Many scientists in Cognitive Science study the cognition of living beings, human or animal ones. However, some capacities of artificial beings are completely different from those of the living ones. Therefore, a new science, Artificial Cognition, will have the task to examine the behavior of artificial beings.
For Cognitive Science, living beings exist; we want to understand the reasons behind their behavior, and their capacities in various situations. We want to know how they memorize, remember, solve problems, take decisions, and so on. We observe them, we use medical imaging to detect what parts of a brain are active when the subject perform a task. One also devises ingenuous experiments that will show how the subject manages to solve a problem cleverly chosen. Naturally, we only study behaviors that exist for at least one kind of living beings.
The situation is different for Artificial Cognition: the goal is to build artificial beings rather than to observe them. Normally, we write computer programs, or we give knowledge to existing systems, and we try to obtain an interesting behavior. For that we usually utilize ordinary computers, but we can also build specialized machines, and this will be probably more frequently the case in the future. Living beings depend on mechanisms created by evolution, which uses mainly a remarkable element, the neuron. They may have extraordinary capacities for adaptation: we can learn to build houses, to write books, to grow plants, etc. Unfortunately, we have also limitations: we cannot increase the size of our working memory to more than about 7 elements; we can only use auxiliary memories such that a paper sheet. They are useful, but not as efficient as our internal memory. We can no more increase the possibilities of our consciousness, many mechanisms of our brain will always be hidden when we are thinking. This is a very serious restriction: consciousness is essential for learning, for monitoring our actions, for finding the reason of our mistakes, and so on.
On the contrary, in Artificial Cognition, we are not restricted to the neuron, we can build the mechanisms that we have defined. This possibility does not exist in the usual Cognitive Science: nature has built the beings that we want to study. In Artificial Cognition, we put ourselves in the place of evolution, which worked during billions of years on zillions of subjects. It succeeded in creating living beings, often remarkably adapted to their background. However, nobody is particularly well adapted to the artificial environments that man created, such as solving mathematical problems, playing chess, managing a large company, etc. As we have invented many of these activities, we have chosen them so that we can have reasonable performance in these domains, using capacities that evolution gave us for different goals such as hunting game for food. At the start, when on tries to build a new system, we are inspired by our methods, such as they have been discovered by Cognitive Science scientists. In doing so, we are using only a small part of the possibilities of Artificial Cognition, we must also utilize all the possibilities of computers, even those that we cannot have. Artificial beings will have much better performances than us when they use not only all of our methods, but also many other methods that we cannot use. We are unable to use many useful methods because we have not enough neurons, because they are not wired in the necessary way; it may be also simply because our neurons have intrinsic limitations, for instance, they do not allow to load new knowledge in our brain easily. Perhaps, there are capacities that evolution did not give us either because they were not useful for our ancestors, or because there are jumps that evolution cannot make.
The methodology and the potentiality of the usual Cognitive Science and of Artificial Cognition are very different. We are not limited to the existing beings, but it is very difficult to build new beings. However, there is a strong tie between these two sciences: building an artificial being is defining a model. If it behaves as living beings do, this model will give an excellent description of the mechanisms that Cognitive Science wants to find. On the other hand, when we want to build an artificial being, the first thing to do is always to start with the implementation of the methods that are used by living beings. Nevertheless, we have to progress from this starting point, and we will arrive perhaps some day to build artificial beings that will be able to achieve tasks extremely difficult for us. For instance, we will see artificial beings capable of building other artificial beings more effective than themselves.