Use Of AI Technologies Research Articles

Legal Governance of Brain Data Derived from Artificial Intelligence

Legal Governance of Brain Data Derived from Artificial Intelligence

LAW IN DIGITAL REALITY

LAW IN DIGITAL REALITY

The Preliminary Elementary School Teachers’ Perceptions and Attitudes on the Future English Education Using AI Technology: Focusing on the Students Majoring in English Education

Purpose: The purpose of this study is to investigate preliminary elementary school teachers’ perceptions and attitudes about the upcoming future English education, namely the fourth industrial revolution era. Method: For the research, 91 preliminary elementary school teachers were surveyed. As for a questionnaire form, this study defines preliminary elementary school teachers’ attitudes in the following categories; 1)interests in English education using AI technology, 2)innovation resistance and anxiety about English educa-tion using AI technology. Results: The results of the survey data were as follows. First of all, the preliminary elementary school teach-ers’ interest in the impact of AI technology on English education was high, but their interest remain at the ‘per-sonal’(1-2 stages) level. Second, the level of the preliminary elementary school teachers’ innovation resistance was not high, but the anxiety level was above average. They showed willingness to take AI technologies as in-structional tools and positive attitudes toward AI technology-embedded future classroom. On the one hand, they were anxious about a lack of knowledge about new teaching method and skills related with utilizing AI technology into their classroom. Conclusion: The curriculum should be the tailored curriculum to meet their level and needs, which was re-quired in the fourth industrial revolution through the use of AI technologies. It is to show the possibility of using AI technology to learn English so that we can maintain the current positive perception of the English education using AI that the preliminary school teacher showed. Also, in order to be open to any paradigm changes related to English education in the era of the 4th industrial revolution, concerns and proposals for a new method of Eng-lish education should be actively discussed. Finally, the university of education, which is a teacher training insti-tution, need to introduce to preliminary elementary school teachers what AI technologies can be combined with English education and what are their characteristics, and to guide how AI technology is being applied to English education

DIGITALIZATION AND ARTIFICIAL INTELLIGENCE IN BANKS: A STEP INTO THE FUTURE

The author of the article emphasizes the importance of using digitalization and artificial intelligence in banks. The transition to such a model in a particular area will be a serious driver of growth for them and a catalyst for the use of AI technologies. Innovations in the field of digitalization of the banking sector are considered. The plan for the development of the digital ruble project was studied. The introduction of the fast payment system (SPB) is considered. The application of artificial intelligence in the banking sector is studied. The forecast of revenues of the artificial intelligence market is made.

General risks of using AI technologies in the field of road traffic safety

The research subject is legal provisions and scientific sources reflecting the procedure of using AI technologies in the field of road traffic safety. The research object is social relations defining the fundamentals of the use of AI technologies in the field of road traffic safety. Based on the analysis of regulatory documents and scientific literature, the author outlines a set of technological, social, and legal risks of using artificial intelligence in this field, and emphasizes particular problems of legal regulation. The research methodology is based on the set of general scientific and specific methods of cognition (formal-legal, analytical, the system method, analysis, synthesis, modeling, comparison, etc.). The author formulates the conclusion that the accentualization of technological, social and legal risks as and when AI technologies are used in the field of road traffic safety, helps to organize the work of public authorities in advance and step-by-step, and to find a wide range of legal instruments helping to eliminate or minimize possible risks, raise the effectiveness of public administration of social relations in the field of road traffic safety, and promote the achievement of strategic socio-economic goals of the state.  The scientific novelty of the research consists in a comprehensive analysis of theoretical legal and organizational aspects, characterizing the risks of using AI in the field of road traffic safety, and an accentualization of particular problems of legal regulation and the prospects of implementation of AI technologies in this field.       

Prospects for the introduction of artificial intelligence technologies in higher education

At present, comprehensive research, from various points of view (social, economic, ethical, legal), devoted to the implementation of artificial intelligence technologies in various spheres of society, is of particular relevance. It is important to identify opportunities and threats, to determine the limits of the use of artificial intelligence in practice. The article is devoted to the implementation of artificial intelligence technologies in the field of higher education. The perspective directions of using artificial intelligence in the field of higher education are considered and analyzed. The authors come to the conclusion that artificial intelligence is not at all a competitor to the teaching staff, either in teaching or in evaluating students knowledge. Artificial intelligence is an auxiliary, but valuable tool that can perform and improve a large number of different operations carried out at the university, help in organizing an effective educational process and building the necessary communications. The effective use of AI technologies in higher education will allow the selection of the most optimal learning strategy, adapted to the individual abilities and needs of students and the needs of the labor market.

Artificial intelligence, human rights, democracy, and the rule of law: a primer

In September 2019, the Council of Europe's Committee of Ministers adopted the terms of reference for the Ad Hoc Committee on Artificial Intelligence (CAHAI). The CAHAI is charged with examining the feasibility and potential elements of a legal framework for the design, development, and deployment of AI systems that accord with Council of Europe standards across the interrelated areas of human rights, democracy, and the rule of law. As a first and necessary step in carrying out this responsibility, the CAHAI's Feasibility Study, adopted by its plenary in December 2020, has explored options for an international legal response that fills existing gaps in legislation and tailors the use of binding and non-binding legal instruments to the specific risks and opportunities presented by AI systems. The Study examines how the fundamental rights and freedoms that are already codified in international human rights law can be used as the basis for such a legal framework. It proposes nine principles and priorities that are fitted to the novel challenges posed by the design, development, and deployment of AI systems. When codified into law, these principles and priorities create a set of interlocking rights and obligations that will work towards ensuring that the design and use of AI technologies conform to the values of human rights, democracy, and the rule of law. The purpose of this primer, co-produced by The Alan Turing Institute and the Council of Europe, is to introduce the main concepts and principles presented in the CAHAI's Feasibility Study for a general, non-technical audience. It also aims to provide some background information on the areas of AI innovation, human rights law, technology policy, and compliance mechanisms covered therein. In keeping with the Council of Europe's commitment to broad multi-stakeholder consultations, outreach, and engagement, this primer has been designed to help facilitate the meaningful and informed participation of an inclusive group of stakeholders as the CAHAI seeks feedback and guidance regarding the essential issues raised by the Feasibility Study.

When do Citizens Resist AI-Usage in Public Policy? Evidence from the COVID-19 Crisis

In the effort to contain the COVID-19 outbreak and mitigate its consequences, many hopes were placed on the use of AI-technology. Indeed, AI-based algorithms have informed decision-making in many aspects of the crisis, including diagnosis, infection tracking, outbreak forecasting, and allocation of essential resources and services. How do citizens view the incorporation of AI technology in making major public policy decisions? Using original survey data from the U.S. and Israel, I show that the public trusts humans significantly more than algorithms in making pandemic-related highstake decisions. However, experimental evidence indicates that this clear preference does not translate uniformly into lower support for policies that rely on algorithmic assessment. Rather, views on the use of algorithms differ substantially depending on the decision context in which it is deployed. The analysis indicates that while deployment of AI in public policy may be acceptable in some cases, it could trigger substantial opposition in other, theoretically-predictable contexts.

Job candidates’ reactions to AI-Enabled job application processes

Organizations are increasingly using AI-enabled technology and tools in their recruiting processes. However, little is known about how job candidates view AI-enabled job application systems and whether those views influence the likelihood that they will apply for jobs in such cases. Our research finds that attitudes toward AI use in the job application process in general, and attitudes toward organizations that use AI in the job application process in particular, are strongly related to the intent of prospective employees to apply for jobs at those organizations that have AI-enabled job application processes. Given the growing use of AI technology and tools in candidate recruitment, and given that organizations primarily select from and offer jobs to those who have completed the job application process, a better understanding of what influences candidates’ reactions to AI-enabled recruiting could provide valuable insights into how organizations can more effectively manage those activities.

AI Affecting Local Search in Strategic Decision-Making

Artificial intelligence technologies could be used to direct executives’ scarce attention to improve the quality of decision making and in particular, improve strategic search. However, use of such technologies could also amplify bias or induce local search. We draw from literature on local search as well as literature on managerial implications of AI technologies to specify how the use of AI technologies could affect search in the context of strategic decision-making. We propose that AI tools can broaden search space, change cognitive-attentional dynamics of the search process, or affect interpretation of cues. We further detail what factors are likely to affect this, including managerial, organizational and industry characteristics. We thus contribute to the literature on local search by detailing how technologies might alleviate or aggravate the situation, and to literature on AI technologies by providing guidance on how these technologies could be used in the strategy process in an optimal way.

Use of Artificial Intelligence in Education

Today, artificial intelligence is one of the emerging technologies which are capable of altering every aspect of our social interactions. In education, AI has begun producing new teaching and learning solutions that are now undergoing testing in different contexts. This paper will let the stakeholders in education sector to understand the extent to which AI will be used in the education and its perceived benefits. This paper provides examples of use of AI in education, particularly in developing countries like India wherein providing education to all is seen as one of the sustainable development goals. First, this paper provides an overview of AI to the reader. It was observed that AI has evolved from simple rule based systems to data-driven systems to contextdriven systems that have advanced capabilities. Next, the paper talks an approach to putting AI into use in education to improve learning outcomes. Indeed as a new technology, AI when used in education will bring changes to ‘learning experience’ by having adjustable learning environment that creates ‘personalized learning experience’. Finally, this paper presents some examples of use of AI technology in education sector aimed at improving learning experience and quality of learning.

Перспективы внедрения технологий искусственного интеллекта в сфере высшего образования

At present, comprehensive research from various points of view (social, economic, ethical, and legal) on the implementation of artificial intelligence technologies in various spheres of society’s life is of particular relevance. It is important to identify opportunities and threats, to determine the limits of the use of artificial intelligence in practice. The article is devoted to the introduction of artificial intelligence technologies in higher education. Prospective directions of using artificial intelligence in higher education are considered and analyzed. The authors conclude that artificial intelligence is not a competitor to the teaching staff, either in teaching or in evaluating students’ knowledge. Artificial intelligence is an auxiliary, but valuable tool that can perform and improve a large number of different operations performed at the University, help in organizing an effective educational process and building the necessary communications. Effective use of AI technologies in higher education will allow you to select the most optimal learning strategy adapted to the individual abilities and needs of students and the needs of the labor market.

THE LIMITS OF THE POSSIBLE AND PERMISSIBLE IN THE TECHNOLOGICAL APPROACH TO LEGAL KNOWLEDGE

Problem setting. New complex challenges of the present, including transformation and complication of heterogeneity and entropy of the Internet space, intensive development of robotics, technologies of artificial intelligence, can not but affect the state and development of the entire legal system of the state and legislation in various spheres of public relations. It is necessary to formulate criteria for a typology of legal problems that can be solved by digital formalization, and which require the use of the potential of "personal knowledge" to which intuition and practical experience are involved, etc.Recent research and publications analysis. The results of studies of these problems make it possible to point out that, as a whole, a systematic scientific understanding of the complex, voluminous and multidimensional problem of clarifying the perspectives and limits of the technological approach in professional legal practice, legal expert activity, influence on the transformation of legal norms, jurisprudence and legal education and the like need further careful study. The rapid development of new technologies, in particular artificial intelligence technologies, the Internet of Things, cloud technologies, etc., is contributing to changes in current legislation. Today, advanced economies are already pondering the question of regulating the status and use of AI technologies. While these are only the first bold steps, in the future, all of these can affect global changes in the legal system - perhaps full-fledged comprehensive institutions of law and institutions of law, even the branches and branches of law.Paper objectiv. The purpose of this article is to consideration of certain aspects of digitization of law and the limits of possible and admissible in the technological approach to legal knowledge on the basis of the results of understanding of this problem by different representatives of the humanities and interdisciplinary researchers.Paper main body. The article substantiates the importance and methodology of the technological approach in law, the limits of the use of this approach. It is shown that since the intensive development of innovative technologies, their widespread adoption in various spheres of public life is a significant factor in the development of modern society, this gradually leads to the formation of a new "digital" reality. It is disclosed that innovative technologies are not only potentially applicable, but have long been effectively used in the legal sphere, due to which, in particular, the correct and quick solution of various tasks is ensured, which contributes to more efficient provision of legal services, ensuring professional legal practice, etc. It is revealed that in the new reality, law becomes not only a means, a tool that provides digitalization of the economy, management and other segments of society, but also the object of digitalization, as a result of which it experiences changes in its form, content, system, structure, mechanism of action and demonstrates tendencies to strengthen these transformations.Conclusions of the research. In the face of new reality, law becomes not only a means, a tool that ensures the digitization of the economy, governance and other segments of social life, but also the object of digitalization, in which it changes its form, content, system, structure, mechanism of action and demonstrates a tendency to enhance these transformations. The following are legally and in fact possible and relevant directions and forms of the use of artificial intelligence technologies in legal practice, in particular in the judiciary: information and documentary support of legal practice, which includes automated intellectual classification of legal documents, formation and documentation of cases, elaboration through the use of artificial intelligence technologies of projects of solutions to various legal problems by means of using and analyzing databases; intellectual expert-analytical support of legal practice by comparison of technologies of artificial intelligence of norms of law, comparison of normative legal acts in order to determine their hierarchy, establishment of norms and acts of higher legal force from among those that are compared; generating and issuing expert assessments within the framework of forensic expertise or specialist opinion (use of knowledge bases (expert systems), automated systems for supporting legal decisions based on artificial intelligence); facilitating decision-making on large volumes of heterogeneous tasks in difficult uncertainty conditions, based on inaccurate, insufficient or poorly structured information.

Transparency and Fairness in Machine Learning Applications

Businesses and consumers increasingly use artificial intelligence (“AI”)— and specifically machine learning (“ML”) applications—in their daily work. ML is often used as a tool to help people perform their jobs more efficiently, but increasingly it is becoming a technology that may eventually replace humans in performing certain functions. An AI recently beat humans in a reading comprehension test, and there is an ongoing race to replace human drivers with self-driving cars and trucks. Tomorrow there is the potential for much more—as AI is even learning to build its own AI. As the use of AI technologies continues to expand, and especially as machines begin to act more autonomously with less human intervention, important questions arise about how we can best integrate this new technology into our society, particularly within our legal and compliance frameworks. The questions raised are different from those that we have already addressed with other technologies because AI is different. Most previous technologies functioned as a tool, operated by a person, and for legal purposes we could usually hold that person responsible for actions that resulted from using that tool. For example, an employee who used a computer to send a discriminatory or defamatory email could not have done so without the computer, but the employee would still be held responsible for creating the email. While AI can function as merely a tool, it can also be designed to act after making its own decisions, and in the future, will act even more autonomously. As AI becomes more autonomous, it will be more difficult to determine who—or what—is making decisions and taking actions, and determining the basis and responsibility for those actions. These are the challenges that must be overcome to ensure AI’s integration for legal and compliance purposes.

Welcome to AI matters, volume 3, issue 4

Welcome to the final issue in our third year! This issue features the second installment of essays on the "Responsible Use of AI Technologies" from the winners of the ACM SIGAI-sponsored student essay contest. In addition to having their essay appear in AI Matters , the contest winners received either monetary prizes or one-on-one Skype sessions with leading AI researchers.

There Is No Agency Without Attention

Over the decades, the view of agency in artificial intelligence (AI) has narrowed to one that emphasizes acting in a way that maximizes reward. This perspective fails to make contact with the broader academic and legal communities where agency is bound up with personal accountability. To explore this gap in meaning, we introduce a spectrum of control that characterizes standard approaches to constructing agents and points the way toward agents that can be held responsible. The linchpin that enables agents to control their actions in the “right way” is attention. Broadly construed, attention lets an agent that is responsive to its environment consider the relationships among its actions, goals, and norms while also avoiding distraction. This ability enables strategic norm violations and opens the door to artificial, human‐level agency.

Welcome to AI matters, volume 3, issue 3

Welcome to the third issue in our third year of AI Matters ! In the spring, ACM SIGAI sponsored a student essay contest on the "Responsible Use of AI Technologies." This issue features the first set of winning essays from the contest, with the second set of winning essays to appear in the next issue.

Sustainable Policy Making: A Strategic Challenge for Artificial Intelligence

Policy making is an extremely complex process occurring in changing environments and affecting the three pillars of sustainable development: society, economy and the environment. Each political decision in fact implies some form of social reactions, it affects economic and financial aspects and has substantial environmental impacts. Improving decision making in this context could have a huge beneficial impact on all these aspects. There are a number of Artificial Intelligence techniques that could play an important role in improving the policy‐making process such as decision support and optimization techniques, game theory, data and opinion mining and agent‐based simulation. We outline here some potential use of AI technology as it emerged by the European Union (EU) EU FP7 project ePolicy: Engineering the Policy Making Life Cycle, and we identify some potential research challenges.

The artifical intelligence applications to learning programme

The Artificial Intelligence Applications to Learning Programme has been funded since 1987 by what is now known as the Training, Enterprise and Education Directorate (TEED). The Programme aimed to explore and accelerate the use of AI technologies in learning, in both the educational and industrial sectors. The ten demonstrator projects were evaluated for their impact on industry and on further and higher education, while the project was in progress and later during its dissemination phase. The most useful outcomes of evaluation emerged during the latter phase, when the innovations had had an opportunity to become established and brought to market. There were issues related to technology-drive and the need to find problems for which the solution existed through group collaboration. One profitable line of development was to use AI to enrich training systems. An ideal training system must feel “good” to the client, should go beyond existing adaptive training systems, offer a high rate of training, be cost effective, have visual appeal, give sophisticated feedback, should fit closely with the user's current practice, and should have a shele life of more than 3 years.

Design Practice and Application Domain: Primary Factors in Intelligent User-System Interface Design

Through the use of AI technology, the potential exists to make revolutionary changes in military command and control. Knowledge based systems can enable a commander and staff to accommodate large amounts of information efficiently and effectively, to generate operations plans rapidly, and thereby allow exploitation of early maneuver opportunities. This paper addresses the issues of application domain and human factors design practice as they relate to the development of effective user system interfaces for expert systems.