Human thinking is a complex cognitive process that includes the use of many different techniques, methods and forms of cognition. The differences between them are conditional, and very often all these terms are used as synonyms, but it makes sense to make some distinction between them. The methods of thinking and scientific knowledge are understood as general logical and general epistemological operations used by human thinking in all its spheres and at any stage and level of scientific knowledge. They equally characterize both everyday thinking and scientific thinking, although in the latter they acquire a more definite and ordered structure. Methods of thinking, as a rule, characterize the general, epistemological orientation of the course of thought at a particular stage of cognitive activity. For example, when moving from the whole to the part, from the particular to the general, from the concrete to the abstract, etc.
Methods are called more complex cognitive procedures, which include a whole set of different research methods.
A method is a system of principles, techniques, rules, requirements that must be followed in the process of cognition.
This definition of a method expresses its operational essence; the method contains a set of requirements that characterize the order of cognitive operations. Aspects of the method: subject-content, operational, axiological.
The subject content of the method lies in the fact that it reflects knowledge about the subject of research; the method is based on knowledge, in particular, on the theory that mediates the relation of the method and the object. Many philosophers admit that the method is the same theory, but turned with its edge to the knowledge and transformation of the object; it is a system of normative rules derived from a theory (or from certain knowledge in general) for the purpose of further knowledge of an object. The subject richness of the method testifies to the presence of an objective (objective) basis for it. The method is meaningful, objective.
The operational aspect indicates the dependence of the method is no longer
as much from the object as from the subject. The formation of rules-prescriptions is significantly influenced by the level of scientific training of a specialist, his ability to translate ideas about objective laws into cognitive techniques, his experience in applying certain techniques in cognition, the ability to improve them; considerations of convenience and "economy of thought" influence the choice and development of rules. Often, on the basis of the same theory, modifications of the method arise, depending only on subjective moments. Method is subjective, or subjective (for that matter).
The axiological aspect of the method is expressed in the degree of its reliability, economy, efficiency. The scientist sometimes faces the question of choosing one of two or more similar methods. A decisive role in the choice may be played by considerations related to greater clarity, comprehensibility or effectiveness of the method. When in the 1920s a discussion on questions of methodology took place in our country and a part of natural scientists faced the problem of which method to give preference to - elemental (mechanistic) or systemic ("dialectic") - the physiologist A.F. Samoilov stated, in particular : "Those Marxists who are inspired by the belief in the power of the dialectical method in the knowledge of nature, if at the same time they are specialists in the natural sciences in any particular area of natural science, must prove in practice that by applying dialectical thinking, the dialectical method, they are able to go further rather, with less labor than those who follow the other path. If they prove this, then without any struggle, without excessive fruitless offensive polemics, the dialectical method will win its place in natural science. The natural scientist is not, above all, stubborn. He uses his present method only and solely because his method is the only method. I would like to use the worst method, and not the best, not in the world. Prove in practice that the dialectical method leads rather to the goal - tomorrow you will not find a single natural scientist who is not a dialectician" ("Dialectics of Nature and Natural Science" // "Under the Banner of Marxism", 1926, No. 4-5, p. 81) .
These are the main aspects of the method of scientific knowledge: subject-content, operational and axiological.
Methods of scientific knowledge can be divided into three groups: special, general scientific, universal. Special methods are applicable only within individual sciences. The objective basis of such
methods are the corresponding special-scientific laws and theories. These methods include, for example, various methods of qualitative analysis in chemistry, the method of spectral analysis in physics and chemistry, the Monte Carlo method, the method of statistical modeling in the study of complex systems, etc. General scientific methods characterize the course of knowledge in all sciences. Their objective basis is the general methodological laws of cognition, which also include epistemological principles. These include: methods of experiment and observation, the modeling method, the hypothetical-deductive method, the method of ascent from the abstract to the concrete, etc. Universal methods characterize human thinking in general and are applicable in all spheres of human cognitive activity (taking into account their specificity). Their objective basis is the general philosophical patterns of understanding the world around us, man himself, his thinking and the process of cognition and transformation of the world by man. These methods include philosophical methods and principles of thinking, including the principle of dialectical inconsistency, the principle of historicism, etc.
Methods of scientific thinking.
Analysis and synthesis. Analysis is a method of thinking associated with the decomposition of the object under study into its constituent parts, aspects, development trends and modes of functioning with the aim of studying them relatively independently. Synthesis is the opposite operation, which consists in combining the previously identified parts into a whole and in order to obtain knowledge about the whole by identifying those essential connections and relationships that unite the parts previously identified in the analysis into a single whole. These two interrelated methods of research receive their concretization in each branch of science. They can turn from a general technique into a special method: for example, there are specific methods of mathematical, chemical, and social analysis. Analytical Method received its development in some philosophical schools and directions. The same can be said about synthesis.
abstraction and idealization. These methods belong to the general scientific methods of research. Abstraction is a process of mental selection, isolating individual features, properties and relations of a particular object or phenomenon that are of interest to us in the context of the study, and at the same time abstraction from other properties, features, relationships that are insignificant in this context. Temporary distraction from a number of features, properties and relationships of the studied pre-
metov allows a deeper understanding of the phenomenon. Depending on the goals of research, different types of abstraction are distinguished. If you need to create general concept about a class of objects, an abstraction of identification is used, during which one mentally abstracts from dissimilar features and properties of a certain class of objects and singles out common signs that are common to the entire class. There is also such kind of abstraction as analytical or isolating abstraction.
Idealization is a relatively independent method of cognition, although it is a kind of abstraction. The results of idealization are such concepts as "point", "line" in geometry, "material point" in mechanics, "absolutely black body" or "ideal gas" in physics, etc. In the process of idealization, there is an extreme abstraction from all real properties of the object with the simultaneous introduction into the content of the formed concepts of signs that are not realizable in reality. A so-called ideal object is formed, which can be used by theoretical thinking when cognizing real objects. For example, the concept of a material point does not really correspond to any object. But a mechanic, operating with this ideal object, is able to theoretically explain and predict the behavior of real, material objects, such as a projectile, an artificial satellite, a planet in the solar system, etc.
Induction, deduction, analogy. Induction is a characteristic method of research for the experimental sciences. When using this technique, thought moves from knowledge of the particular, knowledge of facts to knowledge of the general, knowledge of laws. Induction is based on inductive reasoning. They are problematic and do not provide reliable knowledge. Such conclusions, as it were, "lead" the idea to the discovery of general patterns, the justification of which is later given in other ways. In the literal sense, induction means induction.
Reception, according to the epistemological orientation opposite to induction, is deduction. In deductive reasoning, the movement of thought goes from knowledge of the general to knowledge of the particular. In a special sense of the word, the term "deduction" denotes the process of logical inference according to the rules of logic. Unlike induction, deductive reasoning gives reliable knowledge, provided that such knowledge was contained in the premises. In scientific research, inductive and deductive methods of thinking are organically linked. Induction leads human thought to hypotheses about causes and general laws.
dimensions of phenomena; deduction makes it possible to derive empirically verifiable consequences from general hypotheses and in this way to substantiate or refute them experimentally.
Analogy. With an analogy based on the similarity of objects in some respects, properties and relationships, an assumption is made about their similarity in other respects. Inference by analogy is just as problematic as in induction, and requires its further substantiation and verification.
Modeling. Inference by analogy underlies such a method of research, which is now very widespread in science, as modeling. In general, modeling, due to its complex complex nature, can rather be attributed to the class of research methods than techniques. Modeling is such a research method in which the object of interest to the researcher is replaced by another object that is in relation to the similarity to the first object. The first object is called the original, and the second is called the model. In the future, the knowledge gained in the study of the model is transferred to the original on the basis of analogy and similarity theory. Modeling is used where the study of the original is impossible or difficult and involves high costs and risks. A typical modeling approach is to study the properties of new aircraft designs on their reduced models placed in a wind tunnel. Modeling can be subject, physical, mathematical, logical, symbolic. It all depends on the choice of the nature of the model.
A model is an objectified in reality or mentally represented system that replaces the object of knowledge. Depending on the choice of means of constructing the model, different types of modeling are also distinguished. With the emergence of new generations of computers in science, computer modeling has become widespread on the basis of programs specially created for this purpose. Computer modeling includes the use of mathematical and logical modeling.
Observation is the original method of empirical knowledge. Observation is a purposeful study of objects, based mainly on such sensory abilities of a person as sensation, perception, representation; in the course of observation, we gain knowledge about the external aspects, properties and characteristics of the object in question.
The cognitive result of observation is a description - fixation -
tion by means of the language of initial information about the object under study. The results of observation can also be recorded in diagrams, graphs, diagrams, digital data, and simply in drawings.
The structural components of observation include: the observer himself, the object of study, the conditions of observation and the means of observation - installations, instruments and measuring instruments.
At first glance, it may seem that observation refers to passive, purely contemplative means of cognition, and certainly in relation to experiment it is such. But with external passivity in observation, what is called the active character of human cognition is fully realized. Activity is manifested primarily in the purposeful nature of observation, in the presence of the observer's initial attitude: what to observe and what phenomena to pay special attention to. This also determines the second moment of activity of observation, namely, its selective character. However, in the process of observation, the scientist does not ignore phenomena that are not included in his attitudes. They are also recorded and may eventually become the basis for establishing the main facts. The activity of observation is also manifested in its theoretical conditionality. We defined observation as a method based on the sensory cognitive abilities of a person, but rational ability in the form of theoretical attitudes is also constantly manifested in observation. In methodology, the phrase is widely known: "A scientist looks with his eyes, but sees with his head." So an amateur and a geologist, looking at the same piece of rock, see, observe different things. Similarly, the layman and the egologist, observing the behavior of animals, will record different results of this observation. F. Bacon was wrong, who hoped to clear his mind of all "idols" before the observation. In practice, this would mean the erasure of all the knowledge that the scientist received in the process of education. The best example of this is the work of Galileo, who created a telescope to observe celestial phenomena, which led to significant progress in the collection of empirical material in this area. The activity of observation is also manifested in the selection by the researcher of the means of description.
It is possible to construct a fairly rich classification of types of observation, which we cannot do here. Let us note only two important types of observation, which differ in their attitude towards a qualitative and quantitative description of phenomena. Qualitative observation has been known to man since ancient times. The science of modern times begins with the widespread use of quantitative observations and, accordingly,
vein descriptions. This type of observation is based on the measurement procedure. Measurement- this is the process of determining the ratio of one measured quantity characterizing the object under study to another homogeneous quantity taken as a unit. An example is the procedure for measuring a person's height or weight. The transition of science to quantitative observations and measurement underlies the emergence of the exact sciences, since it opens the way to their mathematization and makes it possible to make the experimental verification of theoretical hypotheses more effective.
Experiment is, like Observation, the basic method at the empirical stage of cognition. It includes elements of the observation method, but is not identical to the latter. It is a more active method of studying an object than observation. Practical intervention in the course of research in it is mainly associated with the search for suitable conditions for observation or the use of appropriate devices that enhance the human senses. With the development of the experimental method, the scientist turns from an observer of nature into a natural scientist. Metaphorically speaking, this method enables the scientist to "question nature."
An experiment is an active, purposeful method of studying phenomena in precisely fixed conditions of their course, which can be recreated and controlled by the researcher himself. The experiment has a number of advantages over observation: during the experiment, the phenomenon under study can not only be observed, but also reproduced at the request of the researcher; under experimental conditions, it is possible to detect such properties of phenomena that cannot be observed in natural conditions; the experiment makes it possible to isolate the phenomenon under study from complicating circumstances by varying the conditions and to study the phenomenon in its "pure form"; Under the conditions of the experiment, the arsenal of devices, tools and apparatus used is sharply expanded.
In the general structure of scientific research, the experiment occupies a special place. On the one hand, it is the experiment that is the link between the theoretical and empirical stages and levels of scientific research. By design, an experiment is always mediated by prior theoretical knowledge: it is conceived on the basis of relevant theoretical knowledge, and its goal is often to confirm or refute a scientific theory or hypothesis. The results of the experiment themselves require a certain theoretical interpretation. However, the experimental method
by the nature of the cognitive means used, it belongs to the empirical stage of cognition. The result of experimental research is, first of all, the achievement of factual knowledge and the establishment of empirical patterns.
Another important epistemological feature of the experiment is its simultaneous belonging to both cognitive and practical human activities. The purpose of experimental research is to increase knowledge, and in this respect it belongs to the field of cognitive activity. But since the experiment involves a certain transformation material systems, it is a form of practice. Experiment, being a form and method of cognition, at the same time acts as a basis and criterion for the truth of knowledge, albeit on a limited scale. The boundary between experiment and other forms of practical activity is relative, and in some cases, when it comes to a large-scale industrial or social experiment, the latter turns out to be a full-fledged form of practical activity.
The experimental method, having arisen in the depths of physics, then found wide distribution in chemistry, biology, physiology and other natural sciences. At present, the experiment is increasingly spreading in sociology, acting both as a method of cognition and as a means of optimizing social systems. In essence, since the time of Galileo, the experimental method has not undergone significant changes in terms of its structure and role in cognition. Significant changes have taken place in the technical equipment of the experiment, new types of experiment associated with the use of computers have arisen, and the scope of the experimental method has expanded. The fundamental novelty in the understanding of the experiment, perhaps, concerns only the need to take into account the interaction of the object under study with measuring instruments, which in the time of Galileo did not seem relevant.
The following types of experiment are distinguished: 1) research, or search, experiment; 2) verification or control experiment; 3) reproducing; 4) insulating; 5) qualitative or quantitative; 6) physical, chemical, social, biological experiment. A research, or search, experiment is aimed at discovering new phenomena unknown to science or their new, unexpected properties. For example, a series of experiments with conductors at various temperatures ended at one time
discovery of the phenomenon of low-temperature superconductivity. And experiments with conductors of complex physical and chemical composition have recently led to the discovery of high-temperature superconductivity. Experiments with cathode rays resulted in the discovery by Roentgen of a new type of penetrating radiation, named after him, and experiments with x-rays led to the discovery of radioactivity by A. Becquerel. In developed sciences, a verification or control experiment plays an important role. The object of verification is one or another theoretical prediction or one or another hypothesis. In relation to theoretical hypotheses, the experiment can be confirming, refuting and decisive. An experiment is confirmatory if it is conceived to confirm the empirically verifiable consequences of a hypothesis; accordingly, it will be refuting if it is put for the purpose of refutation. It is called decisive if the goal is to refute one and confirm the other of two (or more) competing theoretical hypotheses. This difference is relative. An experiment conceived as a confirmatory experiment may turn out to be a refuting one, and vice versa. As for the decisive experiment, due to the complex and ambiguous nature of the connection between theory and experience, many researchers deny its existence, although at a certain stage of the rivalry of hypotheses, it can create conditions for a temporary preference for one of them. An example of a verification experiment is one of the experiments to test the wave theory of light. At the beginning of the last century, S. Poisson, analyzing the mathematical part of Fresnel's wave theory of light, came to an unexpected conclusion: if this theory is correct, then a white spot should form in the center of the shadow formed by an impenetrable screen in the path of a point light source. This conclusion was nothing more than an empirically verifiable consequence of Fresnel's theory, which seemed highly improbable to both corpuscular and wave theory proponents of light. According to Poisson, an experiment was later set up to disprove Fresnel's theories, but instead, his results brilliantly confirmed Fresnel's theory. The white spot in the center of the shadow was discovered and named Poisson's spot.
A special kind of experiment is thought experiment. If in a real experiment a scientist, in order to reproduce, isolate or study the properties of a particular phenomenon, puts it in various real physical conditions and varies them, then in a mental experiment
In the case, these conditions are imaginary, but the imagination is strictly regulated by the well-known laws of science and the rules of logic. The scientist operates with sensory images or theoretical models. The latter are closely related to their theoretical interpretation, so a thought experiment is more theoretical than empirical methods research. Thought experiment cannot be considered as a form of human practical activity. It can be called an experiment in the proper sense only conditionally, since the way of reasoning in it is similar to the order of operations in a real experiment. A classic example is Einstein's thought experiment with a free-falling elevator. The result was the formulation of the principle of equivalence of heavy and inertial mass, which is the basis of the general theory of relativity.
Conducting an experimental study includes a number of stages. The first stage includes the planning of the experiment, during which its purpose is determined, the type of experiment is selected, and its possible results are thought out. It all depends on the research problem that the scientist is trying to solve. In the course of planning an experiment, it is essential to identify those factors that influence the phenomenon under study and its properties, as well as to identify a set of those quantities that must be controlled and measured. The second stage of the experiment is connected with the choice of technical means for conducting and controlling the experiment. The technique used in the experiment, including measuring instruments, must be practically verified and theoretically substantiated. Statistical control methods are widely used in modern experiment. The experimental study ends with the stage of interpretation of the results of the experiment, which includes statistical and theoretical analysis, as well as interpretation of the results of the experiment.
Hypothesis as a form and method of theoretical research.
The purpose of theoretical research is to establish laws and principles that allow one to systematize, explain and predict the facts established in the course of empirical research. There was a period in the history of methodology when some scientists and philosophers believed that the main method of theoretical research is the inductive method, which makes it possible to logically derive general laws and principles from facts and empirical generalizations. But already at the end of the XIX century. it became clear that such a method to build
it is forbidden. There is no unambiguous discursive path leading from knowledge of facts to knowledge of laws. A, Einstein stated this in his own way. Having proclaimed that the highest duty of physicists is the establishment of general laws, he adds that "it is not a logical path that leads to these laws, but only intuition based on insight into the essence of experience" (Einstein A. "Physics and Reality". M., 1964, p. . 9). But what Einstein calls "insight-based intuition" is actually complex. cognitive technique, called the hypothesis method, within which the researcher's intuition is manifested.
In methodology, the term "hypothesis" is used in two senses: as a form of existence of knowledge, characterized by problematic, unreliable, and as a method of forming and substantiating explanatory proposals, leading to the establishment of laws, principles, theories. A hypothesis in the first sense of the word is included in the hypothesis method, but it can also be used outside of it.
The best way to understand the hypothesis method is to get acquainted with its structure. The first stage of the hypothesis method is familiarization with empirical material subject to theoretical explanation. Initially, they try to explain this material with the help of laws and theories already existing in science. If there are none, the scientist proceeds to the second stage - putting forward a guess or assumption about the causes and patterns of these phenomena. At the same time, he tries to use various methods of research: inductive guidance, analogy, modeling, etc. It is quite possible that at this stage several explanatory assumptions are put forward that are incompatible with each other.
The third stage is the stage of assessing the seriousness of the assumption and selecting the most probable one from the set of guesses. The hypothesis is tested primarily for logical consistency, especially if it has a complex form and unfolds into a system of assumptions. Next, the hypothesis is tested for compatibility with the fundamental intertheoretical principles of the given science. For example, if a physicist, while explaining facts, finds that his explanatory assumption is in conflict with the principle of conservation of energy or the principle of physical relativity, he will be inclined to abandon such an assumption and look for a new solution to the problem. However, there are periods in the development of science when the scientist tends to ignore some (but not all) of the fundamental principles of his science. These are the so-called revolutionary or extraordinary periods,
when a radical breaking of fundamental concepts and principles is necessary. But the scientist takes this step only if everything has been tried. traditional ways problem solving. Thus, the founders of electrodynamics were forced to abandon the principle of long-range action, which was of fundamental importance in Newtonian physics. M. Planck, having tried many ways of the traditional explanation of the radiation of a completely black body, abandoned the principle of continuity of action, which until that moment was considered "inviolable" in physics. N. Bohr called such hypotheses "crazy ideas". But what distinguishes these ideas and conjectures from schizophrenic delusions is that, while breaking with one or two principles, they remain in agreement with other fundamental principles, which determines the seriousness of the proposed scientific hypothesis.
At the fourth stage, the proposed assumption is unfolded and empirically verifiable consequences are deduced from it. At this stage, a partial reworking of the hypothesis is possible, the introduction of clarifying details into it with the help of thought experiments.
At the fifth stage, an experimental verification of the consequences derived from the theory is carried out. A hypothesis either receives empirical confirmation or is refuted as a result of experimental verification. However, the empirical confirmation of the consequences of the hypothesis does not guarantee its truth, and the refutation of one of the consequences does not unequivocally testify to its falsity as a whole. All attempts to build an effective logic of confirmation and refutation of theoretical explanatory hypotheses have not yet been successful. The status of an explanatory law, principle or theory is given to the best hypothesis based on the results of verification. From such a hypothesis, as a rule, the maximum explanatory and predictive power is required. Hypotheses are of particular value, from which the so-called "risky predictions" (K. Popper's term) are derived, which predict unbelievable facts in the light of existing theories or empirical intuition. These risky predictions primarily include the prediction by Mendeleev based on the hypothesis of the periodic law of the existence of unknown chemical elements and their properties, or the prediction by the general theory of relativity of the deviation of a beam of light passing near the Sun from a straight path. Both predictions received experimental confirmation, which contributed to the transformation of the periodic law and the general theory of relativity from hypotheses into theories.
Familiarity with the general structure of the hypothesis method allows us to define it as a complex complex method of cognition, which includes all its diversity and forms and is aimed at establishing laws, principles and theories.
Sometimes the method of hypothesis is also called the hypothetical-deductive method, bearing in mind the fact that putting forward a hypothesis is always accompanied by a deductive derivation of empirically verifiable consequences from it. But deductive reasoning is not the only logical device used in the framework of the hypothesis method. When establishing the degree of empirical confirmation of a hypothesis, elements of inductive logic are used. Induction is also used at the stage of guessing. An essential place in putting forward a hypothesis is the conclusion by analogy. As already noted, a thought experiment can also be used at the stage of development of a theoretical hypothesis. As for the intuition that Einstein speaks of, it is embedded in all stages of the hypothesis method, from the analysis of the facts to be explained to the acceptance by the scientific community of a well-founded hypothesis as a law or theory. It is intuitive insight that can allow a scientist to single out from the totality of facts the main ones leading to the advancement of a brilliant conjecture. Intuitive insight can also manifest itself in the choice of an analogy that leads to a heuristically valuable guess, and so on. Discursive thinking within the framework of the hypothesis method is constantly interspersed with intuitive steps of thought. But the ability for intuitive insight is not given to a brilliant scientist "from God", although genius also has innate elements. As Einstein believed, intuitive insight is largely a product of "penetration into the essence of experience", which depends mainly on high professionalism and hard constant work of the mind to solve the problem.
An explanatory hypothesis, as an assumption about a law, is not the only kind of hypothesis in science. There are also "existential" hypotheses - assumptions about the existence of elementary particles unknown to science, units of heredity, chemical elements, new biological species, etc. The methods of putting forward and substantiating such hypotheses differ from explanatory hypotheses. Along with the main theoretical hypotheses, there may be auxiliary hypotheses that make it possible to bring the main hypothesis into better agreement with experience. As a rule, such auxiliary hypotheses are later eliminated. There are also so-called working hypotheses, which
allow better organization of the collection of empirical material, but do not claim to explain it.
The most important version of the hypothesis method is mathematical hypothesis method, which is typical for sciences with a high degree of mathematization. The hypothesis method described above is the content hypothesis method. Within its framework, meaningful assumptions about laws are first formulated, and then they receive the corresponding mathematical expression. In the method of mathematical hypothesis, thinking takes a different path. First, to explain quantitative dependencies, a suitable equation is selected from related fields of science, which often involves its modification, and then they try to give a meaningful interpretation to this equation. Describing the method of mathematical hypothesis, S. I. Vavilov wrote: Let us suppose that it is known from experience that the studied phenomenon depends on a number of variables and constants, interconnected approximately by some equation. By rather arbitrarily modifying and generalizing this equation, one can obtain other relationships between variables. This is the mathematical hypothesis or extrapolation. It leads to expressions coinciding or diverging with experience, and accordingly applied further or discarded.
I. V. Kuznetsov, a specialist in the methodology of science, tried to identify various ways of modifying the initial equations in the process of putting forward a mathematical hypothesis: 1) the type, general form of the equation changes; 2) quantities of a different nature are substituted into the equation; 3) both the type of the equation and the type of quantity change; 4) limiting boundary conditions change. All this gives grounds for the typology of the method of mathematical hypothesis.
The scope of application of the method of mathematical hypothesis is very limited. It is applicable primarily in those disciplines where a rich arsenal of mathematical tools has been accumulated in theoretical research. These disciplines primarily include modern physics. The method of mathematical hypothesis was used in the discovery of the basic laws quantum mechanics. So, E. Schrödinger took the wave equation of classical physics as a basis for describing the motion of elementary particles, but gave a different interpretation of its terms. As a result, a wave version of quantum mechanics was created. W. Heisenberg and M. Born took a different path in solving this problem. They took the canonical equations of Hamilton from classical mechanics as a starting point in putting forward a mathematical hypothesis, retaining their mathematical
mathematical form or type of equation, but introduced into these equations a new type of quantities - matrices. As a result, a matrix version of the quantum mechanical theory emerged.
The hypothesis method demonstrates the creative nature of scientific research in the process of discovering new laws, principles and creating theories.
The rules of the hypothesis method do not unambiguously predetermine the results of the study and do not guarantee the truth of the knowledge obtained. It is the creative intuition, the creative choice from the variety of possible ways to solve the problem that leads the scientist to a new theory. Theory is not calculated logically and is not discovered, it is created by the creative genius of the scientist and it always bears the stamp of the scientist's personality, as it lies on any product of a person's spiritual and practical activity.
§ 3. Computer and philosophy*
The emergence and intensive development of electronic computing technology with an ever-expanding scope of its use, interconnected with changes in the vital spheres of society, including the economy, social structure, politics, science, culture and everyday life of people, is the object of study of various humanitarian disciplines including philosophy.
The first systematic attempts to identify and study the philosophical problems associated with computer technology and the opportunities it opens up were undertaken in the framework of what can be called the cybernetic movement in a broad sense.
The founder of this intellectual movement, the American mathematician N. Wiener, during the years of the Second World War, was developing mathematical means for controlling fire using computing devices that provide calculations for a shot. Forced in the course of this work to investigate the performance by a person of those functions that were to be transferred to the electrical system - primarily the function of predicting the future - scientists turned to the problems of human conscious activity and neurophysiology. In the summer of 1947, the term "cybernetics" appeared - so a group of scientists, united around Wiener and Rosenbluth, decided
* The paragraph was written by I. Yu. Alekseeva, senior researcher at the Institute of Philosophy of the Russian Academy of Sciences, Ph.
name "the theory of control and communication in machines and living organisms" (See: Wiener N. "Cybernetics or Control and Communication in Animal and Machine", 2nd ed. M., 1968, pp. 56-57). The main concepts of the new theory were such concepts as "information", "feedback", "coding", "adaptation", "homeostasis", etc.
The ideas of cybernetics have gained great popularity both among scientists of various specialties and among the general public. The use of the term "cybernetics" was not unambiguous. Hopes were pinned on cybernetics to create a unified theoretical base for many disciplines that studied various information processing processes in the 19th and 20th centuries: the theory of wire communication, the theory of radio communication, the theory of automatic control, the theory of mathematical machines, etc. Often these disciplines began to be called cybernetics ( or technical cybernetics), while many scientists continued to work in such areas without using cybernetic terminology.
Cybernetics was also characterized as "a general theory of control, not directly related to any applied area and at the same time applicable to any of them" (Vir St. "Cybernetics and production management". Translated from English. M .: State. ed. - in physical and mathematical literature, 1963. P. 20), and as an exact science of control, without fail using quantitative methods (Berg A. Preface to the Russian edition / / Ibid. P. 5).
The cybernetic movement as a whole included a variety of areas, including artificial intelligence, various types of modeling, and the use of logical and mathematical methods in biological, medical, socio-economic (and other humanitarian) research. This circumstance found expression in the characterization of cybernetics as "the study of control processes in complex dynamic systems, based on the theoretical foundation of mathematics and logic and using automation tools, especially electronic digital computers, control and information-logical machines "(Biryukov B.V. "Cybernetics and Methodology of Science". M., 1974. P. 13).
In line with the cybernetic movement, philosophical and logical-methodological studies of management, information, thinking, cognition, the structure of scientific knowledge and the prospects for its development were carried out. The idea of commonality (identity or similarity) of regularities that determine the processes of management and processing of information in various fields is characteristic of the cybernetic movement.
reality and the idea of the fruitfulness of the use of mathematical and logical-mathematical interpretations of these processes at various levels of abstraction received a specific refraction in numerous comparisons of human thinking and computer operation.
The emergence of computer systems, which began to be called intelligent systems (IS), and the development of such a direction as artificial intelligence (AI), prompted a fresh look at a number of traditional epistemological problems, outline new ways of studying them, and pay attention to many remaining earlier in the shadow aspects of cognitive activity, mechanisms and results of cognition. During the heated debates of the 60s and 70s on the topic "Can a machine think?" In essence, various answers were presented to the question of who can be the subject of cognition: whether only a person (and, in a limited sense, animals) or a machine can be considered a thinking subject, possessing intellect and, therefore, a cognizer. Supporters of the latter option tried to formulate a definition of thinking that would allow talking about the presence of thinking in a machine - for example, thinking was defined as solving problems (See: Botvinnik M. M. "Why did the idea of artificial intelligence arise?"// "Cybernetics: development prospects". M., 1981). [It should be noted, however, that the ability of a computer system to make any decisions can also be (and is being) questioned]. Opponents of the supporters of "computer thinking", on the contrary, sought to identify such characteristics of human mental activity that can in no way be attributed to a computer and the absence of which does not allow us to speak of thinking in the full sense of the word. Such characteristics included, for example, the ability to be creative, emotionality (See: Tyukhtin V.S. "The ratio of the possibilities of natural and artificial intelligences" / / "Problems of Philosophy". 1979. No. 3).
Computer modeling of thinking gave a powerful impetus to psychological research into the mechanisms of cognitive activity. This was manifested, on the one hand, in the penetration into psychology of the “computer metaphor”, which focuses on the study of human cognitive activity by analogy with the processing of information on a computer, and, on the other hand, in the intensification of research that seeks to show the fruitfulness and independent value of other approaches - for example , the study of thinking in the context of a general theory of activity. O.K. Tikhomirov, specially
investigating "the relationship between cybernetic and psychological approaches to the study of thinking", insisted that "the widespread convergence of human thinking and the operation of a computer is not justified." At the same time, he notes, "it was the development of cybernetics that made obvious the incompleteness of the theories of thinking and behavior that dominated psychology, putting forward new aspects for study" (Tikhomirov O.K. "The structure of human mental activity. (Experience of theoretical and experimental research)". Moscow Publishing House University, 1969, p. 4). Describing the significance of analogies between human thinking and computer processing of information, the English researcher M. Woden writes: "To the extent that the analogy with a computer can serve the general human interests of a deeper knowledge of the mind, the careful use of "psychological" terminology in relation to a certain type of machine should encouraged rather than prohibited ... analogies make it possible not only to identify similarities between compared objects, but lead to the discovery of really important similarities and differences "(Boden M. A. "Artificial Intelligence and Natural Man". 2nd ed. L., 1987. P 421).
Computer modeling of thinking, the use of methods of mathematical and technical sciences in its study gave rise to hopes during the "cybernetic boom" for the creation in the near future of rigorous theories of thinking that would describe this subject so fully that it would make any philosophical speculation about it superfluous. Hopes of this kind, however, were not destined to come true, and today thinking, being the subject of study of a number of special sciences (psychology, logic, artificial intelligence, cognitive linguistics), also remains an attractive object of philosophical consideration.
In the last two decades, in computer science, significant attention has been paid to such a traditionally included in the field of philosophy subject as knowledge. The word "knowledge" began to be used in the names of areas and components of computer systems, as well as the systems themselves (knowledge-based systems; knowledge bases and knowledge banks; representation, acquisition and use of knowledge, knowledge engineering). The topic "computer and knowledge" became the subject of discussion in a much broader context, where at first
plan came out of its philosophical-epistemological, social and political-technological aspects.
As for such a field as AI, it would not be an exaggeration to say that in the 80s the concept of knowledge replaced the concepts of thinking and intelligence, which traditionally occupied an honorable place in the reflection of AI professionals on their activities. The theory of artificial intelligence has sometimes become characterized as "the science of knowledge, how to extract it, represent it in artificial systems, process it inside the system and use it to solve problems" (Pospelov D.A. "Situational management: theory and practice". M. , 1986. P. 7.), and the history of artificial intelligence, excluding its early stages, as the history of research on methods of knowledge representation (See: "Representation and use of knowledge" / Edited by X. Ueno, M. Ishizuka. M. ,
The expansion of the scope of IP, the transition from the "world of cubes" to such more complex areas as medicine, geology and chemistry, required intensive efforts to formalize the relevant knowledge. IS developers are faced with the need to identify, organize a variety of data, empirical information, theoretical positions and heuristic considerations from the relevant field of science or other professional activities and set methods for processing them using a computer in such a way that the system can be successfully used in solving problems for which it is intended (search for information, diagnosis, etc.). This led to changes in the nature of the data in the memory of a computer system - they began to become more complex, structured data appeared - lists, documents, semantic networks, frames. For elementary data processing, their search, recording in the allotted place and a number of other operations, special auxiliary programs began to be used. The procedures associated with data processing became more complicated and became self-sufficient. There was such a component of the intellectual system as the knowledge base.
The term "knowledge" has acquired a specific meaning in AI, which D. A. Pospelov characterizes as follows. Knowledge is understood as a form of representation of information in a computer, which has such features as: a) internal interpretability (when each information unit must have a unique name by which the system finds it, and also responds to requests in which this name is mentioned); b) structuring (inclusion of some
information units into others); c) connectivity (the ability to set temporal, causal spatial or other kinds of relationships); d) semantic metric (possibility of setting relationships that characterize situational closeness); e) activity (execution of programs is initiated by the current state of the infobase). It is these characteristics that distinguish knowledge in IS from data - "determine the line beyond which data turns into knowledge, and databases grow into knowledge bases." (See "Artificial intelligence. Reference edition in 3 books." Vol. 2. M., 1990. P. 8).
Using the terminology of L. Wittgenstein, we can say that this understanding of knowledge as a form of information representation "works" within the framework of a special language game characteristic of AI. In the course of this language game, formulations can appear that can cause bewilderment for an epistemologist who tries to evaluate them from the point of view of the usual philosophical interpretations of knowledge. Such formulations include the statement that has become a "commonplace" that data is not knowledge, as well as proposals to use this or that language as knowledge or expressions like "by knowledge we understand such and such a type of formula."
At the same time, the just given characteristic of knowledge in IS is not completely isolated from what we usually understand as knowledge. Features such as internal interpretability, structuredness, coherence, semantic metrics and activity are inherent in any, more or less large blocks of human knowledge, and in this sense, knowledge in a computer system can be considered as a model or image (in the broad sense of the word) of one or another piece of human knowledge.
However, the relationship of knowledge in the AI-specific sense with knowledge in the more familiar, "ordinary" sense is not limited to the similarity of certain structural characteristics. After all, a significant part of the information presented in the knowledge base of IP is nothing but knowledge accumulated in the area where this system should be applied. The study of this knowledge (fixed in the relevant texts or existing as unfixed in the text and even unarticulated knowledge of an individual expert) from the point of view of the tasks of building an IS determines the technological approach of AI to knowledge as such.
The technological approach to knowledge involves the formulation, research and solution of technological questions about knowledge. The latter include questions like "How should (can,
is it permissible) to handle (deal with) knowledge, meaning the achievement of such and such a goal?". "Contact" or "deal" with knowledge implies here not only the acquisition, storage or processing of knowledge, but also any mental and speech acts , carried out in relation to knowledge - for example, the statement that someone ("a") knows something ("p"), can be interpreted as a mental act performed by some "observer" in relation to the knowledge possessed by the subject "a" (in subject "a" can act as an "observer").
In the broadest interpretation, the technological approach to knowledge is an integral element of the life of any person. In this sense, both primitive man, who uses primitive signals to transmit information, and our contemporary, choosing between mail, telegraph, telephone and telefax, can be considered decisive technological questions regarding knowledge.
An example of a technological approach to the study of knowledge as a special entity is the characteristic of Socratic maieutics in Plato's dialogues. The art of Socrates to ask leading questions in such a way that the interlocutor eventually comes to the right conclusions about the subjects under discussion (at least, to such conclusions that Plato himself considers true), is characterized here as the art of awakening the true opinions that live in the human soul, in whereby opinions become knowledge. Perhaps the most expressive illustration of this procedure is given in the well-known example from the Meno dialogue, where a slave boy solves a geometric problem. Generally speaking, all Plato's dialogues demonstrate the Socratic technique of "awakening" knowledge. However, we find the actual technological approach to the study of knowledge in Plato only in those cases when this technique itself becomes the subject of reflection, when it itself is considered as a means for performing some actions on knowledge. Fragmentary characteristics of this technique are found in many dialogues - the same "Menon" can serve as an example, where it is said about the awakening of knowledge by questions. She was awarded a more detailed consideration in the dialogue "Theaetetus". Here Socrates spoke of his art as similar to the craft of his mother, the midwife Fenareta, and what was characterized in the Menon as a technique for awakening knowledge is here characterized as a kind of obstetrics technique for "men pregnant with thought" (See: Plato. Works in 3 vols. T. 2. M., 1970. S. 234).
Technological questions about knowledge can be, to a certain extent, opposed to existential questions - that is, questions
himself about how knowledge exists, what it is. Questions of the latter type include, for example, questions about the relationship of knowledge with opinion or belief, about the structure of knowledge and its types, about the ontology of knowledge, about how cognition occurs.
Until the second half of this century, the existential approach to the study of knowledge was predominant. This does not mean, of course, that the very technology of obtaining, transferring, storing and processing knowledge, as well as evaluating the results of cognition that claim the status of knowledge, did not develop. It is enough to recall the development of printing and technical devices for transmitting information, teaching methods and pedagogical research on the technique of transferring knowledge and cultivating the ability to independently acquire and use knowledge, the development of scientific methods and research on these methods. However, even when these ways of working with knowledge became the subject of research, they were correlated not so much with knowledge as a special kind of entity, but with a cognizable reality (which could be interpreted as physical, mental or psychic, depending on the worldview of the researcher). Many of these considerations may, after certain interpretations, be qualified as technological, but this will still refer to the result of our interpretation rather than to the study itself.
The flourishing of technological (in the above sense) studies of knowledge is associated with the development of epistemic logic and artificial intelligence. A rather typical feature of research in epistemic logic is the development of certain means for deciding whether a certain kind of formula (containing epistemic operators corresponding to the words "knows", "believes", "doubts", "denies", etc.) .) provable in such and such a calculus or generally valid for such and such type of models. From the point of view of a technological approach to knowledge, this issue can be understood as a question of legitimation (legalization) using a certain symbolic-conceptual apparatus of the results of death-speech activity in relation to the knowledge of a certain subject (or group of subjects), expressed in a form suitable for use of this apparatus. The nature of the legitimated results is determined both by the peculiarities of the formalisms used and by the position of the researcher in relation to existential questions about knowledge.
The technological questions about knowledge explored in AI are, to a large extent, about how knowledge is represented.
The problems of knowledge representation are connected, in turn, with the development of appropriate languages and models. There are various types of models: logical, production, frame, semantic networks and others. Logical models involve the representation of knowledge in the form of formal systems (theories), and the language of predicate logic is usually used as the knowledge representation language in such models. Production representations can be characterized (in a simplified way) as systems of rules of the form "If A, then B", or "Premise - action". Network models involve the selection of some fixed sets of objects and the assignment of relations on them (these can be relations of various kinds: spatial, temporal, naming relations, etc.). Frame representations are sometimes thought of as a kind of semantic networks, but the former are characterized by having fixed structures of information units that define places for the frame name, slot names, and slot values. (A description of the main models of knowledge representation can be found in the reference publication "Artificial Intelligence", vol. 2, mentioned above, and also, for example, in: "The Handbook of Artificial Intelligence". V. 1. Massachusetts ets., 1986). Each of the mentioned models has its advantages and disadvantages in relation to a particular range of tasks.
The advantages of logical models using the language of predicate logic are related to the deductive possibilities of predicate calculus, the theoretical validity of the conclusions made in the system. However, such models in complex subject areas may turn out to be too cumbersome and not visual enough as domain models or corresponding pieces of knowledge. Production models have become widespread due to such advantages as the ease of formulating individual rules, replenishment and modification, as well as the mechanism inference. As a disadvantage of the production approach, the low efficiency of information processing is noted when it is necessary to solve complex problems. The advantages of semantic networks and frame models lie, on the one hand, in their convenience for describing certain areas of knowledge (and the corresponding fragments of reality studied in these areas), when the main (in terms of the tasks for which the IS is created) objects of the subject area and (or) a system of concepts in which specific situations will be analyzed, and the properties of objects (concepts) and the relationship between them will be described. And although in general for these
types of models, there are significant problems with the organization of output, frame systems have been evaluated by many as promising due to the possibility of summing up sufficiently strict logical and mathematical foundations for them. Of course, in IS it is not at all necessary to implement only one of the mentioned models of knowledge representation "in its pure form". A combination of different models can lead to more efficient systems. At the level of AI theory, this is sometimes reflected in the development of new types of knowledge representation models that combine the features of models that have already become traditional.
Within the framework of the technological approach to knowledge carried out by AI, the questions of economy of knowledge representation by means of certain means, their deductive capabilities, and efficiency in solving problems are considered. At the same time, the influence of AI theory (and, in particular, knowledge representation) on the study of knowledge as such extends far beyond the technological approach. Comparing the influence of certain models of knowledge representation on existential studies of knowledge, we cannot help but notice the difference in the role played, on the one hand, by the logical approach and, on the other hand, by such approaches as production, frame, and others, sometimes combined under the general name of heuristic (See: Popov E.V. "Expert systems". M., 1987) or cognitive (see: "Representation and use of knowledge" / Edited by X. Ueno, M. Ishizuka. M., 1989) approach. It should be noted that both of these divisions can only be accepted conditionally: the division "logical - heuristic" or "logical - cognitive" is doubtful, since logical models are characterized by the presence of heuristics and, in addition, these models may contain assumptions regarding cognitive behavior. An example is the IS developed by the group of V. K. Finn, which is considered by its creators as an implementation of the logic of common sense, combining natural rationalism and natural empiricism (See: Finn V. K. "On a generalized JSM method for automatically generating hypotheses" // "Semiotics and Informatics". 1989. Issue 29).
Nevertheless, in general, the logical approach to the representation of knowledge in IS has not yet led to any major changes in the existential consideration of knowledge, to the emergence of new influential concepts in this area. Other approaches, on the other hand, have a more noticeable impact on the study of existential questions about knowledge - as an example, one can refer to the frame concept.
the concept of the structure of knowledge, which has received a certain distribution both in psychology and in cognitive linguistics. What has been said would be misinterpreted as an argument in favor of the advantages of these types of knowledge representation models over logical ones.
The fact is that the logical approach to the representation of knowledge, like the logical calculus themselves, arose on the basis of interpretations of knowledge that developed over many centuries - on the basis of what can be called classical rationalistic epistemology with its characteristic propositional interpretation of elementary knowledge, consideration theories of mathematic sciences as exemplary forms of organization of knowledge, strict standards for the correctness of reasoning. The level of classical epistemology and the development of its conceptual foundations is so high that over the period of time during which research on the representation of knowledge in computer systems is being conducted (and this period is negligible compared to the "age" of classical epistemology), these studies, which have as their the conceptual basis of classical epistemology itself, naturally, should rather demonstrate its possibilities in applying to a new range of tasks than stimulate significant changes in it. The assertion that non-classical logics, which are increasingly used in the representation of knowledge, also develop on the conceptual basis of classical epistemology, may, at first glance, seem paradoxical. Nevertheless, it is true to the extent that non-classical logics are modifications of classical calculi and share with them those deep conceptual premises that can be opposed in a certain sense to the conceptual foundations of other approaches. From this point of view, work on logic natural language and reasoning of common sense testify to the high flexibility of the tools developed on the basis of classical epistemology and the richness of its possibilities.
Other approaches to knowledge representation are quite closely related to the development of cognitive psychology. However, this trend itself was formed under the influence of the "computer metaphor", when cognitive processes began to be considered by analogy with the operation of computers. It is not surprising, therefore, that what is happening in AI has had and is having a noticeable impact on cognitive psychology (as well as on an even younger direction - cognitive linguistics). This is also true for the representation of knowledge itself. Both frame and network models are based on the corresponding
developing concepts of the structures of human perception and memory. It is significant that the concept of a frame as a cognitive structure was motivated by the tasks of developing IS. However, this concept has independent meaning as a psychological and epichtemological concept and is used in the study of problems that go beyond the actual development of computer systems (See, for example: Fillmore I. "Frames and the semantics of understanding" / / "New in foreign linguistics". M., 1988. Issue 23. "Cognitive aspects of language").
Today we can say that the representation of knowledge in a computer in the form of systems of rules (which is typical, first of all, for production models) corresponds to a new approach in philosophical and epistemological research, which emphasizes the rules and regulations governing human activity. This approach is presented in the works of A. I. Rakitov. In the mid-1980s, A. I. Rakitov and T. V. Andrianova predicted the possibility of the emergence of new trends in epistemology, primarily related to the study of the cognitive function of rules as a special epistemological category and the identification of a mechanism for rationalization and regulatory transformation of intellectual creativity. Such assumptions (and the formulation of the problem of developing epistemology in this direction) were due to the fact that in order to build knowledge bases for computer systems, it was necessary to study the mechanisms of the functioning of knowledge from such an angle that it would reveal the rules for the operation of these mechanisms, i.e. "instructions , indicating which classes of actions or individual actions and how should be performed "(Rakitov A.I., Andrianova T.V. "Philosophy of the Computer Revolution"//"Problems of Philosophy". 1986. No. 11. P. 78).
In the book "Philosophy of the Computer Revolution" (Moscow, 1991), AI Rakitov puts forward the idea of "information epistemology". "The emergence of "intelligent technology" and the burning interest in the nature and possibilities of machine thinking, generated by the computer revolution," he writes, "led to the formation of a new, non-traditional section of epistemol
Lecture:
The concept, types and functions of science
One of social institutions spiritual sphere of society is science. Science received state and public recognition in Russia only at the beginning of the 18th century. On January 28 (February 8), 1724, by decree of Peter I, the first scientific institution, the Academy of Sciences and Arts, was founded in St. Petersburg. Science plays a significant role in the life of an individual and society as a whole. Thus, the professional success of a person directly depends on the degree of possession of scientific knowledge. And the progressive development of society cannot be imagined without the achievements of science. What is science? The first word associated with science is knowledge - the basis of science, without which it loses its meaning. Knowledge is created as a result of the research activities of scientists and social institutions (scientific institutions). Therefore, we formulate and remember the following definition:
The science- this is a special system of knowledge about a person, society, nature, technology, obtained as a result of the research activities of scientists and scientific institutions.
The features of scientific knowledge were discussed in the lesson (see Scientific knowledge). If necessary, you can repeat or study this topic. In this lesson, we focus on the types and functions of scientific knowledge.
The variety of phenomena of the real world led to the emergence of many types of sciences. There are about 15 thousand of them. All of them are divided into:
- natural - natural sciences, including astronomy, physics, chemistry, biology, etc.;
- social and humanitarian - sciences about society and man, including history, sociology, political science, economics, jurisprudence, etc.;
- technical types - sciences about technology, which include computer science, agronomy, architecture, mechanics, robotics and other sciences about technology.
The social purpose of science lies in the functions it performs. Each science is characterized by specific functions, but there are also common to all sciences:
Cognitive
Cultural and ideological
: science influences the formation of the human personality, determines its relationship to nature and society. A person who does not have scientific knowledge, who bases his reasoning and actions only on personal everyday experience, can hardly be called cultural. Examples: a group of scientists put forward a new hypothesis of the origin of life on our planet; philosophical studies prove that there are an infinite number of galaxies in the Universe; N. checks and critically comprehends scientific information.Production
: science is a special “workshop” designed to supply production with new equipment and technologies. Examples: pharmaceutical scientists have created a new drug to fight viruses; genetic engineers have developed a new method of weed control.Social : science affects the living conditions of people, the nature of labor, the system of social relations. Examples: studies have shown that a 1% increase in education spending in the coming years will lead to an increase in the pace of economic development; Hearings were held in the State Duma, at which scientific forecasts of the prospects for the development of the space industry in the Russian Federation were discussed.
predictive : science not only equips people with new knowledge about the world, but also gives forecasts for the further development of the world, pointing out the consequences of changes. Examples: Soviet theoretical physicist, academician A.D. Sakharov published an article entitled "The Danger of Thermonuclear War"; environmental scientists warned about the danger of pollution of the waters of the Volga River for living organisms.
Scientists and social responsibility
Science includes not only a system of knowledge, but also scientific institutions and scientists. recognized center fundamental research science in our country is Russian Academy of Sciences (RAS) - the heiress of the Academy of Sciences and Arts of Peter the Great, who moved to Moscow in 1934. The RAS includes the largest scientists conducting research in medicine, agriculture, education, energy and many other areas. Scientists, researchers, experts, laboratory assistants are a special category of people. They have a scientific outlook and take great pleasure in scientific research. creative activity. Their works contribute to the development of a certain branch of science. The main task of scientists is to obtain, substantiate and systematize new true knowledge about the real world.
The reality surrounding us in scientific knowledge is reflected in the form of concepts and terms. This is the fundamental difference between science and art or religion, which reflect knowledge about the world figuratively. The features of scientific thinking and activities of scientists are:
- selection of objective, reliable and accurate scientific facts;
- formulating a problem and building a hypothesis that can solve it;
- use of special research methods and data collection;
- theoretical substantiation of concepts, principles, laws;
- testing knowledge with evidence.
- the principle of "do no harm";
- there is no place for subjectivity in science;
- truth is dearest of all;
- honestly recognize the merits of your predecessors and many others.
Exercise: Illustrate any function of science with an example🎓
Each person, as he moves along the line of life, learns the world around him. To do this, he uses the senses and logic, comparing the appearance of objects, smells, texture, distances, sizes, as well as the influence of the properties of objects on each other during their interaction. I think it's not a secret for anyone: someone needs superficial knowledge, and someone wants to get to the bottom of things. There is an opinion that the second approach not only allows us to understand many aspects of our life, but also to spend it calmly and happily.
Surely you have thought about the fact that often our conclusions are devoid of objectivity, distorted by incomplete knowledge of the facts and biased due to ignorance. However, the quality of life and what we do directly depends on the way we think. As a result, you can pay dearly for such frivolity, or you can try to develop the mastery of scientific knowledge in the broad sense of the word.
scientific thinking is a way of perceiving the world, in which the quality of knowledge is improved, thanks to skillful control over the components of this process and following the criteria of intellectuality.
As a result of such work on oneself, a person has a number of undeniable advantages. He is able to raise issues that are important to him, expressing them clearly and precisely. Collect information about them and soberly evaluate it, using abstract thinking for a more effective presentation. Come to informed conclusions and decisions by testing them under appropriate conditions. For him, the opportunity opens up to think openly in terms of various concepts and realize their meaning, put forward assumptions and test them in practice. As a result, a person can interact productively with people, offering solutions to complex problems.
AT At the same time, the researcher must have a certain degree of courage in defending his opinion, even if it is unpopular.
How can such results be achieved? What tools should you use? One of the components of scientific thinking is. In the previous paragraph, the phrase “criteria of intelligence” was heard - what is it? These are personality, thought process and speech traits that help to structure information about the subject of reflection and get a more complete picture of the problem posed.
Among them, first of all, such qualities as accuracy and clarity. The clarity of the problem posed is formed by clarification. For example, asking the question “How do I arrange the furniture in the bedroom?” sounds completely different. and “How can I arrange the furniture in my bedroom so that there is enough space for morning exercises and the opportunity to watch movies?”. In order not to waste time on unnecessary information, the information should be related to the problem posed - be relevant.
Obviously, to solve the issue of the location of furniture, its color is not always so important. In addition, consideration of the problem should be deep and take into account the full breadth of aspects and opinions. So, it is worth considering whether to watch a movie from a projector or is it better to hang a plasma panel? If there is a projector, will there be enough space between it and the wall for comfortable viewing of the picture? Won't the color of the wall change the color of the image a lot? What kind of exercises will I do - twist the holo hoop or warm up on the rug? How much space do I need?
This is the initial toolkit of scientific thinking. Scientists studying various fields of knowledge apply it to form links in the chain of scientific research, combining theoretical and empirical methods. Let's take a look at what such a historical discipline as archeology does. Let's start with setting the task - the search for material sources of the past and their interpretation in order to study the history of mankind.
It is obvious that the excavation site is not chosen by chance: before that, scientists think about where it will be possible to collect more useful information required to answer a specific historical question? To do this, they analyze the available data by studying the area, historical written sources and the works of other researchers.
Character traits such as empathy and honesty will allow you to develop points of view that are different from your own.
During excavations, archaeologists strictly record the circumstances of the discovery of artifacts, classify the objects found, establish their age, considering the entire complex of archaeological material in the context of the area where they were discovered. Based on this, they put forward versions and assumptions that can be confirmed by the found antiquities. At the same time, archaeologists understand that future research may force us to reconsider the beliefs of the past.
In addition to meeting the criteria of intellectuality and the application of scientific methods, a scientist must possess some character traits that will help him develop the objectivity of his judgments. The humble scientist is able to be sensitive to his knowledge, being aware of where he may be mistaken and on what issues his point of view will be limited. At the same time, the researcher must have a certain degree of courage in defending his opinion, even if it is unpopular.
At the same time, such qualities of character as empathy and honesty will allow you to realize the value of the views of other people and develop points of view that are different from your own, as well as avoid double standards. However, do not forget about confidence in your reasoning, while maintaining intellectual autonomy - the ability to follow logic, instead of blindly accepting the opinions of others. Of course, on the research path there will be difficulties that cannot be overcome without perseverance.
Scientific thinking is a term well known to scientists, scientists and researchers. However, the style of scientific thinking implies a connection with ordinary thinking, and we know and use many of its elements unconsciously all our lives.
Scientific thinking is a way of thinking that differs in certain characteristics from ordinary or empirical thinking (empirical - translated from Greek based on experience, observation).
To capture the connection and difference between them, let's define two key concepts:
- What is thinking? This is a process of research and cognitive activity of a person, the purpose of which is an objective reflection in the mind of the essence of objects, phenomena and objects of the surrounding reality.
- What is science? This is a certain activity of people, which consists in the development, systematization of information about the world, the purpose of which is to explain the events and phenomena of the world around on the basis of laws.
Ordinary thinking a person regularly uses in his life. It is based on everyday subjective experience, using the simplest form of analysis. The type of thinking, characterized by scientific character, uses the methods of evidence, consistency and objectivity in its functioning. Formation scientific view thinking happened quite recently, although its foundation was laid by the philosophers of Ancient Greece.
Peculiarities
The main features of scientific thinking listed below are universal and determine the main differences from ordinary thinking.
- Objectivity. Other methods of cognition are characterized in combination of objective and subjective perception, for example, the image of artistic activity implies an assessment given by the person who creates it. And if you remove it, the image loses its value. Science, on the other hand, focuses on separating the personal from the objective (Newton's law does not give us information about the personality of this scientist, about what he loved or hated, while any portrait made by the artist bears the imprint of a subjective vision)
- Focus on the future. The style of scientific thinking involves the study of not only objects, objects and phenomena that are relevant to the present, but also those that will be important in the future. It is important for science to foresee how objects in their original form will be modified into any products necessary for mankind. This determines one of the tasks of science as a whole - to determine the laws in accordance with which objects develop. The way of scientific thinking determines the possibility of constructing the future from separate fragments that exist in the present. Science is engaged in isolating the right “pieces”, parts, forms, which will later become objects or objects that humanity needs.
- Consistency. The theoretical principles on the basis of which a complex of knowledge is built form a certain system. It is built over years and centuries, contains a description and explanation of facts and phenomena, which subsequently determine concepts and definitions.
- Awareness. It lies in the fact that the methods by which the study of objects, objects, their relationships with each other are realized and controlled by the scientist.
- Having your own concept material. Scientific knowledge fixes theories, concepts, laws in its own language - formulas, symbols, etc. The formation of this language takes place throughout the entire period of the existence of science, and it is regularly updated.
- Validity. In science, there are many assumptions and hypotheses that may not be proven in a certain period of time. However, all of them aim to become objectively proven and substantiated.
- Use of the experiment. Like empirical methods of cognition, scientific methods involve the use of experiments in situations where concepts and theories are formed. However, the style of scientific thinking allows you to use the results obtained for a larger number of conclusions and objects.
- Building theories. An experimental method of obtaining information, a person imprints in the form of a theory. Theoretical principles are preserved for centuries and passed down from generation to generation.
Scientific picture of the world
The style of scientific thinking determines the formation scientific picture peace.
The scientific picture of the world is a type of knowledge system from different areas, united by one general scientific doctrine.
It combines mathematical, physical, chemical, biological theories and laws that give a general description of the world. In addition to the scientific picture of the world, a person has a religious, artistic, philosophical and other views on reality. However, only the scientific type of perception is characterized by objectivity, consistency, analysis and synthesis.. With the development of society, the knowledge of the world was increasingly based on the scientific method, which is reflected in modern philosophy, religion, and works of art.
The connection between scientific and ordinary thinking
In the process of development of science, a person came to the conclusion that the difference between these types of thinking is not categorical.
The scientific and non-scientific way of knowing the surrounding world is based on the same mechanism - abstraction.
The essence of this phenomenon lies in the ability to abstract from the specific properties of an object in order to highlight its essential properties. Signs of the initial level of abstraction are the comparison and "sorting" of objects, objects, people in everyday life. For example, a person divides his environment into close and not pleasant to him, into superiors and subordinates, food - into tasty and not tasty - in order to understand how to behave in accordance with his goals.
Similarly, the scientific type and the ordinary type of thinking are prone to the same mistakes: for example, if an event follows something, it means that it happened as a result of it.
Scientific thinking in modern society
Most people, being far from science in general, regularly use its fruits and methods of cognition in their lives. Since the 17th century, science has occupied a strong position in society, relegating religious, philosophical pictures of the world to the background. However, scientists note that in recent decades the situation has begun to change again and an increasing number of people choose an unscientific way of knowing. In connection with this situation, there is talk that there is a formation of two types of people:
- The first type is people who are close to the style of scientific thinking. This person is active, independent, flexible, loves everything new and has a positive attitude towards change. This type loves disputes and discussions, tries to adhere to an objective assessment of the world.
- Another type of people is oriented towards the non-scientific way of knowing. They are close to everything mysterious, interesting, having practical use. Feelings are more important for them than the essence of things, they do not strive to obtain evidence and verify the results. An important place in the life of such a person is determined by faith, authoritative personalities, their opinions.
Scientists are asking the question: why does modern man choose a reorientation from the scientific to the non-scientific way of knowing the world? And they come to the conclusion that in many matters science turned out to be powerless, and sometimes even brought harm. A person, seeking to protect himself, plunges into religion and philosophy - these forms of the picture of the world bring him peace and confidence in the future.
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Despite the fact that the concept of thinking is very multifaceted and includes many features, ways of thinking can always be conditionally divided into empirical and scientific.
The empirical way of thinking, which is considered ordinary, everyday, suggests that a person perceives the world subjectively, simply constantly interacting with it. The scientific way is different. What, what it is and what kind of thinking is considered scientific - we will analyze in this article.
The essence of scientific thinking and its place in our life
The formation of scientific thinking as the main way of cognizing the surrounding reality began relatively recently, but its foundations and basic laws began to be laid by ancient Greek thinkers. And despite the fact that now the concept of "scientific thinking" is more familiar to scientists, researchers and scientists, it is closely connected with the empirical thinking of a person, and each of us knows and applies certain elements of it in life.
But still, to establish the difference between ordinary and scientific thinking, we should identify two central concepts:
- Thinking is the cognitive and exploratory activity of a person striving for an objective reflection in his mind of the essence of objects, objects and phenomena of reality around him.
- Science is an activity consisting in the collection, development and systematization of data about the world, which sets itself the goal of explaining the events and phenomena of the surrounding world on the basis of scientific laws.
From this we can conclude: if in empirical thinking a person operates with his subjective experience and uses the simplest forms of analysis, then in scientific thinking he applies the methods of objectivity, consistency and evidence.
But as science has developed, man has come to the conclusion that the difference between the two ways of thinking under consideration is not at all as categorical as it might seem at first glance. Both of them are built on a single mechanism - abstraction.
This means that a person, cognizing the world, uses his ability to "disconnect" from the specific characteristics of objects and phenomena in order to see the essential. An example is the comparison of objects and phenomena, people and objects and their sorting.
To illustrate this, it suffices to recall how we divide our environment into close people and those with whom we do not want to communicate, we divide colleagues into subordinates and bosses, we define food as tasty or not tasty, and so on. We need all this so that we can better understand how to act in certain situations, based on our goals and objectives.
But, one way or another, we can still distinguish two categories of people:
- Scientifically oriented people. As a rule, they are very active, psychologically flexible, independent, willing to accept new things and ready for change. They prefer, tend to evaluate the world objectively.
- People oriented to the style of unscientific thinking. Such people gravitate towards everything interesting, mysterious and of practical use. In life, they are guided by feelings, leaving the essence of things, evidence and verification of results in the background.
We do not undertake to judge which style of thinking is better, because everyone can have their own views on this matter. But still we can point out that scientific thinking (even if it is applied only occasionally) has a number of tangible advantages. Firstly, it contributes to the acquisition of basic knowledge about the multitude of objects and phenomena of the surrounding world, and therefore serves as insurance against ignorance, stupidity and illiteracy.
Secondly, this way of thinking perfectly develops not only exact and mathematical, but also creative and.
Thirdly, scientific thinking forms an inquisitive mind and motivates a person to solve a huge number of tasks - educational, professional, business, personal. In addition, it lays the foundation for teamwork, and therefore creates the value of mutual understanding and mutual support. However, the importance of science in human life and society is very well described in this video.
Features of scientific thinking
Science is a special sphere of human life, in which knowledge about the surrounding reality is developed and theoretically systematized; it simultaneously represents both an activity to obtain new knowledge and its result, i.e. the totality of the knowledge that underlies the scientific picture of the world.
And, of course, the thinking of people who gravitate towards science is different from the thinking of “ordinary people”. Here are some features of scientific thinking that we can highlight:
- Objectivity. If we take any other way of thinking and cognition, then we will see a symbiosis of objective and subjective perception. In scientific thinking, subjective and objective are clearly distinguished. For example, when we look at an artist's painting, you will always see the imprint of his subjective view, and when we study Newton's laws, we do not get any information about the scientist's personality.
- Consistency. Theoretical basis, on which any complex of scientific knowledge is based, creates a specific system. This system can be built up over tens and even hundreds of years, and includes both descriptions and explanations of phenomena and facts that later define terms and concepts.
- Validity. The array of scientific knowledge includes a huge number of theories, hypotheses and assumptions. Some of them are proven and some are not. But in any case, each of them pursues the goal of being reasonably proven or refuted in the future.
- Focus on the future. Science and scientific thinking involve the study of phenomena, objects and objects that are not only relevant for the current time period, but also those that will be important in the future. Science strives to foresee the development, modification and transformation of what it studies into something that will be useful to mankind in the future. This is the reason for one of the fundamental tasks of science - the definition of laws and patterns of development of objects and phenomena. Scientific thinking allows you to construct the future from the individual elements of the present.
- Conceptuality. With the scientific way of thinking, all laws, terms and theories are fixed in a specific language - with the help of symbols, formulas and other signs. At the same time, this language has been formed throughout the time that science exists, and is also in a state of constant development, additions and improvements.
- . Absolutely all the scientific methods that scientists and researchers use in their work, studying phenomena, objects and the connections between them, are extremely accurately realized by people and are under their constant control.
- Experimental approach. Like empirical methods of cognition, scientific cognition involves experiments, in particular in those cases when any concepts and theories are formed. But only the scientific way of thinking contributes to obtaining a sufficient amount of results with which to draw reliable conclusions.
- Theory building. Using the experimental method of obtaining information, scientists compose theories from the information.
In addition to the above features of scientific thinking, we can point out a few more:
- logical consistency - scientific knowledge and its elements should not contradict each other;
- Validation and reproducibility - all reliable scientific knowledge must, if necessary, be again confirmed empirically;
- simplicity - the maximum possible range of phenomena should be explained using a relatively small number of bases and without the use of arbitrary assumptions;
- continuity - out of many new ideas competing with each other, preference should be given to the one that is “less aggressive” with respect to previous knowledge;
- availability of methodology - scientific knowledge should involve the use of special methods and techniques, and they should be justified;
- accuracy and formalization - knowledge obtained through scientific thinking must be extremely accurate and recorded in the form of clear laws, principles and concepts.
If we summarize all of the above, we can conclude that scientific thinking can perform cognitive, practical-activity, cultural and cultural-ideological functions, as well as a social function, because it contributes to the study of the life and activities of people and often determines the ways and means of practical application of the knowledge and skills.
Here it would be appropriate to say that any scientific knowledge (knowledge obtained through scientific thinking) has two levels - empirical and theoretical.
Empirical level of knowledge
Empirical knowledge is knowledge, the reliability of which has been proven; knowledge based on hard facts. Things that exist separately cannot be called facts. For example, a thunderstorm, Pushkin or the Yenisei are not facts. The facts will be statements that fix a specific relationship or property: during a thunderstorm it rains, the novel "Eugene Onegin" was written by A. S. Pushkin, the Yenisei flows into the Kara Sea, etc.
Speaking of scientific thinking, we can say that science never operates with "pure" facts. All knowledge obtained empirically requires interpretation based on specific premises. In this respect, facts will only make sense within the framework of certain theories. An empirical law is a law whose validity is established solely from experimental data, but not from theoretical considerations.
Theoretical level of knowledge
Theoretical knowledge can take one of four basic forms:
- Theory. It is defined either as a system of central ideas regarding a certain field of knowledge, or as a form of scientific knowledge, thanks to which one can get a holistic view of the patterns and relationships of the surrounding world.
- Hypothesis. It can be interpreted either as a form of scientific knowledge, or as a hypothetical judgment about the causal relationships of the phenomena of the surrounding world.
- Problem. It is always a contradictory situation in which contradictions arise when explaining some phenomena. The problem requires an objective theory for its solution.
- Law. A law is an established, repetitive and significant relationship between any phenomena of the surrounding world. Laws can be general (for large groups of phenomena), universal and particular (for individual phenomena).
These forms of scientific thinking are designed to stimulate scientific research and contribute to the justification of the results obtained with their help. They also clearly show the complexity of the nature of the type of thought presented.
The peculiarities of scientific thinking and the presence of two main levels of scientific knowledge determine, among other things, the principles and methods of scientific thinking. Let's consider their main provisions.
Principles and methods of scientific thinking
One of the basic principles of scientific thinking is the use of experiment. This is similar to empirical thinking, but the difference is that with a scientific approach, the results of experiments apply to a wider range of phenomena, and the researcher has the opportunity to draw more diverse conclusions.
This is done through the construction of theories. In other words, one of the features of the scientific approach is that we can analyze and generalize the data obtained as a result of experiments.
Another principle of scientific thinking is that the researcher should always strive for detachment and objectivity. While empirical thinking always involves the direct participation of a person in the experiment and his subsequent assessment of what is happening, scientific thinking allows you to observe from the outside. Thanks to this, we no longer run the risk of accidentally or deliberately distorting the results of the experiment.
And, according to another important principle of scientific thinking, the researcher must systematize data to build theories. Even so long ago (before the 19th century), the empirical approach was most often used, when phenomena were considered separately from each other, and the relationships between them were almost not studied. But now the theoretical synthesis of knowledge and its systematization is much more important.
As for obtaining knowledge itself, the scientific way of thinking requires the use of special methods for this - ways to achieve a specific goal or solve a specific problem. The methods of scientific thinking (knowledge), as well as the levels of scientific knowledge, are divided into empirical and theoretical, as well as universal.
Empirical methods include:
- Observation- purposeful and meaningful perception of what is happening, due to the task. The main condition here is objectivity, which makes it possible to repeat the observation or use some other research method, for example, an experiment.
- Experiment- purposeful participation of the researcher in the process of studying an object or phenomenon, involving an active influence on it (an object or phenomenon) using any means.
- Measurement- a set of actions aimed at determining the ratio of the measured quantity to another quantity. In this case, the latter is taken by the researcher as a unit stored in the measuring instrument.
- Classification- distribution of phenomena and objects by types, categories, departments or classes based on their common features.
Theoretical methods are divided into the following:
- Formalization- a method in which scientific knowledge is expressed through the signs of an artificially created language.
- Mathematization- a method in which mathematical achievements and methods are introduced into the studied area of \u200b\u200bknowledge or the field of human activity.
At the same time, it is important to remember that theoretical methods are designed to work with historical, abstract and concrete knowledge and concepts:
- historical is what has developed over time;
- abstract is an undeveloped state of an object or phenomenon, in which it is still impossible to observe its established features and properties;
- concrete is the state of an object or phenomenon in its organic integrity, when all the diversity of its properties, connections and aspects is manifested.
There are a few more universal methods:
- Analysis- real or mental division of a phenomenon or object into separate elements.
- Synthesis- a real or mental connection of individual elements of a phenomenon or object into a single system.
- - selection from the general private, from the general provisions - the provisions of the special.
- Induction- reasoning leading from particular provisions and facts to general conclusions.
- Application of analogies- a logical method in which, by the similarity of objects and phenomena in one way, conclusions are drawn about their similarity in other ways.
- abstraction- mental selection of essential features and relationships of the object and their distraction from others that are insignificant.
- Modeling– study of phenomena and objects through the construction and study of their models.
- Idealization- mental construction of concepts about phenomena and objects that do not exist in the real world, but have prototypes in it.
These are the basic methods of scientific thinking. Naturally, we have omitted a lot of details and indicated only the basics, but we do not pretend to comprehensively address this issue. Our task is to introduce you to the basic ideas and concepts, and we think that we have coped with it. Therefore, it remains only to sum up.
Brief Summary
The development of scientific thinking influenced the formation of a scientific picture of the world - a special type of knowledge system from different areas, united by a single general scientific doctrine. It combines biological, chemical, physical and mathematical laws that give a general description of the world.
In addition to the scientific picture, people have philosophical, artistic and religious views on the surrounding reality. But only scientific perception can be called objective, systemic, synthesizing and analyzing. In addition, the reflection of scientific perception can be found in religion, and in philosophy, and in the products of artistic activity.
Scientific knowledge and scientific thinking have most seriously influenced alternative ways of perceiving the world. AT modern world one can observe that on the basis of the achievements of science, changes are taking place in church dogmas, social norms, art, and even the everyday life of people.
We can safely say that scientific thinking is a method of perceiving reality that improves the very quality of knowledge, contributing to. As a result, a person has a set of tangible advantages: he begins to realize and understand the most relevant individual tasks, set more realistic and achievable goals, and more effectively overcome difficulties.
Scientific thinking helps to improve the life of each individual and society as a whole, as well as understanding the meaning of life and its purpose.