Do the Problem of Induction and the Problem of Universals stem from the same underlying mechanism?

The Problem of Universals can be explained by showing the two viewpoints held. One view is that universals (qualities or characteristics that objects can have) are real, that is that they exist separately from individual instances that contain these qualities. The other is that we cannot justify this claim and that universals do not exist, that these qualities can only exist within actual instances of the qualities.

The Problem of Induction deals with the justification of the usage of induction (a form of logic in which generalizations are made from particular instances). The Problem of Induction is that in order to attempt to justify that induction is logical one must use induction. This circular reasoning cannot justify induction logically. Because we move from particulars to generalizations, inductive logic is underdetermined by the instances. We cannot observe all objects that a generalization subsumes, so the same generalization can follow from an infinite number of variations on the same evidence.

Neural Networks explain a vast majority of how our brains store and recall information. Our brains do three very important things that may explain why we use, but cannot justify, Universals and Induction.

1) Our brains store data from similar experiences in similar places. This may not seem like a big deal but it’s important. The data we observe is stored under a system that naturally classifies it under its observable qualities.

2) Our brains can interpret incomplete data. In neural networks when enough instances of an input have trained the network (like your brain learning from observations) incomplete inputs (ones that resemble the earlier instances but do not contain all of the same inputs) will produce a very similar result to the original instances. This shows that when the qualities of an object are observed and coincide with another the qualities of another object there is an inherent link between them. These shared qualities link the two physically through their shared neural connections.

3) The brain learns by repeated experience of certain inputs. The more an experience is repeated the “better” the brain is trained to give an output. As more and more observations of qualities are made the brain embeds these qualities as structures used in connecting observations.

From these three premises we can see that induction appears to happen simply due to neural network processes in the brain. When many instances of observation occur with similar qualities they create similar outputs. Your brain has modeled what it expects to be the outcome of specific instances. This is exactly what induction is!

The qualities of things that we observe behave similarly. These repeated observations of similar qualities create models of these qualities in our brains. This means we can think about these qualities without observing individual instances which leads us to believe that these qualities are universal.