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with as quickly as possible.

It is important, first of all, to forestall the conflation of “complex/simple” and “complicated/simplistic.” All science is (to put the point mildly) difficult, and no branch of contemporary science is simplistic in the sense of being facile, superficial, or easy. In opposing complex systems to simple systems, then, I am not claiming that some branches of science are “hard” and some are “soft” in virtue of being more or less rigorous—indeed, the hard/soft science distinction (which roughly parallels the physical/social science distinction, at least most of the time) is precisely the conceptual carving that I’m suggesting we ought to move beyond. There are no simplistic sciences: all science is complicated in the sense of being difficult, multi-faceted, and messy. Similarly, there are no simplistic systems in nature; no matter how we choose to carve up the world, the result is a set of systems that are decidedly complicated (and thank goodness for this: the world would be incredibly boring otherwise!). This point should be clear from our discussion in Chapter One.

If all systems are complicated, then, what makes one system a complex system, and another a simple system? This is not an easy question to answer, and an entirely new academic field—complex systems theory—has grown up around attempts to do so. Despite the centrality of the concept, there’s no agreed-upon definition of complexity in the complex systems theory literature. We'll look at a few different suggestions that seem natural (and suggest why they might not be entirely satisfactory) before building our own, but let’s start by trying to get an intuitive grasp on the concept. As before, we’ll tighten up that intuitive account as we go along; if all goes well, we’ll construct a natural definition of complexity piece by piece.