General Artificial Intelligence in Self-developing Reflective-Active Environments

The purpose—explain identify the features of General Artificial Intelligence (AGI), from the standpoint of scientific rationality stages (classic, non-classical, post-non-classical), and show its difference from traditional Artificial Intelligence (AI). The latter is currently implemented mainly with digital computers and implements the functions of recognition, forecasting and preparation of answers to simple questions. New conditions force us to consider AGI from the standpoint of functionalism, as a man–machine system, purposefully functioning in a self-developing poly-subject (reflexive-active) environment. Design/Methodology/Approach—AI development paradigm should consider aspects of its immersion in the social and humanitarian environment and the innovative atmosphere. The new paradigm of AI development should reflect the unformalized cognitive dynamics of AI models and support the self-development of AI systems under pressure from the external environment. The methodology of creating AGI is based on the ideas of the subject-oriented and ontological approach, functionalism, the phenomenology of subjective reality, the convergent cognitive architectures, as well as the methods of creating a self-developing poly-subject (reflexive-active) environment. AGI becomes a hybrid, purposefully integrating the capabilities of a machine and a person. Findings—General properties, value-semantic and intentional-volitional operational structures of the phenomenon of subjective reality do not lean itself on direct formalized and algorithmic representation in discrete computer systems of von Neumann architecture. The study of consciousness in the context of subjective reality made it possible to formulate the main systemic, structural, functional, and operational characteristics of human cognitive activity, which allows a new approach to the modelling of cognitive architectures that meet the tasks of building AGI. The characteristics of subjective reality cannot be fully represented in the paradigm of physicalism; that is, it cannot be represented only with the help of physical devices. The chapter proposes a non-reductionist way of taking this characteristic into account by considering the problem of consciousness in an ontological and epistemological context, which allows representing the processes of consciousness and cognitive activity of a person and a group of people indirectly and inversely. Originality/Value—State-of-the-art cognitive architectures and traditional AI approaches practically ignore solving the problems of AGI. They are more focused on the formalized construction of a thinking model, identifying physical blocks and processes of mental activity. At the same time, for AGI, ontological, subjective and hybrid reality issues are of the most importance, especially in explanations of the activity of consciousness, unconsciousness, and causeless processes, which can act purposefully in conditions of goal uncertainty. AGI must help to describe the phenomena of subjective reality, which causes physical changes, explain the ability of goal setting, free will, the ability of self-management by the physical actions of an individual in a team, etc. Research/Practical/Social/Environment implications—the chapter give rise to a new type of control, which differs from the traditional control in digital reality. The chapter’s results made it possible to uniquely find the optimal measure of centralization and autonomy of control loops that can ensure the preservation and strengthening of the integrity of a complex poly-subject system functioning in a reflexive-active environment, the interpretation of which does not fit into the narrow framework of digital and algorithmic reality, and traditional AI. Research limitations—the AGI approach based on exceptional methods of constructing subjective reality also has its limitations. For example, the approach we propose to explain the connection between the human brain, consciousness, thought processes and environment does not yet allow us to explain the information and cognitive processes generated by the effect of subjective reality nonlocality, which arises, e.g., at the atomic level of the human brain and should be considered when studying cognitive processes.