A singular intelligence

There’s been some chatter in the popular IT press recently about the ‘Singularity’. Sounds like science fiction? Something out of a Star Trek movie, perhaps? ‘Entering the Singularity now, captain; phasers on stun.’ Well, it is science fiction, but it’s not that sort of singularity: there are no wormholes in sight. No, it’s much more like TheMatrix plot or the future context of The Terminator: superintelligent machines, created by humans, taking over the world. Artificialintelligence-wise, it’s a relatively old concept, first written about by Vernor Vinge in his 1981 novella True Names: in 1981 it was unthinkable, apparently, that a computational intelligence could sustain self-awareness in real time. The postulate behind the Singularity is that there is a point in the future when in silica intelligence has higher cognitive power than in corpo intelligence. From that point on, it’s all downhill for humans: the new society based on computational intelligence becomes too complex to understand. We quickly cease to be the dominant form of ‘life’ and, well, a while later a digital David Attenborough prompts adoring reviews from a digital press for its description of the human, i.e. lower, form of life. Unless there’s a mad genius out there – and in the readership there are perhaps many who fit the bill – able to thrust a computational intelligence able to dominate the world fully formed and ticking into it, such a takeover is either going to be (a) an emergent property or (b) criminally irresponsible knowledge engineering. Asimov had it right in his examination of three laws of robotics – scratch a superintelligence with the goal of protecting humans and you find a domineering parent who takes all dangerous toys away. Before the Singularity, however, there is a major role for responsible knowledge engineering. The papers published in this journal describe the forward steps you have made to, for instance, assist professionals in their duties, improve engineering, make prosthetics better, make society a better place to live in and, well, simply make a better life for many people. Long before any hard, controlling, singular computational intelligence, there is the knowledge engineering community – soft, beneficent, singular intelligences – self-aware in real time. This month’s papers are typical of these themes. Übeyli continues her investigation of electrocardiogram signal diagnostics, this time with support vector machines using two types of signal from the Physiobank database. The study shows that support vector machines trained on electrocardiogram power spectral densities obtained by eigenvector methods lead to accurate classifications. With uncanny timing, Kim, Lee, Oh and Kim present ‘An early warning system for financial crisis using a stock market instability index’, which measures the differences between current and past market conditions. The authors study comparative time series modelled by an asymptotic stationary autoregressive model using artificial neural networks. To see whether they say ‘I told you so’ you’ll have to read the paper. DOI: 10.1111/j.1468-0394.2009.00528.x Editorial___________________________