Issue link: http://cp.revolio.com/i/356
21 WWW.hPLUSMAgAzIne.CoM 21 it's arguable that, if we'd had strong ai instead of narrow ai involved, a crisis like this would never have come about. ben geortzel is the Ceo of AI companies novamente and biomind; a math PhD; writer; philosopher; musician; and all-around futurist maniac. with 30x leverage, you're effectively betting $3000. This means that if the instrument you're betting on goes up by 10%, you make $300 from your $10 investment. but if the instrument goes down by 10%, you lose $300, which may be more money than you have. Leveraged investment obviously has great potential for both risk and reward — so its effective usage hinges on the accurate assessment of risk. And risk assessment is one place where AI and other advanced software comes into play. The central aspect to consider, in understanding the strengths and limitations of advanced techniques for risk assessment, is context. The known mathematical and AI techniques for estimating the risk of complex fi nancial instruments (like credit default swaps, and various other exotic derivatives) all depend on certain contextual assumptions. They apply well in some contexts, and not others. At this stage, some human intelligence is required to fi gure out whether the assumptions of a given mathematical technique really apply in a certain real-world situation. So, if one is confronted with a real- world situation where it's unclear whether the assumptions of a certain mathematical technique really apply, it's a human decision whether to apply the technique or not. As a single example, Iceland's fi nancial situation was mathematically assessed to be stable, based on the assumption that (to simplify a little bit) a large number of depositors wouldn't decide to simultaneously withdraw a lot of their money. This assumption had never been violated in past situations that were judged as relevant. oops. And of course, these technical considerations synergize with human psychology in various ways. Suppose you work for a fi nancial institution and you're asked to assess the risk of some complex fi nancial instrument like a credit-default swap. Suppose the tools that you have at your disposal don't let you make a confi dent assessment? What are you going to do? Admit it, or just try your best, and hope the world doesn't fall too far short of the assumptions of the techniques you apply? bear in mind that the reward structure for high-level fi nancial employees tends to give big bonuses for decisions that lead to short- term gains. So if you play a role in a big win you may get rich but if you play a role in a big loss, the worst that happens is you'll need to fi nd another job. but consider a more interesting question: What happens in another decade or two, when the AI fi eld has progressed a bit and we have yet more intelligent software that is able to automatically assess whether the assumptions of a certain mathematical technique are applicable in a certain context? It may sound cavalier to say so (and the reader should understand that, as the owner of a small business, I've certainly not escaped the impact of the recent credit crunch), but my feeling as an AI expert is that these sorts of problems we've seen recently are merely hiccups on the path to super-effi cient fi nancial markets based on advanced AI. (on the other hand, it's hard to say exactly how long it will take for AI to achieve the needed understanding of context, to avoid this sort of "minor glitch.") once the transhuman future fully kicks in, it's quite possible that money will become obsolete. or maybe, as in Charles Stross's novel Accelerando, the next form of intelligence will emerge from complex AI-powered fi nancial instruments. but well before these radical possibilities come about, I'd suggest that a big difference will be made by the deployment of more strong-AI-ish fi nancial analysis systems with broad understanding of context. Whether further glitches occur along the path to this future is another question, of course and the best piece of advice I can offer in this regard is that the movers and the shakers of the fi nancial world should pay attention to the limitations — as well as the power — of current techniques, while also keeping an eye on the development of more advanced AI methods capable of overcoming these limitations.