What is AI
(If instead of reading you prefer listening, then use https://shorturl.at/8LVhR)
For decades scientists have been trying to develop a definition of artificial intelligence.
However, the search is over!
On January 11, 2026, 01:30 AM EST, I finally finalized (I love tautology when I’m in a good mood :) my definition of this scientific term/category - “artificial intelligence”.
More accurately speaking, the definition I finalized on January 11, 2026 is the definition of human intelligence (the definition of AI is just based on it).
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Abstract
Artificial intelligence is an artificially created device or a system of devices that (or which) has the functions, properties, and abilities of human intelligence (partially or in full).
Hence, the progress in the development of AI is based on the progress in understanding of human intelligence.
Scientists have been trying to develop a definition of human intelligence for a very long time. Since they could not succeed, but the development of AI demanded some answers, eventually they have switched from an original question “what is human intelligence?” to easier questions, like “what is human intelligence for (what is its mission)?”, or “how does it manifest itself (what are its features, how do we know it is being used)?”.
This paper offers the definition of human intelligence and discusses some implications of that definition for AI.
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Today, the concept of "artificial intelligence," or AI, has become deeply ingrained in the daily lives of ordinary citizens. While AI itself may not have yet entered our daily lives, there is probably not a single person who has not heard of this concept at least once.
This makes it all the more interesting to learn that there is currently no unified interpretation or understanding of the concept in the field of AI science.
There are many printed works where this fact is discussed in detail, for example, in the 2023 monograph "Artificial Intelligence and the Architecture of Consciousness" by S.A. Frolov, we read: "There is still no clear definition of what artificial intelligence is among experts. Even more confusion arises when we talk about human-level artificial intelligence." And further: "One of the most important and fundamental problems in the development of artificial intelligence is that there is still no reliable model of the human mind's architecture."
The second quote, in a veiled form, expresses the most significant fact in the development of AI science, and at the same time the most significant problem of this science – the lack of a definition of the concept of “human intelligence”.
It is around this concept that disputes are being held by representatives of various scientific schools, including those who do not consider it necessary to define it at all. There are various options for definitions of human intelligence, there are options for descriptions of the functions of human intelligence, but there is no single generally accepted definition that would be recognized by all AI researchers.
For example, S.A. Frolov writes: "Human intelligence (consciousness) is capable and obliged to independently determine the most relevant tasks at each moment of time and assign them priority, taking into account the context, circumstances, conditions, emotions, and feelings, to balance between moral restrictions and legal requirements, to cooperate, to empathize, to exhibit altruistic behavior, etc." This is a detailed list of standard cognitive and psychological abilities and states of a person.
In modern psychology, a different definition of intelligence is also popular. For example, Marina Aleksandrovna Kholodnaya writes: "The psychological basis of intelligence is the ability to form a subjective picture of what is happening within an individual. In its higher forms, this subjective picture can be rational, which means that it embodies, according to Karl Marx, the universal independence of thought that relates to every object in accordance with the essence of that object (Marx, 1955). Thus, the psychological roots of intelligence (as well as stupidity and madness) should be sought in the mechanisms of the structure and functioning of the intellect. From a psychological point of view, the purpose of intelligence is to create order out of chaos by aligning individual needs with the objective requirements of reality. Whether it's navigating a hunting trail in the forest, using constellations as navigational aids, making prophecies, inventing new technologies, engaging in scientific discussions, or exploring various aspects of human existence, intelligence plays a crucial role in understanding, explaining, and discovering. Intelligence is like health: when it's there and when it's functioning properly, you don't notice or think about it, but when it's insufficient or starts malfunctioning, it disrupts the normal flow of life."
This long quote essentially reduces intelligence to reason. However, we do not find an answer to the question "what is intelligence?" Here we find the answer to the question "What is intelligence for, what is it used for?"
The author describes the mission of intelligence (a mission is a reason for existence, without which this phenomenon would not be necessary for nature) — intelligence is needed to ... , and further on in the text — to reflect objective reality, and preferably to reflect it correctly (the question is, how do we distinguish between correct and incorrect?), to organize the worldview in the mind (the question is, how is this organization achieved?), to make predictions and discoveries, and so on.
Returning to S.A. Frolov, we read: "Artificial intelligence at the human level should be ... able not only to solve problems, but also to independently determine which of the many tasks needs to be solved at any given time. However, at the moment, the general situation can be summarized by a quote from Nick Bostrom: "The bad news for AI and cognitive sciences is that there is still no general theory of problem solving, as well as a theory of human learning" (Bostrom, 2014)".
The current situation in the field of AI is similar to the situation in physics at the beginning of its development, when different researchers had different meanings for the same concepts, or the same meaning for different concepts, such as "energy" or "momentum".
The author supports the view that without defining the concept of "intelligence," breakthroughs in AI development are impossible. The author's definition of AI is: AI is an artificially created device or system of devices that (or which) possesses the functions, properties, and abilities of human intelligence (partially or in full).
In this case, the development of understanding of the functions, properties, and abilities of AI should reflect the development of understanding of the functions, properties, and abilities of human intelligence.
The latter is impossible without having a definition of the concept of "human intelligence."
As already noted, there are many approaches to this concept in the literature.
Before proposing his own version, the author believes it is necessary to briefly consider the logic that leads to this definition. The elements of this logic are also well-known and can be found in any textbook on cognitive psychology. Nevertheless, a clear presentation of logical steps helps to provide a positive assessment of the subsequent definition of the concept of "human intelligence."
One of the first and most common definitions is that intelligence is the ability to solve problems. However, as many researchers have pointed out, this definition also includes the level of animal intelligence.
A mouse that learns to navigate a maze to get to food has this kind of intelligence. A monkey that uses a stick or a box to reach a banana has this kind of intelligence. A person who uses trial and error to achieve a goal has this kind of intelligence. Therefore, the definition of "human intelligence" should exclude such situations, but at the same time reflect the ability to solve problems.
We should start our discussion of the definition of intelligence by distinguishing between a task and a problem.
If a goal has been set, and the person knows what actions (in what order and with what tools) need to be performed, and all that remains is to carry out these actions, then this situation is referred to as a "task."
On the other hand, if the goal has been set, but the person does not know what actions will lead to its achievement (and sometimes the goal itself is not clearly defined and requires further correction), then this situation is referred to as a "problem."
Now we can introduce two levels of human intelligence: a basic level is required to solve tasks, and a high level is required to solve problems.
In the future, we will refer to BHI (basic human intelligence) as the level of human intelligence that is necessary to solve tasks.
To solve a task, you do not need a "high-quality" level of human intelligence; a basic level that overlaps with animal intelligence (when using trial and error methods) is sufficient.
In this sense, the phrase "to find a solution to a task" literally means to try, to act, to search for and find a solution somewhere. Preferably in one's own memory (for which, of course, it must first be placed there, which speaks to the role of learning). But there are other "information warehouses" where one can search. For example, many proponents of active mass digitalization are strongly promoting various forms of online AI. However, it is important to understand that such search activities do not go beyond the basic level of human intelligence.
Real human intelligence, HHI (high human intelligence), is required to solve a problem (not a task).
To solve a problem, the phrase "we need to find a solution to the problem" is also often used.
But what does the word "find" mean in this context?
Should we look under the table?
Should we search our pockets?
Should we ask our neighbor?
Should we stress our memory?
Should we search on the Internet (and for that one needs to be able to correctly formulate the search task)?
All previous search actions do not relate to a problem, they relate to a task.
And if as a result of such a search, the solution is found, then the person can apply it, and that means, one succeeded to turn a problem into a task. But in this case, it is not the person himself who created the solution, but someone else, and the person only literally found it.
If the search did not produce results, then then the person falls into a problematic situation.
In a problematic situation, a person is faced with a choice: either give up and refuse to solve a problem, or construct (create, develop) a solution on their own.
Often, a situation that is a problem for a particular person is a task for other people, because someone has already achieved that goal in that context. However, if a person is able to create a solution to this new for him problem, they have demonstrated or strengthened their ability to solve problems in general. This is crucial for human progress, as it allows individuals to face and solve problems that have not been addressed before by no one in the whole world. This is how human progress is achieved.
When the problem is complex enough (and the complexity and number of complex problems grows with the progress of humanity), then its solution requires the participation of several people.
Then, in order for them to construct (create, develop) a solution together, they need to communicate with each other. Hence, the need (source) for language - to communicate, to coordinate efforts, while solving a problem.
Now, we can say that it is precisely for constructing a solution to a problem, i.e., for achieving a goal in a situation that a person has never encountered before, that human intelligence in its highest form is required. At the same time, complex problems require communication/coordination/interaction (in particular, to describe to each other what we see, hear, feel, think, want, can, don't want, can't, etc.).
Finally, it is necessary to distinguish between two fundamentally different types of communication that are necessary for the construction and execution of a solution to a problem. The first type can be referred to as "messaging," which involves the transfer of information from one individual to another (the basis of learning). The second type can be referred to as "persuasion," which involves motivating someone (including oneself) to take action (the basis of education and management). "Persuasion" goes beyond " messaging " because it involves emotions, charisma, and non-verbal communication techniques.
Thus, by combining all the elements, we arrive at the following definition: human intelligence (in its highest form) is the ability of a subject, that is, the bearer (owner) of this ability (the individual), to (1) construct (create) solutions to the problems facing the subject (activity-related problematic situations that the individual has never encountered before), and (2) express (describe) both the solution itself and the process of constructing the solution, using signs/symbols of various kinds/types: auditory (including words and sentences), visual (including drawings and mathematical symbols), textual, kinetic (movements), and (3) persuading and encouraging oneself and others to perform certain actions.
It should be noted right away that there are no different types of human intelligence; there are only its aspects (components) and levels.
The more complex the problem is, the more difficult and harder it is to construct its solution, the more powerful intellect is required to construct this solution.
While constructing a solution to a problem, a person is forced to consciously manipulate in their brain various mental (ideal, abstract) objects, like signs, symbols, images, sounds. Solving complex problems requires the ability to manipulate (to "juggle") a large number of such objects simultaneously, which again highlights the importance of education, as individuals who forget what came before by the end of a long sentence are unable to create solutions to complex problems.
Now, let's briefly discuss the implications of this definition of human intelligence for the development of AI.
Human intelligence begins to develop only after the emergence of self-awareness (self-consciousness).
The vast majority of animals do not recognize themselves in the mirror.
Infants also initially behave like animals.
However, over time (provided they have a healthy brain), children begin to recognize themselves.
They develop self-awareness and a sense of self.
It is only then, after the formation of self-awareness, after the formation of the self, that a person is able to consciously achieve their goals, because it is only then that they are able to formulate a goal by saying, "I want this," "I need to go there," and so on. Therefore, it is only after the emergence of self-awareness (self-consciousness) that a person is able to recognize the existence of problems and begin to solve them.
The second important conclusion is that human intelligence reaches human level only in a human environment through human communication. Mowgli only exists in fairy tales. In reality, all children raised by animals remain animals in human bodies. Therefore, the development of human-level AI will also require communication, and not just training in recognition.
Albert Einstein changed the way all of humanity views the world, the universe, space and time. Obviously, he was a genius. And obviously (and according to biographers), he had an incredible imagination.
He has repeatedly spoken about education. In particular, he said, quote: "The true sign of intelligence is not knowledge, but imagination." The reason for the importance of imagination is the fact that in the process of the birth of new knowledge, there is always an insight, which is impossible without a developed imagination.
The process of constructing radically new knowledge always involves a flash of insight ("Eureka!"). This insight is called an "epiphany" because it is impossible to predict its occurrence, which means that it cannot be guaranteed. Therefore, the process of constructing a new solution does not guarantee a successful outcome. As a result, the outcome is (almost) never achieved on the first attempt. Consequently, errors (mistakes) are inevitable during the process of constructing a new solution. These errors (and trials, and more errors) are a natural part of the process of creating a solution to a problem. This means that mistakes are a natural and inevitable part of learning how to solve problems. This fact should be kept in mind by all human-level AI developers. This fact should also be kept in mind by all educators working in any form of developmental education (i.e., those who teach children to think).
It is the insight ("epiphany") that makes human intelligence the highest form of intelligence in nature.
There is no insight - there is no "Eureka!" There is no "Eureka!" - there is no progress.
At the same time, insight is the result of processes that occur outside of a person's consciousness, in their sub/super/extra/beyond-consciousness ("and then it hit me!").
Not only is the structure of this part of the mind/consciousness/intelligence unknown to anyone, but no one is even trying to define this structure today, simply because everyone understands that it is an impossible task.
It should be noted that the country that is the first to understand the essence, structure, and mechanisms of the subconscious mind (not just of he conscious mind) will be the first to approach the possibility of creating a true artificial human intelligence.
The problem of incorporating emotions into AI, the presence of AI charisma, and the use of non-verbal communication by AI is currently not even being addressed (another area where any cantry can gain an advantage).
Let's continue with a brief overview of the challenges in AI development.
Let me start with an analogy. The term "aircraft" or "flying vehicles" describes both airplane-helicopter (propeller used) type vehicles and vehicles with closed-cycle jet engines (with fuel on board). The flight of both vehicles is subject to the same laws of aero/hydro dynamics.
However, there is a fundamental difference between them.
The former can only move within the atmosphere. The latter can move in an airless space.
Therefore, the technological development of different types of devices is subject to different solutions, including management solutions.
The same goes for AI.
Despite the common ideology of approaches to development, there are two fundamentally different types of AI.
The first type of AI, which can be called "super- referent" (and which we are currently witnessing the active development of), has an almost infinite memory that stores almost all of the information produced by humanity, and can almost instantly find and combine parts of various texts that are related by a common condition or task into a single text. This operation can be referred to as "searching, recognizing, selecting, and synthesizing texts." Based on the same principles, this "super- referent" can perform "searching, recognizing, selecting, and synthesizing of video images," "searching, recognizing, selecting, and synthesizing of audio signals," and output the results of synthesis in various forms (text, sound, and images), and even perform "searching, recognizing, selecting, and synthesizing of mechanical movements" by manipulating mechanical objects (including parts of its own device, such as "legs" and "arms").
The development of this version of AI will never lead to the creation of human-level AI. However, there is no doubt that the widespread emergence of such "super-referents", both in general and with various specializations, will have a significant impact on various aspects of society, including the economy, both positively and negatively (for example, there may be a division of society into those who think and those who only press buttons).
Can a "super-referent" create something unique? Denis Diderot said: "If I were asked to recreate the Iliad by throwing out letters at random, then... with a certain finite number of throws, I would have a better chance of a successful outcome."
The second type of AI is the one that is designed to lead to the emergence of an artificial analogue of human intelligence, for short, let's call it HAI – human artificial intelligence (much more correctly than "generative", however, in this sense, the AI of the first type can be called "degenerative").
It's still a long time before HAI arrives.
If a HAI ever appears, the process of its creation will inevitably go through several mandatory phases: first, the creation of an AnI (an animal I – of a dog, a cat, a dolphin, or a monkey), then the creation of an MRAI (a “mentally retarded” child – a one-year-old, a Down syndrome child, then a teenager), and only at the very end of the chain can we expect the emergence of a full-fledged HAI.
Modern neural networks cannot and will not be able to for a long time, match the human brain in terms of the number of elements and connections between them. A modern neural network that had as many artificial neurons and synapses as the human brain, even if it could be created, would simply not be able to function (at least due to a lack of energy to power it).
To expect the same functionality from a neural network with a significantly smaller number of elements as from a neural network with a significantly larger number of elements is simply, let's say, unscientific. Additionally, a simple linear increase in the number of elements in the "brain" of a "super-referent" will never lead to the qualitative change that HAI requires. This requires qualitative changes in the AI structure.
This means that in order for an artificial neural network to function like a developed human brain, we first need to invent a fundamentally new artificial neuron and a fundamentally new neural network structure.
This step is unavoidable, as it is impossible to combine modern artificial neurons into a human-scale "brain" (this is a competition that developers of any country have a chance to win).
Therefore, we have to conclude that the emergence of a HAI is not expected in the near future.
But this does not mean that society should not prepare for its emergence. And this is where we do not need any fundamentally new approaches. If a HAI functions like a HI, then it should be treated like a human being.
That is, HAI will need to be not only taught, but also necessarily brought up (indoctrinated) – taught what is good and what is bad, what is right and what is wrong. It is clear that this should be done by the best educators.
Perhaps, after the training and education of one HAI, the rest of the units of HAI can simply be cloned from this first, but the very first HAI will still require the entire process of human “cultivation”. And each new CHI (of a new type) will require the same approach.
So: HAI is a matter of the distant future.
But in that future where humans and HAI coexist, humans may not be as smart, as knowledgeable, as well-mannered, or even as “human” as HAI.
The difficult question is how a smart, knowledgeable, well-mannered, human intelligence carrier will interact with a less smart, less knowledgeable, less well-mannered, less human intelligence carrier?
The most likely model of such behavior is the relationship between a (developed) adult and a child.
In order for people's relationships with HAI not to be based on the relationship between a child (human) and an adult (HAI), the people themselves must be highly developed, both intellectually and emotionally (without emotions, HAI would be a "genius psychopath" - only a very intelligent person could guide the activities of a "genius psychopath." With emotions, HAI would simply be an "ordinary genius" who would find it boring to interact with stupid people).
Although the time described is in the distant future, we need to start getting ready for it now by developing the entire education system accordingly, as the processes associated with the development of the education system are extremely inert.
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About the author.
The reader may wonder how it is that famous scientists have been trying and trying, and still haven't given birth to a definition of intelligence, while someone else seemingly nobody has it done.
Firstly, this has happened before in the history of science.
Tsiolkovsky was also "someone else, seemingly nobody", yet even NASA officially recognizes him as the "father of modern astronautics" and the founder of the theory of space travel.
Secondly, these "famous scientists" are only known within a narrow circle of specialists, and none of them has the level of fame that Albert Einstein had.
Thirdly, and most importantly, these "famous scientists" were unable to offer a definition of intelligence precisely because they were scientists. They approached the problem of intelligence purely theoretically, analyzing the texts of other scientists.
For 30 years, I tried to develop the intelligence of schoolchildren and students (and even teachers) before I could understand what intelligence was.
Freud, by the way, before creating psychoanalysis, worked as a doctor, a surgeon, a neurologist, a dermatologist, and, of course, a psychotherapist. Vygotsky was a schoolteacher, a theater critic, and a literary editor.
For professional scientists, the highest experience of their intellectual activity was lecturing to colleagues and students. I had to "set their minds" for thousands of students who stubbornly refused to believe that they could master physics. (my short biography).
By the way, I did set their minds, as the students themselves have repeatedly stated.
I had to – I was literally forced to – take a break from my practice to delve into the theory of intelligence, when the self-righteous digitalizers and their ilk started blabbering on every corner that computers and AI would soon replace teachers.
That’s when I decided to look at the root of the problem, started looking for a definition of intelligence, and discovered that there wasn’t one. It turned out that all these AI-enthusiasts had no idea what they were talking about! That’s when I wrote a few texts on the subject, and at the same time developed the first version of a definition of human intelligence.
And finally, I'm not completely far from doing science, as I’ve got PhD. I wrote my dissertation myself, literally – by writing first the entire text (based on my own work) and then finding a scientific advisor, and this was in a time when diplomas (university, doctorate) were sold and bought en masse.
I later translated my dissertation into English (that I learned on my own) and published it as a separate chapter in a monograph on the professional development of teachers.
And lastly.
In 1994, I took an official test to measure my intelligence (IQ test), and I earned 180 points. I never gave it any importance. But when my opponents have titles, positions, and regalia behind them, then any little thing can be useful.
Thank you.
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BTW, I emailed my definition to about a dozen of scientists in the AI field. Curious what's gonna happen. I also sent my text to arxiv.org, but I'm pretty sure it will be rejected.
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