Philosophy of Science for Scientists

Many years ago my wife and I hosted a married couple we didn’t know for dinner. He was a law school student but she was a local Ph.D. student studying the philosophy of science. Having recently obtained my doctorate in engineering I commented that there was no such thing as a philosophy to science. Rather, I naively said, science flowed from observations of facts, logical and mathematical arguments, or simply from one’s own thoughts of how the world behaved. Was I wrong!

This woman explained that there was, indeed, a philosophy to science. She told me how scientists held particular views on what to study and how to study it and that the scientific method was subjected to biases and underlying prejudices of the scientist himself. I was flabbergasted, surprised to hear such thoughts because I believed science was, shall we say, independent of the scientist.

Along comes this splendid book, Philosophy of Science for Scientists by Lars-Goran Johansson: a lovely textbook for undergraduates. It is a highly readable introduction to how one can view the practice of science. I wish I had read such a book while in school and I wish my professors had spent some time, even just a lecture or two, explaining how students can see science from a view point a bit removed from our studies. It would have expanded everyone’s view of science and opened us to a better way to see what we were doing.

The book begins with a look how science started in ancient Greece where Thales believed water was “responsible for the change in all things.” A reasonable position, writes Johansson, because all living things require water. This approach is consistent with a modern view of science in that it is based on observation. We observe the world, form hypotheses, and conduct tests and experiments to verify our hypotheses. The ancients did not have access to the complicated experimental apparatuses we have (no super colliders, few controlled experiments) but they were excellent observers of their world.

The text shows how knowledge can grow with propositions to justify a true belief. For example, ancient astronomers observed the planets and formed a model of planets revolving around our Earth. We have better knowledge today, but at that time the geocentric model fit their observations quite well. While we now subscribe to a heliocentric solar system, ancient tables depicting the orbit of the moon about earth are very accurate up to this day.

There is a lovely treatment of hypothesis testing with a slightly contrived example of a medical test for an AIDS medicine. The authors state the null hypothesis to test, provide example data, and discuss how one can either accept or reject the null hypothesis. It’s a simple example, but illustrative. (In engineering I never learned about hypothesis testing in school, but later learned about it in operations research. This would have been good to hear first in a classroom.)

Here’s a great example of observation bias of the observer. Robert Rosenthal, a psychologist, asked students to experiment with mice to see how well they performed in solving a maze to find a food bowl. The students measured the time it took each mouse to get to the bowl. They were told some of the mice were “gifted” and would solve the maze quicker than the other mice. The students found the gifted the mice did, indeed, find the food quicker than the other mice. The students also found the gifted mice refused to move only 11% of the time but the other, non-gifted, mice refused to move 20% of the time. Of course, there were no differences between the mice, only the bias of the students from the original instructions.

The book touches on what I think is a crucial topic: paradigm shifts. A short discussion from Thomas Kuhn’s The Structure of Scientific Revolutions, now over 50-years old, shows how Kuhn viewed changes in scientific thought. For example, there is Newton’s analysis of lunar motion as continual free fall. Interestingly, earlier in the book we met Ptolemy’s geocentric view of the solar system, and the inevitable use of epicycles to explain, say, the retrograde motion of Mars. I believe it would have been beneficial for the author to have gone from epicycles to the concept of encrustation within Complexity theory to show a current view of the shift in paradigms. (This is one of the few shortcomings I found.)

The next part of the book explores Causes, Explanations, Laws and Models. Cause is wonderfully illustrated by an experiment on the wing length of fruit flies with a genetic defect. Fruit flies with this defect will have shortened wings if the temperature is around 20-degrees Celsius when the flies are maturing. If, however, the temperature is 32-degrees Celsius the wings grow to normal length. Does the genetic defect cause the wing length shortening or does the temperature do so? The answer depends on how we compare populations of fruit flies: If we compare at the same temperature then the defect is caused by the gene. If we compare populations at different temperatures then we would say temperature is the cause of the defect. It’s an interesting discussion point and worthwhile for students to think about.

The author explores Explanations with an example of stork populations and birth rates; the two declined remarkably between 1966 and 1980. The correlation between birth rates and the presence of storks was so consistent it was calculated that the probability of coincidence was 0.1%.

Figure 1: Birth rates have a remarkable correlation to the presence of storks in West Germany
between 1965 to 1980. (Image from Johansson, Philosophy of Science for Scientists.)

Figure 1 is from the text — note how closely the trends coincide. The author suggests the correlation was due to industrialization. This is an interesting discussion point for students. (The figure, by the way, is drawn with whimsy and reflective of the general tenor of the text — serious in content but approachable for an undergraduate.)

The author goes on with causes and effects, and Bayesian probabilities. The author presents a good argument for why explanations need to show the reason for a phenomena and not just some relationship. For example, ancient observers could predict a new moon accurately but they did not know why their predictions were true. Along comes Newton with his theory of gravity to explain orbital motion as a mathematical law, not just a table of observations. New moons are now predicted with reason, not just tabular notions.

The author discusses other topics and the reader will find all of them of interest. Please see the Table of Contents alongside this review.

In short, this is an excellent introduction to understanding science in a general sense. Students and practitioners will find it worthwhile to read and discuss. I wish I had read such a text long ago but I am glad to have benefited from it even now. 

David S. Mazel is a practicing engineer in the Washington, DC, area. He welcomes your comments to mazeld at gmail dot com.