Karl Popper and the Problem of Induction or the Principle of FalsifiabilityJune 27, 2021
In 1666, an apple fell on the ground while a young scientist was sitting in the garden. It was Isaac Newton, the scientist who wondered why the motion of the apple was not upwards or sideways but directly downwards. This event inspired him for the theory of gravity.
This theory explained the motion of the planets as well as the motion of apples. So what happened next? Do you think Newton then put together evidence that proved his theory unequivocally correct? According to Karl Popper, no!
Scientists, like all of us, learn from their own mistakes. Science dictates when we realize that a certain way of thinking about reality is wrong. These two sentences sum up Karl Popper’s view of what humanity’s best hope is for learning about the workings of the world.
Before Popper developed his ideas, many people believed that scientists started with a hunch about what the world was like, and then gathered evidence that showed that hunch was true.
According to Popper, scientists try to prove their theories wrong. The testability of a theory involves seeing whether it is falsifiable. The typical scientist starts with a daring guess or assumption, then tries to disprove it with a series of experiments or observations.
Science is a creative and exciting enterprise, but it doesn’t prove anything right. All he does is get rid of wrong points of view and hope to approach the truth in the process.
Popper was born in Vienna in 1902. Although his family later converted to Christianity, Popper was of Jewish descent, and when Hitler was in power in the 1930s, he wisely settled first in New Zealand and then in England, where he taught at the Lonclon School of Economics.
He had a wide range of interests in his youth. He was interested in science, psychology, politics and music, but philosophy was his true passion. Throughout his life, he made important contributions to both the philosophy of science and the philosophy of politics.
Until Popper began writing his scientific method, many scientists and philosophers believed that the way to do science was to find evidence to support assumptions. If you wanted to prove that all swans were white, you had to observe plenty of white swans. If all the swans you looked at were white, it seemed reasonable to assume that your hypothesis “all swans are white” was correct.
This kind of reasoning went from “All swans I have ever seen are white” to “All swans are white”. But it is clear that a swan you do not observe can be black. For example, black swans are found in many zoos in Australia and around the world. Therefore, the statement “All swans are white” cannot be the result of logical proof.
Even if you have observed thousands of all white swans, the result may still be inaccurate. The only way to prove definitively that all swans are white is to look at each swan individually. If there is even a single black swan, the result “All swans are white” will be falsified.
This problem is a version of the Induction Problem written by David Hume in the eighteenth century.
Induction is very different from deduction. This is the source of the problem. Deduction is a style of logical argument in which if the premises (initial assumptions) are true, the conclusion must also be true. Let’s take a frequently used example: “All men are mortal” and “Socrates is man” are two premises followed by the logical conclusion “Socrates is mortal”.
If you accept “All men are mortal” and “Socrates is human” and deny the truth of the statement “Socrates is mortal”, you will be contradicting yourself. It would be like saying “Socrates is both mortal and not mortal”. One way to think about this is that in deduction the truth of the conclusion is somehow contained in the premises, and logic just reveals it.
Let’s look at another example of deduction:
Premise 1: All fish have gills.
Premise 2: John is a fish.
Conclusion: So John has gills.
It would be absurd, completely illogical, to say that the first proposition and the second proposition are true, but the conclusion is false.
Induction is very different from that. Induction often involves reasoning from selected observations to general conclusions. If you observe that it rains every Tuesday for four consecutive weeks, you can generalize that it will rain every Tuesday from now on. That would be an example of induction. A single rainless Tuesday is enough to refute the claim that it rains every Tuesday. The example of four rainy Tuesdays in a row is a very small sample of all possible Tuesdays.
However, even if you make countless observations, as with white swans, you may be hindered by the existence of one example that does not fit your generalization: a single rainless Tuesday or a non-white swan.
And this is the Problem of Induction; induction that seems so unreliable