In an earlier post I contrasted induction and deduction while suggesting that induction is the currently favored term used in science. However, I also suggested that the two philosophies can be used in concert with one another. Indeed, as much as one can argue about the virtues of one philosophy or the other, science actually advances on a cycle between the two!
Let’s review. To put things simply, induction emphasizes the individual, whereas deduction begins with generalizations. Science largely began with a focus on deduction, trying to find universal laws and hoping to explain as much about the world as possible. In the 19th century, generalizations reached a pinnacle of overuse, particularly for explaining human characteristics. While deduction became disfavored because of those missteps, induction rose to favor on the heels of more quantitative techniques for describing the individual objects of study.
Criticisms and attempts to further distinguish the two range from the practical limitations of the respective philosophies to the innateness of ideas. The debate over the origin of ideas about universals is as at least as old as Plato and Aristotle. For the most part, science has sided with Aristotle on the importance of experience (empiricism). In a way this explains science’s gravitation towards the principles of induction, but in the process, the problem of induction has been cast aside.
The problem of induction is the impossibility to observe every individual case. Here’s a classical quote on the issue:
When they propose to establish the universal from the particulars by means of induction, they will affect this by a review of either all or some of the particulars. But if they review some, the induction will be insecure, since some of the particulars omitted in the induction may contravene the universal; while if they are to review all, they will be toiling at the impossible, since the particulars are infinite and indefinite.
-Sextus Empiricus (160-210 CE) from Outlines of Pyrrhonism
In other words, there is always uncertainty about what hasn’t been directly observed and it is impossible to observe everything. To help fill the gaps between observations, we make generalizations that are based on what has been observed so far. In modern science these predictive guides take the form of models. There are different types of models, but one of the most popular is the empirical model. Defining a model as empirical emphasizes the fact that it is built from, or calibrated on, observed data. The purpose of the model is to then help the researcher understand system dynamics and make predictions. But the application of the model (generalization) to unknown situations is deduction.
Although the terms regularly used today are different, in practice modern science uses induction and deduction in a cycle. Data is collected, which is often used to build models. Where weaknesses in these models are found, more data is collected and different model designs are tested in order to make a better model. Thus the cycle of science is a process of continually refining knowledge. Deduction enables predictions and helps to identify exceptions to the generalized models. Induction accumulates more data to test and improve those generalized models.
For more on the philosophical controversy of induction, deduction, and all the entities in between, check out the series of posts on The Lycaeum blog.
Also, hopefully it is easy to see how the scientific method fits nicely into this philosophical model. For example, tomatosphere.org presents the scientific method as a cyclical flow chart that parallels the diagram for the cycle of science presented here.