Entropy of Artificial Intelligence

We describe a model of artificial intelligence systems based on the dimension of the probability space of the input set available for recognition. In this scenario, we can understand a subset, which means that we can decide whether an object is an element of a given subset or not in an efficient way. In the machine learning (ML) process we define appropriate features, in this way shrinking the defining bit-length of classified sets during the learning process. This can also be described in the language of entropy: while natural processes tend to increase the disorder, that is, increase the entropy, learning creates order, and we expect that it decreases a properly defined entropy.

Review of the theoretical approaches regarding the legal protection of objects generated by artificial intelligence systems in the field of copyright and related rights

Keywords: artificial intelligence, copyright, related rights, sui generis The publication provides a descriptive review of existingtheoretical approaches regarding the legal protection of objects generated byartificial intelligence systems in the field of copyright and related rights, namely.1) The inexpediency of legal protection of computer-generated objects. It is concludedthat the absence of legal regulation and free circulation of generated objects isconsidered the easiest option. Still, hardly fair and justified, as the creation of artificialintelligence systems requires large and significant investments in their development.2) The possibility of protecting computer-generated objects by copyright as originalworks. It has been established that extending the concept of «originality» to computergeneratedobjects seems unjustifiable.3) The introduction of the latest iteration of the fiction theory and establishing aspecial legal status for artificial intelligence systems. It is noted that such an approachseems premature because the existing artificial intelligence systems are amanifestation of «narrow» or «weak» artificial intelligence and not artificial generalintelligence.4) Protection of specific generated objects through related rights. It is concludedthat the objects generated by AI systems may be protected in Ukraine through theprism of related rights, under the condition that the relevant object can be attributedto a phonogram, videogram, or broadcast (program) of broadcasters respectively.5) Protection of generated objects through a special legal regime under copyrightlaw. It is described that this approach cannot be considered a universal example forimitating the legal protection of objects generated by computer programs because itsapplication leaves more questions and inconsistencies than solving the problem onthe merits.6) Protection of generated objects through sui generis law. It is assumed that applyingsuch an approach to the protection of objects generated by computer programswill not lead to significant changes in copyright and will protect the interests and investmentsof developers of artificial intelligence systems.

Taxation in the context of mass robotisation and artificial intelligence

The article is devoted to the structure of taxes in the context of robotization and artificial intelligence within the production and service sectors. The increase of robots and artificial intelligence systems will entail the replacement of human labour, which, in turn, will lead to a decrease in budgetary revenues. The article discusses possible options for the future design of robot tax to compensate for budget losses.

Software Engineering and Artificial Intelligence: Re-Enhancing the Lifecycle

As automation is changing everything in today’s world, there is an urgent need for artificial intelligence, the basic component of today’s automation and innovation to have standards for software engineering for analysis and design before it is synthesized to avoid disaster. Artificial intelligence software can make development costs and time easier for programmers. There is a probability that society may reject artificial intelligence unless a trustworthy standard in software engineering is created to make them safe. For society to have more confidence in artificial intelligence applications or systems, researchers and practitioners in computing industry need to work not only on the cross-section of artificial intelligence and software engineering, but also on software theory that can serve as a universal framework for software development, most especially in artificial intelligence systems. This paper seeks to(a) encourage the development of standards in artificial intelligence that will immensely contribute to the development of software engineering industry considering the fact that artificial intelligence is one of the leading technologies driving innovation worldwide (b) Propose the need for professional bodies from philosophy, law, medicine, engineering, government, international community (such as NATO, UN), and science and technology bodies to develop a standardized framework on how AI can work in the future that can guarantee safety to the public among others. These standards will boost public confidence and guarantee acceptance of artificial intelligence applications or systems by both the end-users and the general public.

Towards Autonomous Driving Using Vision Based Intelligent Systems

Vision Based systems have become an integral part when it comes to autonomous driving. The autonomous industry has seen a made large progress in the perception of environment as a result of the improvements done towards vision based systems. As the industry moves up the ladder of automation, safety features are coming more and more into the focus. Different safety measurements have to be taken into consideration based on different driving situations. One of the major concerns of the highest level of autonomy is to obtain the ability of understanding both internal and external situations. Most of the research made on vision based systems are focused on image processing and artificial intelligence systems like machine learning and deep learning. Due to the current generation of technology being the generation of “Connected World”, there is no lack of data any more. As a result of the introduction of internet of things, most of these connected devices are able to share and transfer data. Vision based techniques are techniques that are hugely depended on these vision based data.

Standardization in regulating artificial intelligence systems in Russian healthcare

Artificial intelligence technologies in medical practice are a promising direction in the world. Artificial intelligence medical decision support systems, diagnostic and screening programs can help medical personnel in routine and complex tasks and improve the level of medical care provided to patients. At the same time, the development, production and distribution of artificial intelligence systems must be regulated without fail. Registration and subsequent control (post-registration monitoring) of artificial intelligence systems in medicine require the creation, adjustment of the legal framework and technological regulation. The Russian Federation has developed a promising development strategy in this area. Seven national standards have been developed by experts in the field of Artificial intelligence in healthcare. These standards establish the procedures for conducting clinical and technical trials, performance requirements and the concept of life cycle, a quality management system and risk management. Aseparate standards is devoted to dataset creation for training and testing the developed algorithms, requirements for them and a metadata format. There are plans to bring the developed national standards to the international level, which will allow Russian manufacturers of artificial intelligence systems implemented these national standards to comply with foreign counterparts and become more competitive at the international level. The international community has already supported the development of an ISO standard based on the national standard for clinical trials. The development will be performed based on the technical committee ISO/TC215 (Health informatics) in conjunction with ISO/IEC JTC1/SC42 (Artificial intelligence), this will allow bringing the national requirements for the Artificial intelligence to the international level. The cycle of these standards will summarize recognized methodologies, helping both manufacturers and medical organizations, doctors and patients to produce and use aquality, safe and effective product.

Conceptual Framework—Artificial Intelligence and Better Entrepreneurial Decision-Making: The Influence of Customer Preference, Industry Benchmark, and Employee Involvement in an Emerging Market

Purpose: Technology initiatives are now incorporated into a wide range of business domains. The objective of this paper is to explore the possible effects that Artificial intelligence systems have on entrepreneurs’ decision-making, through the mediation of customer preference and industry benchmark. Design/methodology/approach: This is a non-empirical review of the literature and the development of a conceptual model. Searches were conducted in key academic databases, such as Emerald Online Journals, Taylor and Francis Online Journals, JSTOR Online Journals, Elsevier Online Journals, IEEE Xplore, and Directory of Open Access Journals (DOAJ) for papers which focused on Artificial intelligence (AI), Entrepreneurial decision-making, Customer preference, Industry benchmarks, and Employee involvement. In total, 25 articles met the predefined criteria and were used. Findings: The study proposes that Artificial intelligence systems can facilitate better decision-making from the entrepreneurial perspective. In addition, the study demonstrates that employees, as stakeholders, can moderate the relationship between Artificial intelligence systems and better decision-making for entrepreneurs with their involvement. Moreover, the study demonstrates that customer preference and industry benchmark can mediate the relationship between Artificial intelligence systems and better entrepreneur decision-making. Research limitations/implications: The study assumes a perfect ICT environment for the smooth operation of Artificial intelligence systems. However, this might not always be the case. The study does not consider the personal disposition of entrepreneurs in terms of ICT usage and adoption. Practical implications: This study proposes that entrepreneurial decision-making is enriched in an environment of Artificial intelligence systems, which is complemented by customer preference, industry benchmark, and employee involvement. This finding provides entrepreneurs with a possible technological tool for better decision-making, highlighting the endless options offered by Artificial intelligence systems. Social Implications: The introduction of AI in the business decision-making process comes with many social issues in relation to the impact machines have on humans and society. This paper suggests how this new technology should be used without destroying society. Originality/value: This conceptual framework serves as a valuable organizational spectrum for entrepreneurial development. In addition, this study makes a valuable contribution to entrepreneurial development through Artificial intelligence systems.

Neurotechnology and development of students and teachers’subjectivity in inclusive education

В статье рассматриваются результаты и последствия внедрения смарти нейротехнологий в инклюзивное образование. Цель работы — изучить их влияние на развитие субъектности студентов и преподавателей, применяющих цифровые технологии. Новизна исследования заключается в попытке интегративно осмыслить социально-психологические проблемы нейрообразования, связанные с внедрением и применением систем искусственного интеллекта в инклюзивном образовательном процессе, в рамках которого формируется и развивается субъектность. Изучение подводных камней нейрообразования необходимо для осмысления результатов воздействия цифровых технологий на становление и развитие обучающихся и педагогов как субъектов воспитательно-образовательного процесса. Варианты преобразования инклюзивного образования и его субъектов должны рассматриваться в контексте изменения ценностей, целей, концептов и концепций, которые определяют и трансформируют взаимоотношения человека с собой и окружающим миром. Результаты исследования показали, что нейротехнологии вызывают серьезные изменения в инклюзивном образовании, влияют на отношение человека к себе и окружающему миру и в конечном итоге могут привести к потере субъектности. Соответственно, их использование подразумевает высокую культуру инклюзивного образовательного процесса, развитие человеческих и профессиональных качеств педагогов и обучающихся. Нейрообразование может сыграть существенную роль в становлении и совершенствовании человека как субъекта при условии формирования нейросреды в контексте цифровой и общечеловеческой культуры. The article focuses on the results and consequences of the introduction of smart and neurotechnologies in inclusive education. The purpose of the study is to analyze the development of the subjectivity of students and teachers using digital technologies. The novelty of the research lies in the desire to integratively reflect on socio-psychological problems related to the introduction and application of artificial intelligence systems in an inclusive educational process, within which subjectivity is formed and developed. The study of the problems of neuroeducation is necessary for understanding the results of the impact of digital technologies on the formation and development of students and teachers as subjects of the educational process. Options for the transformation of inclusive education and its subjects should be considered in terms of changing values, goals, concepts that define and transform a person’s relationship with themselves and the world around them. Research results showed that neurotechnologies bring serious changes in inclusive education; they affect a person’s attitude towards himself or herself and the world around him or her and can eventually lead to a loss of subjectivity.They can be introduced only on the basis of a high culture of the educational process, highly developed human and digital competencies of teachers and students. Neuroeducation can play an essential role in a person’s formation and improvement as a subject provided the neuro-environment is created on the basis of digital and human culture.