A problem in the artificial intelligence field is that 'there is no universally accepted definition of intelligence'. With this article I hope I can shed some light to this issue (or obscure it, who knows):
Intelligence: is the capacity to generate new information consistent with information previously assimilated or generated.
The key words in this definition are, information, new and consistent:
First we have the pure creative fields, like does belonging to the arts: music, panting, sculpture or literature, to name but a few. In all of them the artist shape his work according to the laws of harmony and beauty. Very interesting is the case of literature (in my opinion creation in its pure state) where the writer creates his work according to the rules present in the readers minds, so with language he brings them sensations, emotions, fillings and thoughts. And the artist is considered even more genius if his work gives birth to new beauty norms (new styles or trends) that differ from the established ones, but without doubt, are consistent with meta-laws of a superior rank.
Engineers, IT engineers, mathematicians, architects, etc. also create new information, but according to the rules of their own field: physical laws, availability of raw material and parts, rules of the underlying logic machine or mathematical laws. And usually their aim is to solve a specific problem or to satisfy some type of basic need. The information generating process in this cases can be compared to the physical process of building a house: we start with a target in mind (the building), and starting from an empty plot of land, we add new elements, which in turn allow adding more elements, until the house is completed.
The same happens in all fields of research, from the scientist in his lab, to the policeman who tries to solve a crime, and the doctor working to diagnose a disease: they must relate the data they collect with their knowledge, to elaborate theories (once again, new information) in order to explain the investigated phenomenon. Interestingly in this fields, it is quite common to use the expressions, find a solution or make a discovery. The underlying meaning of these expressions is that the information searched for is unknown or new for those who is doing the research, but it must be present in an explicit or implicit way in the information field in which the researcher is working.
At this point we can see that there is not much difference in the way the various knowledge fields have been built. A writer, a mathematician or an IT engineer do not differ very much in their way of working. All produce new information; only the laws that govern that information change.
We can also notice that the intelligent factor, the generation of new information, is present in almost any human activity. When we learn, in the school or from experience in every day life, we are not only storing new data in our mind, we are establishing links between the acquired information and what we have previously learnt. Those links in turn are what make up the understanding of any issue, that is, the capacity to internalize the explanation of the newly learned information based on what we already know. And those relationships between the acquired and the preexisting information are the new information that every intelligent process must generate. Also, when we perform any task, for example, prepare a meal fallowing a recipe we know well, we do not act without thinking. We must adapt what we know (the recipe) to our circumstances ("oops this ingredient is missing"). We establish links between what we know and what we encounter. Once again, this relationships are new information which allows us to qualify our performance as intelligent.
So, according to the enunciated definition and the exposed explanations, the generation of new and consistent information is what allows us to identify a process as intelligent. Is like radiation to nuclear reactions. There is radiation, then we have a nuclear reaction. Is there new consistent information, then we have intelligence.
I think that the definition of intelligence presented in this article is good for three reasons:
An interesting exercise to test these statements could be to apply this definition to the conversations, activities and tasks of every day life. Lets see if this article is in fact coherent and intelligent ;)
Disclaimer: I am in the process of correcting the English of this article.
Intelligence: is the capacity to generate new information consistent with information previously assimilated or generated.
The key words in this definition are, information, new and consistent:
- By information we mean, not only pure data, but also, the rules and laws that govern that data. These, at the same time can also be ruled by principles or meta-rules, and so on.
- By new we mean data unknown to the person, entity or system capable of acting intelligently. For example, when a teacher proposes a math problem to his pupils, its solution is new or unknown to them, but not for the teacher.
- Finally, we have an intelligent process, only if the generated information is consistent or coherent with the base information (data, rules and meta-rules). This criterion is commonly used to measure the level of intelligence the human thinking process result. In this way, a solution to a problem that actually solves nothing is considered a stupid thing: is not consistent with the problem. If the solution solves the problem, but requires a lot of time or energy, it is considered as not so intelligent. But, if the solution is correct and also efficient and effective in time and resources, then it is an intelligent one: it is consistent with the problem and with the 'minimum effort' law, for example. The more coherence the result has with the base information field, the more intelligent we can assume the generator process is.
First we have the pure creative fields, like does belonging to the arts: music, panting, sculpture or literature, to name but a few. In all of them the artist shape his work according to the laws of harmony and beauty. Very interesting is the case of literature (in my opinion creation in its pure state) where the writer creates his work according to the rules present in the readers minds, so with language he brings them sensations, emotions, fillings and thoughts. And the artist is considered even more genius if his work gives birth to new beauty norms (new styles or trends) that differ from the established ones, but without doubt, are consistent with meta-laws of a superior rank.
Engineers, IT engineers, mathematicians, architects, etc. also create new information, but according to the rules of their own field: physical laws, availability of raw material and parts, rules of the underlying logic machine or mathematical laws. And usually their aim is to solve a specific problem or to satisfy some type of basic need. The information generating process in this cases can be compared to the physical process of building a house: we start with a target in mind (the building), and starting from an empty plot of land, we add new elements, which in turn allow adding more elements, until the house is completed.
The same happens in all fields of research, from the scientist in his lab, to the policeman who tries to solve a crime, and the doctor working to diagnose a disease: they must relate the data they collect with their knowledge, to elaborate theories (once again, new information) in order to explain the investigated phenomenon. Interestingly in this fields, it is quite common to use the expressions, find a solution or make a discovery. The underlying meaning of these expressions is that the information searched for is unknown or new for those who is doing the research, but it must be present in an explicit or implicit way in the information field in which the researcher is working.
At this point we can see that there is not much difference in the way the various knowledge fields have been built. A writer, a mathematician or an IT engineer do not differ very much in their way of working. All produce new information; only the laws that govern that information change.
We can also notice that the intelligent factor, the generation of new information, is present in almost any human activity. When we learn, in the school or from experience in every day life, we are not only storing new data in our mind, we are establishing links between the acquired information and what we have previously learnt. Those links in turn are what make up the understanding of any issue, that is, the capacity to internalize the explanation of the newly learned information based on what we already know. And those relationships between the acquired and the preexisting information are the new information that every intelligent process must generate. Also, when we perform any task, for example, prepare a meal fallowing a recipe we know well, we do not act without thinking. We must adapt what we know (the recipe) to our circumstances ("oops this ingredient is missing"). We establish links between what we know and what we encounter. Once again, this relationships are new information which allows us to qualify our performance as intelligent.
So, according to the enunciated definition and the exposed explanations, the generation of new and consistent information is what allows us to identify a process as intelligent. Is like radiation to nuclear reactions. There is radiation, then we have a nuclear reaction. Is there new consistent information, then we have intelligence.
I think that the definition of intelligence presented in this article is good for three reasons:
- It is very simple and specific. I think it even admits a mathematical formalization.
- It isolates theintelligent fact that have in common the processes qualified that way.
- It fits the behavior patterns that common sense tell us are intelligent.
An interesting exercise to test these statements could be to apply this definition to the conversations, activities and tasks of every day life. Lets see if this article is in fact coherent and intelligent ;)
Disclaimer: I am in the process of correcting the English of this article.
