David Sloan Wilson on Seeing Like A Scientist
So back in the beginning of the Enlightenment, to be a scientist meant emulating Isaac Newton. And so that way you had to be mechanistic, you had to be mathematical, you had to create a physics of social behavior.
So if you look at the whole origins of the neoclassical economic paradigm, it was that we want to be like Newton. And all the way through, you can see that on the one hand, of course, these are powerful methods, they're amazing methods, and yet at the same time, up until very recently (and I'm talking only a few decades) they were de facto denials of complexity. Because you can talk about complexity in words, but when you build mathematical equations you find that they're extremely constraining and the simplifying assumptions they must make to remain tractable.
In 2009 George Akerlof wrote an economics article titled "The Missing Motivation of Economics," and the missing motivation was norms. And so we've been talking about norms as just absolutely fundamental to human society. Evidently they were missing from economics. Why? Because they were intractable mathematically, that you had to make the assumption of self-regarding preferences, basically, or else you couldn't grind through the math.
And so that's the degree to which, for all of its power, this Newtonian ideal was a de facto denial of complexity. And with the experiments, you can only vary at most two or three factors, and you have to hold everything else constant. And so everything that we associate with science was also a de facto denial of complexity up until the advent of computers.
And then—only then [with computers, and now AI]—did we gain the capacity to model the complex world as it really is.