â¦ The worst part of philosophy is the philosophy of science; the only people, as far as I know, who read the works of philosophers of science are other philosophers of science.
This is the view of Arizona State University physicist Lawrence Krauss, author of the 2012 book A Universe from Nothing. He is certainly not the only physicist to criticize the philosophy of science. Richard Feynman, who shared the 1965 Nobel Prize in Physics for his work on quantum field theory, asserted that “the philosophy of science is as useful to scientists as ornithology is to birds.” It’s quite a position. In a recent commentary from Nature, we describe how a better understanding of one aspect of the philosophy of science, namely causal inference, can help us be better scientists.
What is causal inference? Quite simply, it’s about understanding whether X causes Y. For example, the majority of people who develop lung cancer are smokers, but does that mean that smoking causes lung cancer? In the 1950s, this was a legitimate research question: Could other differences between smokers and non-smokers explain the association, or could a third factor influence both? The causal effect of smoking on lung cancer is now clear, but it has taken years to establish and get the point across. This is because it is notoriously difficult to determine causation, and epidemiology has a knack for highlighting supposed links between, for example, behavior and health, which do not reflect cause and effect relationships. .
In science today, there is a huge interest in replicating the results, sparked by somewhat contested evidence that much of the published scientific results may be wrong, or at least misleading. If we took more care to repeat our studies, to verify that we get a broadly similar result each time, then our results would surely be more robust. Maybe, but a solid conclusion can always be wrong: X and Y can be correlated very reliably, but may not reflect a cause and effect relationship. This focus on replication stems from a widespread, but in our opinion incomplete, notion of falsification (supported by the philosopher of science Karl Popper) at the heart of the scientific enterprise. In fact, this is rarely how scientists work in practice.
Many scholars will refer to Popper if they are in a hurry to explain the basis of their inferences, but forgery is not everything. Another approach to questioning potentially causal associations is best explanation inference. Peter Lipton, the late Cambridge University science philosopher, described this as the search for the ‘most beautiful’, not just the ‘most likely’, an explanation characterized by ‘the scope, precision, mechanism. , unification and simplicity â.