Faith underlying science
Proponents of faith as a virtue frequently argue that even science is based on blind faith—faith in causality, or faith that the universe obeys laws accessible to human intelligence, or faith in some specific underlying principles. In his book An Enquiry Concerning Human Understanding, 18th-century philosopher David Hume argues that science is based on “the principle of the uniformity of nature”—that patterns observed in the past will continue to be observed in the future—and that this principle cannot itself be logically derived. A recent post by a friend of mine summarizes some of Hume’s discussion.
All of these arguments about faith at the heart of science seem to misunderstand what science really is in practice. Science is not about discovering irrefutable philosophical truths, nor is it merely a sequence of logical or mathematical operations strung together at length. Logic and mathematics are just a few of the tools used in the course of scientific inquiry, some of which stem from our in-born intuitions about the world, but most of which were devised because we discovered that they were useful. Arithmetic with small numbers and very simple logic are intuitive; the formal generalizations of both of these (of which there are many) are entirely artificial. Scientists are constantly on guard for cases where their tools are steering them wrong. In the 20th century physicists discovered that our intuitive Euclidean geometry was a poor model for the large-scale structure of our physical world and that our intuitive view of mechanics was only relevant to objects in a very limited range of sizes. Sociologists and economists have been forced to construct incredibly elaborate models to replace simple arithmetic in the complex systems they study, where one and one don’t quite make two.
Science is, by my definition, empirical: it is an attempt to explain and predict observable phenomena. You don’t need faith that the universe is explicable to give it a try, and your predictions don’t need to be perfect for them to be useful. Even in physics, the most fundamental of sciences, we are quite sure that our best models of how the universe operates are (slightly) wrong. Physicists keep working to improve the models, and they seem to be making more and more accurate predictions, but the notion of a perfect and complete model that can be expressed in the language of mathematics is nothing more than an appealing goal. Such a model may not exist.
Good science does not even take causality for granted. It is possible to derive a great many scientific hypotheses which model the stock market (or the winning lottery numbers) as a function of the weather in Timbuktu; many of these models will even correspond with all available data. Further evidence will most likely show these models to offer little or no real predictive power, however, for a simple reason: there is little or no causality between the phenomena in reality. Scientists study causality just as they study every other phenomenon—skeptically, with an acceptance of causal models only when they appear to offer real predictive power.
While Hume makes a convincing case that the uniformity of nature cannot be proven logically, this in no way undermines its value as a scientific theory. Huge quantities of evidence show that certain types of observed patterns tend to repeat themselves. While there is no guarantee that this will continue in the future, it does provide the basis for a wide range of valuable scientific models. Hume disproves the absolute guaranteed truth of the proposition, but not its utility.
While Hume didn’t have our modern understanding of science or notions of statistical certainty available to him, he did offer a solution to his own problem. He argued that inductive reasoning based on the uniformity of nature was a capacity we had simply been granted by “Nature” as a way of allowing us to cope with the world around us. In other words, such reasoning proves useful so we make use of it even if we have no guarantee that it’s true in a philosophical sense.
Once you figure out what they’re talking about, some of these philosopher guys aren’t entirely useless.