The scientific and manifest images

In 1960, Wilfrid Sellars gave some lecturers on the Scientific Image of Man and the Manifest Image of man.  These were later published, and seem to be available on the net as a pdf file.  Roughly, the scientific image is how the world looks to science (particularly physics), while the manifest image is how it looks to us.

Right now, I am looking at a table (actually, my desk).  And it presents itself to me as a solid object with a smooth surface.  That solid object can be said to be part of the manifest image.  However, science describes it as mostly empty space, but with an array of atoms.  The atoms are separated by space.  To science (that is, to physics), there really isn’t a surface nor anything particularly smooth.  This array of separated atoms in space is part of the scientific image.

Why the difference?

I will mainly be looking at the differences between those images, and discussing why there is such a difference.

In recent posts, I have been discussing how we get information about the world by means of carving it up into parts.  The way that we carve up the world gives us the manifest image.  The way that science carves up the world gives us the scientific image.

Perception – discrimination

Perceptual discrimination is the act of distinguishing between different items that are in the perceptual field.  In this post, part of my series on perception, I will look at barcode scanning to illustrate what discrimination is, and its role.  And I will use this example to further clarify the distinction between direct perception and indirect perception, at least as I use those terms.

These days, we see bar codes on many of the items that we purchase.  And the store clerk typically uses a scanner to read that bar code and identify which item we are purchasing.

Perception – direct vs. representational

The two most important theories of perception are representationalism on the one hand, and direct perception on the other.  There are probably many versions of each of those, and there are some other theories which I see as less important.  By far, the dominant theory — the one most widely accepted — is representationalism.  However, as mentioned in the previous post in this series on perception, I happen to prefer the idea of direct perception.

In this post, I plan to do to things:

• I will briefly describe both representationalism and direct perception, and their disagreements;
• I shall try to address some of the misconceptions about direct perception that seem to crop up.

RTH4 – Correspondence with reality

In my previous post in this series, I explained why I thought there were problems with truth as correspondence to the facts.  In this post, I will discuss the idea of truth as correspondence with reality.

There’s an intuitive sense in which “correspondence with reality” seems to be about what we think we mean when we talk about the truth of a statement.  The biggest difficult, though, is that we would need a good account of what “correspondence” means before we could ever get started with using truth.

Getting information

In an earlier post, I wrote:

That leaves, as one of the basic problems for a cognitive agent, the problem of getting information about the world.

In this post, I want to discuss why that is a problem.

Many people seem to hold the view that sensory cells in the body passively receive input from the world, and that how we perceive the world depends on what we do with that passively received data.  That seems to be the view of proponents of sense-data accounts and of proponents of computationalism.

The cognitive agent’s problem

A lot of theorizing about cognition has to do with the such questions as

• What is thinking, and how is it done?
• What is experience, and how come we have it?

Then, having selected such issues, theorists then set themselves the problem of how would one design an agent or a robot which can do such things as think and have experience.

When I started thinking about cognition, I took a different approach.  I looked at the problems that a cognitive agent needs to solve.  Most obvious, among those, is the problem of survival as a biological organism.  And, having settled on a problem that agent needs to solve, I set about trying to understand what could evolve to solve that problem.