Specified Complexity

This argument was first put forward by William Dembski. According to Dembski, specified complex patterns indicates some form of guidance in their formation, which is indicative of intelligence. In the video below, Stephen Meyer explains this concept.

What is the probability of life arising purely by chance?

Why is it that it couldn’t have happened by chance?

Well you can never say never for sure. Okay you can’t say something couldn’t for sure but you can say that it would be vastly more improbable than not that life did arise by chance. So improbable in fact that people would dismiss it as being not a credible hypothesis. Let me explain why. Here’s an illustration I used to use with my students. I’ve got a bag here of scrabble letters so I asked my students to test the hypothesis that chance is an effective way of building new information, of generating new information. What I have them do is I’d have them walk up to or I’d walk out into the aisles have them pick out letters at random and then take those letters and go and write whatever letter they chose on the blackboard and have them do it in the sequence that they chose the letters. And invariably what would turn up on the blackboard would be some gibberish like Z S U A E T, you know whatever and obviously improbable arrangement of characters but not specified to perform a function, not meaningful okay and that’s the problem with chance. It generates unspecified arrangements but not specified arrangements. 

Yeah you get gibberish vs. “time and tide wait for no man.”

Exactly and you know chance does a great job of giving you the gibberish but it will not, it does not produce information. Now occasionally we’d have a situation in which we’d get a student you know maybe the first three students would come up with something like “bin” or “um”, or something that was at least word-like and the students would often start to kind of do cat calls and “Ha, we got you. We’re going to produce a lot of information by chance” but I would always win the point of the argument by allowing the experiment to keep going and eventually the gibberish would completely swamp the meaningful.

With 150 letters going down the line, the fact is you would have gibberish.

Yeah absolutely.

And there’s a reason for that and I’ve got a little demonstration on that point as well. It’s called the problem of combinatorials. And this is what people don’t realize. Before we get to the slide, I have a visual aid. It’s a little dinosaur puzzle and it’s got four dials. On each dial there are six possibilities, one for each of six dinosaurs and you’ve got a dial for the head, the torso, the tail and the label of each dinosaur. And the idea here in the puzzle is you’re trying to turn it to get the Tyrannosaurus Rex – head, body, tail and label all lined up. Now what are the odds of doing that, by just turning the dials at random. That’s the problem of combinatorials. There’s lots of different combinations so the odds are actually very small. You’ve got a 1 in 6 chance of getting the correct head. And then a 1 in 6 chance of getting the correct body, tail and label. And you might want to say the odds are 6 plus 6 plus 6 plus 6 but that’s not how it works because you have to take into account all the different combinations that can be formed. If I’ve got a head on one of them, 6 possibility here but on the second dial for the torso I’ve also got a 1 in 6 possibility so it’s there’s actually 6 times 6 possibilities and then when you get to the 3rd dail I get another times 6 and the 4th now another times 6 it ends up that you actually have 1296 possible combinations so the odds of getting the correct one are only 1 in 1296. Now if I give you 10 seconds and you get to turn the dial three times is it more likely or less likely than not that you will stumble on to the correct combination? Well it’s obviously less likely than not and it’s not impossible but it’s far more likely that you won’t solve the problem by chance than you will solve the problem by chance.