Tuesday, September 08, 2009

A sustainable answer to the cruel logic of exponential math

Simply a Deep Thought(tm):

Humans had, for most of our development, millions, thousands, hundreds and even tens of years to adjust to the new problems of our growing species. How best to protect the tribe from animals? How best to store grains? How best to protect our group from other groups who would attack us? How to attack other groups and get their stuff? All of these questions have been addressed with the luxury of some considerable time -- and in a time when significant loss of life was not all that rare.

In the last 200 years, though, our growth has risen to insanely high levels. (Strangely, most population growth experts expect it to top out at some point fairly soon, though why that should be so I have no idea.) We have had to invent, nearly on the fly, systems to handle our basic human needs. We have often done so while incurring large loss of life, and I'm not even counting warfare and genocide - simple death from starvation has been an ongoing catastrophe of enormous proportions.

When I consider the state of our American experiment, I am concerned that we do not have a sustainable model. We still follow an extractive model, and routinely waste enormous resources, lost in our obsession with free markets and social Darwinism.

Social Darwinism is not who we are as creatures. We are hard-wired to be more community-minded, and are obviously striving to get more and more community minded all the time. But we have a hard time imagining a better future, and remain fixed on the structures that have "worked" in the past.

Our society, like so many others around the world, has a jobs/work crisis. Humans need to feel productive to remain happy, and far too many are not producing at anything like their potential. The value of specialization, the value of economies of scale, the power of technological acheivements - these are all forces that free humans from various kinds of work. But we have operated under the impression that the goal is a society where no one has to work, which has sadly led us to a society where not enough people have useful work to do.

In considering the best ways to create work/jobs, we must start to value more highly the need of humans to have meaningful work. Even if it means we "pay" more. We might pay teachers more, even though we might not "have" to. We might "pay" to have more manufacturing work done nearby, even though we could "pay" less for it to be done elsewhere.

I've been trying to formulate a model that would be universal enough to be adopted by almost any society. My thought begins with something like, "for every 2,200 humans, we need one dentist, for every 100,000 humans we need 1,400 farm workers, for every 28,500 humans we need 100 carpenters," and so on. The idea is to have communities that are optimally sized and ensure a wide variety of vocations. A single social unit of say, 300 million, is simply too large to manage. My current thought is to establish something rather like colleges and universities, but these institutions would have missions that do not revolve around education (though some could and would), but would have some focus or speciality. I can imagine a transportation college, where engineers would design forms of transportation and workers could produce it; the rest of the community would work to support that. It's not something I've finished thinking through, so there are a lot of issues. But the core of the idea is to create communities of sizes that would more readily allow adaptation, change and growth over time, so that we wouldn't have to work solely on systems that worked for communities of a half a billion souls or more.

If we don't grab hold of our own destiny, the cruel logic of math will leave us with a single system for all 20 billion of us, in which errors are far more costly, innovation is therefore harder, and far too many will fail to lead the kind of productive and satisfying lives that they could if we only built smarter structures and systems.

1 comment:

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