The Failures of Mathematical Anti-Evolutionism
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The Failures of Mathematical Anti-Evolutionism (Jason Rosenhouse) (z-lib.org)
The Parallel Tracks of
Mathematical Reasoning 3.1 math is simple, reality is complex Having covered the basics of evolution, let us now consider the basics of mathematics. When asked to describe what mathematics is, most people shudder and talk about mind-numbing arithmetical algorithms and tedious symbol manipulation. They have unpleasant flashbacks to high school algebra classes. Mathematicians find this frustrating since too many people profess their distaste for our subject without ever having experienced the real thing. Arithmetic and algebra are tools that we use in doing our job, but they are not what get us excited about our work. As an analogy, woodworkers had better be proficient with tools like a band saw and a drill press. They need to be able to hammer a nail and drive a screw. But using saws and drills, hammers and screwdrivers, is not really the point of it all. For woodworkers, the pleasure comes from seeing a pile of wood, envisioning a finished project, and using their skills to bring it to fruition. Mathematicians experience something similar. For us, the pleasure comes from devel- oping abstract models of reality and using them to learn something about how the world works. My students often complain that mathematics is difficult because it is so abstract. I understand their frustration. Our inability to handle and manipulate mathematical objects can make it difficult to wrap our minds around them. However, there is an important sense in which my students have it backward. Mathematics is simple, it is reality that is complex. Everyone who has ever looked at a road map understands this point. (Nowadays people typically rely on global positioning systems 58 3.1 math is simple, reality is complex 59 to get around, but I will assume everyone still understands this reference.) The reality is a dense network of roads, only a small portion of which is visible when you are lost among them. What is needed is a diagram to show you how all of the roads interrelate, and that is what the map provides. The map omits most of the reality. It does not depict the location of every squirrel and tree, and it does not show you every house or shop you will encounter. It is instead an abstract representation of those aspects of reality specifically relevant to getting you to your destination. The map is useful precisely because it is abstract. You probably did not think you were doing mathematics by looking at a map, but in a very practical sense you were. Looking at an abstract representation of reality to plot your route is the same kind of activity as manipulating numbers to learn about physical objects. For example, if there are five kids over here and another three over there, then there are eight altogether. Something important has been accomplished upon realizing that this statement has nothing to do with kids, but is instead a statement about the abstract properties of collections of objects. “Mathematical modeling” is the art of designing abstract rep- resentations of reality, with the intent of learning about reality by studying the abstractions. The basic idea is to discard most of reality so that the model is amenable to study, and then to hope that the remaining bits are the parts relevant to our problems. If our ultimate concern is with the real world, and if we see the model as primarily a tool for learning about the world, then we are doing science. If instead we study the abstract model for its own sake, then we are doing mathematics. This distinction is somewhat crude, and the lines between science and mathematics are often very fuzzy, but we have captured something important nonetheless. Here is an example to show how the process plays out. In the eighteenth century, the city of Königsberg was located in Prussia. (Today it is known as Kaliningrad, and is located in Russia.) The city was divided into four land masses by the Pregel River, and these |
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