Earlier quoted context omitted.
This is going to sound a little harsh, but that's not the intention. I am genuinely curious about emergent phenomenon of computation. I spent a lot of time messing around with toy evolutionary algorithms. I never really got any satisfaction out of those experiments. eventually I found this [1], and felt sort of foolish. Has anything really happened with emergent properties in the last 10 years or so? [1] http://lessw…
I've never seen emergence "used as an explanation in its own right." I also don't understand why you would feel foolish after reading this.
As for feeling foolish after playing with evolutionary algorithms - I'm not the OP but I can relate somewhat given how I saw people learning evolutionary algorithms and neural networks at my university (and I'm pretty sure it's not a local phenomenon). Evolutionary algorithms are usually explained as inspired by biological evolution, with implicit (and sometimes explicit) note that "evolution made us, therefore evolution is superpowerful, therefore evolutionary algorithms - which are just evolution in code - will be superpowerful too!". Except they're not, and the whole concept is bullshit. It's a belief in Random Number God. Throw enough shit at the wall and something will stick. Evolution is terribly, terribly inefficient, and so are the evolutionary algorithms.
Sure, this inefficiency gives them some interesting properties that may help them avoid particular types of local optimas, etc. But those are mathematical features of an algorithm type, and have nothing to do and share no power with evolution, or magic.
The whole problem stems from people trying to transfer virtues of biology to computing by using a surface metaphor. There's a post on LW that covers it nicely:
http://lesswrong.com/lw/vx/failure_by_analogy/
"So... why didn't the flapping-wing designs work? Birds flap wings and they fly. The flying machine flaps its wings. Why, oh why, doesn't it fly?"
Or about neural networks,
"A backprop network with sigmoid units... actually doesn't much resemble biology at all. Around as much as a voodoo doll resembles its victim. The surface shape may look vaguely similar in extremely superficial aspects at a first glance. But the interiors and behaviors, and basically the whole thing apart from the surface, are nothing at all alike. All that biological neurons have in common with gradient-optimization ANNs is... the spiderwebby look."
I encounter a lot of similar "medieval thinking" in CS departments. I don't know why. It probably goes in common with the concept of not caring about how the world works.
Oh, this one is also good: http://lesswrong.com/lw/rj/surface_analogies_and_deep_causes....
[0] - it's also a good trick I picked up while hanging on LW; if you don't know why something happens, label it as unknown explicitly. Say "this process is driven by magic", or "caused by Divine Intervention" instead of trying to invent equivalently-informative but sciency-sounding labels like "emergent behaviour" or "spontanous self-organization". This way you'll never forget that your theory still has holes that need to be filled in, and you won't accidentally confuse yourself (or others).