It is shown that the implementation of breakthrough progress in artificial intelligence cannot be accomplished without a radical modernization of the methodological framework for research in this area. This upgrade can be performed only with the use of conceptual and methodological apparatus of dialectics. Its consistent application to objects, in either case connected with ideas about the intellect, results in the formulation of the dialectic symmetry principle. The first practical steps for the implementation of the proposed concept in practice are associated with the creation of a new education paradigm, which operates, including ideas that “education” being understood as a public institution, is not reducible to individual learning. Education in modern conditions can and should be viewed primarily as a tool to influence public consciousness, or more precisely, its subsystems.

We present a model of behavior that unifies behavior-based acting and conversational policies for speaking. This model is applied to the domain of air traffic control.

It is shown that the creation of artificial intelligence systems, gradually approaching human intelligence, cannot be limited by binary logic and the classical interpretation of the category of truth. The nature of human thinking is variable, which requires the use of flexible algorithmic platforms that operate with multivalued logic. It is shown that the existing approaches to the interpretation of the essence of intelligence, going back to the Turing test, are not consistent. More adequate is a criterion built on the ability of the intellect to lie, including creative particulars. It is shown that using multi-valued logic is a promising tool for constructing the algorithmic basis of artificial intelligence. It is shown that the use of just such logic is of interest from the point of view of studying self-organization processes in a telecommunication environment, resulting in the appearance of “spontaneous intelligence”, too. An analogue of such intelligence, for example, is the phenomenon of bureaucracy. It is shown that the question of the essence of the intellect is a prerequisite for the further development of non-trivial logical systems since the functioning of the intellect cannot be reduced to the operations of classical formal logic.

The fact that the theory of neural networks permits the completeness of the concept of global evolutionism has been shown. This concept in the current philosophical literature is seen, inter alia, as an effective platform for interdisciplinary cooperation, the need for which is becoming more acute, which is reflected in the anniversary report of the Club of Rome in the form of the thesis on the "New Enlightenment". The theory of neural networks allows us to give a consistent interpretation of the category of "complex", in accordance with which a system of arbitrary nature is treated as "complex" if it is possible to indicate a complementary analog of a neural network. With this interpretation, the evolution of systems of an arbitrary nature can indeed be described in a uniform way. In particular, the philosophical law of transition from quantity to quality can be reduced to a description in terms of information theory (through the description of the evolution of a neural network complementary to a complex system). The main result of the work is a new interpretation of the dialectical philosophy categorical apparatus on the basis of the theory of neural networks.

It is shown that voting procedure in any authority can be treated as Hopfield neural network analogue. It was revealed that weight coefficients of neural network which has discrete outputs −1 and 1 can be replaced by coefficients of a discrete set (−1, 0, 1). This gives us the opportunity to qualitatively analyze the voting procedure on the basis of limited data about mutual influence of members. It also proves that result of voting procedure is actually taken by network formed by voting members.