OK, Ive chatted off and on about a new kind of liberalism, and from the email Ive gotten, most of what I think Ive engendered has been confusion. Part of that is probably because Im confused myself, and just working these ideas out, in a public playing field. So its time to stretch a bit and see what we can do.
Heres some background on what Im talking about, and Ill warn you that Im about to get academic on your ass.
Everyone has heard of chaos theory, emergence, and the such at this point. James Gleick wrote a good book on the subject, as did John Holland. I was blessed to have studied with the guy who I consider to be the unsung founder of the discipline, Horst Rittel. He wrote a series of papers on the subject in the early 70s, several along with Mel Webber, that I believe really opened the door.
The key concept they introduced was that of tame and wicked problems. I have the monograph somewhere, and so will quote from memory, which I hope to improve when I dig it out. Tame problems are those which can be accurately modeled in a repeatable fashion in limited, closed systems
a classical physics experiment, for example. Millions of different labs all over the world can do the rolling ball down the ramp experiment, and the results will be essentially the same. All of modern experimental science is founded, fundamentally, on the concept that physical phenomena can be reduced to tame experiments.
Wicked problems, on the other hand, inherently cannot be modeled in a reductive fashion, and cannot be simplified into models which can be readily analyzed in an isolated environment. In effect, to model a wicked problem, you have to completely reproduce the thing modeled, much like Borges famous map.
Problems in street traffic analysis, economics, weather prediction are wicked problems.
Advances in math applications and computer science, however, have enabled us to come up with ways to predictively model wicked systems, and that, Ill argue, is the foundation of chaos theory.
Much of the modeling today is done with what are called cellular automata.
Cellular automata (CAs) are dynamical systems that are discrete in state, space, and time. In the simplest case, a CA consists of a one-dimensional lattice of identical cells, each of which can be in one of a number of states. Again in the simplest case, let’s say each cell can be either white (0) or black (1). At each time step, all cells in the lattice update their state simultaneously by using a fixed update rule which is the same for each cell. This update rule takes as input the local neighborhood configuration of a given cell (i.e., the current states of the cell and its r neighbors on either side), and returns the new state of the cell depending on this local neighborhood configuration. Thus, this update rule can be represented as a lookup table which lists all possible local neighborhood configurations together with the corresponding new cell states.
Different update rules (or lookup tables) give rise to different kinds of CA dynamics when this update rule is iterated over time, ranging from fixed point or simple periodic behavior to highly complex or even “chaotic”. The particular behavior of a CA can be visualized in a space-time diagram, in which the CA lattice configurations are plotted over time, usually starting with a random initial configuration.
What were doing here is modeling highly complex systems by assuming that they can best be represented by a large number of autonomous actors and a set of rules governing their behavior and interaction.
Wolfram, in his new book, seems to be making the argument that this isnt just a representation, but the real underpinning of much of modern math and physical science (note: havent read the book yet, would love to hear from someone who has).
Ill argue that it provides a great metaphor for understanding human behavior and social systems, and right now in looking at the appropriate response in the WoT.
Lots of us are reaching for that metaphor, including the Gedankenpundit and Oxblog, in their discussion. Joe Katzman is tying it to technological changes in his discussion of 4th Generation warfare
Instapundit says:
In this, as I’ve said before, the learning curve, and the ability to learn and act faster than the enemy, is the key. American civilians, using civilian technology and their own inherent ability to self-organize, were able to neutralize the terrorist plan in 109 minutes, as Flight 93 demonstrates.
I talk about it here.
You can start to see where I’m going with this; think of flexible groups of autonomous individuals, rather than tightly structured drill teams.
Ill try and get some time this weekend to link this to a new conception of liberalism
Ill call it engineered liberalism, in honor of all the engineerists out there. But here are some of the concrete concepts to play with. I’m sure folks who know this better than me will chime in, and I welcome comments and corrections.
Its late, I owe a bunch of links in this, Ill fill them in later
Some useful definitions.