Jonah Tang

After discussing the shortcomings of empiricism in the last post, we move on to what might appear to be a solution to the empirical problem of extrapolation but, in fact, predates formal empiricism by about three millennia. Long before empiricism was formalized by Locke, logic was already widely used by the ancient Greek philosophers. Thus, an understanding of rationalism is very important to the understanding of knowledge and information.

The operation of rationalism was very well captured in the character of Sherlock Holmes, Doyle’s protagonist in his most famous detective series. In A Study in Scarlet, Holmes said that “from a drop of water, a logician could infer the possibility of an Atlantic or a Niagara without having seen or heard of one or the other. So all life is a great chain, the nature of which is known whenever we are shown a single link of it.”

According to Wikipedia, rationalism is the belief that “all knowledge, including scientific knowledge, could be gained through the use of reason alone”. Now, as mentioned in my previous post on empiricism, the scientist’s job is to doubt everything. That was what Descartes did, being the Renaissance man that he was. (Descartes was a lawyer, philosopher, mathematician, and theologian.) Assuming nothing, what can we prove? “Cognito, ergo sum”, said Descartes: I think, therefore I am. Assuming nothing, I can prove at the very least that I exist simply because the one who is thinking (assuming is thinking) exists and I am the one thinking.

Of course, after that axiom, Descartes could not prove that anything else exists without assuming that God, or some supreme ”thinker”, also exists. Based on this assumption, Descartes developed formal empiricism and is widely accepted as the father of modern philosophy. He is also widely accepted as the father of modern mathematics and laid the foundations on which Newton, Lorentz, and Einstein would build their theories.

Descartes was a developer of geometry which is a very ancient art that relies purely on rationalism. Geometry was first formalized by Euclid based purely on axioms such as: a point is that which has no dimensions, and a straight line is the shortest distance between two points. Descartes took it further. The Cartesian coordinate system uses the counterintuitive x, y, and z axes that are perpendicular to each other, rather than the bearing, azimuth, and distance away used by the polar coordinate system. Think about this: if you wanted to describe a location relative to you, would you say “5 yards in front, 3 yards to the left, and 4 yards up”, or would you just point (indicating both bearing and azimuth) and say how far away the location is from you? This is the main problem with rationalism. People who cannot handle abstract logic find it very difficult to accept, but those who do greatly appreciate the beauty of its mathematical elegance.

However, counterintuitive as it is, the Cartesian system greatly simplifies problems. Without describing coordinates as perpendicular axes, calculus would never have taken off as quickly as it did. Cartesian algebra and calculus is so simple that high school students can handle them with minimal effort while college students with concentrations in physics, mathematics, or computer science often have great difficulty applying polar algebra and calculus.

Moreover, while real experiments may produce variable results, thought experiments do not. For a long time, people such as Michelson and Morley tried to detect ether which they thought was the medium in which light propagated. They spent a lot of money on finding the best apparatus and a lot of time repeating the experiment to minimize random error, but they could only conclude within a certain standard deviation that they could not find the elusive “ether”. Not too long later, Einstein came along with an explanation that did not even require him to lift a finger in experimentation.

In the Einstein’s Mirror thought experiment, Einstein imagined that he was travelling in a train at the speed of light and looking in a mirror. He asked this question: would there be an image in the mirror since his face and the mirror was travelling at the same speed as light leaving his face? Essentially, if light was like sound, he would not because light would not be able to escape his face, yet it should. Thus, the theory of relativity was born and the laws of classical physics were overhauled without a single experiment.

In fact, later on, when the Rayleigh expedition proved conclusively that the theory of relativity was correct, Einstein was purported to have said that if it had proved otherwise, he “would be sorry for the good lord because the theory is correct”. Such is the confidence of rationalists on their approach, and rightly so. Unlike empirical knowledge, there is no standard deviation or confidence limit on knowledge derived logically from axioms. For any axiom A: if A then B; if B then C; therefore if A then C.

However, back to the problem that Descartes faced after proving that the “thinker” exists, faith is required to prove that anything else exists. I am very tempted to skip ahead and write on faith in the next post but the next two levels, priori and authority, also depend greatly on faith. Therefore, I will be writing on those in my next post.

Posted by Jun Ren Tang at 11:16 PM | Permalink | Comments (0)

The Information Renaissance is an assigned topic for this blogging assignment and I just thought that before jumping into what the Information Renaissance is, it would be nice to talk about what information is. I have read previously, probably about ten years ago, that there were seven layers, or types, of knowledge: empiricism, rationalism, priori, authority, faith, instinct, and one more that I have forgotten (or maybe there were only six and it was so long ago that I have forgotten how many there were). Knowledge is somewhat related to information so I believe that discussing these six (and the seventh if I remember or if someone who reads this happens to know what it is and tells me) would be helpful in any discussion of the Information Renaissance. In this post, I will discuss empirical knowledge since most modern scientists believe that it is the most applicable to modern science.

Empiricism, as defined by Wikipedia, is “a theory of knowledge emphasizing the role of experience, especially sensory perception, in the formation of ideas, while discounting the notion of innate ideas.” The scientific method proposes that scientific enquiry should begin with a general survey of the field followed by the formation of a hypothesis based on trends in certain aspects in the field. The final step is the empirical investigation to falsify the null hypothesis and establish the theory as current scientific fact that is valid until another empirical experiment falsifies its hypothesis. Thus, an understanding of empirical methods, especially its shortcomings, is crucial to anybody who wishes to claim that he/she is a scientist, especially an information scientist. So, what exactly is empirical knowledge? The following example gives some insights.

Anderson University, where I got my undergraduate degree, is not famous, or probably even “good” for physics. It has no particle accelerators, nuclear reactors, or any other “cutting-edge” instruments worth boasting about on the departmental website. So while students at the big schools were crashing elementary particles into each other, physics students at Anderson were reproducing the “classics,” the experiments that were done by Michelson and Morley, Newton, and other people who lived more than a century ago.

As we all know, the master’s job is not to contradict. However, the scientist’s job is to doubt everything. Hence, I questioned the wisdom of reproducing the experiments that have already been repeated a million times by people all over the world for at least the last hundred years, and which produced results that have already made it into science textbooks as “fact.” Of course, my professor was able to resolve the perceived contradiction. According to him, empirical knowledge is NOT current knowledge that is derived from experiments but knowledge that is derived from current experiments.

Newton and company may have gotten the same results for more than three hundred years, but it takes just ONE contrary experiment to disprove their theories. This is the scientific method, and this is empirical knowledge. It is what makes the scientific method work. As the great American physicist Richard Feynman famously said “You can know the name of a bird in all the languages of the world, but when you're finished, you'll know absolutely nothing whatever about the bird... So let's look at the bird and see what it's doing -- that's what counts.”

However, empiricism, especially pure empiricism, has its shortcomings. Is the moon still there when we stop looking at it? Does the clock actually move when we are not checking the time, or does it merely show the correct time when we do? When a tree falls in the middle of a forest so far from civilization that nobody observes it, does it make a sound? For the pure empiricist, we do not know for sure. We only know what we CURRENTLY observe. Previous experience counts for nothing because it takes only ONE valid contradiction to disprove the theory.

As Dr Groom often mentions in his research methodology class, case studies are only totally valid for the specific time, place, and people on which the case study is made. It cannot be applied to a “universe”. Therefore, while Feynman was absolutely right that observation is “what counts”, observation is limited to the time, place, and subjects that are observed. Observation does not tell us anything that can be reasonably extrapolated to other cases, which leads us to reasoning and rationalism which will be the topic of the next post in this series.

Posted by Jun Ren Tang at 12:08 AM | Permalink | Comments (0)