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The prospects for the use of artificial intelligence (AI) are one of the most discussed topics in medicine today. The very possibility of having an omniscient virtual assistant at hand soon seems incredibly tempting, so it seems quite normally to see numerous reports on the application of each newly emerging advanced neural network technology in various fields of medicine and biotechnology. Of course, the emergence of ChatGPT caused the greatest public outcry in recent times, because the new natural language processing algorithm underlying it has allowed human to bring communication between man and machine to a whole new level. Of course, despite the myriad benefits of using AI, the use of ChatGPT and other AI tools in medicine raises many ethical and legal questions. However, it is worth remembering the history of the emergence of any other breakthrough technology to accept the existing controversy as an integral part of progress. The desire of a person to make his work easier and shift part of the work onto a computer always makes him take a step forward in the development of technologies, which, in the end, do not allow a person to work less, but make him work in a new way.

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In the context of global technological transformations and active penetration of artificial intelligence technologies and neural network algorithms into the digital space of socio-political communications, a new format of socio-political interactions is being formed today, defined by the widespread use of “smart” tools and mechanics of content generation and broadcasting in communication processes. In this regard, there is a demand for scientific research into the processes of the influence of artificial intelligence and neural networks on the content and functional parameters of modern socio-political communication interactions. The purpose of this study was to determine the relationship between “smart” technologies and the transformation of the contemporary space of sociopolitical communications in terms of the formation of risks, threats and challenges of a new type associated with the introduction of digital solutions based on the application of artificial intelligence technologies and neural network algorithms in the current practice of sociopolitical communications. The main research question is the extent and nature of the impact of the introduction of artificial intelligence technologies and neural network algorithms in the contemporary space of socio-political communications. To achieve the research goal and answer the research question, the authors applied the method of discourse analysis of scientific sources on the research topic, as well as conducted an international expert study, which allowed to identify key expert positions on the research topic and, based on the compilation of expert assessments, to identify the main risks, threats and challenges of socio-political nature formed in the processes of modern digital communications. The main conclusion of the paper is the thesis, substantiated and confirmed by the results of the research, that there is a wide range of socio-political risks, threats and challenges associated with the introduction of artificial intelligence technologies and neural network algorithms into the processes of contemporary digital communication. The paper provides a meaningful analysis of these risks, threats and challenges of a new type that can significantly affect the nature, dynamics and scenarios of the contemporary technological development of key spheres of life of the contemporary state and society.

This paper is devoted to the construction of routes for evacuation of employees from the building in case of an emergency situation. Fire extinguishing and fire control system as well as public address and evacuation systems are considered. Graph theory is applicable to construct optimal evacuation routes. There are also many solution methods suitable for practical use. Computer software "Program for building routes for evacuation of employees from the building in case of emergency" was developed. It is designed to calculate evacuation routes for employees of institutions or residents of high-rise buildings in case of an emergency situation. It is designed to calculate evacuation routes for employees of institutions or residents of high-rise buildings in case of an emergency situation. The results of numerical calculations are displayed in the form of a graph. The conclusion presents the future prospects for the development of fire safety systems. [ABSTRACT FROM AUTHOR]

The paper analyzes possible ways of protecting artificial intelligence systems and their elements with the help of intellectual property law from the perspective of European Union law. This paper deals with copyright law, patent law and sui generis database protection in relation to artificial intelligence systems. The paper begins with an analysis of whether and how an artificial intelligence can be protected by means of copyright. The author analyzes the European Union’s copyright acquis and concludes that the elements of the AI system, as well as the entire artificial intelligence system, that are implemented in software, can be protected by copyright as a computer program if the originality requirements are met. However, the originality requirement is unlikely to be met in all cases in this context. The same issue with the originality requirement applies to potentially possible copyright protection of artificial intelligence systems as databases. Therefore, it is concluded that the fulfillment of copyright requirements for protection of an artificial intelligence system must be established in each particular case. The author also considers whether patent law is applicable to protect artificial intelligence systems. For this purpose, the provisions of the patent law of the European Union, in particular, of the European Patent Convention, are analyzed. The author concludes that the artificial intelligence system may be patentable as a “computer-implemented invention” in case all the requirements for patent protection are met. Sui generis database protection is also considered as an additional possibility for legal protection of artificial intelligence systems, taking into account that its applicability is limited to the European Union. Whether sui generis database protection is applicable to the artificial intelligence system should be decided on a case-by-case basis.

Copyright of Scientific Bulletin of Polissia is the property of Chernihiv State Institute of Economics & Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The term photography means both the technological process of the formation of photographic image in the traditional or digital way, as well as its end product, that is, a photograph in the form of a print on light-sensitive paper or a digital file. The aim of the paper is to depict photography as a technique dependent on the development of science, but, at the same time, affecting the development of many areas of life and research. The article presents the most significant stages in the history of photography. It does not merely focus on listing the most prominent names, currents and works. Most importantly, it portrays the speed with which photography improved, together with new experiences and inventions of apparatus and technological processes, continuous striving for excellence in the image obtained, as well as fundamental changes to the function of photographic image once the press, Internet and social media came to be, allowing one to share pictures taken all over the world in a split second. The perfection of the photographic image and its vast spread led to the use of pictures uploaded to the Internet in AI algorithms.

Objective: to substantiate the mechanisms of legal protection of intellectual property objects created with the use of artificial intelligence.Methods: the use of artificial intelligence to create works that are traditionally considered copyright objects was investigated with a set of general scientific and theoretical-legal methods of scientific cognition, including comparison, analogy and synthesis. In addition, the practice of using artificial intelligence, including neural networks, to create such works was considered in several aspects on the basis of retrospective and multifactor analysis.Results: the paper summarizes the current practice of using artificial intelligence to create works that traditionally belong to intellectual property objects (texts, images, music, software), taking into account the formulated scientific and legal positions. Several qualitatively different variants of the use of artificial intelligence were identified. For each of these variants the mechanism of legal protection was proposed and the areas of their effective application were indicated. Proposals were made to regulate the legal protection of the results of artificial intelligence activity; this was made not in the paradigm of competing doctrines, but by combining several tools, each of them to be applied in a relevant situation.Scientific novelty: the paper presents ontological differentiation of the results of artificial intelligence activity and the corresponding mechanisms of their legal protection. The author propose to consider the results of activity created by artificial intelligence not as a single object of legal regulation, but as a set of externally similar, but ontologically different objects, each requiring a separate approach to legal protection.Practical significance: the ontological differentiation of the results of artificial intelligence activity and their corresponding legal protection mechanisms proposed in this paper is relevant both as a basis for further research and as proposals to supplement civil legislation.

Copyright of NaUKMA Research Papers in Philosophy & Religious Studies is the property of National University of Kyiv-Mohyla Academy, Faculty of Humanities and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: to answer the question whether the authors’ moral rights the in the digital environment correspond to their original purpose, and to determine the impact of the development of social networking platforms, artificial intelligence technologies and non-fungible tokens (NFT) on the transformed role and features of the protection of the author’s moral rights under modern conditions.Methods: the research is based on historical-legal, comparative-legal and formal-dogmatic methods. Legal institutions and legal practice on the issue of protection of the author’s moral rights are subjected to critical analysis.Results: the genesis and normative fixation of the author’s moral rights are investigated in historical retrospect. It is noted that at present the protection of these rights is insufficiently regulated at the international level, while national copyright law, for example, of continental European states, provides a sufficiently strong protection of the author’s moral rights; however, the effectiveness of the latter is weakening in the digital age. The paper analyzes the changing landscape of copyright relations caused by technological progress: in social networks, in the generation of works by artificial intelligence, and in the creation of digital works of art. The thesis is substantiated that the author’s moral rights are undesirable in the context of social platforms. The paper proposes solutions to the issues of authorship of works created by artificial intelligence, violation of author’s rights, and integrity in case of full or partial borrowing of a work to generate a new work by artificial intelligence. The role of NFT technologies in solving the problem of preserving the author’s moral rights is defined.Scientific novelty: the work fills a gap in research on the relationship between copyright and technological development. It identifies and evaluates the innovations in the purpose and content of the author’s moral rights, caused by the processes of digitalization, and attempts to solve the problem of the author’s rights compliance with technological progress.Practical significance: the obtained results may serve as a conceptual basis for further development and improvement of national legislation and international legal regulation in the field of copyright protection, transformation of the objectives, role and place of the author’s moral rights in the digital environment.

The emergence of artificial intelligence language services has raised hopes related to facilitating the task of publication activity. Members of the academic community wondered whether chatbots could optimize the process of scientific writing. ChatGPT, a language model capable of, among other things, generating scholarly texts, received particular attention. The cases of writing academic papers using ChatGPT have led to a number of publications analyzing the pros and cons of using this neural network. In this paper, we investigate the possibility of using ChatGPT to write an introduction to a scientific paper on a topical issue of the Arctic governance. A set of queries to ChatGPT network, based on the logic of the commonly accepted in academia publication format IMRAD, has being developed. This format is characterized by structural and functional elements, which served as a logical basis for the queries. The responses received from ChatGPT were analyzed for their compliance with the requirements for a scientific article, according to the IMRAD publication format. The result of the analysis showed that ChatGPT is not able to meet the requirements for publishing a scientific article in the modern scientific publication discourse.

The paper aims to present the theoretical and methodological foundations for developing and implementing artificial intelligence (AI) instruments in higher education within the HumanCentered AI framework and considers ChatGPT as a specific case. It is oriented toward critically analyzing scholarly literature from various disciplines to support a-disciplinary approach to utilizing AI research in higher education. The authors begin by outlining the foundations of the research, then by analyzing the implications of the “lessons” of the COVID-19 pandemic for the development of higher education in the age of AI. This is followed by an analysis of technologies such as ChatGPT that have the potential to radically change higher education in the near future. After that, the authors move on to general remarks about the prospects and challenges of using AI technologies in higher education. The relevance of the research is characterized by the analysis of the latest developments in the field of AI and their possible impact on higher education. The main results of the paper are characteristics of areas in which AI technologies can be implemented in higher education – accreditation and licensing of universities, student recruitment, teaching and learning – as well as areas in which AI technologies should not be used. In conclusion, two hypotheses are formulated, and three general and five specific conclusions about the use of AI technologies in higher education are made.

Copyright of Biuletyn Polskiego Towarzystwa Językoznawczego is the property of Polish Linguistic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The availability of digital infrastructures and the fast-paced development of accompanying revolutionary technologies have triggered an unprecedented reliance on Artificial intelligence (AI) techniques both in theory and practice. Within the AI domain, Machine Learning (ML) techniques stand out as essential facilitator largely enabling machines to possess human-like cognitive and decision making capabilities. This paper provides a focused review of the literature addressing applications of emerging ML tools to solve various Project Scheduling Problems (PSPs). In particular, it employs bibliometric and network analysis tools along with a systematic literature review to analyze a pool of 104 papers published between 1985 and August 2021. The conducted analysis unveiled the top contributing authors, the most influential papers as well as the existing research tendencies and thematic research topics within this field of study. A noticeable growth in the number of relevant studies is seen recently with a steady increase as of the year 2018. Most of the studies adopted Artificial Neural Networks, Bayesian Network and Reinforcement Learning techniques to tackle PSPs under a stochastic environment, where these techniques are frequently hybridized with classical metaheuristics. The majority of works (57%) addressed basic Resource Constrained PSPs and only 15% are devoted to the project portfolio management problem. Furthermore, this study clearly indicates that the application of AI techniques to efficiently handle PSPs is still in its infancy stage bringing out the need for further research in this area. This work also identifies current research gaps and highlights a multitude of promising avenues for future research.

The article presents the results of a study to identify trends in the coverage of digital technology and artificial intelligence in scientific papers. Semantic units reflecting aspects of digitalization, artificial intelligence, augmented reality are revealed. The main semantic units, reflecting different aspects of the research field are digitalization; artificial intelligence (additional semantic units: knowledge representation, theorem proving, computer vision, robotics, machine learning, multi-agent systems, artificial intelligence tools); neural networks (additional semantic units: learning with a teacher, learning without a teacher, input data); strong or general artificial intelligence, weak or applied artificial intelligence; Marusya voice assistant, Alisa voice assistant, Siri voice assistant, Bixby voice assistant, Google Assistant; speech recognition, fingerprint recognition, human face identification. Quantitative changes in the coverage of digital technologies, artificial intelligence, augmented reality elements in scientific papers of scientists for the period from 2016 to 2021 are presented and graphically visualized. The analysis of quantitative characteristics of materials and content component of semantic units on the indicated theme is given. The subject of the study is the publications of Russian and foreign authors, dealing with the issues of digitalization and artificial intelligence, included in the database of the Russian Institute of Scientific and Technical Information of the Russian Academy of Sciences (VINITI RAS) for the period from 2016 to 2021.

The present paper functions as an introduction to this special issue of mediAzioni, which brings together selected papers presented at the Translating Europe Workshop entitled "L'intelligenza artificiale per la traduzione verso una nuova progettazione didattica?" (3 December 2021), focusing on the pedagogical implications of Artificial Intelligence (AI), with a particular emphasis on Neural Machine Translation (NMT). The article revolves around three main themes. First, it considers the impact of emerging neural technologies on language services, redefining the traditional role of the translator and creating new responsibilities and tasks. Despite the considerable progress that NMT has made compared to previous models, it still has shortcomings that are almost "invisible" because they often lack clear grammatical or morphosyntactic marking. Such errors require a certain cognitive effort to identify, since they involve problems that are less obvious to the untrained eye, such as textuality or inadequacies at the level of discourse. Secondly, the article looks more closely at professional practices, especially those related to pre-editing, post-editing and proofreading. Particular emphasis is placed on the indispensable role of the human in translation workflows that integrate NMT not only at the level of post-editing and text revision, but also at the level of translation project management. Finally, the paper moves on to the implications of NMT for the training of translators and beyond, discussing key insights from the workshop participants regarding future teaching practices at university level. The article concludes by outlining the structure of this special issue and providing a brief synopsis of the collected papers.

The digitalization of industry is a hot topic marking the entry into a new era of industrialization. The combination of enterprise management and digital technology has become an important task of modern enterprise management. Against such a backdrop, the application of various digital technologies has changed the production, marketing and other functions of enterprises. Artificial intelligence is an important means of realizing the digitalization of enterprises. At the international online conference AI Journey 2022, the President of the Russian Federation Vladimir Putin stated the need to implement artificial intelligence in the economy, social sphere and in the activities of government agencies. According to him, "the importance of breakthroughs in the field of artificial intelligence is colossal". At present, scientific research to assess the impact of the introduction of artificial intelligence technologies on the innovative activity of enterprises is of great interest. The purpose of the study is to substantiate the impact of the adoption of artificial intelligence technologies on the performance of substantive innovation enterprises based on the data of Chinese exchange-listed enterprises from 2012 to 2019. Based on the literature analysis, the main hypothesis of the paper is that artificial intelligence technologies have a positive impact on the substantive innovation in enterprises. To assess the impact of artificial intelligence technologies, the paper uses a statistical model with fixed effects. The fixed effects model was constructed based on the Ordinary Least Squared (OLS) method. To decide on the selection of initial, control and resultant variables, the research results of Li Wenqian et al. were used. The results of the study showed that artificial intelligence technology has a positive effect the substantive innovation in enterprises. These findings were confirmed by the result of robustness and non-homogeneity test. The results of the non-homogeneity test showed significant differences in the impact of AI technologies on substantive innovations in enterprises with different forms of ownership. The most significant influence of AI technologies on substantive innovation was found in private enterprises, followed by the second most significant influence on substantive innovation in state-owned enterprises and insignificant influence in Sino-foreign joint ventures. The results of this study can be used to evaluate the effectiveness of the application of artificial intelligence technology in other industries.

Artificial intelligence methods are getting frequently used in research and development in learning analytics, which is aimed at analyzing data collected during learning to enhance its results. The same aim is relevant for instructional design models, the most widely applied is ADDIE model, which cuts course design into steps. The first two research fields are criticized for a weak connection to teaching practice, while the third lacks evidence-based and measurable nature. This literature review aims to show the prospects of bringing the three fields together. The theoretical analysis of the paper covers AI definition, its techniques and methods, areas of application in educational setting, the definition of learning analytics, its borders with other fields, spheres of application, definition and the essence of instructional design, as well as the concept of ADDIE model which frames the practical analysis of the review. Forty-three articles were included in the final sample. The solutions described there correlate with the tasks of the instructional design steps and are systematized according to them. It was found that the least number of solutions described in the literature were assigned to the analysis, design and evaluation steps, more articles were assigned to the development step, and the largest number of papers considered the application step. It can be due to the difference in the availability of data at different ADDIE steps. The weak focus of teachers on methodological reflection at the assessment step also may play a role. These deficiencies open up the opportunities for future research and developments. To push these solutions forward it is crucial to elaborate on the models, to move from anecdotal experiments to a wide-scale practice, and to enhance required competencies among the faculty. The questions and conclusions presented in the article help to set a new pedagogically-oriented framework for discussions of AI and learning data analytics.

The research was aimed at analyzing current approaches to the organization and design methodology of visualization database built on the basis of computer vision. Such approaches are necessary for effective development of diagnostic systems using artificial intelligence (AI). A training data set of high quality is a mandatory prerequisite for that. Material and methods. The paper presents the technology for designing an annotated database (SBT Dataset) that contains about 1000 clinical cases based on the archived data acquired by the Federal Neurosurgical Center, Novosibirsk, Russia including data on patients with astrocytoma, glioblastoma, meningioma, neurinoma, and patients with metastases of somatic tumors. Each case is represented by a preoperative MRI. The Results and discussion. The dataset was built (SBT Dataset) containing segmented 3D MRI images of 5 types of brain tumors with 991 verified observations. Each case is represented by four MRI sequences T1-WI, T1C (with Gd-contrast), T2-WI and T2-FLAIR with histological and histochemical postoperative confirmation. Tumors segmentation with verification of the tumor core elements boundaries and perifocal edema was approved by two certified experienced neuroradiologists. Conclusion. The database built during the research is comparable in its volume and quality (verification level) with the state-of-the-art databases. The methodological approaches proposed in this paper were focused on designing the high-quality medical computer vision systems. The database was used to create artificial intelligence systems with the “physician assistant” functions for preoperative MRI diagnostics in neurosurgery.

INTRODUCTION. The world has many times faced cardinal changes triggered by technological development. Creation of the Internet and the emergence of the artificial intelligence have become the major trend of the ongoing changes with the signifi-cant potential to affect all spheres of live, including the military affairs and the geopolitical phenomena in general. In this paper, in particular, we discuss the opportunities and challenges of the rapid technological development in the defense sector in the context of globalization. The pace and the nature of changes in defense dictate the necessity to analyze the current and future challenges of our digitized age in search of adequate and timely legal and strategic practical solutions. Cyber means of warfare are the weapons of the present. Over the past decades, cyber means of warfare have been frequently used against states in the context of international and non-international armed conflicts, as well as outside of such context. Thus, the fundamental scientific questions that arise are the following: a) are the current legal regulations at international and national levels sufficient to address all the challenges caused by the spillover of armed conflicts into the virtual domain and by the future advancement of cyber weapons, and b) are the current cyber weapons or those of the future capable of changing the nature of “war” described by General Carl von Clausewitz yet in the 19th century as a violent method of forcing its political will by one party of the conflict to the other. We have analyzed the above-mentioned questions in the light of the cyber weapons, which already exist and are being used for military purposes, in the light of possible advancement of cyber weapons and integration of AI into them, as well as in the light of the Big Data management. We have reflected on the dangers, which the smart and entirely data driven world would face, from legal and geopolitical perspectives, through the several possible scenarios of development, emphasizing, in particular, the probable military (defense) aspect of data management. While most frequently the specific problems of application of International Law to the traditional cyber warfare situations become subject for academic debates and discussions, we stress the necessity to also analyze the legal and practical implications of further advancement of cyber weapons, as well as the necessity to consider the role of Big Data management in changing the nature of war and, consequently, also the applicable legal solutions.MATERIALS AND METHODS. The works of academics and international scholars in the field of international law and, specifically, international humanitarian law, and military theorists, as well as international treaties, commentaries to international treaties, and national cyber defense and cyber security strategies comprise the theoretical basis for the current paper. The research has been conducted via general and specific scientific methods of cognition, in particular the dialectical method, comparative legal method, method of interpretation, as well as methods of deduction, induction, analysis, synthesis, and others.RESEARCH RESULTS. The ongoing changes taking place in the world have resulted in a situation, when cyber domain is considered one of the traditional war domains. In this context the international community is now debating more flexible interpretations of international legal regulations in order to most efficiently address the new reality. It is also important that states at national level undertake measures to timely and adequately address the challenges already created and those that potentially may take place as a result of the globalization along with the rapid evolution of the cyber technologies and their military use. In the current article we conclude that the categories of the present generation of cyber weapons are lawful. However, the future developments in cyber weapon technologies, as well as the possible quasi-military implications of Big Data management raise many theoretical and practical questions deserving attention. The efforts of the international community and individual states in the field of legal regulation of cyber technologies should be directed toward creating guarantees that the products of the technological development are used for the benefit of humankind. As one of such measures The Authors indicate national cyber security and cyber defense strategies, which according to the Authors, should be elaborated giving due consideration to the possible future developments.DISCUSSION AND CONCLUSIONS. In this paper we analyze the peculiar features of evolution of the world in the 21st century and argue that wars are not static and autonomous phenomena isolated from the global context and all the changes taking place in the world. In particular, we address one of the most popular debates among the scholars in the field of military affairs concerning the issue whether the nature of war has changed or will change overtime, referring to Carl von Clausewitz’s thoughts. With regard to the current generation of cyber weapons, we conclude that even if they might prima facie seem to be inherently indiscriminate (such as, for example, nuclear weapons) in reality cyber weapons are not per se indiscriminate, but rather are weapons with a very high potential of being used indiscriminately or in violation of the principle of discrimination. However, the high potential of indiscriminate use of cyber weapons does not outlaw the cyber weapons as such. We also agree with the widely accepted opinion that the cyber weapons, which are currently used, are sufficiently regulated by the International Law. At the same time, the future tendencies for advancement and improvement of military cyber technologies, inter alia, via integration of artificial intelligence, may seriously call into question the possibility of their application in compliance with the international legal regulations. Finally, the possible scenarios of advancement of Big Data management have led us to the conclusion that big data management per se has the potential of being used as a weapon with less lethal or even non-lethal consequences, however equally effective in enforcing one’s policy as the traditional weapons or potentially kinetic cyber-weapons. If big data analysis at its current stage of development does not produce very accurate predictions, the well-distributed and structured informational flow in the cyber domain is capable of influencing and manipulating behaviours. In such case if Big data monopoly (including both: hardware and soſtware) vests in one of several actor, it could drastically change the nature of war by making the element of violence redundant and consequently alter the geopolitical balance. One of the measures for early response to future challenges, in our opinion, could be through reflecting on lex ferenda in cyber security and cyber defence national strategies. From the analysis of the content of different strategies we could conclude that most states acknowledge cyberspace as a military domain like land, air or maritime, analyse the main specific characteristics of current generation of cyber weapons, and set state objectives and action plan for cyber offense, cyber defense and cyber deterrence respectively. While the future advancement of cyber means of warfare and the quasi-military dimension of the big data management seem to be overlooked by states in general.

The development of information technologies, including artificial intelligence, is leading to their widespread use in many areas of our lives. With the rapid development of artificial intelligence, the number of cases of its application to generate digital images, audio, video, etc. is growing. Counterfeiting digital audio files is dangerous from the point of view of being used by criminals to exert information and psychological influence and manipulate society and individuals. There are modern methods for detecting audio fakes made by artificial intelligence. They are highly accurate, but not without drawbacks. The main drawback is the complex architecture and high resource intensity. The aim of this paper is to develop a neural network that would allow detecting audio fakes with satisfactory accuracy and whose training would not require significant computing resources. A method was chosen for modification, namely, the method of detecting audio fakes using a convolutional neural network. The method for detecting audio fakes was modified by building a model with a new architecture with fewer layers, which significantly reduced the time and computational resources required compared to analogues. The experimental results obtained using the modified method show satisfactory efficiency and accuracy of the system. Errors of the first kind amounted to 24%, errors of the second kind - 9%. The developed modification is implemented in a software application with a convenient and simple interface. [ABSTRACT FROM AUTHOR]

Objective: international law obligates states to prosecute those who have violated laws in armed conflicts, particularly when the international community now has International Criminal Court (ICC).That is why the aim of the paper is to discover the responsibility for the crimes made with the use of AI-based autonomous vehicles in accordance with the provisions of the Rome Statute of the ICC.Methods: doctrinal analysis allowed to research the positions of experts on the responsibility for the crimes made with the use of AI-based autonomous vehicles in accordance with the provisions of the Rome Statute of the ICC. Results: this paper argues that the ICC can only exercise jurisdiction over natural persons who allegedly have committed the crimes under its jurisdiction, as compared to autonomous weapons. This paper argues that the persons who facilitate the commission of the alleged crimes are highly likely to be criminally responsible for providing means for the alleged crimes to be committed by AI-based autonomous weapons under Article 25(3)(c) of the Rome Statute and concludes that the Rome Statute provides a solution even to AI-based autonomous weapons.Scientific novelty: this paper addresses to the highly relevant issues of the responsibility for the crimes made with the use of AI-based autonomous vehicles in accordance with the provisions of the Rome Statute of the ICC.Practical significance: the results achieved in the paper can be used in regulation design for AI-based autonomous weapons. It can also be used as a basis for the future research in the sphere of liability of AI-based autonomous weapons and AI in general

The paper aims to demonstrate the students’ interaction with artificial intelligence (AI) of educational information and communication technologies (ICTs). The study focuses on the students’ groups studying the Foreign Language discipline and belonging to the non-linguistic departments of the university. The paper explains and defines "AI" and "ICT" concepts as well as the "interaction in the educational process." The necessity of studying the students’ interaction with AI is becoming a great sign of the era of digitalization of higher education. The primary scientific method of the study is modeling. As a result, the students’ interaction with AI is shown via the model demonstrating some systematic factors of interaction and dynamic processes influencing its course. The study’s principal conclusion became the correlating interrelation between the levels of AI influence on the students and their reflexive and evaluation abilities within linguistic competence.

The current social and cultural debates on AI and how it is being embedded into the reality of social life have reignited scientific debates on how to study AI, what counts as data, and the conditions under which information and data pertaining AI turn into knowledge. In this paper the authors’ focus was exploring new sources of data on AI and methods of AI phenomena examination. The paper presents the results of a comparative analysis of Google, Yandex, and Baidu’s websites. Contrary to these companies commonly being perceived as online search engines, Google, Baidu, and Yandex have multiple offerings across mobile products and services, knowledge products, translation services, open platforms for startups, PC client software and AI technologies. In the first part of the paper the authors compare information presented on these companies’ websites about their goals, their technologies, how they define AI, the proclaimed social problems associated with using AI, and the forms of interaction between these companies and their audiences. The second part of the paper analyzes 20 projects that won the Google AI Impact Challenge contest. Analyzing these projects allowed for identifying areas of application of AI technologies inside and outside organizations, for characterizing AI’s potential roles as a mediator in relations between people, and finally for highlighting utopian and dystopian scenarios associated with implementing AI in social relations. In the conclusion the authors formulate a set of broader questions for social analytics concerning artificial intelligence grounded in the results of their analysis.

The previous studies have described the extraction of plant parenchyma by computer image processing technology, and the purpose of this paper is to verify the effectiveness of the algorithm., this paper implements the algorithm by using Matlab language, and designs several groups of experiments. The experimental results show that: when denoising, using 9*9 as a template to perform median filtering on the image has a better effect, and block binarization facilitates the extraction of axial parenchyma; when processing mathematical morphology, using 3*3 Axial parenchyma and vessel morphology can be successfully extracted from cross-sectional images of broad-leaved wood after dilation of the image by cross-shaped structuring elements and erosion of images by disc-shaped structuring elements with radii ranging from 1 to 10 When calculating the area threshold of the closed area, the area threshold is determined by using 8 domains to mark the area of the closed area and using the area histogram, so that the axial parenchyma can be better separated from the catheter. At present, the method has been experimented in 10 different tree species, all of which have achieved good results. This also fully proves the effectiveness of the artificial intelligence algorithm. The implementation of the algorithm also lays the foundation for future research on intelligent wood recognition based on axial thin-walled tissue morphology; it provides a shortcut to measure the content of axial thin-walled tissue in different tree species; and it is a prelude to the development of an image-based wood recognition system for axial thin-walled tissue.

Copyright of Cybernetics & Systems Analysis / Kibernetiki i Sistemnyj Analiz is the property of V.M. Glushkov Institute of Cybernetics of NAS of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cybernetics & Systems Analysis / Kibernetiki i Sistemnyj Analiz is the property of V.M. Glushkov Institute of Cybernetics of NAS of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Cybernetics & Systems Analysis / Kibernetiki i Sistemnyj Analiz is the property of V.M. Glushkov Institute of Cybernetics of NAS of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper proves that speech genres as forms of text production and interpretation claim to be one of the main objects of formal linguistic analysis in comprehensive papers on cognitive modeling – an intensively developing trend of artificial intelligence. Understanding a speech genre as a form of spiritual socio-cultural activity (artistic, scientific, political, ideological, etc.) at the level of its objectification through a system of speech actions in the text as a communication unit allows to describe the systems of speech genres in various spheres of communication. The authors analyze speech genres which objectify the main stages of an academic theoretical research. By means of artificial intelligence, the research solves the problem of recognition of the speaker’s intentions while performing cognitive-speech actions forming the genre form of a text. It contributes to the development of the fundamental problem of “understanding” the meaning of an utterance by a machine. The research is based on the interdisciplinary complex method of text analysis. In terms of software implementation, the offered approach obtains a small set of high-level linguistic features of the clauses with the templates and then trains classifiers on these features. In order to create templates, the authors carry out linguistic and psychological analysis that deals with identifying markers of cognitive and speech actions as accurately as possible in accordance with the standards of perception. In the course of our study, the authors have obtained high indexes of cognitive and speech action identification, ranging from 0.78 to 0.99.

The article reveals the main ethical problems and contradictions associated with the use of artificial intelligence. The paper reveals the concept of “artificial intelligence”. The authors analyse two areas of ethical problems of artificial intelligence: fundamental ideas about the ethics of artificial intelligent systems and the creation of ethical norms.The paper investigates the work of world organizations on the development of ethical standards for the use of artificial intelligence: the Institute of Electrical and Electronics Engineers and UNESCO. The study analyses the main difficulties in the implementation of artificial intelligent systems: the attitude of employees to the use of robots in production activities and the automation of processes that affect their work functions and work organization; ethical issues related to retraining and re-certification of employees in connection with the introduction of new software products and robots; ethical issues in reducing staff as a result of the introduction of artificial intelligence and automation of production and business processes; ethical problems of the processing of personal data of employees, including assessments of their psychological and physical condition, personal qualities and character traits, values and beliefs by specialized programs based on artificial intelligence, as well as tracking the work of employees; ethical contradictions when using special devices and tracking technologies in robotic technology and modern software products, which also extend to the employees interacting with them.

The article deals with the problem of implementation of personalization in marketing communications based on empathy of brand consumers. The paper substantiates the significance of artificial intelligence in the collection and processing of a large amount of personal data of users of the online space. The article presents an analysis of the main scientific approaches of Russian and foreign authors specializing in the study of the emotional component in the construction of personalized online communications. The authors present the results of the comprehensive research of consumers’ attitude to the personalization of marketing communications based on the artificial intelligence capabilities. In the course of the study the authors consider the technologies of using artificial intelligence mechanisms in the construction of personal communications in the online environment. The article gives theoretical substantiation of the need to use the mechanism of empathy in the construction of personalized communication with consumers. The paper substantiates conclusions about the possibility to build empathic connection between brands and their consumers under the condition of activating the function of emotional contagion, the effectiveness of using the emotional state of consumers in the preparation of personalized offers. The study describes the specifics of using personalized marketing communications as a modern marketing tool, which is expressed in the impact on the identification of buyers at the subconscious level. The article presents the technologies of personalization through consumers’ attitudes towards personalized communications. The paper presents the results of an empirical study conducted by the authors of the article in the spring of 2020, aimed at determining the willingness of consumers to share information about their emotional states. The article makes the conclusions about the existence of consumers’ need for trusting relationship with brands based on the mechanism of empathy; about the possibility of increasing the effectiveness of personalized brand communications through the use of segmentation of consumers depending on their mood; about the benefits of using artificial intelligence technologies in marketing communications.

The incorporation of artificial intelligence (AI) into industrial processes has seen substantial development, characterized by the shift from Industry 4.0 to the future concept of Industry 5.0. The article identifies a significant gap in knowledge regarding how openness in AI engagement influences consumer trust and confidence in news media. This gap highlights the need for further exploration into the relationship between transparency in AI processes and consumer perceptions. The research utilises a combination of qualitative and quantitative approaches, gathering insights from academic literature, industry viewpoints, and actual data. We conduct an extensive analysis of existing literature to investigate the process of incorporating artificial intelligence into news creation and its influence on the level of confidence consumers have in the news. We have identified a significant lack of knowledge about the impact of openness in AI engagement on consumer views and trust in news media. Expanding on this discrepancy, we suggest a systematic methodology that incorporates controlled experiments and surveys to evaluate the influence of different degrees of openness on consumer trust and involvement with AI-generated news content. In addition, the paper examines the difficulties in establishing confidence in artificial intelligence (AI) inside the European Union, including several aspects such as technological, ethical, social, and legal considerations. The document presents a thorough plan to guarantee the secure development and execution of AI, with a focus on the significance of transparency, ethics, and teamwork. The study’s results provide vital insights for politicians, news organisations, and industrial businesses as they navigate the intricate process of integrating AI. Comprehensive Plan for Secure AI Development, to address the challenges outlined, the article presents a thorough plan for ensuring the secure development and execution of AI within the European Union. This plan emphasizes the significance of transparency, ethics, and collaboration in building trust and confidence in AI technologies.

Objective: comparative evaluation of output data of a set of trained convolutional neural network (CNN) models and interpretation of pathological changes in lumbar spine by radiologists during magnetic resonance imaging.Material and methods. More than 12,000 anonymized archives were collected to generate training and test neural network datasets from patients aged over 18 years. Each archive consisted of a set of programs in two planes containing T2-TSE, T1-TSE and T2 sequences with fat suppression program. Subsequently, the selected studies were tagged in two steps, directly consisting of manual tagging and its validation by experts. CNN training was performed separately for normal analysis, qualitative detection of individual pathological changes, and quantitative analysis. The accuracy of the models was verified by comparing the protocols of five radiologists and the output of CNN models in two steps. The first, intermediate stage evaluated the accuracy of the neural networks in detecting disc bulges, protrusions and extrusions, spinal canal stenosis, lateral stenosis, foraminal stenosis, spondylolisthesis and facet joint arthrosis. In the final stage, in addition to the pathologies considered in the intermediate one, the accuracy of detecting degenerative changes of the occlusive plates, synovitis of intervertebral joints, intervertebral discs degeneration, osteophytes, transitional vertebrae, hypertrophy of yellow ligaments and Schmorl’s hernia was tested. The reference value for all pathological changes considered in this paper was determined by majority vote and, in case of disagreement, by an external radiologist. The radiologists’ interpretations were then compared with those of the trained model.Results. The artificial intelligence (AI) showed comparable sensitivity and specificity values compared to the reference result in a group of experienced radiologists for binary classification (presence/absence) of individual lumbosacral spine degenerative changes. The sensitivity and specificity of AI results were 0.88 and 0.97 for extrusions, 0.81 and 0.94 for protrusions, 0.87 and 0.98 for central stenosis, 0.83 and 0.85 for lateral stenosis, 0.92 and 0.84 for foraminal stenosis, 0.85 and 0.5 for osteoarthritis, 0.73 and 0.96 for occlusive plates degeneration, 0.85 and 0.84 for intervertebral joint synovitis, 0.91 and 0.88 for osteophytes, 0.93 and 0.72 for intervertebral disc degeneration, 1.0 and 1.0 for transitional vertebrae, 0.8 and 1.0 for spondylolisthesis, 0.67 and 0.99 for yellow ligament hypertrophy, and 0.75 and 1.0 for Schmorl’s hernia, respectively. The accuracy of quantitative size characterization of lumbosacral spine protrusions and extrusions showed unsatisfactory results, but improvements in the quality of determination of these parameters are planned in future work.Conclusion. AI models showed comparable performance to expert radiologists in detecting lumbosacral spine degenerative changes. Consistent improvement of CNN models based on comparative evaluation with radiologists improves the sensitivity and specificity of pathologic change detection.

Until recently, intellectual creativity was considered as an exclusively human phenomenon and intellectual property legislation was built on the basis of motivating and enhancing human inventiveness. This self-evident assumption is being challenged due to the development of artificial intelligence technologies in the recent decades. In this article author analyzes some aspects of intellectual property law development, including the possibility of recognizing an artificial intelligence as a creator of intellectual activity results. The author examines the legal status of artificial intelligence under Armenian law and foreign intellectual property legislation, analyzes existing approaches to the legal regime and intellectual property ownership of objects created with the help of artificial intelligence. The paper aims to determine the proper right holder to content generated by artificial intelligence and formulate some policy prospects of artificial intelligence regulation. The methodological basis of the research includes general scientific and special legal methods. The author places particular emphasis on the dogmatic (doctrinal) research methods, which made it possible to analyze existing approaches to protection of intellectual property rights. The research is also based on the comparative legal method and analytical legal method of commenting current law of Armenia and foreign countries. The results of the study allow author to substantiate that the actual right holder to the content produced by the neural network is the programmer of the underlying algorithm system. The author concludes that the construction of a solid legislative system should be carried out taking into account the specifics of the areas of application of artificial intelligence, ensuring a balance between the interests of individuals, society and the state related to the development of innovative technology.

The breakneck expansion of artificial intelligence (AI) technologies in recent years has attracted the attention of higher education researchers. However, their curiosity often comes down to using specific AI tools, such as text and image generators, translators, and personal assistants in the educational process. This paper considers a broader question: what fundamental problems and challenges does the penetration of AI technologies into human lives originate for higher education? The authors offer a working definition of what it means to give/receive higher education in the age of AI. This definition identifies five critical characteristics of higher education: 1) the professor and the student continue to be in a subject-subject relationship and learn from each other; 2) higher education should prepare for life in conditions of “human-machine” interdependence; 3) these conditions imply choice in situations of uncertainty; 4) the spread of AI technologies brings enormous opportunities and 5) almost unpredictable dangers, risks and threats to humans. The authors consider general principles and specific problems associated with entering AI tools into society and higher education. They discuss the inevitability of the evolvement of “machine-machine interdependence” related to the development of autonomous agents. In conclusion, several theses and counter-theses summarize the article’s argumentation.

In the presented paper the necessity of introducing digital tools into the activities of the enterprise in order to improve its efficiency is noted. Special attention is paid to the issues of using certain elements of artificial intelligence. Types of chatbots, peculiarities of their practical application. As well as advantages and disadvantages, are analyzed. The comparative analysis of services for chatbots is performed. The requirements to be considered in the technical specification to the main functions, system functioning, customer information, information security, documentation are formed. The tasks included in the project on creation of chatbots are defined. Recommendations are made on the calculated part of economic efficiency.

Copyright of Journal of History / Habaršy Tarihi Seriâsy is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Physics, biology, chemistry, for example, do not already only study programs in many universities but are at the forefront of the development of science, and that is science itself. The development of the basic foundation becomes the mother of science, such as mathematics, as a suspicion of the birth of new sciences. The interests related to the life and welfare of humans always invites the possibility of the birth of science in concepts, but mathematics confirms it. In certain cases, as an application, or it gives birth to answers in technology form, which is distorted according to the social demands of society. Every science has its methodology, which is based on the logic that helps to reason. A natural model is an approach to generating methods, as well as the principles that develop in artificial intelligence based on mathematics. This principle not only changes the way of perceiving data, but it also establishes new definitions of data, and changes statistics, optimization, and other fields. Each science also has implications for other sciences but also has applications that are also related to other sciences. Every science supports technology to improve social welfare. Historically, century by century, many new scientific fields were born, and it has evidence from the publication of scientific works to books as scientific standards. Then, the teaching curricula supported its initial dissemination and its development through research with evidence of scientific publications either through papers in proceedings of scientific meetings or articles in the journals. A study program about science in the related faculty is mandatory, and it is as the spearhead in further scientific and technological development. So everything starts and ends at one point, namely the birth of new science, as the birth of data science. This paper describes the birth of science by involving historical traces. The reflection of scientific development is starting from the foundation to become a scientific field, namely data science. It also illustrates the roadmap of a scientific indirectly.

Subject of Research. The paper presents the idea of combining various stages of production of optical devices in a single logical sequence from the design of optical elements, through the mechanical and technological production stages, to the calculation of their manufacturing cost. This idea is all the more attractive because it is possible to control the entire process and save time and budget to decide on the most suitable production option already during the design stage. The information is important to be objective, related to the specific type and volume of production, and easily verified and controlled at the initial design stage. Method. The method consisted in combination of all stages for optical device creation on a “turnkey” basis, including the analysis and visualization of options for the device optical scheme, taking into account mechanical and technological aspects and calculation of the “project-product” cost, depending on the volume of production, with recommendations for its optimization. It is known that there are several alternative circuit solutions when designing optical elements, especially for image quality assurance approaching to the resolution diffraction limit: options for lenses containing only spherical surfaces or having different quantity of optical elements in the scheme, or lenses with non- spherical surfaces. At the design stage the choice is difficult. In this case, the decision is made taking into account the lens production technological processes. Main Results. The choice of the optimal lens optical scheme is performed. Evaluation of an optical device manufacturing possibility at the earliest stage is carried out, when the designed variants of its optical scheme, the manufacturing tolerances for optical elements and the volume of production are known. The manufacturing cost for optical elements of the given device for various variants of its optical scheme is determined. The study of alternative circuit solutions is carried out, for example, lens variants that contain only spherical surfaces or have a various number of optical elements in the scheme, or use non-spherical surfaces. At the design stage, the right choice is difficult. In the case presented in this paper, the solution is developed taking into account the technological processes of lens production. Aimed at this, a new software tool, called PanDao, has been applied providing a preview to producibility, fabrication technologies needed and production cost to be expected at the early design stage of optical systems. To illustrate the use of the PanDao software, two pinhole lens schemes have been developed and compared with a forward-facing input pupil that coincides with the aperture of the lens; the design of the first lens is consisted of the three spherical components, the second lens is a combination of four aspherical optical components. Practical Relevance. The possibility of manufacturability analysis for the lens system at the stage of optical design is shown, and determination of the optimal technological sequence of an optical device manufacturing is performed within the conditions of its production given volume. Modeling of the manufacturing process for various optical components gives the possibility to choose the optimal production chain and evaluate the need and cost of manufacturing, assembly and equipment testing. An additional advantage is the calculation of the device cost at an early design stage, which serves to optimize its optical scheme in some cases, and sometimes even avoid the prototyping stage. This approach is first implemented in PanDao software and is now available to a wide range of researchers.

Purpose: Process optimization in healthcare using artificial intelligence (AI) is still in its infancy. In this study, we address the research question “To what extent can an AI-driven chatbot help to optimize the diagnostic process?” Design / Method / Approach: First, we developed a mathematical model for the utility (i.e., total satisfaction received from consuming a good or service) resulting from the diagnostic process in primary healthcare. We calculated this model using MS Excel. Second, after identifying the main pain points for optimization (e.g., waiting time in the queue), we ran a small experiment (n = 25) in which we looked at time to diagnosis, average waiting time, and their standard deviations. In addition, we used a questionnaire to examine patient perceptions of the interaction with an AI-driven chatbot. Findings: Our results show that scheduling is the main factor causing issues in a physician’s work. An AI-driven chatbot may help to optimize waiting time as well as provide data for faster and more accurate diagnosis. We found that patients trust AI-driven solutions primarily when a real (not virtual) physician is also involved in the diagnostic process. Practical Implications: AI-driven chatbots may indeed help to optimize diagnostic processes. Nevertheless, physicians need to remain involved in the process in order to establish patient trust in the diagnosis. Originality / Value: We analyze the utility to physicians and patients of a diagnostic process and show that, while scheduling may reduce the overall process utility, AI-based solutions may increase the overall process utility. Research Limitations / Future Research: First, our simulation includes a number of assumptions with regard to the distribution of mean times for encounter and treatment. Second, the data we used for our model were obtained from different papers, and thus from different healthcare systems. Third, our experimental study has a very small sample size and only one test-physician. Paper type: Empirical

The last decade has seen significant progress in computer-aided image analysis and recognition, with modern computer-aided diagnostic algorithms not only catching up with, but in many aspects surpassing human abilities. At the heart of this breakthrough is the development of deep convolutional neural networks, which have given a new impetus to medical diagnosis, particularly of skin cancers. In this paper, we analyzed photo-based skin disease classification systems developed using algorithms based on deep learning convolutional neural networks. Such methods have been variously reported to enable automated diagnosis of skin neoplasms with high sensitivity and specificity. A disease that requires more detailed analysis of graphic images — skin melanoma — was chosen as the main object of study. Early diagnosis of melanoma is of great socio-economic importance, as in this case the prognosis of patients is significantly improved. The aim of this work is to analyze the results of artificial intelligence (AI) applications in dermatology, especially in the context of early detection of skin melanoma. Scientific articles were searched in PubMed, Scopus and eLIBRARY databases using the keywords “convolutional neural networks”, “skin cancer” and “artificial intelligence”. The depth of the search was 10 years. The final analysis included 38 sources where the results of our own research were presented. The advantages of artificial intelligence methods for dermatologists were analyzed. Artificial intelligence can significantly assist dermatologists in developing visual neoplasm diagnosis skills and improve diagnostic accuracy. The use of AI to process dermatoscopic data in conjunction with the analysis of anamnestic and clinical information from medical records will reduce the burden on the healthcare system through correctly diagnosed benign skin tumors. All of this promises to have a significant impact on the future development of dermatovenerology.

Everyday, artificial intelligence (AI) is being increasingly integrated into the teaching and learning process at Russian universities. The high level of quality of feedback from AI tools leads to the spread of AI plagiarism – unauthorized borrowing of generative AI materials – among students. The purpose of this study is to: a) highlight aspects that determine students’ understanding of the issues of compliance with author’s ethics and the problem of plagiarism when interacting with generative AI; b) develop a questionnaire to determine students’ understanding of the issues of compliance with author’s ethics and the problem of AI plagiarism; c) conduct an online survey of university students, analyze and discuss the results obtained. The paper highlights five aspects that determine students’ understanding of the issues of compliance with author’s ethics and the problem of AI plagiarism when completing educational assignments and preparing research texts: a) students’ general understanding of the issues of compliance with author’s ethics and the problem of plagiarism in an academic environment; b) students’ experience of AI tools for educational purposes; c) students’ understanding of the problem of AI plagiarism and attitude towards borrowing materials from generative AI; d) teachers’ actions to prevent AI plagiarism among students; e) the policy of educational organizations regarding student compliance with ethics and AI plagiarism. An online questionnaire was developed to determine the degree to which students understand the issues of compliance with copyright ethics and the problem of AI plagiarism. 1,599 students from 29 universities of the Russian Federation took part in the survey. The results showed that in general, in the Russian student community, plagiarism is a widespread social phenomenon, many types of which are perceived by young people as a norm of academic behavior. Despite the relatively high awareness of students in the field of AI technologies, the extremely rare use by teachers of specialized subject disciplines of AI tools in the educational process I’d the reason for the current low level of spread of AI plagiarism in the academic environment. At the same time, it is necessary to state that students lack a systematic understanding of exactly how they can “legally” use generative AI materials and what exactly will be considered AI plagiarism. According to students, the importance of understanding the issues of compliance with author ethics and the problem of AI plagiarism will depend, on the one hand, on the actions of teachers to explain to students the rules for using generative AI materials, and on the other hand, the presence in universities of a regulatory framework regulating the field and the extent to which students use AI in the educational process.

Introduction. Many molecular genetic analyses have been proposed to predict the course of prostate cancer (PCa). They have the potential to develop artificial intelligence (AI) algorithms by processing large amounts of data and define connections between them.Objective. To evaluate the possibilities of using artificial intelligence in early diagnosis and prognosis of prostate cancer.Materials & methods. We conducted a systematic review of the literature on the Medline citation database. We have selected papers that provide data on the use of AI in vitro, in vivo and in silico systems to determine biological and genetic markers and/or their relationship to clinical data of PCa-patients from 2020 to 2023. The quantitative synthesis includes 16 articles.Results. AI can identify metabolic and genetic «signature» of PCa, the key elements of signal pathways, thus fulfilling complex tasks in the field of bioinformatics. AI analyses various biomaterials: prostate tissue, blood, and urine. When evaluating prostate tissue for aberrations, AI can help a pathologist. For example, AI can predict the histological status of genes, eliminating the need for IHC or tissue sequencing, significantly reducing the economic cost of predicting the severity of the disease. In most cases, prostate tissue sequencing provides information to the attending physician, allowing the start of optimal treatment, considering the molecular or genetic «signature» of PCa. AI can be used as an alternative to existing population screening tools and a predictive castration-resistant PCa. The use of AI capabilities is more appropriate for blood and urine analysis, procedures that do not require additional economic costs for biomaterial sampling. In theory, this may be more affordable for the patient and the medical institution. It is worth noting that a few studies were conducted in silico (based on the analysis of molecular genetic databases without validation on cell lines or on real patients) and are useful as background information. However, the results can serve as a robust basis for further research in molecular diagnostics and genomics.Conclusion. It is possible to use AI in the search for key metabolites and genes of the elements of signalling pathways, as well as the determination of metastasis potential, because molecular or genetic «signature» of PCa allows the physician to start optimal treatment.

Modernity demonstrates a critical need for pedagogical support and the development of a methodology to enhance critical thinking in the face of escalating misinformation and advanced media manipulation, mainly through deepfake technology. The paper focuses on creating a comprehensive framework for detecting manipulated content and identifying indicators such as pixelization, unnatural expressions, etc. With attention to international and Ukrainian efforts, the work advocates for ongoing research adapted to evolving technologies to improve media literacy programs in combating emerging forms of misinformation. Problem statement. The problem is the urgent need for a comprehensive methodology that fosters critical thinking skills to combat disinformation and manipulation of artificially reproduced media content, particularly in the context of emerging technologies like deepfakes. The challenge involves assessing existing pedagogical approaches, addressing gaps, and equipping both learners and educators to navigate the complexities of the digital age. Digital transformation, in general, and the spread of artificial intelligence for media generation, in particular, are irreversible processes in the modern world, so the urgent issue, given the challenges of the digital economy and the needs of the digital society, is to find forms, methods, and means of shaping the critical thinking of citizens to counteract manipulation and disinformation by synthetically reproduced media content. It is essential to develop a database with systematically organized materials categorized based on identified markers for the subsequent creation of training materials to solve the outlined issues. Materials and methods. A comprehensive approach was employed, combining general (systemic, instrumental, and functional approaches, dialectical and comparative analysis, synthesis, and systematization for the study of pedagogical, scientific-technical, and methodological literature), specific (observation and analysis of educational practices), and general-logical methods (extrapolation, induction, and deduction for formulating conclusions) in scientific research to solve the tasks set in the study. This allowed for the examination of the current state, evaluation of the practical results of implementing the developed methodology for critical thinking formation, and identification of priority avenues for improving education in the context of the strategy to enhance media literacy and critical thinking among the population and science. The study aimed to determine priority pathways within the framework of the development of methodology of critical thinking and pedagogical support to counteract disinformation and manipulation of artificially reproduced media content and to characterize its potential scientifically. The development of critical thinking and pedagogical support to counteract disinformation and manipulation of artificially reproduced media content requires the following materials analysis: scientific-technical literature (materials offering a scientific understanding of the technical aspects related to media content creation, modification, and reproduction), methodological literature (guides and methodologies focused on developing educational frameworks and strategies to enhance critical thinking in the context of media literacy), synthetically reproduced media content (media content, especially in the context of emerging technologies like deep fake to identify modification markers). Results. The study is devoted to analyzing, identifying, and systematizing markers and signals for identifying media manipulation to create a database for the methodology in the form of methodological cards. A comprehensive database with classification is being developed, focusing on methodological interactive cards with 66 curated cases of deepfakes and synthetically reproduced media (in Ukrainian). This initiative aims to provide educators, researchers, and learners with a versatile resource for understanding the challenges posed by manipulated media. Conclusions. In response to the escalating threat of disinformation and advanced media manipulation, there is a critical need to develop a robust methodology for enhancing critical thinking skills. The study highlights global concerns about false information, mainly through deepfake technology, jeopardizing public trust and enabling psychological manipulation. Future research should consider revising media literacy programs to elevate citizens' critical thinking in the face of evolving digital landscapes and the increasing capabilities of artificial intelligence in generating media content.

The Theses deal with the theoretical foundations and methodological implications for scholarly research that arise from the development and implementation of artificial intelligence (AI) technologies into society’s daily life. The reader is introduced to age-old intellectual debates about AI and recent research concerning human-centered AI, artificial sociality (AS), and online culture. The paper presents the working definition of AI. It claims that AI has to be examined in relation to AS. The paper argues that the human-machine-interdependence is a new reality of artificial sociality. It envisages AI research as multidisciplinary and potentially a-disciplinary scientific activity. The questions the Theses raise: What should we be concerned about as artificial intelligence advances? Can AI technologies solve modern society’s problems and bring human beings to a new level of community and well-being? Are there ‘no-AI areas’ in society? Do human biases and prejudices influence AI technologies? The paper’s essential assertion is that the challenges posed by AI technologies and AS should be addressed apropos three P’s of the capitalist society: private property, profit, price.

Background. Generally, haze can be considered to be one of the most fundamental phenomena causing image visibility degradation. Numerous haze removal approaches have been proposed and most of them have achieved significant progress. In this paper the problem of dehazing images using deep neural network technologies is raised. Materials and methods. Our method is based on a physics-informed convolutional autoencoder. To achieve the best results in image dehazing, the black channel prior was integrated into the loss function. The model was trained on synthetically obtained pairs of clean and hazy indoor and outdoor images. The efficiency of the developed method was compared with AOD-net, CAP and Dehaze-Net. Results. It is established that the algorithm developed as part of the study is able to dehaze dense images. On the average, the method copes well with its task and is not inferior to large-scale neural networks. Conclusions. It was decided to improve the parameters of the model, as well as make small changes to the learning process to eliminate the problem of image lightening having large celestial areas.

Background. Currently, society has been taken over by the “digital revolution”. Digital technologies have begun to be actively used by people in their lives and are con-stantly being improved. Public opinion regarding the rapid introduction of digital tools into human life is polar: for some, digitalization is a benefit, for others it is a threat. The sphere of education, as one of the key areas influencing the formation and development of the per-sonality of future specialists, is subject to constant transformations. The introduction of artificial intelligence into the educational process is the most discussed topic of recent times. A new resonance in this area was caused by the use of neural networks by students when preparing certification papers. In this regard, the academic community and social activists began to discuss the use of prohibitions and restrictions in this area. In this regard, it is important to understand how the younger generation views in using neural networks in education. The purpose of this work is to study the opinions of young people about the use of artificial intelligence in the educational process. Materials and methods. To achieve this goal, secondary analysis of data presented by The Russian Public Opinion Research Center and Public Opinion Foundation was used, as well as the results of the author’s research: focus groups, a questionnaire survey among young people in Penza region. The study used systemic and institutional approaches. Results. The results of the study showed that young people have clear ideas about what artificial intelligence is. In addition, young people are trying to use the capabilities of neural networks, including as part of their education. Con-clusions. Modern youth quickly adapt to innovations and enthusiastically begin to use the achievements of science, considering them “helpers” in their lives. Compared to older gen-erations, young people do not see the threat that artificial intelligence can pose to society. Digital technologies are perceived by the younger generation as a necessity of today; their use in their lives allows them to simplify some processes and everyday practices.

The research paper presents the results of Russian articles analysis in the field of neurotechnology and artificial intelligence published from 1998 to 2023 in peer-reviewed journals indexed in the international scientific database Scopus. The methods of scientometric and bibliographic analysis with the construction of terminology maps and cartography were used for the analysis. The analysis allowed to identify the positive dynamics of publication activity in the field of neurotechnologies and artificial intelligence, the most active authors, key topics and areas of cooperation, as well as to form recommendations and describe the prospects for the development of this topic. The presented results can contribute to more effective planning of scientific research and partnerships for further development of the considered sphere and strengthening Russia’s position on the global scientific stage.

The most important property, a distinctive feature of any intelligent system, is its decision-making ability. In this case, the more complex the problem to be solved, the more and more diverse the initial data, and the more critical it is that the decision to be made was comprehensively considered and evaluated. In many cases, simultaneously arriving various initial data, if considered separately, and decisions based on such consideration lead to completely different results, often contradicting each other. Therefore, in the process of development and implementation of artificial intelligence (AI), it is especially important to investigate the “mechanism” of decision-making in conditions of the inconsistency of incoming initial data and the need to establish some generalizing rule, according to which it is possible to find a harmonizing solution taking into account various influencing factors. It is evident that when establishing the rules of decision-making, it is necessary to strive for a “positive” result from the point of view of the problem being solved. This undoubtedly requires analyzing the consequences of the decision made in a set time scale, which can be provided by appropriate feedback that will allow us to make the necessary corrective actions. Artificial intelligence in modern forms of practical realization has, as a rule, a digital embodiment. It should be taken into account that the digital representation of data inevitably shows an inaccurate display of initial values when processes of a continuous nature are considered and analyzed. Since a digital model has certain limitations and characteristic properties when analyzing and processing initial data, it is logical to assume that for this reason, there can be some general approach, some general rule, according to which a decision is made in the conditions of diverse initial data and the need to take into account the relevant consequences after the decision is made. This paper attempts to find a decision-making mechanism, harmonizing it according to the incoming external and available internal input data.

The article discusses the possibilities of using artificial intelligence in the field of social insurance. The relevance of the topic and the importance of using artificial intelligence technology in this area are established, since it can improve the activities of the insurance sector and solve various problems. The purpose of the work is to study the specifics of the use of artificial intelligence technologies in social insurance and their impact. The paper examines current technologies and areas of artificial intelligence application. The software solutions used by social insurance authorities are thoroughly disclosed. It is determined that artificial intelligence technologies are used in social insurance for data analysis, risk forecasting and decision-making. The functions and capabilities of artificial intelligence in this area are widely disclosed in the article. It is established that these technologies can be used to process large amounts of information, to collect customer data, to predict risks, or as a virtual for risk forecasting or as virtual assistants. The author analyzes the challenges and risks that arise when using technology. It is determined that the main ones are problems with confidentiality and access to technology. Options and methods for solving problems are proposed, such as data regulation, development of ethical standards, increasing transparency, etc. In addition, the advantages of using technology in the field of social insurance are identified. These include increased work efficiency, improved quality of service, and reduced fraud. Conclusions are drawn that show that the use of artificial intelligence technologies in the field of social insurance has great potential. This contributes to the development of insurance companies and improvement of their work.