Computer Models Find Patterns In Asymmetric Threats

The Narrative Fallacy brings us a story about a project by University of Alabama researchers to develop a database capable of anticipating targets for future guerrilla attacks. Quoting Space War: "Adversaries the US currently faces in Iraq rely on surprise and apparent randomness to compensate for their lack of organization, technology, and firepower. 'One way to combat these attacks is to identify trends in the attackers' methods, then use those trends to predict their future actions,' said UA-Huntsville researcher Wes Colley. 'Some trends from these attacks show important day-to-day correlations. If we can draw inferences from those correlations, then we may be able to save lives by heightening awareness of possible events or changing the allocation of our security assets to provide more protection.' Researchers reviewed the behavior signatures of terrorists on 12,000 attacks between 2003 and mid-2007 to calculate relative probabilities of future attacks on various target types."

Comments

Re:Terrible idea

[caffeinemessiah]

The attacks are surprises and random, how are they going to try to extrapolate patterns with computers?

Even better -- if you look in television static long enough, you are going to find a pattern. Either they've found some hidden predictor of attacks, or maybe someone needs a course in basic Ramsey theory, which deals with conditions under which order (patterns) must occur even in random noise.

Consider this example (*not* meant as an analogy for the discrete math nazis): you have an infinite sequence of completely random letters over the alphabet. What is the probability of finding "abc" repeated 15 times with a gap of exactly 10 letters between successive repeats? If the stream is indeed completely random, then the probability is non-zero and you will EVENTUALLY (probably) see the "pattern".