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Reader Jeff asked three good questions about some of the issues I discussed in my series on the logic of science that I would like to address here. What follows are his questions and my responses.

“First, in Part II you discuss the concepts of Know-How and Know-Why. I am curious as to what extent these concepts might be applied to understanding the differences between the Hard Sciences (Physics, Chemistry, &c.) and the Soft Sciences (Psychology, Sociology, &c.) Are what we call Soft Sciences sciences at all?”

Science has considerable prestige as providing reliable knowledge and as a result many fields of study aspire to that label. But the issue of what distinguishes science from non-science is as yet unresolved. The know-how/know why distinction of Aristotle ceased to be considered viable as a means of distinguishing science from non-science when Newton came along. His laws of motion and gravity were spectacularly successful in explaining the motion of objects, especially the solar system. He thus provided the ‘know-why’ that had been previously missing from the purely empirical field of astronomy, lifting it into the realm of science. [Read more…]

(For other posts in this series, see here.)

The roots of religion lie in deep evolutionary history. The book Why we Believe in God(s) by J. Anderson Thomson with Clare Aukofer (2011) marshals the evidence from psychology and neuroscience to argue that the tendency to belief in supernatural agencies by itself has no survival value but that it exists because it is a by-product of qualities that evolved for other purposes and which do have survival value, such as the tendency to detect agency behind natural events.
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Theologians often try to claim that they can arrive at eternal truths about god by using pure logic. In some sense, they are forced to make this claim because they have no evidence on their side but it is worthwhile to examine if it is possible to arrive at any truth purely logically. If so, we can see if that method can be co-opted to science, thus bypassing the need for evidence.

In mathematics, there is one way to prove that something is true using just logic alone and this is the method known as reductio ad absurdum or reduction to absurdity. The way it works is like this. Suppose you think that some proposition is true and want to prove it. You start by assuming that the negation of that proposition is true, and then show that this leads to a logical contradiction or a result that is manifestly false. This would convincingly prove that the starting assumption (the negation of the proposition under consideration) was false and hence that the original proposition was true.
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Karl Popper’s model of falsification makes the scientific enterprise process seem extremely rational and logical. It also implies that science is progressing along the path to truth by successively eliminating false theories. Hence it should not be surprising that practicing scientists like it and still hold on to it as their model of how science works. In the previous post in this series, I discussed how Thomas Kuhn’s work cast serious doubt on the validity of Karl Popper’s falsification model of scientific progress, replacing it with a seemingly more subjective process in which scientists switched allegiance from an old theory to a new one based on many factors, some of them subjective, and that this transition had some of the elements of a gestalt switch. This conclusion was disturbing to many.
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(For other posts in this series, see here.)

The philosopher of science Pierre Duhem said in his book The Aim and Structure of Physical Theory (1906, translated by Philip P. Wiener, 1954) that despite the fact that there is no way to isolate any given theory from all other theories, scientists are saved from sterile discussions about which theory is best because the collective ‘good sense’ of the scientific community can arrive at verdicts based on the evidence, and these verdicts are widely accepted. In adjudicating the truth or falsity of theories this way, the community of scientists are like a panel of judges in a court case (or a panel of doctors dealing with a particularly baffling set of symptoms), weighing the evidence for and against before pronouncing a verdict, once again showing the similarities of scientific conclusions to legal verdicts. And like judges, we have to try to leave our personal preferences at the door, which, as Duhem pointed out, is not always easy to do.
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(For other posts in this series, see here.)

The previous post illustrated a crucial difference between science and religion that explains why scientists can resolve disagreements amongst themselves as to which theory should be considered true but religious people cannot agree as to which god is the one true god. In competition between scientific theories, after some time the weight of evidence is such that one side concedes that their theory should be rejected, resulting in a consensus verdict. In religion, since evidence plays no role, and reason and logic are invoked only when they support your own case and discarded by appealing to faith when reason goes against you, there is no basis for arriving at agreement. It would be unthinkable for a scientist to argue in favor of his or her theory by denying evidence and logic and telling people that they must have faith in the theory for it to work.
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(For other posts in this series, see here.)

In the previous post, I discussed Karl Popper’s idea of using falsification as a demarcation criterion to distinguish science from non-science. The basic idea is that for a theory to be considered scientific, it has to make risky predictions that have the potential that a negative result would require us to abandon the theory. i.e., declare it to be false. If you cannot specify a test with the potential that a negative result would be fatal to your theory, then according to Popper’s criterion, that theory is not scientific.

Of course, I showed that falsification cannot be used to identify true theories by eliminating all false alternatives, because there is no limit to the theories can be invented to explain any set of phenomena. But steadily eliminating more and more false theories surely has to be a good thing in its own right. This is why falsificationism is highly popular among working scientists because it enables them to claim that science progresses by closing down blind alleys.
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(For other posts in this series, see here.)

In the previous post in this series, I wrote about the fact that however much data may support a theory, we are not in a position to unequivocally state that we have proven the theory to be true. But what if the prediction disagrees with the data? Surely then we can say something definite, that the theory is false?

The philosopher of science Karl Popper, who was deeply interested in the question of how to distinguish science from non-science, used this idea to develop his notion of falsifiability. He suggested that what makes a theory scientific was that it should make predictions that can be tested, saying that “the criterion of the scientific status of a theory is its falsifiability, or refutability, or testability.” (Conjectures and Refutations: The Growth of Scientific Knowledge, 1963, p. 48)
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In mathematics, the standard method of proving something is to start with the axioms and then apply the rules of logic to arrive at a theorem. In science, the parallel exercise is to start with a basic theory that consists of a set of fundamental entities and the laws or principles that are assumed to apply to them (all of which serve as the scientific analogues of axioms) and then apply the rules of logic and the techniques of mathematics to arrive at conclusions. For example, in physics one might start with the Schrodinger equation and the laws of electrodynamics and a system consisting of a proton and electron having specific properties (mass, electric charge, and so on) and use mathematics to arrive at properties of the hydrogen atom, such as its energy levels, emission and absorption spectra, chemical properties, etc. In biology, one might start with the theory of evolution by natural selection and see how it applies to a given set of entities such as genes, cells, or larger organisms.< [Read more…]