Structure and Emergence in Social Interaction

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These are fragmentary notes in an evolving essay.

The systems I admire most don't (didn't think to) have a lot of structure up front. They do have enough structure to create a substrate on which experiments can take place, in messy fashion, and after a while, they evolve a complicated ecosystem which is messy, has redundancies, and weird internal design, but they work.

Twitter is a great example of the emergence of a complex system based on a simple substrate. Retweeting, the "@user" public address convention and #hashtags are things that weren't designed into the system, but evolved as people interacted on the system. The evolution was messy, and the resulting conventions are creaky and prone to errors, but generally work and have delighted millions.

(the ecosystem of Twitter apps)

Flickr didn't design the capability to play games via the groups and the tags, but some of the most fun on Flickr is had there.

Wikipedia looks well-organized at first glance, but it's been a long evolution with a lot of chaos. The organization of the data is complicated and messy, but it tracks the real world better for it, I think. (I mention Wikipedia because of discussions I've had with people who are trying to mash up structure and wikis. It's a challenge, and I'm not always comfortable seeing the hybridization of structure and emergence -- I think it's better to do one or the other.)

(for expansion another time: the super-simple but flexible system design of the Atari 2600 and the great variety of games that were written for it.)

(Perhaps unrelated, but it comes to mind, a timescale observation: Twitter's structure runs at a scale of hours to days; Flickr's runs at a scale of days to weeks; Wikipedia runs at a scale of weeks to months.)

Or a natural metaphor: a coral reef offers some structure, and scaffolding to create a complex ecosystem, but doesn't have structure to define the ecosystem.

More of what I'm talking about is in Kevin Kelly's book "Out of Control", although it's been long enough since I read it that I can't point to a specific part (besides the whole thing). Here's one little story that speaks to me:

"There was no evolutionary pressure in Koza's world toward simple solutions. His experiment could not have found that distilled equation because it wasn't structured to do so. Koza tried applying parsimony in other runs but found that parsimony added to the beginning of a run dampened the efficiency of the solutions. He'd find simple but mediocre to poor solutions. He has some evidence that adding parsimony at the end of evolutionary procedure -- that is, first let the system find a solution that kind of works and then start paring it down -- is a better way to evolve succinct equations."

"But Koza passionately believes parsimony is highly overrated. It is, he says, a mere 'human esthetic.' Nature isn't particularly parsimonious. For instance, David Stork, then a scientist at Stanford, analyzed the neural circuits in the muscles of a crayfish tail. The network triggers a curious backflip when the crayfish wants to escape. To humans the circuit looks baroquely complex and could be simplified easily with the quick removal of a couple of superfluous loops. But the mess works. Nature does not simplify simply to be elegant."

"Humans seek a simple formula such as Newton's f=ma, Koza suggests, because it reflects our innate faith that at bottom there is elegant order in the universe. More importantly, simplicity is a human convenience. The heartwarming beauty we perceive in f=ma is reinforced by the cold fact that it is a much easier formula to use than Koza's spiral monster. In the days before computers and calculators, a simple equation was more useful because it was easier to compute without errors. Complicated formulas were a grind and treacherous. But, within a certain range, neither nature nor parallel computers are troubled by convoluted logic. The extra steps we find ugly and stupefying, they do perfectly in tedious exactitude."

Structure is represented in this story by parsimony. You can define structure up-front, but then you miss the unfolding of a complex dynamic ecosystem.

Formal structure is a great solution for the right kind of problem. But it interferes with emergence.

Keywords: complexity, emergence, chaos


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