Objective embodiment of logic: from computational machines to life and intelligence?

Zhelnin Anton Igorevich ORCID: 0000-0002-6368-1363 PhD in Philosophy Associate Professor of the Department of Philosophy, Perm State University 614990, Russia, Perm Krai, Perm, Bukireva str., 15 antonzhelnin@gmail.com

Introduction. The metamorphoses of the logical

The subject of logic is considered to be the universe of human reasoning. In this case, it is worth recognizing that its subject area is limited to mental reality: "The subjects considered by logic are thus of an extrasensory nature - from this point of view they are similar to subjects studied by psychology and are opposed to subjects that natural science explores" ^{[1, p. 288]}. Despite the generally conventional acceptance of this approach, this concept remains ambiguous in philosophical discourse, and its subject area is ontologically vague. E. Lask writes about this: "Ancient as the world charms surround especially the word "logical". He is presented as something ultimate, incomparable, beyond any coordination, beyond which it is not allowed to ask questions" [2. p. 35].

Thus, there is a long tradition that considers logic to be an objective phenomenon. Having originated in Antiquity, it reached its apotheosis in the system of G. Hegel. He has a logical idea that acts as a genuine reality: "Logic shows how an idea rises to a stage where it becomes the creator of nature and passes to a form of concrete immediacy, the concept of which, however, again destroys this image in order to become itself in the form of a concrete spirit" ^{[3, p. 635]}. However, logic did not follow the path outlined by Hegel, starting in the 19th century. to implement Leibniz's plan for strict mathematization. Criticism of psychologism in logic has led to its understanding as a normative science that studies the connections and relationships between thoughts, but remains indifferent to their content. However, the normativity of logic is not enough to recognize it as objective. D.I. Dubrovsky rightly points out that the logical form, despite the fact that it fixes the objective, ultimately exists inside consciousness: "Every logical form is a form of thinking, a form of cognitive activity and its product. Due to the fact that the property displayed and fixed in it (relation, regularity) exists objectively in reality, it does not follow at all that the logical form itself exists outside and independently of consciousness" ^{[4, p. 63]}.

On the other hand, many logicians, partly due to the same struggle with psychologism, tried to outline a different subject area than thinking. She began to postulate language more and more often. This introduces some dissonance into the understanding of the logical subject: thinking as a mental phenomenon is subjective, while language as a sign system is objective: "The objective material shell in the form of which thinking exists is language. Consciousness exists in reality, practically in the form of language, while language is a material manifestation of thought" ^{[5, pp. 15-16]}. However, such a "liberation" from thinking seems half-hearted, because thinking and language exist in an inextricable connection, a kind of fundamental coordination: "Thought is not a given, it is a moment in the process of thinking, and the process of thinking, reason, is the process of language functioning. Language is the condition and mode of existence of the mind, outside of which there is no mind" ^{[6, p. 269]}.

Everyday language did not meet the high standards of logical rigor. Therefore, as noted by Ch.Pierce, "statements must be expressed somehow, and for this reason, formal logic, in order to completely free itself from linguistic or psychological considerations, invented its own artificial language" ^{[7, p. 172]}. Mathematical logic arose, which began to be understood in two ways: as a method of constructing logical systems by analogy with mathematical ones and as a metalanguage in which it is possible to speak about the reasoning itself, including mathematical. D. Hilbert formulated it as follows:  "logical thinking is displayed in logical calculus." The comparative ease of attributing calculus to logic was facilitated not only by its mathematization, but also by the specified vague ontological status. The possibility of transmitting logic using significantly different means than natural language clearly demonstrates their non-identity, including "logic does not form its own world, closed by a language system, logical categories do not grow to linguistic forms" ^{[5, p. 39]}. Meanwhile, the inevitability of the presence of a symbolic record in the case of mathematical logic confirms the connection of the latter with language in an extremely broad sense.

The conceptual foundations of the objectification of logic

Largely due to the convergence of these trends, one of the most original variants of the ontologization of logic appeared, presented in the works of L. Wittgenstein. For him, logic turns out to be something common to language and the world as a "mirror pair", and, consequently, something more fundamental than both of them: "Logic fills the world: the limits of the world are also its limits... Logical judgments describe the scaffolding of the world, or rather, represent them... Logic is not a teaching, but a mirror image of the world. Logic is transcendental" ^{[8, pp. 101, 112, 115]}. Despite the fact that it is often assumed that such hypostasis is characteristic of the early period of his work, in "Philosophical Studies" he expresses himself in an extremely similar way: "Thought is surrounded by a halo. – Its essence, logic, expresses the order, in fact, the a priori order of the world: that is, the order of possibilities that should be common to the world and to thought. It precedes every experience, permeates all events, and no empirical clouds or doubts can touch it" ^{[9, p. 84]}. Further, this idea found expression in the theory of possible worlds, according to which the laws of logic embody an invariant order for their entire multiverse, while the laws of nature vary. This leads to the radical conclusion that logic with its laws would remain even if reality did not exist at all: "Logic deals with a form of reasoning that does not depend on meaningful interpretation, the truth characteristic of logical judgments does not depend on the existence of the world, their form does not change with the replacement of categorical terms" ^{[6, p. 260]}. Here the a priori logic reaches its crescendo: it grows to a certain basic order, which returns to the ancient understanding of the logos.

The ideas of the objectivity of logic are also growing in Russian philosophical discourse. V.I. Shalak, dealing with the problems of protology (i.e., the foundations and genesis of logic), believes that it begins with the fact that the phenomena of the world itself are connected, and logic is simply its most abstract expression: "The fundamental nature of the laws of logic lies in the fact that it is distracted from the concrete It is aimed at studying the most general rules of operating with signs that go beyond the interest of specific sciences. It is for this reason that the laws of none of the other sciences can violate the laws of logic. By violating them, they will violate their own laws" ^{[10, p. 90]}. In our opinion, the concept of protology can be used in an ontological way, understanding by it the objective foundations of logic. Ya.A. Slinin puts about the same interpretation into his concept of logic-ontology: "In textbooks on logic they usually write that it is the science of forms and laws of thinking. To this we can also add that it is the science of the basic, most general properties of those objects that we think about. Logic-ontology studies the subjects we think about, their formal and most general features" ^{[11, p. 15]}.

The embodiment of logic in physical computing devices

But these trends remain theoretical abstractions. If we talk about the practical side of the objectification of logic, then we are talking about its application to the field of computing. Not only the theories of algorithms and computability themselves arose, but also the corresponding technique, the first computer devices. K. Shannon and a number of other theorists showed the possibility of implementing Boolean operations through the operation of relay-contact circuits. The possibility of such an embodiment of logic, like nothing else, clearly demonstrates the fundamental possibility of its removal beyond the subject. D.I. Dubrovsky calls such a mode of logic alienated, because it breaks away from its authentic source, thinking: "It is independent in the sense that it can exist in a form alienated from the human psyche, i.e. in the form of a system graphic signs, in the computer program, in the design of a technical device" ^{[4, p. 63]}. Over time, it became clear that the same logical states can be realized using different physical phenomena: "Logical values can be attributed to physical states, for example, "valve open/closed", "charge is/is not present", "light is polarized/not polarized", etc." ^{[12, pp. 93-94]}. For a number of reasons, transistors have become the backbone of computer technology progress. In them, the basic operations, called logic gates, are implemented electrically.

In the beginning, strictly speaking, it was not the computing devices themselves that were created, but their abstract models - the Turing machine and others. The priority of the model is a sign of both teleology and hylomorphism. The teleology is obvious, because before the machines, there was an ideal project in the minds of theorists. Hylomorphism also means the primacy of the structure before their specific implementation option. As H. observes. Putnam, "the "logical description" of the Turing machine does not contain any data on the physical nature of the machine as a whole. In other words, any given "Turing machine" is an abstract machine that can have an almost unlimited number of different physical implementations" ^{[13, p. 35]}. But we are not talking about absolute hylomorphism: a real computer is the result of a compromise between its logical and computational structure with its "rules of the game" and the material and technical substrate through which it is implemented. The trend of objectification of logic manifests itself in an ontologically expanded version of the Turing-Church principle, according to which it is necessary to take into account the substrate of the Turing machine, since it provides its ability to calculate physical processes by emulating them on physical processes inside the machine ^{[14, p. 73]}. To date, the conventional substrate remains integrated circuits consisting of billions of transistors. But this does not mean that this option will remain optimal indefinitely.

Representations of the logical in the biological

Modern science has come to the conclusion that the substrate for logical operations can be phenomena not only of a purely physical nature. Due to the abstractness of the computing machine, there is no formal prohibition that a living organism should serve as its embodiment: "A Turing machine is simply a system having a discrete set of states connected in certain ways. A Turing machine does not have to be a machine. A Turing machine could well be a biological organism" ^{[13, p. 73]}. The question of the potential and limits of the logical representation of biological is relevant not only in the context of experimental breakthroughs in the creation of logic gates and calculators from living objects, but also in the context of fundamental problems of the essence of life. The question of the existence of what can be defined as bio-logic is not unambiguous. The point of view of G. Bateson is indicative, who believed that initially nature itself used those principles, which were then artificially repeated in physical computing devices: "A well-known technique that life uses constantly, and untamed matter only in very rare cases. This is the reception of a valve, switch, relay, chain reaction, etc. In these cases, the inanimate world roughly imitates life" ^{[15, p. 114]}. However, synthetic biology so far proceeds by simply repeating the principles of an ordinary computer on various biosubstrates (genes, proteins, cells, bacterial colonies). For example, in the case of genome-based logic modeling, we are talking about its artificial reprogramming so that it begins to implement familiar logical functions: "The long-term goal of synthetic biology is the ability to reprogram gene networks that make decisions in order to implement them as logical elements in living systems" ^[16]. This approach imposes principles on life from the outside, using it as a transistor mechanism: "Recently, biologists and physicists have managed to make living cells perform mathematical actions, like transistors" ^{[17, p. 114]}.The alternative is to search for the immanent logic of the living. First, it should be based on a non-reductionist understanding of life. Secondly, it is necessary to show this logical principle in subtle unity with the objective content of the living. Thirdly, let us repeat, the extrapolation of logic to nature transforms the very understanding of the first, namely, returns us to an expansive understanding of logic. Its beginning was laid by Heraclitus in the doctrine of the logos not only as reason, but also as a world order: "He justifies the superiority of his logos over the logos of others by the fact that his logos is an exact copy of the logos of the Universe, which he managed to translate from the "language of nature" thanks to understanding the grammar of the cosmos. Heraclitus explains his philosophical method as hermeneutics, as the art of reading and interpreting the cosmic logos or the eternal book of nature" ^{[18, pp. 7, 64]}. In this context, it is worth noting that thinking itself is a real process, and if logic resides in it in its most developed state, then it is likely that other ontological phenomena contain its simpler forms (or their beginnings), the long genesis of which led in the final to the appearance of its human form.

The grounds that allow us to attribute at least logical similarity to a living being are the pronounced expedient aspects of the latter. I. Kant, analyzing the concept of teleology, noted: "Calling nature and its ability to act in organic products an analogue of art is completely insufficient, because in this case an artist (a reasonable being) thinks outside of it. It organizes itself, however, in each kind of its organic products according to the same pattern as a whole, but with the necessary deviations that are required for self-preservation under the given circumstances" ^{[19, pp. 247-248]}. Later, a compromise term "teleonomy" was proposed, designed to reflect the directed behavior of organisms based on objective patterns ^[20]. It is ensured by the harmonious work of numerous information and cybernetic mechanisms that function intensively at all levels of biological organization. K. Lorenz believed that adaptation as a way of living is essentially an information process: "The very word 'adapt' implicitly implies that this process establishes some correspondence between what adapts and what it adapts to. What a living system learns in this way about external reality, what is "imprinted" or "imprinted" in it, is information about the relevant data of the external world" ^{[21, p. 50]}. Information has an important endogenous role, maintaining homeostasis and ensuring the consistency of parts of the body. The presence of a hierarchy of feedbacks allows life to remain in a state of dynamic equilibrium, to implement self-adjustment and selection of behavioral models and trajectories of interaction with the environment ^[22]. Most often, the fundamental intention of the living is described as self-preservation, but the dynamic nature and broad autonomy are appropriately reflected by the concept of autopoiesis ^[23]. Meanwhile, the understanding of the living as an autopoietic system, according to H. Maturans and F. The concept of teleonomy overshadows Varela: "If living systems are physical autopoetic machines, teleonomy becomes only an invention of their description, which does not reveal any features of their organization, but which reveals the consistency of their operation within the domain of observation. Living systems as physical autopoietic systems are purposeless systems" ^{[23, p. 86]}.

Changing the angle: from teleology to algorithm

At first glance, denying the literal expediency of the living is a strong counterargument against its logic. It is not for nothing that Hegel saw in the teleology of life a manifestation of the fact that a logical idea begins to return to itself from a natural otherness: "Teleology in general has a higher principle – a concept in its existence, which the concept in itself and for itself is infinite and absolute – the principle of freedom, which, completely confident in its self-determination, is absolutely devoid inherent in the mechanism of external determinability... The goal is a concept that has returned to itself in objectivity" ^{[3, pp. 788, 793]}. However, let us recall that the understanding of logic itself has changed dramatically in connection with the computational revolution, when "in order to build algorithms, it turns out to be transformed into an axiomatic technique" ^{[24, p. 35]}. That is, logic itself began to break away from the thinking subject through its "mechanization". Goal-setting has been replaced by the concept of an algorithm as aimed at achieving the result of a discrete sequence of steps, which has become central to a number of new computational directions.  But note that logic is often interpreted broadly as the order of something (thoughts, actions).No one would dare to call computers goal-setting, but this does not prevent us from recognizing that their work is based on algorithms. But we can also say about organisms that they implement ordered sequences of actions to achieve a result, i.e. that their behavior is to some extent algorithmized. V.I. Shalak offers a general scheme for formalizing result-oriented behavior and recognizes that it is applicable to living things: "An elementary "brick" of purposeful behavior can be It is described as follows: “If there is a C, do d to achieve G.” Let's call it an elementary rule of purposeful behavior and write it in the form: C : d : G... Note that the behavior described by the rules of the type "C : d : G" is peculiar not only to humans, but also to many representatives of the animal world" ^{[25, p. 13]}. Note the importance of implicative communication for the formalization of teleonomic types of action. In our opinion, the above scheme can be divided into two conditional parts. 1). C ? d: if there are conditions C, then perform actions d. 2). If actions d are performed, then the result G is achieved. In case of actually successful implementation, this scheme is reduced according to the transitivity rule: 3). With G: if there are conditions C, then the result G is achieved. Attributing algorithmic and therefore broadly logical functioning to a living being may also be an error of the "observation domain". Often, allusions to the algorithmicity of life for verification turn out to be a metaphor designed to reflect the complexity of its organization and the high role of information and cybernetic aspects necessary for self-preservation: "All forms of life primarily fight for a place in the sun not with each other, but against the chaos of inanimate nature. Bacterial, fly, and human cells are primarily chaos killers and anti–accumulators of entropy (disorder). Their weapon is a universal chemical and morphological organization, as well as the organized behavior of molecules and organelles controlled by software programs" ^{[26, p. 38]}. The question of whether or not the behavior of a living being is such should be based on a strict distinction between ontological and epistemological plans, while recognizing the primacy of the former: bio-logic should be inscribed in bio-ontology.

Refutation of the algorithmicity of the living: the case of the genome and the brain

To refute the algorithmicity of life in ontological terms is a non–trivial task. It is worth focusing on such general properties of the algorithm as discreteness and determinism. The first means that the algorithm can be divided into a finite number of "steps". The second is that each next step of the algorithm is uniquely determined by the previous ones. None of this is incompatible with the reality of the living. Even the most computationally similar biosystems – the genome and the brain – turn out to be living totalities whose behavior is alien to the implementation of strict and unambiguous formalisms. So, despite the fact that the genome at the beginning of the study was interpreted as a cipher consisting of combinations of only four elements - "letters", further progress has shown that its activity is multidimensional and comprehensively connected with other levels of the organization of living beings by a dense network of reciprocal connections. E. Schrodinger noted the insufficiency of the concept of "code" in relation to the genome: "The term cipher code, of course, is too narrow. At the same time, chromosomal structures serve as a tool for the development that they also foreshadow" ^{[27, p. 47]}. This inseparable totality of the genome, organism and environment is most vividly reflected by modern epigenetics, which proves that DNA is not a metaphysically "frozen" substance, it itself interactively changes, not only structurally, but primarily functionally (through "subtle" modulation of the expressive activity of genes in real time). Such a complex organic integrity does not fit into the metaphor of machine computing. It is fair to conclude that the semiotic (code) interpretation of the genome is just the product of an epistemological "domain" and cannot be ontologically hypostatized: "Of course, we are not talking about the genetic processes and mechanisms themselves, which, of course, are a biochemical substance, but about their description, meta-representation... No semiotic models are capable of describing the processes of biochemical interaction" ^{[28, p. 97]}.To a much greater extent, this conclusion also applies to the brain, the nervous system, which is also often represented as computational. Moreover, this was embodied in literally logical versions that go back to the McCulloch-Pitts model of nervous activity ^[29]. Its central idea is that the work of each neuron as a unit of the network obeys binary logic, embodied in the principle of "all or nothing"): "The law of nervous activity "all or nothing" is sufficient to ensure that the activity of any neuron can be represented as a proposition" ^{[29, p. 100]}.  The activity of a neural network in this context represents complex logical statements, which are a set of simple (spikes of individual neurons) connected by bundles: conjunction correlates with the summation of input signals by a neuron, disjunction – processing alternative signals, negation – signal inhibition, implication – a sufficient condition for transmitting a signal further, etc. The further formation of a computational metaphor is mainly related with the analogy between the brain and the computer, which was started by J. von Neumann. He was the first to identify differences in the functioning of the nervous system and computers. However, they were more concerned with details: not the purely electrical, but the electrochemical nature of the pulse, the largely analog nature of its signal, and the many times greater parallelism in the processing of information by the brain. From his point of view, they did not negate the fact that the neuron really obeys the principle of "all or nothing", and therefore its functioning can be described by a binary number system, complementary to classical two-digit logic: "Nerve impulses can be considered as markers: the absence of an impulse represents one value (say, the binary digit 0), and its presence is another value (say, the binary digit 1)... The nerve impulse should be considered as a marker (binary digit 0 or 1) in a special, logical role" ^{[30, p. 127]}. That is, on the one hand, the work of the nervous system is theoretically radically simplified: all the qualitative specificity, the variety of neurons and their spikes, in principle, all their material morphological certainty are theoretically leveled with the simultaneous absolutization of common and quantitatively expressible aspects (the number of synapses and spikes in them, their speed, amplitude, frequency, etc.). In the limit, such a model boils down to the described "there is an impulse-there is no impulse" dichotomy, when the brain is represented as an aggregate of a huge set of binary events that do not carry any knowledge about their content. On the other hand, the computational model of the brain was largely based on an overly expansive interpretation of the concept of computation, which transformed from operations on numbers into any processing of information in code form. Thus, P. Churchland identifies calculation with the operation of states representing something: "We can consider a physical system to be computational when its physical states can be considered as representing the states of some other systems, where transitions between its states can be explained as operations on representations... Nervous systems are also physical devices with causal interactions that represent transitions between states... they are configured so that their states represent the outside world, the body in which they live, and in some cases parts of the nervous system itself – and transitions in their physical states represent calculations" ^{[31, p. 62, 67]}. Of course, the nerve signal represents data in a special symbolic form, but it is unlikely that this form is purely quantitative and therefore computable. The brain, like any other biosystem, is a fundamentally high-quality object with gigantic internal heterogeneity: "If we talk in more detail, there are hundreds of different types of neurons in the brain, and individual synapses contain hundreds of different proteins. Duplication and divergence shape the evolution of the brain in the same way as in biology in general" ^{[32, p. 551]}. This diversity is not an accident of evolution, it is adaptively tailored to the variety of behavior tracks implemented by the brain and problem situations solved by it. The function in this case is primary, it is capable of modifying its substrate. Therefore, the computer's inherent division into hardware and software cannot be detected in the brain. However, the difference in architecture is not the main argument against the algorithmicity of the brain. Unlike simply following algorithms, the brain's work is essentially creative, it rebuilds itself depending on life experience, environmental conditions, needs, etc. Therefore, the concept of autopoiesis as an immanently inherent self-generating activity is applied to it to the maximum extent. The phenomena providing the latter, such as neuroplasticity and neurogenesis, have been studied relatively recently. K. Malabu believes that it is neuroplasticity as the ability to flexibly rearrange the neural networks of the brain that is the central evidence against the metaphor of the brain as a machine: "The analogy between the cybernetic sphere and the cerebral sphere is based on the idea that thinking is reduced to calculation, and calculation – to programming. The discovery of the plasticity of brain function has made such a comparison controversial. The rigidity, immutability and anonymity of the control center is opposed by a model of flexibility, which assumes a certain degree of improvisation, creativity, and aleatory" ^{[33, p. 35]}. Thus, the brain is an organic totality, whose life is irreducible to processing arrays of zeros and ones. This dichotomy itself is false, because in a nerve impulse, qualitative specificity, its content loading, modulation by various bioagents, environmental and behavioral contexts are primary. Biosystems are systems that do not calculate, but adapt to the environment: "These are natural adaptation processes that unfold over time and do not follow forced algorithms. The actions of the mechanisms of adaptation to the environment and its changes can be described quite well, in addition to the ideas of a "natural parallel computer" ^{[34, pp. 40-41]}. Logic correlates with life even more indirectly: in fact, the main similarity is the presence of binary "values" in some biosystems and the similarity of the functioning of some of them to the implementation of Boolean operations, which, firstly, is a strong simplification in itself, and, on the other hand, is a consequence of the epistemological domain of the human subject cognizing it, generating logocentric models, since he himself is the bearer of logic.

Refutation of the algorithmicity of the living: the case of intelligence

In the final part, we will turn to intelligence as another possible "candidate" for the embodiment of logic. It would seem that it is the human intellect that is the cradle of the logical. However, there is a well-known tendency to separate intelligence from humans, based on the presumption that a special type of computing machine can imitate it or even possess it. An important role was played by the vagueness of the definition of AI and its boundaries. H. Dreyfus insists on a definition that emphasizes that AI claims to model human thinking: "AI is an attempt to model intelligent human behavior using programming methods that have little or no resemblance to human thought processes" ^{[35, p. 29]}. Other theorists, on the contrary, give a definition that does not correlate in any way with thinking or other mental term: "In essence, the creation of artificial intelligence is a struggle to develop the best possible agent program in this particular architecture" ^{[36, p. 1249]}.

However, the more fundamental reason is the long–maturing tradition of representing the human mind itself as computational in nature, including the transformation of the concept of intelligence is primary before the concept of AI. The merging of the concept of "intelligence" with formal adherence to rules and processing of information flows led to its deanthropologization, a paradoxical separation from human consciousness: "Consciousness seeks meaning in the meaningless. Intelligence is looking for a repetitive algorithm. In human reality, you can always find an algorithmic part and a non-algorithmic one. The first is intellectual, coupled with knowledge. The second is conscious" ^{[37, p. 26]}. This dualistic gap has led not only to the very possibility of the concept of machine intelligence, but also to the idea of the existence of natural bio-intelligence, which also does not need consciousness: "Life adapts to what it is. In it, the intelligence of a living organism is packed into instinct, into the natural mind" ^{[37, p. 23]}.

However, such natural intelligence is still radically different from AI: modern science has refuted the idea of organisms as Cartesian automata. Intelligence in this perspective appears as a certain stage of the evolutionary process, which was reflected, for example, by A. Bergson: "An essential function of intelligence, as shaped by the evolution of life, is to illuminate our behavior, prepare our impact on things, foresee events favorable or unfavorable for a given situation" ^{[38, p. 29]}. Despite the fact that it can be described in mechanistic and computationalist terms, presenting itself as an analytical "ability to associate like with like, notice, and create repetitions" ^{[38, p. 46]}, in the end it is still an organic product of the evolutionary process.

Moreover, bio-intelligence is always rooted in the very bodily organization of a living being, and, as we have shown, it is an unalgorithmizable totality, where everything is reciprocally intertwined and does not obey description in machine terms. The living intellect embodied in the body is always "sharpened" under the teleonomy of the organism, being a special, highest form of adaptation. J. Piaget noted on this occasion: "The dual nature of intelligence, at the same time logical and biological, is what we should proceed from" ^{[24, p. 6]}. The presence of physicality and the psyche rooted in it with its complex neural and sensory-motor physiological basis is the vital framework on which the cognitive "superstructure" is realized, such intellectually loaded phenomena as conceptual thinking and reasoning, understanding, speech: "A "machine" that could use natural language and recognize complex images She must have a bodily organization that allows her to "feel at home in the world" ^{[35, p. 281]}. The importance of the corporeal dimension for intelligence and consciousness is reflected in the concepts of enactivism ^[39], "embodied mind" ^[40], the theory of the self by A. Damasio ^[41] and others. Damasio, for example, believes that self-awareness has a necessary basis for the proto-self, literally immersing the Ego in the somatic plane, expanding consciousness through dynamic processing of information flows coming from the body in sensory, kinesthetic, emotional registers. Therefore, such a "broadened consciousness" is much broader than intelligence, acting as its necessary foundation: "Expanded consciousness is not the same as intelligence. Expanded consciousness should inform the body about the widest range of knowledge, while intelligence refers to the ability to manipulate knowledge so successfully that new reactions can be planned and produced. The expanded consciousness must expose and manifest knowledge so clearly and effectively that intellectual processing can take place. Expanded consciousness is a prerequisite for intelligence" ^{[41, p. 198-199]} It is obvious that the concept of AI is a product of one–sided hypertrophy of the logical principle in intelligence to the detriment of the biological one.

Once again, living organisms do not calculate, but adapt. The difference is that the result of the calculation is formally set a priori, while the result of adaptation, the degree of its "success" is summed up purely a posteriori and depends on a large number of highly varying and non-formalized parameters, the external environmental context. Therefore, even the authors discussing the computationalist foundations of natural intelligence recognize the insufficiency of the concept of computation and the need to take into account the adaptive background of intelligence as a property of a biological "agent" ^[42]. However, recognizing the natural dimension of intelligence is not enough. A person's personal intelligence is intrinsically social, because it is formed and functions only within the framework of human society, the system of culture and language. Therefore, intelligence is not a kind of self-sufficient substance, but is inscribed in both a natural and socio-cultural context: "Human intelligence has both biological and social roots and is by no means an isolated and independent absolute entity" ^{[43, p. 65]}. This is due to the fact that the very natural foundations of intelligence (neural networks and even genes) are located with culture in a system of reciprocal connections, in a kind of mutual co-creation: "Society and culture have a significant impact on the formation and functioning of the brain; they largely determine the modes of activity of certain neural networks. In turn, the architectonics and activity of various brain regions have a reverse effect on society and culture, giving them specific features. Society, culture, and the brain are an integral system, each element of which affects the other elements in one way or another" ^{[44, pp. 85-86]}. Modern researcher P. Wang, defining intelligence as "the ability of a system to adapt to the environment when working with insufficient knowledge and resources," compares it with reasoning systems (logical systems), highlighting their invariant features (the presence of a formal language, semantics, a set of inference rules), and eventually comes to the conclusion that "to be a system of reasoning is neither necessary nor sufficient to be intelligent" ^{[46, p. 40]}.

Implemented through computer devices and their networks, the logical and computational dimension is insufficient for the "embodiment" of living intelligence, and a fatal ontological gap remains between them. It is the latter that creates an obstacle to the creation of an autonomous "general" ("strong") AI, which makes the concept of "strengthening (augmentation) of intelligence" preferable ^[47], which assumes not the replacement of human intelligence with machine intelligence, but the expansion of its abilities through the use of technologies that are obviously ontologically inferior to it, preserving the status of a means.

Conclusion

Summing up, we can conclude that the concept of the objective embodiment of logic has a long history and is based on certain ontological grounds. The main practical manifestation of this idea remains the use of logic in the functioning of special physical computer devices. In turn, it itself became possible due to a theoretical transformation in understanding the essence of logic as such, the dense fusion of logic with mathematics and the theory of computation. Logic-like elements are found at various levels of computer hardware and software (from transistor architecture and bit encoding of information to many algorithmic principles in the implementation of program code). At the same time, the question remains open to what extent the similarity of logic to the operation of a physical computer device is essential and whether it is not based on a superficial and therefore false analogy.

The success of the physical realization of logic has given rise to optimism in its transfer to other media, including biological ones. In the case of the living, he encounters ontological obstacles related both to the emergence of life, its irreducibility to its physico-chemical basis, and to the non-rhythmic nature of its functioning. The cases of even such computationally similar systems as the genome and the brain show that they turn out to be fully living totalities that are alien to formal adherence to pre-established rules. This strangeness stems from such a central phenomenon of life as autopoiesis. He is an active self-creation that avoids standardization and expresses itself in the permanent formation of life as other in relation to oneself. It can be concluded that the imposition of logic on a living person is inhibited by the presence of his own immanent "bio-logic", which by its very nature is absolutely different from the accepted idea of the logical.

The situation is even more paradoxical with the attempt to represent intelligence as a logical and computational phenomenon. Despite the fact that intelligence is considered the main receptacle of logic, real living intelligence also turns out to be alien to it, since it de facto always turns out to be physically "flattened", immersed in somatics. As such, it is a special form of adaptation of the living. The logocentric understanding of intelligence tries to detach it from this vital foundation, which conceptually finds expression in the idea of a non-biological, purely machine form of it. But precisely because of this ontological gap, AI is not intelligence in the full sense of the word. The hypertrophy of logical and computational structures does not allow him to make up for the lack of flexibility and adaptability of natural intelligence. Logic is radically insufficient to model living intelligence. Again, this does not negate the possibility of a special immanent bio-logic of the living, but the main question is not only its essential specificity, but also to what extent it is an objective phenomenon, and to what extent it is a product of epistemological attribution, an anthropomorphic metaphor of the cognizing subject himself.

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