shows how behavioural economics and social psychology have led us astray by putting the focus way too much on individuals. A particular target is the concept of nudges which (as described in Brainjacking ) have been hugely over-rated. But overall the key problem ties to another psychological concept: framing. Huge kudos to both Nick Chater and George Loewenstein - a behavioural scientist and an economics and psychology professor - for having the guts to take on the flaws in their own earlier work and that of colleagues, because they make clear just how limited and potentially dangerous is the belief that individuals changing their behaviour can solve large-scale problems. The main thesis of the book is that there are two ways to approach the major problems we face - an 'i-frame' where we focus on the individual ...

Introducing Artificial Intelligence – Henry Brighton & Howard Selina ****

It is almost impossible to rate these relentlessly hip books – they are pure marmite*. The huge  Introducing  … series (a vast range of books covering everything from Quantum Theory to Islam), previously known as …  for Beginners , puts across the message in a style that owes as much to Terry Gilliam and pop art as it does to popular science. Pretty well every page features large graphics with speech bubbles that are supposed to emphasise the point. Funnily,  Introducing Artificial Intelligence  is both a good and bad example of the series. Let’s get the bad bits out of the way first. The illustrators of these books are very variable, and I didn’t particularly like the pictures here. They did add something – the illustrations in these books always have a lot of information content, rather than being window dressing – but they seemed more detached from the text and rather lacking in the oomph the best versions have. The other real problem is that...

The Laws of Thought - Tom Griffiths *****

In giving us a history of attempts to explain our thinking abilities, Tom Griffiths demonstrates an excellent ability to pitch information just right for the informed general reader.  We begin with Aristotelian logic and the way Boole and others transformed it into a kind of arithmetic before a first introduction of computing and theories of language. Griffiths covers a surprising amount of ground - we don't just get, for instance, the obvious figures of Turing, von Neumann and Shannon, but the interaction between the computing pioneers and those concerned with trying to understand the way we think - for example in the work of Jerome Bruner, of whom I confess I'd never heard.  This would prove to be the case with a whole host of people who have made interesting contributions to the understanding of human thought processes. Sometimes their theories were contradictory - this isn't an easy field to successfully observe - but always they were interesting. But for me, at least, ...