"I shot the cat with my proton gun."

I often listen to lectures and audiobooks when I drive more than 2 hours because I don't always have the privilege of enjoying a good conversation with a passenger.  Recently I was listening to some philosophy of science podcasts on my iPhone while driving from Boston to New York when the following sentence popped into my head:

"I shot the cat with my proton gun."

I had just listened to three separate Podcasts (one about Kant, one about Wittgenstein and one about Popper) when the sentence came to my mind.  What is so interesting about this sentence is that while it is effortless to grasp, it uses two different types of concepts in a single sentence, a "proton gun" and a "cat."  It is a perfectly normal sentence, and the above illustration describes the sentence fairly well (photo credits to http://afashionloaf.blogspot.com/2010/03/cat-nap-mares.html for the kitty, and http://www.colemanzone.com/ for the proton gun).

Cat == an "everyday" empirical concept

"Cat" is an everyday "empirical" concept, a concept with which most people have first hand experience (i.e., empirical knowledge).  It is commonly believed that such everyday concepts are acquired by children at a young age -- it is an exemple of a basic level concept which people like Immanuel Kant and Ludwig Wittgenstein discuss at great length.  We do not need a theory of cats for the idea of a cat to stick.

Image from shadowpaw99

Proton Gun == a "scientific" theoretical concept

On the other extreme is the "proton gun." It is an example of a theoretical concept -- a type of concept which rests upon classroom (i.e., "scientific") knowledge.  The idea of a proton gun is akin to the idea of Pluto, an esophagus or cancer -- we do not directly observe such entities, we learn about them from books and by seeing illustrations such as the one below.  Such theoretical constructs are the the entities which Karl Popper and the Logical Positivists would often discuss.  

While many of us have never seen a proton (nor a proton gun), it is a perfectly valid concept to invoke in my sentence.  If you have a scientific background, then you have probably seen so many artistic renditions of protons (see Figure below) and spent so many endless nights studying for chemistry and physics exams, that the word proton conjures a mental image.  It is hard for me to thing of entities which trigger mental imagery as non-empirical.  

How do we learn such concepts?  The proton gun comes from scientific education!  The cat comes from experience!  But since the origins of the concept "proton" and the concept "cat" are so disjoint, our (human) mind/brain must be more-amazing-than-previously-thought because we have no problem mixing such concepts in a single clause.  It does not feel like these two different types of concepts are stored in different parts of the brain.

The idea which I would like you, the reader, to entertain over the next minute or so is the following:

Perhaps the line between ordinary "empirical" concepts and complex "theoretical" concepts is an imaginary boundary -- a boundary which has done more harm than good.  

One useful thing I learned from Philosophy of Science, is that it is worthwhile to doubt the existence of theoretical entities.  Not for iconoclastic ideals, but for the advancement of science!  Descartes' hyperbolic doubt is not dead.  Another useful thing to keep in mind is Wittgenstein's Philosophical Investigations and his account of the acquisition of knowledge.  Wittgenstein argued elegantly that "everyday" concepts are far from "easy-to-define." (see his family resemblances argument and the argument on defining a "game.")  Kant, with his transcendental aesthetic, has taught me to question a hardcore empiricist account of knowledge.

So then, as good cognitive scientists, researchers, and pioneers in artificial intelligence, we must also doubt the rigidity of those everyday concepts which appear to us so ordinary. If we want to build intelligent machines, then we must be ready to break down own understanding of reality, and not be afraid to questions things which appear unquestionable.

In conclusion, if you find popular culture reference more palatable than my philosophical pseudo-science mumbo-jumbo, then let me leave you with two inspirational quotes.  First, let's not forget Pink Floyd's lyrics which argued against the rigidity of formal education: "We don't need no education, We don't need no thought control." And the second, a misunderstood, yet witty aphorism which comes to us from Dr. Timothy Leary reminds us that there is a time for education and there is a time for reflection.  In his own words:  "Turn on, tune in, drop out."

Understanding versus Interpretation -- a philosophical distinction

Today I want to bring up an interesting discussion regarding the connotation of the word "understanding" versus "interpretation," particularly in the context of "scene understanding" versus "scene interpretation." While many vision researchers use these terms interchangeably, I think it is worthwhile to make the distinction, albeit a philosophical one.

On Understanding
While everybody knows that the goal of computer vision is to recognize all of the objects in an image, there is plenty of disagreement about how to represent objects and recognize them in the image. There is a physicalist account (from Wikipedia: Physicalism is a philosophical position holding that everything which exists is no more extensive than its physical properties), where the goal of vision is to reconstruct veridical properties of the world. This view is consistent with the realist stance in philosophy (think back to Philosophy 101) -- there exists a single observer-independent 'ground-truth' regarding the identities of all of the objects contained in the world. The notion of vision as measurement is very strong under this physicalist account. The stuff of the world is out there just waiting to be grasped! I think the term "understanding" fits very well into this truth-driven account of computer vision.

On interpretation
The second view, a postmodern and anti-realist one, is of vision as a way of interpreting scenes. The shift is from veridical recovery of the properties of the world from an image (measurement) to the observer-dependent interpretation of the input stimulus. Under this account, there is no need to believe in a god's eye 'objective' view of the world. Image interpretation is the registration of an input image with a vast network of past experience, both visual and abstract. The same person can vary their own interpretation of an input as time passes and the internal knowledge based has evolved. Under this view, two distinct robots could provide very useful yet distinct 'image interpretations' of the same input image. The main idea is that different robots could have different interpretation-spaces, that is they could obtain incommensurable (yet very useful!) interpretations of the same image.

It has been argued by Donald Hoffman (Interface Theory of Perception) that there is no reason why we should expect evolution to have driven humans towards veridical perception. In fact, Hoffman argues that natures drives veridical perception towards extinction and it only makes sense to speak of perception as guiding agents towards pragmatic interpretations of their environment.

In philosophy of science, there is the debate of whether the field of physics is unraveling some ultimate truth about the world versus physics painting a coherent and pragmatic picture of the world. I've always viewed science as an art and I embrace my anti-realist stance -- which has been shaped by Thomas Kuhn, William James, and many others. While my scientific interests have currently congealed in computer vision, it is no surprise that I'm finding conceptual agreement between my philosophy of science and my concrete research efforts in object recognition.