review: “Emergence” by Steven Johnson
“Emergence – the connected lives of ants, brains, cities and software”
New York: Scribner, 2001
Are you familiar with the situation in which you’re having a talk over the hedge with that neighbor that emerges from behind it. Whom you never talk to, but suddenly he starts talking about his nephew and his classmate and how that classmate is related to someone that sounds like your 2nd grade teacher. And so on and so on. That pretty much describes the way how Steven Johnson links everything together; slime molds to Manchester, ants to SimCity and neighborhoods to TIVO. And whenever you think you couldn’t care less about how an ant finds the quickest way to the food area, he’ll tell you how to make sense of it all.
The main issue he is trying to get at, is what he calls ’emergence’.
One of the fundamental laws of emergence is “the behavior of individual agents is less important than the overall system.” (p.145) He differentiates the micro-niveau from the macro-niveau by the use of ants. Although we use the word ‘ant queen’, none of the ants is actually ‘in charge’ of the overall operation. They communicate by the use of pheromone trails, from which an ant can pick up that there are already enough ants out there looking for food. So he might as well take out the trash. Johnson shows us that large patterns can emerge out of uncoordinated local actions. Understanding this concept “has always been about giving up control, letting the system govern itself as much as possible, letting it learn from the footprints.” (p.234) So that means we have to stop looking for the pacemaker, or the ‘queen ant’ so to say. And see the way in which it actually works. How intelligence on macro-niveau is derived from local knowledge. The ants showcase this in five fundamental laws (p.78-79):
01 MORE IS DIFFERENT
02 IGNORANCE IS USEFUL
03 ENCOURAGE RANDOM NUMBERS
04 LOOK FOR PATTERNS IN THE SIGNS
05 PAY ATTENTION TO YOUR NEIGHBORS
I won’t elaborate on these laws, but it’s clear that these ‘rules’ are adaptable to other systems or the programming of software for that matter. In the same way Johnson explains how an image of Pandemonium in John Milton’s ‘Paradise Lost’ inspired Oliver Selfridge to write software that teaches a computer to recognize patterns in a way that relies on a distributed, bottom-up intelligence. The image pictures shrieking demons. To understand how this ‘shrieking’ is reflected in Selfridge’s system, imagine 26 individual demons. Each trained to recognize a letter of the alphabet. When a word is shown to these demons, the a-recognizing demon will shriek when he recognizes an ‘a’. The other demons are likely to not shriek, and the upper-demon will ‘count the votes’. The individual demon does not recognize the alphabet, but when put together the 26 will be able to. A system like this can be made more accurate by adding another layer of demons and a feedback mechanism whereby the various demon ‘votes’ could be graded.
Emergence is basically very similar to the ‘wisdom of a crowd’, but with an elaboration on how patterns, systems and ‘actual’ intelligence emerge from this wisdom. And an emphasis on the fact that the individual agents in these adaptive, self-organizing systems don’t need be intelligent (most systems even work better when these agents are ignorant) to collectively form a system of intelligent higher-level behavior.
Johnson explains all this to show that the more we’ve come to understand these systems of bottom-up intelligence, the more it is being (or can be) reflected in software applications like Amazon’s recommendation system. Or the way a site like Slashdot is being governed by its own users. That an invention like TiVo can possibly mean the end of the concept of ‘channels’ and we’ll just have clusters in the future. And if I want to see an episode of let’s say ‘Home Improvement’, I’ll just tap into that community.
Turns out, talking to your neighbor over the hedge actually makes you smarter. Because “local information can lead to global wisdom” (p.79)
by Minke Kampman