Okay, after getting sucked into the vortex of the damnable Global Warming debate, I’ll attempt a few additional points (see “Global Cooling” comments for the latest salvo of belief vs. skepticism).
One, by “Global Warming” (or just “GW”), I’m referring not to the obvious notion that the climate is changing but to the current view that the average measured temperature of the Earth will continue to rise to the point where we witness massive, even catastrophic changes in our climate. Now the “Al Gore” version of GW—which seems most popular—is the following. One, the ice caps melt. Two, the ocean levels rise. Three, human habitation (especially in coastal areas) is threatened by widespread flooding from the rising oceans. (Add into the mix other effects, such as an increase in extreme weather events.)
Okay, I’m sure the GW folks can add to this, or correct it in any number of ways they see fit. I think it’s a reasonable stab at the basic scenario that lights the we-must-do-something-now fire under GW proponents.
Now, there is I think a lot of confusion out there about science; to be more precise, about our ability to predict the future using the tools of science. We'll have to dig into some details to cash this out. First, the Enlightenment did indeed give us powerful predictive abilities that apply to what I'll call classical systems; systems that are not inherently complex. The standard classical examples involve the prediction of celestial events (when will the comet appear in the night sky, when will the shuttle approach the moon?, etc.). Our mathematics works really well for these types of systems. But in messier, complex systems (the so-called "nonlinear" systems that can't easily be modeled by differential equations, but enough of this), our predictive powers are positively paltry.
Not convinced? Consider: We can't give 7 day weather forecasts to save our backsides (in Central Texas, we can hardly get 2-3 day forecasts), we can't tell where the hurricane will make landfall (the predictive models give us 25 different trajectories, and whadya know, one of them was close!). We can't tell whether the Northeast will have heavy snow in 2009, and on and on. This is the dirty little secret about complex systems. We can't see into their future. And the global weather patterns of the Earth, folks, are a complex system.
So, at this point, the GW folks get red faced, and tell me that I'm screwing up the planet (sometimes they tell me that I'm almost ethically suspect, a sure sign that politics is wrapped too tightly around science). And here's my rejoinder: we don't know, and I suspect that you know that we don't know, but you're terrified that the knuckle draggers around you won't act quickly enough unless you make the issue seem dire, and requiring immediate attention. You trade the healthy skepticism about our predictive powers for some assurance that our kids won't inherit a world with Mel Gibson in it (I mean, in The Road Warrior). And so, over and over I hear: well, maybe we're wrong, but the cost of us not acting as if we're right is too great. It's Pascal's Wager (to which William James once remarked that God should throw out of heaven the Pascal's Wager believers first...).
And my response is: look, reducing carbon emissions is a classic case of over-determination (as philosophers like to put it). We all want clean air, clean water, parks to take our kids, a reduction in dangerous foreign oil, and so on. We have so many reasons to aggressively pursue alternative energy sources, who needs to leap headlong into (I think) suspect claims about our new found abilities to predict the future behavior of complex systems? Who needs the almost religious it-must-be-right fervor about some theory that is hotly debated and which, in spite of the GW rhetoric, is really still murky (I think). Let's get all the benefits of a cleaner future while maintaining a healthy skepticism about our ability to see into the future. Because, with complex systems, we can't.
So, sorry Al (Gore), but the world doesn't need more fear-mongering. We need less. And we can make the world a better place without it.
Subscribe to:
Post Comments (Atom)
1 comment:
As I said earlier, I think you're underestimating the effectiveness of our models of these complex systems. It's certainly true that for systems like the weather, it's very difficult even given almost arbitrarily precise about present conditions to predict future conditions in a certain place on a certain day. But that doesn't mean we can't model the weather and/or predict trends in the weather. Stream flow is something similar in this respect. If I drop a truckload full of rubber duckies into a stream, it's nearly impossible to come up with a model allowing me to predict with any accuracy where a particular one will be in two hours. However, that doesn't mean I can't make a pretty good estimate about the distance traveled by the average duck. And I can make reasonably accurate predictions about what happens to that calculation if I increase wind speed, or amount of water in the stream, etc. Probably not for an individual duck but perfectly useful for characterizing at a more general level.
Post a Comment