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No one really knows what intelligence is and how it works, although we all deal with intelligence all the time, both our own and the intelligences around us. Intelligence is both an individual and a social phenomenon, perhaps intelligence can only be developed in a society where both knowledge transfer and exchange of experience and competition are possible. All this contributes to the development of intelligence.

There is a generally accepted understanding of intelligence that is more or less consistent both at the individual level and among various institutions. Many would agree that the hallmarks of intelligence would be the ability to learn and interact socially. Also the ability to apply the knowledge and skills acquired to solve problems, achieve goals, and develop, both one’s own and group success. It is important to have different views on the nature of intelligence and how best to define and measure it.

Philosophers have debated the nature of intelligence for centuries. Some view intelligence as the ability to reason and acquire knowledge through logic. Others view intelligence as acquiring knowledge from experience and the senses. More recently, developmental theories view intelligence not as a fixed ability, but as an ability that grows through active exploration and interaction with the environment.

There is a view that sees intelligence as a property of the mind. Intelligence is proposed to be studied through IQ tests and tasks that aim to quantify general cognitive abilities such as thinking, memory, spatial skills and speed of information processing. IQ tasks provide a measure of a person’s intelligence compared to others. There is a valid criticism: IQ tests measure only specific skills, under specific conditions and constraints, missing other important aspects of intelligence. One can train the ability to pass specific IQ tests, but how does that help with real-world tasks?

Anthropologists study intelligence in relation to specific cultural environments. They argue that intelligence has different manifestations in different cultures and corresponds to different historical and social contexts. Applying the values and concepts of one culture to assess intelligence in another can be problematic.

There is a theory of multiple intelligences that suggests expanding the definition beyond verbal and logical-mathematical skills to also include interpersonal, musical, spatial, naturalistic, and other aspects. An interesting concept, it shows that intelligence is not only about high IQ, but also many abilities in different areas.

Artificial intelligence has emerged from the capabilities of computer technology. Which at the basic level can perform primitive operations on transfer, storage and processing of data in the form of sequences of arithmetic-logical operations and program control instructions. Creation of really intelligent systems on the basis of such primitive technologies, with appropriate properties inherent in natural intelligence, is a big challenge. And, by and large, no one has achieved any significant results in this area, despite the hype surrounding the topic. What can be said about today’s AI? There are useful tools, especially based on generative models, which help in solving various tasks, but no more.

The easiest way to study intelligence is from top to bottom, from the general to the particular. We all deal with intelligence all the time. For us, intelligence is a common thing, it is not something outlandish and incomprehensible. This simplicity and accessibility is what is misleading. In fact, we do not understand what intelligence is, or rather we do not understand it at all, although we use it all the time. Yes, there are a couple dozen definitions from different points of view, there is no one universal and comprehensive.

The beginning of understanding what intelligence is, occurs when we realize that we know very little about it, and are ready to be open to new concepts and unexpected knowledge, especially in the light of recent scientific breakthroughs and achievements. Conventionally, approaches to the study of intelligence can be divided into two groups. The first is the high-level study of how intelligence works. The second is the study of natural intelligence at the physical level, from the simplest natural phenomena such as DNA sequences to the workings of the human brain and other living organisms. Building artificial intelligence also contributes to general understanding and progress.

Building intelligent systems or knowledge frameworks is very limited. The essence of the limitation is that there can be only two approaches to intelligence work: 1 – pattern recognition based on experience, 2 – inference based on reasoning. If in the first case everything is clear, consider that immediately there is a ready-made solution or a ranked list in which the most probable solutions are selected. In the second case, chains of reasoning can be very complex, branching, interrupted, etc. It can consist of many stages or steps. At each step, the same principle of two possibilities is at work, a decision pattern may finally emerge, or it may be necessary to go back to reasoning.

Scientific research and hypotheses that have advanced our understanding of intelligence

In the early 1900s, psychologists, including Alfred Binet, began creating the first intelligence tests to detect learning disabilities in children. This marked the beginning of intelligence testing and the concept of IQ.

The theory of multiple intelligences was proposed by Howard Gardner. This theory states that there are at least eight different types of intelligence including musical, interpersonal, logical-mathematical, kinetic, etc. This disproved the idea that intelligence is pro one type such as logical intelligence.

Emotional intelligence was introduced by psychologists Peter Salovey and John Mayer. Emotional intelligence includes abilities such as emotion management, empathy and reading social cues. This emphasized the importance of non-cognitive aspects of intelligence.

Advances in brain imaging such as fMRI, PET scans, and EEG have allowed scientists to study and map brain regions that are activated during different cognitive tasks. This has shed light on the neural basis of intelligence. But this does not mean that we have figured out how everything works; on the contrary, the complexity of the brain is staggering. We can’t, like a computer program, see data dumps and trace execution. We can only record activity, and that’s not enough.

The first ideas of artificial intelligence were born by researchers such as Alan Turing, and the development of AI showed the complexity of the problem and the limitations of human cognition. The AI systems created nowadays are mainly based on machine learning models. The idea of machine learning is that on training data the model can learn to reproduce the required result without explicit programming. The idea is interesting, but there is a clear disadvantage: if the data is not representative, i.e. does not cover all typical cases, the model will not work adequately. In fact, it is an approximation by some signs and examples, which is clearly insufficient.

Studies of twins and families have shown that general intelligence is inherited. Identifying specific genes associated with intelligence is an active area of research. It’s a strange thing, such research should be viewed with disbelief, but this line of research should not be dismissed. Overall, an open question.

Large long-term studies of intelligence in childhood and adulthood have shown that cognitive ability is influenced by health, education, and social factors. This has demonstrated the potential for improving IQ. Of course, intelligence can be trained and developed apart from one’s own efforts, social environment, environment are key factors for success.

These studies and hypotheses have advanced the scientific understanding of human intelligence and emphasized its multidimensional nature and potential for growth. Ongoing research seeks to further uncover the biological, social, and other factors that shape intelligence. We are still only at the beginning of the journey, there is a big gap in our understanding of high-level processes and the physics of how it can work. Also, we should not forget that we have many theories and hypotheses, not absolute truths. New research will break down old knowledge, and new hypotheses will push the boundaries of knowledge.