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The goal set by A. Turing – the creation of a thinking machine – is one of the most important scientific problems that has not yet been solved. The modern frontier in this area is the creation of Artificial General Intelligence (AGI). Modern researchers are looking for different ways to solve this challenging task. In their search, many scholars point out that attempts to use exclusive lin­guistic communication to solve this problem are not enough. The authors of this article analyze a wide range of research and compare it with well-known re­search in the field of language and consciousness, which became known as the "Zagorsky experiment". Such a comparison of the latest achievements in the field of AI and an analysis of one of the most breakthrough achievements of neuroscience in the rehabilitation of deaf-blind-mute children is being done for the first time in the literature known to us. Based on the experience of the "Zagorsk experiment", the article concludes that sensory interaction with the outside world is a necessary condition for the creation of AGI. A vision of vari­ous forms of interaction between the machine and the surrounding world is pro­posed: from verbal to non-verbal, from virtual to physical and otherwise. These forms become the basis for the introduction of a new concept of techno-umwelt. Machine transitions from various techno-umwelts can serve as the basis for cre­ating an AGI that has the ability to act as good or better than a human in a vari­ety of environments.

Ethical issues in the development of artificial intelligence (AI) have been widely discussed in recent years, not only in the philosophical, but in the scientific liter­ature. This is largely due to the fear of obvious risks and threats that the growing digitalization causes in almost all areas of social life. Ethical research of artificial intelligence (AI) technologies becomes extremely relevant in the context of cre­ating a general AI system, that is, a human-level agent. This task seems difficult since ethics cannot present to engineers a normative system in the form of a cer­tain hierarchical architecture for its computational implementation. In this re­gard, authors of this article see an opportunity to avoid this uncertainty in de­signing an autonomous system of general AI by constructing particular models based on the classifier of activities. This will allow one to algorithmize the nec­essary ethical functions. There are two circumstances that need to be taken into account in further studies of artificial moral agency: (1) the continuality of any algorithmic model of an ethical system and (2) the effectiveness of the "reinforce­ment learning" method in modeling a situation of uncertainty and the mechanism of physiological pain as one of the factors in the formation of moral behavior.

In 2016, Hiroaki Kitano proposed that artificial intelligence (AI) will be able to overcome a number of human cognitive limitations that slow down the process of scientific discovery [Kitano 2016 web]. Since then, the odds of AI being awarded the Nobel Prize have been widely discussed, particularly within aca­demic community [Engineering for Research Symposium web 2020]. At the AI Journey 2021 conference, some renowned representatives of four scientific dis­ciplines (physics, mathematics, neurobiology, philosophy) discussed this issue and then co-authored this article [AI 2021 web]. In the first part of our paper, we critically analyze the role of AI technologies in natural science research: how useful they can be for fundamental science, what the potential of AI in natural and exact sciences is, and what principal limitations it has. Another part of our article discusses a counter-question of what science can do for the future re­search into AI. Today, it is impossible to imagine machine learning without lin­ear algebra, physics of materials, and brain research. All this falls under what is now commonly referred to as AI, a general umbrella term [Russel, Norvig 2021]. Thus, having served the birth of AI once, how can physics, mathematics, and neuroscience serve it today?

At the Artificial Intelligence for Science: Synergy of Achievements panel discus­sion at the III Congress of Young Scientists that was held in 2023, the usage of AI technology was analyzed on the interdisciplinary level (Biology, Physics, Engineering, Political Science and Philosophy). In this paper, we have analyzed the functions of artificial intelligence in science at all stages of a scientist's work, from hypothesis formulation to experimentation and scientific communi­cation. Previously advanced scientific tools were concentrated in state-funded research centers. The emergence of the artificial intelligence (AI) and super­computers is changing this paradigm: research and development often turn out to be in the hands of private companies. This state of affairs can be compared to a situation where half of the best modern microscopes would be in profit-driven organizations. The rapid development of AI has led to an intensive pene­tration of new technologies into scientific research, but at the same time has raised a number of concerns about their use. The new realities may cause a slowdown in scientific progress. In order to exclude this negative scenario, the authors of the article propose to consider the possibility of creating a sepa­rate scientific field of knowledge – Machine Epistemology, which would com­bine the philosophical approach and achievements in the field of AI. Such a so­lution, according to the authors, would allow us to most efficiently use new technologies to achieve progress in science and set ambitious tasks for hybrid interaction between scientists and artificial intelligence.