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1
Artificial intelligence
Introduction
Although there is no clear definition of AI (not even of intelligence), it can be described as the attempt to build machines that think and act like humans, that are able to learn and to use their knowledge to solve problems on their own.
A 'by-product' of the intensive studies of the human brain by AI researchers is a far better understanding of how it works.
The human brain consists of 10 to 100 billion neurons, each of which is connected to between 10 and 10,000 others through synapses. The single brain cell is comparatively slow (compared to a microprocessor) and has a very simple function: building the sum of its inputs and issuing an output, if that sum exceeds a certain value. Through its highly parallel way of operation, however, the human brain achieves a performance that has not been reached by computers yet; and even at the current speed of development in that field, we still have about twenty years until the first supercomputers will be of equal power.
In the meantime, a number of different approaches are tried to build models of the brain, with different levels of success.
The only test for intelligence there is, is the Turing Test. A thinking machine has yet to be built.
2. Why the current approach of AI is wrong
These following thoughts do not deal with technical problems of AI, nor am I going to prove that humans are the only intelligent species (exactly the opposite, see section 5). What I want to show, is that the whole idea of AI needs to be changed in order to lead to more than just partial results.
2
2.1. Reference Points
Today's AI concentrates entirely on the brain. If you look at the human body, however, it is not clear where to draw the line between which parts of the nervous system belong to the brain, and which don't. But a number of functions are performed by the spinal cord, for example, like withdrawing the hand quickly when touching something hot. It can be vitally important that this action is taken as fast as possible, in order to limit the damage. The only way of doing so is through reflexes, without the intervention of the brain. This is not an example of intelligent decisions outside the brain, but it provides an entry point to the following.
Whenever you talk to somebody, you use a huge amount of assumptions about the background of your counterpart. You usually start with assuming that other person is almost identical to yourself, and by small misunderstandings and questions of him (for the sake of easier reading I will assume that our counterpart is male) you correct that picture you have. When you know somebody, you don't have a list of all his features in your mind, but you know the differences between you and that person (or the difference between him and a third party, be it a single person or a group). I cannot prove this, but it explains why it often is so difficult to describe somebody to another person, since that other person's reference point is different from your own.
We build relations between all the things we know, and we build classes of things by putting objects with certain similar features into one such class. But the most basic difference we see is the difference between ourselves and the objects, the not-ourselves. Man's first reference point is himself, which is obvious when looking around oneself: Isn't that cat looking very nosy at you? Doesn't that monitor's face look at you? Don't that car's headlights look into a certain direction? Haven't you taught that stupid computer programme who the master was, yesterday?
People's categories are based on people, first of all. This is not an intellectual decision, but a natural necessity. How could you ever find out anything without a first reference point that you could relate it to? This also is the reason why in children's minds everything 'lives': They live themselves, so why shouldn't other things? Why shouldn't that teddybear feel hunger, exactly like I do?
The point is clear: No knowledge can be accumulated without a reference point. AI doesn't obey this. Most 'intelligent' programmes are equipped with knowledge, but none has ever had a clear picture of itself that it could relate everything else to. This is the first deficiency.
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