Значение консалтинговых услуг для формирования и развития инновационной экономики

The development of the digital revolution facilitates innovative models that generate new markets and business opportunities. The reappearance of artificial intelligence (AI) has created further potentials and types of market participation. AI is understood as a cutting-edge technology and a key driver of the transition of our economy into the digital economy. It is important to recognize and constantly bear in mind that artificial intelligence systems provide certain benefits but are associated with certain risks and potential negative effects. The European Commission, in its Ethical Guidelines for Trustworthy Artificial Intelligence (2019), emphasizes ethical principles and associated values that must be respected in the development, introduction, and use of artificial intelligence systems: respect for human autonomy, prevention of harm, fairness, and explainability. The question arises as to whether the emerging fundamental ethical principles and regulatory policies concerning AI systems require certain adaptations when it comes to the application of AI technology in connection with the sustainable development goals. The development of artificial intelligence systems compatible with the goals of sustainable development, as defined in the 1987 report of the UN Brundtland Commission as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs”, is encouraged. Sustainability or sustainable development is defined in the literature as a concept based on three pillars - encompassing social, economic, and environmental aspects. The European Commission highlights that sustainable development is a fundamental principle of the Union Treaty and a priority goal of Union policies, along with digitization and a robust single market. In recent years, doctrine has sought to bridge the gap between the two disciplines by introducing the term “Sustainable AI”. The aim of the paper is to understand the development of AI that is compatible with sustainable goals. To understand this, it is necessary to comprehend the basic concepts of artificial intelligence systems and explore the sociological, ecological, and economic implications of these systems, all with the aim of finding ways to achieve the goals of sustainable development and the sustainability of AI systems themselves. These are closely tied to adhering to the highest ethical principles with the responsible use of artificial intelligence systems.

"Background: Artificial Intelligence (AI) has become a ubiquitous phenomenon in recent times, with most organizations today attempting to maneuver their way around developing AI systems with the aim of improving the products and services they provide. However, what complicates developing AI systems is the paucity in frameworks to support organizations with AI System Development (SD). As a result, many organizations are using existing approaches which have been previously applied in earlier emerging Information Technology endeavors. This study explored how a framework can promote effective organizational AI SD. To achieve this a holistic framework for AI SD was conceptualized and examined from an organizational perspective. Method: This study has examined the conceptualized framework People-Process-Data-Technology (2PDT) in AI, through a case study research design. The empirical data was analyzed based on 12 case studies within Australia including 39 interviews with AI experts. We have applied thematic analysis to investigate requirements of organizational AI SD. Results: The results demonstrate that organizations are challenged by key factors, which inhibits their ability to effectively develop AI systems. For example, organizations are not achieving successful delivery of AI systems due to a lack of required skills. Additionally, a plethora of AI technology which is constantly evolving, poor data quality, and the paucity of AI SD frameworks are all contributing to unpredictable delivery outcomes. Conclusion: This paper investigated requirements for effective organizational AI SD by examining the 2PDT framework. The results contribute to AI phenomenon by developing the requirements for AI SD, in terms of people, process, data and technology. It contributes to theory by evaluating and developing AI requirements for effective AI systems. The examination of the framework and case study approach added valuable knowledge to the AI domain. In addition, we contributed to practice by identifying requirements that organizations should consider in achieving better AI SD outcomes."

This chapter explores relationships between the science and profession of psychology and the development of artificial intelligence (AI) and robotic systems. It briefly examines the role of psychology in the development of AI systems and theories. There is a long and intimate history of such a relationship, exemplified in the arts and the social sciences as well as in computer science and engineering. The chapter examines the role that psychology has played in the understanding of the ways in which humans interact with contemporary AI systems, to influence the behaviour of the systems and, in turn, to be influenced by them. Human decision making has been shown to be improved by factors other than intelligence and thereby appears to be a quality which would be retained by humans rather than machines, for example motivational processes, emotions and experience. The chapter examines the state of the profession of psychology and helping professions in the light of developments in AI.

Artificial intelligence technologies are developing intensively today, including due to the development of technologies of stable neural networks and cloud computing infrastructures, fuzzy system technologies, entropy administration, swarm intelligence, evolutionary computations, and many others. etc. At the same time, the problem of almost complete absence of normative legal regulation and normative technical regulation of the foundations, conditions and features of development, functioning and activities, integration into other systems and control over the use of artificial intelligence technologies is global today. The Article is devoted to the study of the specifics of the legal regulation of the use and development of artificial intelligence. Some approaches to the definition of artificial intelligence and the features of legal regulation of this sphere, which take place in the scientific literature, are considered and the author's definition of artificial intelligence is developed and given through the disclosure of its main features. In particular, according to the proposed definition, artificial intelligence is an artificial complex cybernetic computer-software-hardware system possessing the properties of substantivity, autonomy, and also the ability to perceive and analyze data, to self-learn. The question of positioning the artificial intelligence system as a special form of person (for example, the so-called «electronic person»), that is, granting it a certain legal personality depending on various factors and the field of application of such a system, is considered in this article. The article also notes the main possible approaches to legal support for the use and development of artificial intelligence systems, in particular, such approaches include the preemptive universal-total legal regulation and legal regulation aimed at the regulation of specific artificial intelligence systems. The main risks and uncertainties associated with artificial intelligence (and which are of great importance for the adoption of legislation in this field) have been investigated. There are drawn the conclusions about how to develop legislation on the use and development of artificial intelligence: consistently, taking into account the specifics of areas of its application, as well as balancing the interests of individuals, society and the state with regard to proper security and protection of individual rights, and interests related to the development of innovation for the benefit of the whole society.

The article discusses the main trends in the development of artificial intelligence systems and robotics (AI&R). The main question that is considered in this context is whether artificial systems are going to become more and more anthropomorphic, both intellectually and physically. In the article, the author analyzes the current state and prospects of technological development of artificial intelligence and robotics and also determines the main aspects of the impact of these technologies on society and economy, indicating the geopolitical strategic nature of this influence. The author considers various approaches to the definition of artificial intelligence and robotics, focusing on the subject-oriented and functional ones. In the article, AI&R abilities and human abilities are compared in such areas as categorization, pattern recognition, planning and decision making, etc. Based on this comparison, it is concluded in which areas AI&R’s performance is inferior to a human and in which cases it is superior to one. The modern achievements in the field of robotics and artificial intelligence create the necessary basis for further discussion of the applicability of goal setting in engineering, in the form of a Turing test. It is shown that development of AI&R is associated with certain contradictions that impede the application of Turing’s methodology in its usual format. The basic contradictions in the development of AI&R technologies imply that there is to be a transition to a post-Turing methodology for assessing engineering implementations of AI&R. In such implementations, on the one hand, the “Turing wall” is removed, and on the other hand, artificial intelligence gets its physical implementation.

The importance of the topic of the article is due to the fact that nowadays there is a need to understand that the creation of artificial intelligence is associated with the understanding and study of natural intelligence. The problem of defining artificial intelligence is largely reduced to defining intelligence in general: is intelligence monolithic or does this concept define a set of different abilities? To what extent intelligence can be created? Is it possible to create computers with intelligence? These and other questions have not yet been answered by the contemporary science, but these questions have greatly contributed to the formation of tasks and methodologies that form the basis of the theory and practice of contemporary artificial intelligence in philosophy. The purpose of the article is the need to study and substantiate the indicators of overall success in the development of artificial intelligence systems; proving that human psychoreality is an open system of nonlinear type; proving the effectiveness of logo and psycho-machines in the development of artificial intelligence in philosophy. The article gives a theoretical justification for the concepts of “artificial intelligence” and “logo and psycho machines”; the conditions for the effectiveness of the development of artificial intelligence in our time are highlighted, as the scientific direction of artificial intelligence is young, and its structure and range of issues are not so clearly defined. It is now possible to implement formal systems of reasoning in the machine and test their sufficiency for the manifestation of reasonableness in practice.

The development of public and private organizations is an irreversible process, but the pace at which it unfolds is different. While private organizations seek solutions to increase profit, public organizations, in the absence of a competitive environment, carry out their activity with less pressure on operating costs and with a slight passivity in the implementation of new reforms or technologies. Public managers are facing new technological challenges, with the development of artificial intelligence systems. The article aimed to conduct a comparative analysis regarding the implementation and intention to implement artificial intelligence tools in cities-municipalities in Romania versus those in Norway. The study of specialized literature highlighted the fact that in Norway there are extensive debates on the subject of the adoption of a legislative framework regarding the use of artificial intelligence in public institutions, while in Romania these are just beginning to take shape. The analysis carried out showed that in Norway, at the level of public organizations, from the perspective of the structural configuration, there are IT departments with a high number of employees. In Romanian municipalities, the number of workers with IT duties is under 10 civil servants, even if the number of employees in the institution exceeds in some situations over 800 or 1000. Of the nine municipalities in Romania analysed, in two of them, Cluj Napoca and Galați, virtual assistant solutions, called virtual civil servants chatbots, were implemented. In the context of the implementation of artificial intelligence, public management and all the functions it performs will need to be fundamentally rethought.

In modern conditions of development of public relations, the creation of objects of intellectual property rights by artificial intelligence is becoming more widespread. With this in mind, it is important to analyze the international legal experience of regulating the use of artificial intelligence as the author of intellectual property, to further borrow it for domestic laws, as well as to pay attention to problematic aspects of such regulation and make proposals to resolve inconsistencies. The study clarifies the international legal regulation of intellectual property rights created by artificial intelligence, as well as analyses the problematic issues of regulation of artificial intelligence by international law and the features of such regulation in Ukraine and presents positions on the development of artificial intelligence systems and prospects, as well as the prospects for its impact on world society.

As the hostilities in Ukrainian cities remind us once again, urban warfare persistently causes immense suffering and devastating consequences for civilians’ lives and livelihoods. At the same time, the events reveal the challenges urban warfare represents for militaries. The urban environment is one of the most complex environments within which to conduct military operations. To address the challenges this environment poses to militaries, several technologically advanced States are investing in the development of artificial intelligence to enhance a range of their military activities. The ways States have thus far prioritized the development of artificial intelligence systems, however, evidence that investments to improve militaries’ ability to mitigate civilian harm during urban warfare remain rather neglected. Hence, this article aims to demonstrate that despite the risks related to artificial intelligence applications, this technology has great potential for enhancing militaries’ ability to mitigate civilian harm further. But this requires governments to invest more in its development and use to that end. Recognizing artificial intelligence systems’ potential to reduce the military challenge of protecting civilians from harm during urban warfare is a pressing need, considering that conflicts increasingly occur in urban environments where the risks for civilians’ lives and their livelihoods grow exponentially.

In this article, the author discusses the issue of the concept of artificial intelligence, strategies for its development in many foreign countries and Uzbekistan. In particular, the conceptual issues of the development of artificial intelligence are discussed by such global participants of artificial intelligence as the United States, China, the European Union, etc. After studying and analysing the steps of artificial intelligence the author came to conclusion that without a well-planned strategic plan, it is impossible to develop artificial intelligence in Uzbekistan. Furthermore, the first steps on the way of introducing artificial intelligence into all spheres and sectors of Uzbekistan are considered, in particular, industry, medicine, science, transport and communications, etc. Based on the analysis of many strategies and plans of the above states, as well as India, the UAE, Canada, Japan, the author presents his own vision and recommendations for the development of artificial intelligence systems in our country.

Overview of the use of machine learning algorithms for real-time occupational risk assessment and monitoring Machine learning (ML) is an area of artificial intelligence dealing with algorithms that can modify their parameters based on processed data and perform tasks without explicit instructions. The development of artificial intelligence systems and Internet of Things technologies is resulting in ML algorithms being increasingly used in various sectors of the economy, including occupational risk assessment and monitoring. This article provides a review of the scientific literature in this field, which has identified the sectors and types of work environments in which these algorithms are used, defined the data used to learn ML algorithms and identified the most commonly used methods. The potential of UM algorithms to automate hazard identification and occupational risk assessment processes in real time is also presented. Keywords: machine learning, occupational risk assessment, real time, artificial intelligence

Currently, there is a rapid development of artificial intelligence systems that can solve and explain the solution of mathematical problems in the same way as students do. The problem of organizing interaction of artificial and human intelligence which does not lead to the degradation of the student’s thinking skills arises. The article proposes one of the ways to solve this issue through the use of systems such as “smart problems” using the example of a support system for a combinatorics course. In this system, the student sets problems and solves them himself without the help of a computer, but the system can check the solutions to problems without simulating human reasoning. Such a system cannot replace a person, but it becomes an intelligent interlocutor when setting and solving problems. Thus, the task of formulating a problem shows the way to bypass the gap formed with the advent of artificial intelligence.

The aim of this paper is to tease out some of the key issues concerning the relationship between AI and urbanism. This relationship, which is presented in the academic literature as a new driving force of contemporary urbanism, will be investigated through an interdisciplinary approach that places urban studies and philosophy of technology in dialogue. Thus, the analysis will not focus on the technological development of artificial intelligence systems but on how their application can affect urbanistic thinking and vice versa. The chart that is produced by this method is based on two fundamental axes: time and space. AI urbanism will then be inquired first through key turning points in the history of the relationship between technology and the city (modern urbanism, cybernetics and the smart city paradigm). Secondly, the spatial implications of urban AI will be investigated from the point of view of the concrete applications of this technology to the city (Robots, AVs, Software agents) and their impact on the relationships between different urban actors. Ultimately, this work aims to offer a conceptual tool for understanding some decisive implications of the relationship between AI and urbanism, such as the connection between quantitative and qualitative approaches, the implications related to autonomous technology, the economic-political background of AI urbanism, the material urban impact of AI, and the relationship between AI and other urban intelligences. Understanding these implications will be valuable for future research on AI urbanism oriented toward transforming simple technological development into sustainable urban innovations.

In response to Li, Reigh, He, and Miller's commentary, Can we and should we use artificial intelligence for formative assessment in science, we argue that artificial intelligence (AI) is already being widely employed in formative assessment across various educational contexts. While agreeing with Li et al.'s call for further studies on equity issues related to AI, we emphasize the need for science educators to adapt to the AI revolution that has outpaced the research community. We challenge the somewhat restrictive view of formative assessment presented by Li et al., highlighting the significant contributions of AI in providing formative feedback to students, assisting teachers in assessment practices, and aiding in instructional decisions. We contend that AI‐generated scores should not be equated with the entirety of formative assessment practice; no single assessment tool can capture all aspects of student thinking and backgrounds. We address concerns raised by Li et al. regarding AI bias and emphasize the importance of empirical testing and evidence‐based arguments in referring to bias. We assert that AI‐based formative assessment does not necessarily lead to inequity and can, in fact, contribute to more equitable educational experiences. Furthermore, we discuss how AI can facilitate the diversification of representational modalities in assessment practices and highlight the potential benefits of AI in saving teachers’ time and providing them with valuable assessment information. We call for a shift in perspective, from viewing AI as a problem to be solved to recognizing its potential as a collaborative tool in education. We emphasize the need for future research to focus on the effective integration of AI in classrooms, teacher education, and the development of AI systems that can adapt to diverse teaching and learning contexts. We conclude by underlining the importance of addressing AI bias, understanding its implications, and developing guidelines for best practices in AI‐based formative assessment.

As artificial intelligence (AI) becomes increasingly integral to our lives, ensuring these systems are trustworthy and transparent is paramount. The concept of explainability has emerged as a crucial element in fostering trust within AI systems. Nevertheless, the dynamics between explainability and trust in AI are intricate and not fully comprehended. This paper delves into the nexus between explainability and trust in AI, offering perspectives on crafting AI systems that users can rely on. Through an examination of existing literature, we investigate how transparency, accountability, and human oversight influence trust in AI systems and assess how various explainability approaches contribute to trust enhancement. Utilizing a set of experiments, our research examines how different explanatory models impact users' trust in AI systems, revealing that the nature and quality of explanations have a significant influence on trust levels. Additionally, we scrutinize the balance between explainability and accuracy in AI systems, discussing its implications for the development of reliable AI. This study underscores the critical role of explainability in engendering trust in AI systems, providing guidance on the development of AI systems that are both transparent and trustworthy, thereby fostering confidence among users.