I’m writing because I have just watched this Jon Ronson video. In it, Ronson tracks down a trio of academics who have created a piece of computer code that samples and mimics some of his stylings, and then tweets nonsense as Jon_Ronson.
Ronson is incensed by this – rightly or wrongly – but his exploration of their motives ends with them revealing themselves as making a postmodern, or perhaps post-ironic (who the hell knows or cares?) statement about the world being in thrall to the decisions of robots.
The video is interesting. I like these people (I don’t think Ronson does). I like the way they sit in a row on the sofa and absorb his exasperation. And what’s more, they have a point.
In May 2008, I met a very senior mathematician who told me we might be about to encounter a massive financial meltdown. The problem, he said, was that “about 80 per cent of all moves made in financial transactions are the results of decisions taken by black boxes – the dealers just do not know what they are doing any more.”
I wrote the story for New Scientist, and – for very boring reasons to do with timing and news pegs – it got spiked. Six months later, we were in the global financial crisis. At least I can say it’s not my fault.
The black box models used in financial trading are not some value-free piece of mathematical truth. According to Professor Yuri Manin, now retired, but director of the Max Planck Institute for Mathematics in Bonn, they stretch the logical truths of mathematics to breaking point.
The accuracy of the computers’ analyses of the markets was being taken on trust, he said – especially when dealing with “virtual” commodities such as hedge funds and derivatives.
In scientific disciplines, such as theoretical physics, the performance of such models would be judged on whether they reflect the real-world behaviour of the process being modelled. But the closed nature of the models used for virtual transactions, where nothing is actually bought or sold, means their accuracy is uncheckable: there is no “real world” aspect to the process.
In such systems, the values of commodities can flip wildly, Manin said, growing exponentially or collapsing at the stroke of a key. Because the traders have no idea what the parameters of their models are, they are powerless to stop this happening.
It’s the point that Dan O’Hara, a lecturer in literature at Cologne University (and part-time Ronson-baiter), makes in the video. “I want to understand those algorithms, and furthermore I want to help other people understand those algorithms,” he says. “I want to make people aware of these… bits of code that are having really important effects on our lives.”
Sadly, if no one listened to a professor of mathematics, who will listen to a lecturer in literature? Really, though, it doesn’t matter: as long as it remains acceptable for traders to gamble away other people’s pensions in games whose rules they don’t even understand, someone’s got to keep shouting. Sorry, Jon. But you’ll probably get over it.
Michael Brooks’s “Free Radicals: the Secret Anarchy of Science” is published by Profile Books (£12.99)
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