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Reflections on the Limits of Artificial Intelligence

Ubiquity, Volume 2004 Issue December | BY Alexandru Tugui 


Full citation in the ACM Digital Library

Nature is very simple and efficient in everything she makes, and is extremely obvious. We humans like to simulate in an extremely complicated manner what exists quite simply in nature, and what we succeed in simulating falls in the category of artificial intelligence. Artificial intelligence has limits of scope, but they fade away when compared with the performances of natural intelligence. In this study, we undertake to outline some limits of artificial intelligence compared to natural intelligence and some clear-cut differences that exist between the two.

Abstract: Nature is very simple and efficient in everything she makes, and is extremely obvious. We humans like to simulate in an extremely complicated manner what exists quite simply in nature, and what we succeed in simulating falls in the category of artificial intelligence. Artificial intelligence has limits of scope, but they fade away when compared with the performances of natural intelligence. In this study, we undertake to outline some limits of artificial intelligence compared to natural intelligence and some clear-cut differences that exist between the two.

Keywords: intelligence, limits, artificial, robots, digit, law of entropy, ABAC.

Man has always had nature and environment as models for his various achievements, and using those models he succeeded in making machines, tools, and robots with impressive performances. It's been speculated that in the next 40 - 45 years computers could reach the performance of the human brain, and that achievements in the field of artificial intelligence will be quite amazing, even to the extent of making synthetic workers (humanoid robots) with performances very much like a human's. Could all this be really possible? We shall live (some of us by our offsprings) and ... we shall see!

Communication leads to intelligence

The basic idea of the living world consists in transmitting to future generations what is considered important for survival. Over time, a collective memory was created. The modality of transmitting information was complex: from signs to body language, from drawings to speaking as such, from chopped stone to magnetic support. Communication eventually reached various performances:

1. From simple to simple, for instance: speaking - speaking, seeing - speaking, speaking - seeing;

2. from simple to complicated, for instance: speaking - representing, seeing - representing;

3. from complicated to complicated, for instance: representing - representing.

Note: Representing is a codification approach according to a certain algorithm.

The last two variants of communication always assumed a certain technology by means of which communication as such could be made: seeing, speaking, writing, reading. Under such circumstances, we should notice the fact that whereas some people had direct access to this collective memory, other people had an indirect access by traditions and habits.

It is common knowledge that an immediate connection between natural intelligence and the modality of transmitting information and knowledge among the members of a community is made directly. Consider, for instance, the situation of children raised in the wild, who take over the collective memory of the animals with which they live.

In other words, from the beginnings of mankind to the present, people tackled the issue of sharing information among the members of the same community or of different communities, of the same times or of different times. A first stage consisted in the communication based on simple drawings. This communication modality was simple and accessible to all people without needing additional training, because everything was visual!

Then the period of using certain symbols followed, symbols that are hard to understand by those who are unskilled, which limited the access to the transmitted/communicated information. This stage also comprises the period of alphabet use.

The information period assumed the complication of the modality of transmitting data, information, knowledge.

At first sight, everything seems very simple, but data digitizing assumes a set of operations that would eventually lead to the representation as strings of 0 and 1. We show this with the following example: we find by sheer accident a magnetic support on which data and information are stored. To know (see) such data and information, we have to access them with a specialized peripheral depending on the magnetic support, to manage them with a utilitary program, and finally to process them with specialized software. All these steps are necessary because simply seeing such data and information is of no help.

Considering the above, we may synthetize communication between two individuals into one of the following three variants:

    Man (1) - Man (1)

    Man (1) - MMMan (natural) (1)

    Man (1) - intermediary - Man (2)

    Man (1)- peripheral - MMMan (radio, TV, phone, computer peripheral) (2)

Note: MMMan - many men. The index 1 accounts for the fact that the communication process is simultaneous, whole index 2 gives us the clue that there is a discrepancy between the two moments.

We think that artificial intelligence must take into account the communication modalities and the coupling of the intelligent entities to the collective memory of every community.

When will a computer "grow up"?

As we consider the evolutionary character of artificial intelligence, we naturally wonder When will a computer "grow up"? — when we could speak of an "artificial intelligence" of matter, and have contextual procedures that cover most circumstances that occur. In other words, we speak of a transmitted intelligence based on limited, difficult-to-generalize case studies.

Anyway, there are situations of denial of natural intelligence — and we have to acknowledge that, once "formatted," the raw matter of natural intelligence can hardly ever be recovered. We are speaking of children grown in the wild, who lose some of the partial characteristics of their natural intelligence — for example the capacity of formulating sentences even if they have a quite rich vocabulary.

People start learning when they are young! They learn from others' experience (by the rules transmitted via various modalities); they learn from their own experience (by the rules they compile).

We all accept the idea that natural intelligence is specific to the living world, and from this perspective we cannot imagine that humankind will ever reach that level of development that would enable the simulation of natural intelligence in full detail. We think this could be possible only to a certain extent, only if a hybrid system between the living cell and the technical system is made — the so-called bio-techno-system. But one should not misunderstand this idea! The bio-techno-system does not assume the achievement of a technical system having incorporated a sequence of software procedures to simulate the biological system, but the coupling of a living organism and of a technical system where the informational interaction is made by means of the computer system.

The answer to the question above is the more obvious the closer we are to a success in the bio-techno-system field.

Some limits of artificial intelligence

We see on various Internet sites posted discussions, courses and opinions on the future performance of artificial intelligence application fields.

Nevertheless, the specialists in the field are challenged to create equipment and software able to cope with the performance of the human brain. There are assessments of time and memory requirements, operation speed, ethics regarding how such an artificial intelligence system should look and operate. There are even worries that humankind will have to face an additional risk if some intelligent informatic entities are not restricted in running processes and in making major decisions, if they can program themselves (re-writing codes, re-compiling), etc.

Nevertheless, at this point we should take into account certain restrictions and limitations pertaining to artificial intelligence that we will not succeed in overcoming. These are some of these limits:

    1. Artificial intelligence must take into account the law of entropy. At this point, the relevant achievements do not take them into account and do not succeed in simulating them. In nature, the law of entropy leads to the stabilization of any type of system. The passage from a high level of entropy to a low one and vice-versa consumes energy. Most common movements in nature are the result of applying the law of entropy to a given system. We think that by the symbiosis between the living cell (living organism) and the technical systems, the intelligent control of matter could be achieved;

    2. The entire foundation of artificial intelligence is based on informatic procedures that mean to circumscribe the intelligent behaviour of a human being, although experts never succeeded in simulating the behaviour of an ape with an ABAC. As we saw previously, the human being has the quality of complicating things very much when he knows what he must do but mostly when he does not know where he is heading. Therefore, we consider that when the goal is not known very well, the human brain both functionally and structurally will complicate even further the solution procedures, which consumes time and considerable information resources. We strongly believe that bio-techno-systems can be a solution to this problem;

    3. The two pillars of computer science, "0" and "1" together with the truth values "True" and "False" are major borders in artificial intelligence. Any intelligent information procedure is decomposed eventually in strings of "0" and "1", which leads us to the fundamental objection that intelligent machines will never be like humans. We have to consider that bio-systems also work with intermediary values;

    4. Artificial intelligence is based very much on symbolic logic, and has not succeeded in involving so-called affective logic. In affective logic, combinations of truth values may lead to different evaluations. A possible solution could be obtained by using affective computing [1], which undertakes to model affective behavior in various situations.


We believe that we will make considerable progress in the applicative and theoretical fields of artificial intelligence. The limits we synthetized are and will be felt for a long time, yet they will decrease as new materials and new technologies are discovered. At the same time, bio-techno-systems will be solution with a particular technological impact on the evolution of artificial intelligence.




1. Bergeron, B. (2002) Dark Ages II. When the Digital Data Die, Prentice Hall PTR, New Jersey, 2002

2. Denning, P. J., Metcalfe, R.M. (eds.) (1997) Beyond Calculation. The Next Fifty Years of Computing, Copernicus, Springer-Verlag, New York

3. Mesarovic, M., Pestel, E. (1975) Mankind at the Turning Point: The Second Report to the Club of Rome, Reader's Digest Press, New York

4. Moore, A.D. (1969) Invention, Discovery and Creativity, Anchor Books, New York

5. Tugui, A., Fatu, I. (2004) What is the Globally Information Based Society Followed By? in Cyber Society Forum, at

6. Tugui, A. (2004) Calm Technologies in a Multimedia World, in Ubiquity, ACM, Vol. 5, Issue 4, 17-23 March.






About the Author Alexandru TUGUI, PhD, is a Senior Lecturer at "Al. I. Cuza" University, Iasi, Romania


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