Connecting science with perception

by Neil Rickert

I have two ongoing series of posts, one on perception and the other on how science works.  These are very much connected, as I will explain in this post.

My interest in the main topics of this blog led me to study the question of how humans learn.  I understood, all along, that the increase in scientific knowledge is closely related to learning.  Or, as I think Quine puts it, science is learning writ large.  Thus I used the growth of scientific knowledge as a publicly observable instance of learning.

As I studied human learning, I quickly realized the importance of perception.  We cannot observe that the cat is on the mat, unless we are able to detect the presence of a cat and the presence of a mat.  So explaining object recognition and object identification became an important part of what I studied.

Looking at science, I could see the same kind of thing.  Science carefully defines what it observes.  So those careful definitions of what is to be observed are somewhat analogous to the ability of our perceptual systems to identify objects.  From this, I came to understand that science is perception writ large, and that the growth of scientific knowledge is akin to perceptual learning.

Philosophy of science was no help at all.  The typical inductionist account

All the many crows that I have ever seen were black.  Therefore all crows are black.

manages to completely beg the question of how it is possible that we are able to see crows, and how it is possible that we are able to see that they are black.

Although I have said that I am a behaviorist, much of the literature from behaviorist psychology also seemed question begging.  It explains nothing to say that a morsel of food is a stimulus to the organism, unless there is also an explanation of how the creature manages to perceive that what was provided was food.  So again, perception had to be key, even from a behaviorist point of view.

As a result of all of this, I have been studying learning, perception, and how science works.  And I have been connecting those.


Learning is often taken to be pattern discovery.  My studies have led me to conclude otherwise.  As I see it, the principle problem of learning is actually the problem of intentionality, the problem of how to have symbolic representations of things that exist in the world.  And, similarly, the principle problem for science is the problem of intentionality which, in scientific terms, can be expressed as the problem of getting useful and meaningful data about the world.

Typically, knowledge is defined as “justified true belief”.  But this seems just wrong.  Once the intentionality problem is solved, beliefs come easily.  A theory of belief, based on leaving intentionality unexplained (but taken for granted) explains nothing.  AI (artificial intelligence) and computationism explain nothing, because they evade the whole question of intentionality.  So the core problem of knowledge should be the intentionality problem.  For ordinary life, this is where perception and perceptual learning are important.  For science, many of our scientific laws are actually definitions of the meaning of terms, so they are the scientist’s way of handling the problem of intentionality.

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