Humanity is rapidly entering the information age. The weight of the information economy is constantly growing and its share, expressed in total working time, for economically developed countries is already 40-60% today and is expected to increase by another 10-15% by the end of the century.

One of the criteria for the transition of society to the post-industrial and further to the information stage of development can be the percentage of the population employed in the service sector:

  • if in a society more than 50% of the population is employed in the service sector, the post-industrial phase of its development has begun;
  • if in a society more than 50% of the population is employed in the field of information and intellectual services, the society has become informational.

A number of publications note that according to this criterion, the United States entered the post-industrial period of its development in 1956 (the state of California overcame this milestone back in 1910), and the United States became an information society in 1974.

Recognizing the undoubted achievements of the United States and other countries in the field of informatization, it is necessary to understand that a certain proportion of the “information content” of these countries was created by moving a number of material, often environmentally harmful, industries to other countries of the world (“environmental colonialism”), as well as by attracting to the work of scientists from all over the world.

The law of exponential growth of the volume of knowledge.

According to scientists, it took 1750 years for knowledge to double from the beginning of our era, the second doubling took place in 1900, and the third – by 1950, i.e. already for 50 years, with an increase in the volume of information over these half a century by 8-10 times [1]. Moreover, this trend is increasing more and more, as the amount of knowledge in the world by the end of the twentieth century will double, and the amount of information will increase by more than 30 times. This phenomenon, dubbed the “information explosion”, is listed among the symptoms of the beginning of the information age, including:

  • rapid reduction in the doubling time of the amount of accumulated scientific knowledge;
  • Exceeding the level of material costs for the storage, transmission and processing of information of the level of similar costs for energy;
  • the opportunity for the first time to really observe humanity from space (the levels of radio emission from the Sun and the Earth in certain parts of the radio range have approached) [2].

The evolution of social systems (Porat’s diagram) [3].

The concept of a post-industrial society as a general sociological theory of development has been developed quite deeply by foreign researchers, including: D. Bell, J. Galbraith, J. Martin, I. Masuda, F. Polak, O. Toffler, J. Fourastier and others. Namely J. Fourastier defined post-industrial society as a “civilization of services”.

Domestic science turned to this issue much later. This was connected with ideology, in particular with the fact that in terms – post-industrial, informational – they saw an alternative to formational terms – socialist and communist society. The concept of the information society cannot be considered as one with different types of formations, because advancement to the information society is only the most optimal way for the existence and development of any of the modern and future formations.

Among domestic scientists who have made a significant contribution to the development of this area, it should be noted V.M. Glushkova, N.N. Moiseeva, A.I. Rakitova, A.V. Sokolova, A.D. Ursula and others. G.T. Artamonov, K.K. Colin and others

What is the essence and meaning of the informatization process? Approaches to the analysis of the real state and prospects for the development of the processes of informatization of society essentially depend on the answer to this question.

It is important to look at informatization as “a system-activity process of mastering information as a resource for management and development with the help of informatics in order to create an information society and, on this basis, further continue the progress of civilization” [4].

According to a number of authors, the informatization process should include three dialectically interconnected processes:

  • mediatization – the process of improving the means of collecting, storing and disseminating information;
  • computerization – the process of improving the means of searching and processing information, as well as
  • intellectualization – the process of developing people’s abilities to perceive and generate information (knowledge), i.e. the process of increasing the intellectual potential of society, including the use of artificial intelligence. Mass informatization of society is impossible without a computer with an intelligent (friendly) interface.

Specialists note [5] that, unfortunately, social informatization is often understood as the development of information and communication processes in society based on the latest computer and telecommunications technology. Informatization of society, in principle, should be interpreted as development, qualitative improvement, radical strengthening of cognitive social structures and processes with the help of modern information technology tools. Informatization should be “merged” with the processes of social intellectualization, which significantly increases the creative potential of the individual.

When discussed in the late 80’s. The concept of informatization of the country by scientists and specialists highlighted the main idea – it’s not so much the concept of informatization, but the concept of the development of society, all its structures, that informatization is a companion of democratization and is impossible without it.

The process of formation and development of the information society going on all over the world is of an objective nature and cannot but affect our country “from the outside”, but the weak progress in the democratization of our society leads to the absence of a serious social order “from the inside” to improve the information environment.

What is the information society? What is his image?

For example, according to A.I. Rakitova [6], a society is considered informational if:

  • any individual, group of persons, enterprise or organization anywhere in the country and at any time can receive, for an appropriate fee or free of charge, on the basis of automated access and communication systems, any information and knowledge necessary for their life and solving personal and socially significant tasks;
  • in society, modern information technology is produced, functions and is available to any individual, group or organization;
  • there are developed infrastructures that ensure the creation of national information resources in the amount necessary to maintain the constantly accelerating scientific, technological and socio-historical progress;
  • there is a process of accelerated automation and robotization of all spheres and branches of production and management;
  • there are radical changes in social structures, the result of which is the expansion of the sphere of information activities and services.

Scientists distinguish two main theoretical and methodological approaches to the informatization of society:

  • technocratic, when information technologies are considered a means of increasing labor productivity and their use is limited mainly to the areas of production and management;
  • humanitarian, when information technology is considered as an important part of human life, which is important not only for production, but also for the social sphere.

The reasons for the significant spread of the technocratic approach, the identification of the concepts of “informatization” and “computerization” are both objective and subjective. Objectively, the development of new technology in general and, in particular, computer technology is proceeding rapidly, has an “aggressive” character. On the other hand, there is a very significant number of people, both unfamiliar with the problem, and those for whom the introduction of such an identification into public opinion brings tangible financial or political dividends.

Informatization has a clear connection with the environmentally safe, sustainable development of society. The basis of the information economy is knowledge or an intellectual and information resource. Knowledge has undeniable advantages over material resources, strictly subject to the laws of conservation. If people take something from nature, environmental problems are exacerbated, but if they try to take something from their neighbors, conflicts and wars are generated. The socio-economic structure of society, based on the information economy, already essentially avoids most socio-economic and environmental problems and potentially involves the exponential development of society in its main parameters (“knowledge generates knowledge”).

The state policy in the field of informatization of Russia, which received a new impetus at the turn of 1993-1994, includes the following main areas:

  • creation and development of federal and regional systems and networks of informatization with ensuring their compatibility and interaction in the single information space of Russia;
  • formation and protection of information resources of the state as a national treasure;
  • ensuring the interests of national security in the field of informatization and a number of other areas.

The Concept for the formation and development of a single information space in Russia defines the priorities of users of state information resources in the following order: citizens, enterprises, government bodies.

The Concept of Information Security is being actively developed, which is an integral part of the National Security Concept of the Russian Federation and is an officially accepted system of views on the problem of information security, methods and means of protecting the vital interests of the individual, society and the state in the information sphere.

Social informatics – definition, subject field of research, methodological role.

Informatics is understood as a system of knowledge about the production, processing, storage and distribution of all types of information in society, nature and technical devices (in natural and artificial systems).

However, in public opinion, and not only in Russia, the idea was gradually established, according to which the concept of “computer science” is associated exclusively with the last environment – the technical one. There was a need to “protect” the subject field of research by specialists dealing with the problems of informatization of society with a special name. Similar reasons caused, for example, the emergence of a new name in the structure of cybernetics as scientific knowledge – social cybernetics.

The subject of study of social informatics as a science is the processes of informatization of society, their impact on social processes, including the development and position of a person in society, the change in the social structures of society under the influence of informatization [7].

Social informatics is a science that studies a complex of problems associated with the passage of information processes in society.

This new sociological scientific direction arose at the intersection of such disciplines as computer science, philosophy, sociology, and psychology. The term “social informatics” was first proposed by A.V. Sokolov and A.I. Mankiewicz in 1971.

One of the founders of social informatics, Academician A.D. Ursul considers social informatics as the scientific basis for the formation of the emerging information society.

Social informatics, like any scientific knowledge, has a multi-level structure:

Level 1 – theoretical and methodological (main categories, concepts and patterns of information processes in society);

Level 2 – medium (social “cut” of economic, legal, psychological and other aspects of informatization). This level can be called the sociology of informatization;

Level 3 – empirical (social aspects of the creation, implementation and adaptation of information technologies in the relevant subject areas).

The block diagram shows the structure of social informatics as scientific knowledge (social informatics in the broadest sense of the word):

Social informatics should play a methodological role for the so-called branch informatics: economic, legal, psychological, sociological informatics and others.

Any branch informatics, in addition to its subject field (development and adaptation of special information technologies), includes the second and third levels of social informatics as scientific knowledge, for example, legal informatics inevitably deals with social sections of the legal aspects of informatization and social aspects of the creation and implementation of legal information technologies.

At present, Russian universities are actively developing social informatics as a whole complex of academic disciplines [8].

The objectives of the training course “Fundamentals of Social Informatics” are:

  • creating the basis for the ability to correctly navigate the new information reality both in the world as a whole and in Russia;
  • formation of an idea of the urgent need to master computer literacy, without which organic inclusion in the modern information environment and active assistance to its development is impossible;
  • methodological preparation for further study, development and participation in the development of information technologies in the relevant subject area: sociology, psychology, economics, social work, journalism, legal sphere.


The variety of definitions of the concept of information testifies to its complexity, multidimensionality and causes the emergence and formation of information theories that are different in their orientation, and the theories themselves highlight only part of the facets of a certain system of knowledge, which can be called general information theory or “informology” – the science of processes and tasks. transmission, distribution, processing and transformation of information[1].

Statistical information theory.

The emergence of informology as a science can be attributed to the end of the 50s of our century, when the American engineer R. Hartley made an attempt to introduce a quantitative measure of information transmitted through communication channels.

Hartley took the “amount of information” transmitted over a communication channel regarding two equal outcomes and removing uncertainty by providing one of them, as a unit of information, called “bit”.

The creator of the statistical information theory K. Shannon generalized the result of Hartley and his predecessors. His works were a response to the rapid development in the middle of the century of communications: radio, telephone, telegraph, television. Shannon’s information theory made it possible to set and solve problems of optimal coding of transmitted signals in order to increase the throughput of communication channels, suggested ways to combat interference on lines, etc.

In the works of Hartley and Shannon, information appears before us only in its outer shell, which is represented by the relations of signals, signs, messages to each other – syntactic relations.

The Hartley-Shannon quantitative measure does not claim to evaluate the content (semantic) or value, useful (pragmatic) aspects of the transmitted message.

Cybernetic information theory.

A new stage in the theoretical expansion of the concept of information is associated with cybernetics – the science of control and communication in living organisms, society and machines. Cybernetics formulates the principle of the unity of information and control, which is especially important for the analysis of the essence of the processes occurring in self-governing, self-organizing biological and social systems.

The concept developed in the works of N. Wiener assumes that the control process in the mentioned systems is a process of processing (transforming) by some central device information received from sources of primary information (sensory receptors) and transferring it to those parts of the system where it is perceived by its elements as an order. to perform some action. Upon completion of the action itself, sensory receptors are ready to transmit information about the changed situation in order to perform a new control cycle. This is how a cyclic algorithm (sequence of actions) for managing and circulating information in the system is organized. It is important that the content of the information transmitted by the receptors and the central device plays the main role here.

Thus, the cybernetic concept leads to the need to evaluate information as some kind of knowledge that has one value measure in relation to the outside world (semantic aspect) and another in relation to the recipient, the knowledge accumulated by him, cognitive goals and objectives (pragmatic aspect).

Logical-semantic approach.

Attempts to build models of the concept of information, covering the semantic aspect of knowledge contained in a certain statement regarding the designated object, led to the creation of a number of so-called logical-semantic theories (R. Carnap, I. Bar – Hillel, J. G. Kemeny, E.K. Voishvillo and others). In them, information is seen as the reduction or elimination of uncertainty. It is natural to assume that by means of any language, with the help of statements created in it, it is possible to describe a certain set of possible situations, states, alternatives. The semantic information contained in any statement excludes some alternatives. The more alternatives a statement excludes, the more semantic information it carries.

Semantic theory of information.

In the considered theoretical constructions – statistical and semantic information – it was a question of the potential possibility to extract any information from the transmitted message. At the same time, in the processes of information exchange very often there are situations in which the power or quality of information perceived by the receiver depends on how prepared he is for its perception.

The concept of thesaurus is fundamental in the theoretical model of the semantic information theory proposed by Yu.A. Schreider and explicitly taking into account the role of the receiver.

According to this model, the thesaurus is the knowledge of the recipient of information about the outside world, his ability to perceive certain messages.

In the broadest sense of the word, thesaurus is a person’s vocabulary.

In the pragmatic concepts of information, this aspect is central, which leads to the need to take into account the value, usefulness, efficiency, economy of information, i.e. those of its qualities that decisively influence the behavior of self-organizing, self-governing, purposeful cybernetic systems (biological, social, man-machine).

Pragmatic concept of information.

One of the brightest representatives of pragmatic theories of information is the behavioral model of communication – the behavioral model of Ackoff-Miles. The starting point in this model is the target aspiration of the recipient of information to solve a specific problem. A receiver is in a “goal-oriented state” if it is striving for something and has alternative paths of unequal efficiency to reach the goal. A message sent to the receiver is informative if it changes its “goal-oriented state”.

The next stage in the development of pragmatic theories of information was the work of the American logician D. Harrach, who built a logical-pragmatic model of communication. One of the weaknesses of the behavioral model is its unpreparedness to evaluate false messages. Harrach’s model takes into account the social nature of human communication. In accordance with it, received messages must first be processed, after which messages “usable” are selected. It is from the totality of usable messages that the criteria of pragmatic value must be applied.

The family of sciences that specifically study information processes in one or another of their specific content and form grew quite rapidly in the second half of our century. These are cybernetics, systems theory, documentary, linguistics, symbolic logic, etc. The core that unites all these studies is the general theory of information – “informology”, which is based on syntactic, semantic and pragmatic concepts of information.

Formalization of knowledge: methods and techniques. Their effectiveness, comparative analysis.

When looking for the most convenient, rational means and forms of information exchange, a person most often faces the problem of a compact and unambiguous representation of knowledge.

Knowledge representation is a process, the ultimate goal of which is to place a certain amount of knowledge into a kind of “packaging” in which it can start moving through the channels of information exchange, reach the recipient, or linger in knowledge storage points. Such packaging can be a phrase of oral speech, a letter, a book, a reference book, a geographical map, a crossword puzzle, a picture, etc.

Each type of packaging has its own characteristics, but they all share one quality, although not to the same extent: the packaging is designed to ensure the safety of embedded knowledge. And not only and not so much physical, but semantic (semantic). For this, it is necessary that the sender and recipient of the packed knowledge information use some common system of rules for their representation and perception. We call such a system of rules the knowledge representation formalism.

Linguistic methods of knowledge formalization.

The most natural formalism suitable for a person is language (oral speech and writing).

Can any thought or knowledge be expressed in linguistic form? Apparently not. For example, there are dozens of different definitions of concepts – health, intelligence, thinking, information, etc.

A thought that cannot be expressed in a linguistic form cannot be included in the information exchange. Communication of people, thus, is carried out with the help of language as a form of knowledge representation. One and the same meaningful knowledge can be given a different verbal or textual form.

In some areas of human activity, the richness and variety of expressive means of natural language becomes more of a disadvantage than a virtue. For example, the words of the command must be short, sharp, have an unambiguous meaning, otherwise there will be no coordinated and clear joint actions of subordinates. In special branches of science, specific language systems are formed that are, as it were, a “narrowing” of natural language. The language of mathematics stands out as a certain basis for presenting a system of knowledge in the exact, natural sciences. Chemistry, physics, philosophy, etc. have their own language.

The expediency of using such narrowed language systems (dialects) makes it possible to increase the reliability of information exchange processes, since the possibility of misinterpretation of the transmitted information is reduced. At the same time, of course, the circle of recipients also narrows, since in order to perceive information, it is necessary to know the appropriate dialect. The main advantages of a narrowed language are the ability to create and use typical, “standard” packages of knowledge, as well as to largely remove polysemy (semantic ambiguity) present in a natural language.

Polysemy is the enemy of information exchange, a factor in introducing distortion and errors (semantic noise) on the way of information transfer. Therefore, the elimination of ambiguity is one of the most important directions in the development of formal methods of knowledge representation. The creation of the language of science or the language of business prose, often called “clerkship”, is a natural step along this path, a huge work of society over a number of centuries.

So “clerical” is intended to objectify the presentation of information, uses, as a rule, translatable categories and language forms, is devoid of synonymy, operates with specific facts and concepts, is informative (as opposed to informational redundancy), it is inherent in logic, it is algebraic in nature (thought, information , knowledge is expanded into a sequence of words and sentences, gradually forming in a complete, finished form by the end of the text). All these properties are not obligatory for the language of literature, which is characterized by the subjectivity of forms, the possibility of using untranslatable constructions, infinitely rich synonymy, imagery of statements, etc.

Structural methods of knowledge formalization.

Further progress towards the formalization of knowledge leads to the concepts of class and classification.

Classification – the distribution of objects, objects and concepts into groups (classes) according to the discovered properties.

In any emerging science, one of the first principles was the principle of systematization of knowledge. Therefore, classification as a method of scientific systematics immediately began to play an important role in the formation of the core of knowledge of a particular scientific direction.

Classification can manifest itself not only as a tool for organizing scientific knowledge, but also as a factor in social order. Therefore, the existing systems of tariffs and rates, academic degrees and titles, the structure of positions and service posts in the civil service and the army play not only an organizing, but also a stimulating role. Such a model of knowledge has received the name “hierarchical” in science and practice. Its advantages are that it is easy to learn, easy to maintain in working condition (easy to replenish and “clean”), effectively solves the problem of spreading new concepts across hierarchical levels.

Disadvantages of the hierarchical knowledge model:

  • direct connections between the concepts of neighboring levels are indicated weakly, or are completely absent;
  • hierarchical classification is most effective in those cases when the same type of relationship works during the transition from level to level, for example, genus-species.

The systematics underlying the classification can be used as a powerful means of directed exploratory search. So, sometimes it turns out to be useful when considering a group of objects to single out some of their characteristic features as defining ones and introduce a certain measure of the degree of manifestation of these features. This approach is called morphological, since it uses the idea of decomposing an object into its parts (features). Often such a grouping leads to the identification of patterns connecting the objects of each group, which were not known before.

The disadvantages of the hierarchical data model mentioned above are also characteristic of morphological models. They can be eliminated using the so-called branching (tree-like) models of knowledge representation. Separate concepts, facts, knowledge are interconnected by relations expressing the essence of the connections between them. As in the hierarchical model, these can be generic relations, but also other types of relations: “be a representative”, “have”, “inherit”, etc. The unambiguity of links in the tree structure and the variety of relations covered by it makes it possible to increase the “dynamism” of the knowledge system. Indeed, the system of knowledge represented by hierarchical or morphological models is static, or, as they say, declarative.

In a tree structure, you can trace the ascending and descending branches of connections, obtaining formulas for deductive (from particular to general), inductive (from general to particular) and inductive-deductive conclusions.

Thanks to such an organization, the presented knowledge acquires procedurality as an addition to declarativeness, i.e. the ability to derive general knowledge from the structure of relations and concepts. The tree-like structure of knowledge, despite the simplicity and prevalence of information exchange in everyday life, is still quite specific. In it, as in the previous model of knowledge, the paradigm of hierarchy is laid down. At the same time, the internal “world order” of some knowledge system may not correspond to this paradigm.

Consider, as an example, the concept of “workforce”. The totality of knowledge that describes a particular labor collective is extremely diverse, or, as they say, multifaceted. It is often not possible to establish hierarchical relations (genus-species) between aspects, although there is a connection between them. Here is one of the possible aspects: all representatives of the labor collective can be included alphabetically in the list indicating against the last name and first name of each employee the personnel number, year of birth, education, specialty, rank, length of service, etc. Let’s call this list – “List 1”.

Another aspect: all members of the team work on a piece-rate basis and the amount of their earnings is determined on the basis of the so-called. tariff grid. Therefore, having compiled a list of specialties and categories with an indication of the cost of one hour of working time, we form some idea of knowledge about the system of remuneration for members of this team. Let’s call this list “List 2”.

The third aspect: when calculating wages for each employee, we must take into account his actual output over a certain period of work (for example, per month). This means that the third list compiled, say, by the foreman of the site is a list consisting of personnel numbers and the time actually worked by the employee. This is “List 3”.

It is clear that all three lists contain the necessary amount of knowledge about the workforce when it comes to payroll. Similar models of knowledge representation, consisting of list structures linked to each other, are called relational.

There are other ways of representing knowledge besides the hierarchical, morphological, tree-like and relational models listed above. So, for example, the so-called semantic networks are intermediate between the tree-like and relational models. With their help, relationships are established between concepts, facts, knowledge. They are, as it were, a generalization of tree-like models. differ from the latter by removing the requirements of hierarchy. At the same time, semantic networks can be considered a special case of relational models, since it is from them that linked list structures can be built, when the concept that is a node of the semantic network is expanded into a list, and the corresponding relation with another list from a single one becomes a group one.

All the methods of knowledge formalization described above are aimed at creating some stable “bearing structure” on which the shell of a system of specific knowledge can be dressed. In the event that an understanding is reached between the sender and the recipient of knowledge, a mutual agreement regarding this supporting structure, then the information exchange acquires the necessary regulatory basis, which decisively increases its effectiveness.

Information technology.

Traditional information technology is usually understood as information technology based on “hard algorithms”.

Under the new information technology, as a rule, is understood information technology based on “soft algorithms”, using the achievements of artificial intelligence.

Matter, energy, information, knowledge – connection of concepts [2].

The initial premise is the assertion that information is the semantic essence of matter.

The concept of “matter” is identified with the concept of “system”, which includes constituent elements – substance, energy, knowledge and information. These elements, in accordance with the law of conservation of matter, maintain the system in an equilibrium state by mutual transitions from one substance of the system to another. When these elements of the system interact, the substance acts as a carrier of knowledge, and energy – the carrier of information:

Correlation between the concepts of information, data, knowledge.

Concepts – information, data, knowledge are often used as synonyms, despite the fact that they denote different objects.

Information is a universal property of matter, manifested in cybernetic communication processes.

Data is information that serves to draw a conclusion and a possible solution. They can be stored, transmitted, but not act as information.

Knowledge is the result of cognitive activity, a system of concepts about reality acquired with its help.

Information always has a “transport” connotation of transferring knowledge over communication networks, while knowledge is always associated with the personality of its creator.

The following figurative chain corresponding to the logical connection of the understood information, data, knowledge can be proposed – grain, flour, bread.

Problems of artificial intelligence.

Mass informatization of society is impossible without computers with intellectual (friendly) interest, based on the achievements of artificial intelligence (AI).

From research in the field of AI, the direction of knowledge engineering has separated, which is engaged in the identification, structuring, formalization of knowledge for the development of intelligent systems, knowledge-based systems, or expert systems (ES).

ES are computer systems that accumulate expert knowledge and fundamental knowledge in a particular subject area, have the ability to draw logical conclusions and act as electronic consultants for decision makers.

Systems based on knowledge of various subject areas (knowledge bases) are in great demand in the world today.

What is left in the field of AI research, so to speak, in the narrow sense of the word?

1. “Soft” computing. “Hard” calculations are work on algorithms, while “soft” calculations are calculations in which there can be new tasks and a random finding of what is needed. Thus, we are talking about evolutionary algorithms, modeling evolutionary processes.

2. Cognitive graphics (pythogram). This is not illustrative graphics, but graphics that generate new solutions (cognitive graphics). The operator’s eye fixes a certain regularity of the light spot – this is then removed from the computer as a blank for the future solution, i.e. cognitive graphics is a visual depiction of mathematics.

3. Virtual reality. The means of information technology and, in particular, the human-machine interface, make it possible to create a “virtual world” – an artificial three-dimensional space.

The first virtual reality firm was VPL Research (USA), founded in 1984 by Jeron Leinier, the author of the very term “virtual reality”.

4. Modeling of human reasoning (applied semiotic systems). The main problem is that human reasoning is not a system.

Thus, work on AI is being carried out in two complementary areas:

  • in the field of creating computer systems that have the ability to productively manipulate the existing volume of knowledge and generate new knowledge no less than a person.
  • in the field of disclosure of the mechanisms of thinking that a person possesses, with the aim of their subsequent modeling in a computer environment;

In this topic, the categories and concepts of theoretical informatics were considered, without which the analysis of information processes in society is impossible, in further topics the categories and concepts of social informatics proper will be considered.


Resource and socio-cultural concepts of the information environment as a space of social communications.

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