Science as a Game of Natural Intelligence
The article is devoted to the theoretical understanding of implementation of the human-sizedness principle within the framework of post-non-classical science. It is interpreted as a new methodological principle that increases the efficiency of modern science. Thus, post-non-classical science is considered as a system of knowledge, closely connected with people, that develops, on the basis of this approach, more complex criteria for asses­sing the knowledge obtained. People of the 21st century live in the world of more and more intensive communications and are forced to change in order to meet the conditions of their existence. They are born in a space that is constantly saturated with new digital devices, among which they are already quite comfortable to grow and develop. People will not only preserve, but also create new knowledge, discover the “true humanity” in the depths of history, as well as found the human-sizedness of the future, reducing the risks of existence and spontaneous search for models of individual and social balance. Growing up in a dynamic environment, modern man is ready to switch from the rigid, standard picture of the world to a multidimensional and flexible ima­ge of the world continuum. People are potentially able to maintain stability in a difficult to predict situation and confidently navigate in dynamically changing conditions. Research projects immerse people in intellectual competitions to achieve goals and solve problems, which turns into an intellectual sport. People always try to find new ways to interact with nature, develop new tools for this, among which an increasing place is occupied by artificial intelligence, with which you can calculate the many options for communication models. The author focuses on the productivity of this approach in wor­king on complex projects related to plotting the future and designing long-term tasks, when it is crucial to reduce formation risks, to push the horizons of development. The article pre­sents the process of scien­tific knowledge formation as a historically chan­ging one, analyzes a number of its inherent content cha­racteristics and algorithms, which are key to establishment of the modern format of knowledge rationalization.