The Ethics of Artificial Intelligence in Education identifies and confronts key ethical issues generated over years of AI research, development, and deployment in learning contexts. Adaptive, automated, and data-driven education systems are increasingly being implemented in universities, schools, and corporate training worldwide, but the ethical consequences of engaging with these technologies remain unexplored. Featuring expert perspectives from inside and outside the AIED scholarly community, this book provides AI researchers, learning scientists, educational technologists, and others with questions, (...) frameworks, guidelines, policies, and regulations to ensure the positive impact of artificial intelligence in learning. (shrink)

Over the past ten years, we have worked in a collaboration between educators and computer scientists at the University of Illinois to imagine futures for education in the context of what is loosely called “artificial intelligence.” Unhappy with the first generation of digital learning environments, our agenda has been to design alternatives and research their implementation. Our starting point has been to ask, what is the nature of machine intelligence, and what are its limits and potentials (...) in education? This paper offers some tentative answers, first conceptually, and then practically in an overview of the results of a number of experimental implementations documented in greater detail elsewhere. Our key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence. However, within the limits that we describe in this paper, it offers the potential to transform education in ways that—counterintuitively perhaps—make education more human, not less. (shrink)

Over the past ten years, we have worked in a collaboration between educators and computer scientists at the University of Illinois to imagine futures for education in the context of what is loosely called “artificial intelligence.” Unhappy with the first generation of digital learning environments, our agenda has been to design alternatives and research their implementation. Our starting point has been to ask, what is the nature of machine intelligence, and what are its limits and potentials (...) in education? This paper offers some tentative answers, first conceptually, and then practically in an overview of the results of a number of experimental implementations documented in greater detail elsewhere. Our key finding is that artificial intelligence—in the context of the practices of electronic computing developing over the past three quarters of a century—will never in any sense “take over” the role of teacher, because how it works and what it does are so profoundly different from human intelligence. However, within the limits that we describe in this paper, it offers the potential to transform education in ways that—counterintuitively perhaps—make education more human, not less. (shrink)

Purpose The purpose of this paper is to demonstrate the advancements in artificial intelligence (AI) and conversational agents, emphasizing their potential benefits while also highlighting the need for vigilant monitoring to prevent unethical applications. Design/methodology/approach As AI becomes more prevalent in academia and research, it is crucial to explore ways to ensure ethical usage of the technology and to identify potentially unethical usage. This manuscript uses a popular AI chatbot to write the introduction and parts of the body (...) of a manuscript discussing conversational agents, the ethical usage of chatbots and ethical concerns for academic researchers. Findings The authors reveal which sections were written entirely by the AI using a conversational agent. This serves as a cautionary tale highlighting the importance of ethical considerations for researchers and students when using AI and how educators must be prepared for the increasing prevalence of AI in the academy and industry. Measures to mitigate potential unethical use of this evolving technology are also discussed in the manuscript. Originality/value As conversational agents and chatbots increase in society, it is crucial to understand how they will impact the community and how we can live with technology instead of fighting against it. (shrink)

The recent appearance of generative artificial intelligence (AI) platforms has been seen by many as disruptive for education. In this paper I attempt to locate the source of tension between educational goals and new information technologies including AI. I argue that this tension arises from new conceptions of epistemic agency that are incompatible with educational aims. I describe three competing theories of epistemic agency which I refer to as Makers, Managers, and Inforgs. I contend that educators are (...) correct in maintaining the first of these, which is rooted in the educational theories of Locke and Dewey, as their main educational purpose. Competing theories do not serve the goals of learners, even as they must prepare for life in a very different epistemic environment. (shrink)

Like previous educational technologies, artificial intelligence in education threatens to disrupt the status quo, with proponents highlighting the potential for efficiency and democratization, and skeptics warning of industrialization and alienation. However, unlike frequently discussed applications of AI in autonomous vehicles, military and cybersecurity concerns, and healthcare, AI’s impacts on education policy and practice have not yet captured the public’s attention. This paper, therefore, evaluates the status of AIEd, with special attention to intelligent tutoring systems and anthropomorphized (...) artificial educational agents. I discuss AIEd’s purported capacities, including the abilities to simulate teachers, provide robust student differentiation, and even foster socio-emotional engagement. Next, to situate developmental pathways for AIEd going forward, I contrast sociotechnical possibilities and risks through two idealized futures. Finally, I consider a recent proposal to use peer review as a gatekeeping strategy to prevent harmful research. This proposal serves as a jumping off point for recommendations to AIEd stakeholders towards improving their engagement with socially responsible research and implementation of AI in educational systems. (shrink)

Trust and trustworthiness are central concepts in contemporary discussions about the ethics of and qualities associated with artificial intelligence (AI) and the relationships between people, organisations and AI. In this article we develop an interdisciplinary approach, using socio-technical software engineering and design anthropological approaches, to investigate how trust and trustworthiness concepts are articulated and performed by AI software practitioners. We examine how trust and trustworthiness are defined in relation to AI across these disciplines, and investigate how AI, trust (...) and trustworthiness are conceptualised and experienced through an ethnographic study of the work practices of nine practitioners in the software industry. We present key implications of our findings for the generation of trust and trustworthiness and for the training and education of future software practitioners. (shrink)

The paper aims to formulate theoretical and methodological foundations as well as basic research questions for studying intervention of artificial intelligence in everyday life of medical and life sciences in the 21 century. It is an invitation for professional philosophical, theoretical and methodological discussion about the necessity and reality of artificial intelligence in contemporary medical/life sciences and medicine. The authors commence with a proposition of their definitions of ‘artificial intelligence’ (AI) and ‘artificial sociality’ (...) (AS). The next section of the paper deals with a review of basic trends in medical/life sciences and medicine. In what follows the authors debate two problems related to incorporation of AI in reality of current medicine. The first is the potential revision of the principles developed in western medicine; the second is the alteration of the contents and forms of medical education. The authors theorize the dynamic interplay between structural expansion and cultural contraction of medicine and life sciences in current practices of higher education and explore how this introduces an essential tension between the necessity and reality for medical professionals to work with AI. The paper shows that attending to institutional dynamics serves as a critical and timely extension of disciplinary/cross/anti-disciplinary critiques of science and medicine, not only since the current inclusion agenda of the AI in medicine may do little to address the real concerns of a medical profession in the XXI century but also because it may inadvertently undermine the institutional recognition and epistemic acceptance of new anti-disciplinary vista for studying AI per se. In conclusion the authors underline basic outcomes of the discussion and propose further routes for inquiry and research. (shrink)

The paper analysis the strategies and concepts developed in the world in modern directions: innova- tive economy, digital economy, artificial intelligence, Industry 4.0 and others. The problem is to determine the initial fundamental parameters of order and their prospects in the global world, the definition and principles of artificial intel- ligence systems, its structure and important aspects and principles of future science and technology in analysis and synthesis based on synergetic approaches, innovative, information, converged technologies, taking into (...) account the design of future and viable and safe and sustainable development in the context of Industry 4.0, digital economy and Society 5.0. The general scheme of the integrated model of sustainable and socio-humanitarian development in the global system is proposed, which the authors call the noosphere model of sustainable and safe development as an important fundamental platform for the design and creation of AIS. In the XXI century education, science and innova- tive technologies becomes the «basis» of the spiritual and material reproduction of man, transforming the society of the XXI century into an educational society, ensures compliance with the law of advanced development of human quality, quality of social intelligence and quality of educational systems in society. noosphere evolution. Industry 4.0 is the next stage in the digitalization of production technologies with the accelerated introduction of new developments and cyberphysical systems, which is changing business models. Accordingly, Industry 4.0 as a separate segment of digital manufacturing technologies takes its place among other digital sectors. The analysis of the Strategies and Concepts developed in the world in modern directions: innovative economy, digital economy, artificial intelli- gence, Industry 4.0 and others is carried out in the work. The problem is to determine the initial fundamental para- meters of order and their prospects in the global world, the definition and principles of artificial intelligence systems, its structure and important aspects and principles of future science and technology in analysis and synthesis ba- sed on synergetic approaches, innovative, information, converged technologies, taking into account the design of future and viable and safe and sustainable development in the context of Industry 4.0, DE and Society 5.0. The main scientific and technological factors in the 21st century will be the development of: Artificial Intelligence, Nano Technologies, Bio-Media Technologies, Cognitive Technologies and Socio-Humanitarian Technologies. More specifically – this is the modern development of Innovative Technologies: «NBIC SH». Therefore, it is necessary to note the importance of taking into account the principle of I2K2+SH, ie: Intellectualization, Integration, Convergence, Coevolution and Socio- humanitarian technologies. It is important and necessary to take into account modern principles of designing a su- stainable and secure AIS and solving the problem of Harmonization between 2 worlds: Real and Virtual, especially in their hybridization. Our immediate future is a hybrid nonlinear world. Note that digitalization, artificial intelligence and robotics will be the main drivers of global economic growth by 2030E. An important paradigm and platform is the Integrated System: for Industry 4.0, DE and AI, taking into account the complex principle of I2K2+SH. If the transition of the Ukrainian economy to an innovative one does not take place in the next 3-5 years, Ukraine will remain in the backyard of civilization. (shrink)

In this article, I establish a theory of knowledge approach for evaluating the use of computers for educational purposes at the university. In so doing, I trace part of the history of the “enabling factor” of Artificial Intelligence in this sector, an important element that has been integrated into everyday learning environments. The result of my reflection is a dialogical structure, directly inspired by past technology assessment research, which illustrates the conceptual advancement of researchers in the field of (...) learning technologies. The notions covered have implications in future policy-related discourse with regards to education. (shrink)

While an increasing number of organizations have introduced artificial intelligence as an important facilitating tool for learning online, the application of artificial intelligence in e-learning has become a hot topic for research in recent years. Over the past few decades, the importance of online learning has also been a concern in many fields, such as technological education, STEAM, AR/VR apps, online learning, amongst others. To effectively explore research trends in this area, the current state of (...) online learning should be understood. Systematic bibliometric analysis can address this problem by providing information on publishing trends and their relevance in various topics. In this study, the literary application of artificial intelligence combined with online learning from 2010 to 2021 was analyzed. In total, 64 articles were collected to analyze the most productive countries, universities, authors, journals and publications in the field of artificial intelligence combined with online learning using VOSviewer through WOS data collection. In addition, the mapping of co-citation and co-occurrence was explored by analyzing a knowledge map. The main objective of this study is to provide an overview of the trends and pathways in artificial intelligence and online learning to help researchers understand global trends and future research directions. (shrink)

During the 1950s, there was a burst of enthusiasm about whether artificial intelligence might surpass human intelligence. Since then, technology has changed society so dramatically that the focus of study has shifted toward society’s ability to adapt to technological change. Technology and rapid communications weaken the capacity of society to integrate into the broader social structure those people who have had little or no access to education. (Most of the recent use of communications by the excluded (...) has been disruptive, not integrative.) Interweaving of socioeconomic activity and large-scale systems had a dehumanizing effect on people excluded from social participation by these trends. Jobs vanish at an accelerating rate. Marketing creates demand for goods which stress the global environment, even while the global environment no longer yields readily accessible resources. Mining and petroleum firms push into ever more challenging environments (e.g., deep mines and seabed mining) to meet resource demands. These activities are expensive, and resource prices rise rapidly, further excluding groups that cannot pay for these resources. The impact of large-scale systems on society leads to mass idleness, with the accompanying threat of violent reaction as unemployed masses seek to blame both people in power as well as the broader social structure for their plight. Perhaps, the impact of large-scale systems on society has already eroded essential qualities of humanness. Humans, when they feel “socially useless,” are dehumanized. (At the same time, machines (at any scale) seem incapable of emotion or empathy.) Has the cost of technological progress been too high to pay? These issues are addressed in this paper. (shrink)

What does it mean to consider the world of AI through a Christian lens? Rapid developments in AI continue to reshape society, raising new ethical questions and challenging our understanding of the human person. Encountering Artificial Intelligence draws on Pope Francis’ discussion of a culture of encounter and broader themes in Catholic social thought in order to examine how current AI applications affect human relationships in various social spheres and offers concrete recommendations for better implementation. The document also (...) explores questions regarding personhood, consciousness, and the kinds of relationships humans might have with even the most advanced AI. Through these discussions, this book investigates the theoretical and practical challenges to interpersonal encounter raised by the age of AI. (AI Research Group for the Centre for Digital Culture of the Dicastery of Culture and Education of the Holy See). (shrink)

Sequential transformative design of research :224–235, 2015; Groleau et al. in J Mental Health 16:731–741, 2007; Robson and McCartan in Real world research: a resource for users of social research methods in applied settings, Wiley, Chichester, 2016) allows testing a group of theoretical assumptions about the connections of artificial intelligence with culture and education. In the course of research, semiotics ensures the description of self-organizing systems of cultural signs and symbols in terms of artificial intelligence (...) as a special set of algorithms. This approach helps to consider the arguments proposed by Searle :417–457, 1980) against ‘strong’ artificial intelligence. Searle :417–457, 1980) believes that artificial or machine intelligence cannot fully emulate the processes of the human mind. Machine intelligence shows own inevitable weakness. This is non-autonomous tool for computations and data operating. In fact, this tool cannot provide insight into real cognitive conditions. After Lotman and Uspensky, authors expand the meaning of artificial intelligence. The authors identify a cultural type of ‘strong’ artificial intelligence or ‘self-increase of Logos’ in terms by Lotman and Uspensky. The interpretation of human intelligence as imitation of machine intelligence makes possible such immersion of artificial intelligence in culture. The authors reveal a case of self-organizing autonomous generation, encoding, decoding, reception, storage, and transmission of social information in the field of physical training. From the empirical studies it is clear that the organization of collective activities without external control ensures the development of positive emotions and social orientations. Interest in autonomous behavior provides the formation of educational and cognitive motives. As a special set of algorithms, these motives are the most promising and favorable for personal development. (shrink)

This work intends to solve the problem that the traditional education system cannot reasonably adjust the educational integration of children with the arrival of labor force in a short time, and support the education of migrant children in the education policy to integrate them into the local educational environment as soon as possible. Firstly, this work defines the surplus labor force and MC. Secondly, the principles of Artificial Intelligence and Deep Learning are introduced. Thirdly, it (...) analyzes the education of MC and relevant policies, and the data of the education effect of MC are collected and the evaluation effect model is built. Finally, the evaluation model of MC’s education effect is applied to test the effect of EP. The results show that using AI technology combined with DL technology to model the education effect of MC can establish an effective and accurate evaluation model of the education effect of MC, effectively evaluate the impact of local education policies on the education of MC, and give an effective effect analysis of relevant education policies in each period. The result of Adaptive Resonance Theory –Back Propagation algorithm is 65 ∼ 96%, which is much higher than the efficiency of traditional algorithms. This shows that the education integration evaluation model of MC based on AI technology and DL technology can effectively and accurately evaluate the integration effect of MC on the local education system, and then provide reference for local and even national adjustment of education policies. The results provide a new idea for the application of new technology in EP. (shrink)

Communication programs seek to cultivate students who become professionals not only with expertise in their chosen field, but also ethical awareness. The current study investigates how exposure to ethics instruction and internship experiences may influence communication students’ ethical perceptions, including ideological orientations on idealism and relativism, as well as awareness of contemporary ethical issues related to social media and artificial intelligence (AI). The effects were also assessed on students’ support for general uses of AI for communication practices and (...) adoption of generative AI, specifically ChatGPT. The survey results based on a student sample in Taiwan show that internship experience is more significant than ethics instruction on swaying ethical perceptions and behavioral inclinations of adopting AI applications. Adding to the limited body of knowledge on the effect of ethics education and internship programs, the findings also offer insights for how communication education can address emerging ethical challenges brought by new technology. (shrink)

The vision of integrating artificial intelligence in education is part of an ongoing push for harnessing digital solutions to improve teaching and learning. Drawing from Jasanoff (Future imperfect: Science, technology, and the imaginations of modernity. In S. Jasanoff, & S. H. Kim (Eds.), Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power (pp. 1–33). The University of Chicago Press, 2015. 10.7208/9780226276663) and Hasse (Socratic ignorance in processes of learning with technology. In H. Bound, A. Edwards, & (...) A. Chia (Eds.), Workplace learning for changing social and economic circumstances (pp. 76–90). Routledge, 2023), this paper deliberates on how sociotechnical imaginaries are interrelated to the implications of new technologies, such as AI, in education. Complicating Hasses’s (Socratic ignorance in processes of learning with technology. In H. Bound, A. Edwards, & A. Chia (Eds.), Workplace learning for changing social and economic circumstances (pp. 76–90). Routledge, 2023) call for the development of Socratic ignorance to consider our predispositions about new technologies and open new prospects of thought, this paper revisits postphenomenology (Ihde, Technology and the lifeworld: From garden to earth. Indiana University Press, 1990; Ihde, Postphenomenology: Essays in the postmodern context. Northwestern University Press, 1993; Ihde, Postphenomenology and technoscience. The Peking University lectures. State University of New York Press, 2009) and Feenberg’s (Critical theory of technology, Oxford University Press, 1991; Between reason and experience, MIT Press, 2010; Techne: Res Philos Technol 24:27–40, 2020) critical constructivist theories. While embracing the notion of Socratic ignorance, this paper stresses the importance of developing a nuanced understanding of technology that realizes its lack of neutrality and supports the creation of a deeper understanding of how knowledge is produced, deployed, and interpreted in the digital age. Thus, this paper argues that an amalgam of Hasse’s call for advancing Socratic ignorance combined with postphenomenology and critical constructivism can support students in developing a critical understanding of technology and opening new landscapes of imaginaries. (shrink)

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use (...) artificial intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

The rapid development of programs based on the principles of machine learning (ML) and artificial intelligence (AI) signals significant changes in the components of education, namely in the provider, the tool of transmission, and the recipient of knowledge. Historical data analysis regarding the key functions of education serves as the basis for identifying fundamental innovations introduced through AI and ML. The impact of writing, printing, and the Internet has significantly altered the tool for knowledge transmission, influencing (...) the volume of information and the number of knowledge recipients. The implementation of AI and ML transforms not only the tool but also the provider of knowledge itself, which can become impersonal thanks to the corresponding computer programs. With the historically justified increase in the volume of knowledge possessed by humanity, there is a transformation observed in education systems. This is especially true for democratic societies, where the emphasis is increasingly shifting from providing a large amount of knowledge to developing critical thinking. It has been researched that programs based on AI and ML, applying linguistic models, are capable of effectively systematizing knowledge. This lays the foundation for personalizing the entire education process for a specific knowledge recipient, without burdening the provider. However, there have been cases when such imitation misleads scientists, who perceive it as attempts at communication between programs that have an equivalence to the human level. The conclusions drawn indicate a significant transformation of the education system caused by AI and ML-based programs. However, intelligent programs are unable to evolve into independent knowledge recipients due to their inability to consciously attribute meaning to information, transforming it into knowledge. (shrink)

Abstract:A society that uses drills and conditioning to train its machine learning models risks creating an alienated situation between human and machine in social life, as these teaching methods generate a lack of responsibility for the actions produced by such machines. Both John Dewey and Gilbert Simondon present conceptions and ideas that shed a different light on such alienated human–machine relationships in machine learning: that is, a critique of mere drilling and training as an educational method; the mode of existence (...) of technical objects; and the importance of experience and practicality, for example, learning by doing. After giving an introduction to Dewey's and Simondon's conceptions, the analysis of case studies will show, among other things, that machine learning models need constant care by engineers and programmers. This allows us to highlight Simondon's and Dewey's critique of ancient philosophy. Whereas the latter separates thought and practice, labor and leisure, Simondon and Dewey foreground activities that are capable of bringing both together: Dewey's aesthetic experience and Simondon's technical activity. (shrink)

Abstract:Artificial intelligence is profoundly transforming the world in various spheres and already finding its way into educational institutions. This essay aims to examine whether the Deweyan ideal of education can be achieved through such digital means. By analyzing how both the aims and means of education, as defined by Dewey, can be understood in the context of learning with artificial intelligence, the inherent differences of both educational approaches are brought out. It becomes apparent that (...) important concepts that characterize successful education for Dewey, such as intrinsic inquiry, experience-based schooling, and thinking as the method for learning, do not go hand in hand with intelligent teaching systems. (shrink)

_Purpose._ The study aims to understand artificial intelligence as a socio-cultural phenomenon and its impact on education, where the spiritual sphere of humanity, moral norms, values, and human cognitive abilities are preserved, transferred as well as reproduced. A new discourse on the interaction of artificial and authentic human intelligence becomes inevitable, which has led to a situation of uncertainty. Changes in the socio-cultural environment under the influence of artificial intelligence increase potential threats to (...) the educational space, which stimulates to find the ways to eliminate them. _Theoretical basis._ Various approaches of classical and postmodern philosophical heritage were taken as a theoretical basis for the research. _The originality_ of the study is in the interpretation of artificial intelligence as a modern form of alienation of essential human characteristics in the socio-cultural context of information technology. The expansion of artificial intelligence raises awareness of the existential threat to the basic socio-cultural, moral and ethical principles of humanism. It is proved that various forms of alienation in the current existing socio-cultural space are typical of our reality, which changes the system of values, moral principles, and social organization of the community. _Conclusions._ In conclusion, it is proved that AI is a natural stage of scientific and technological progress, which reflects its secondary, derivative nature from human (authentic) intelligence. Human intelligence will always have advantages over AI due to its ability to create, communicate socially and culturally, and be emotional. The dilemma of the counterbalance between human and artificial intelligence is perceived mainly at the emotional level of people. The millennial understanding of the primacy of the creator over his creation can traditionally overcome this contradiction. The universality of human thinking is an undeniable advantage of human intelligence and a guarantee of its, i.e. our, priority. (shrink)

Family health education is a must for every family, so that children can be taught how to protect their own health. However, in this era of artificial intelligence, many technical operations based on artificial intelligence are born, so the purpose of this study is to apply artificial intelligence technology to family health education. This paper proposes a fusion of artificial intelligence and IoT technologies. Based on the characteristics of artificial (...) intelligence technology, it combines ZigBee technology and RFID technology in the Internet of Things technology to design an artificial intelligence-based service system. Then it designs the theme of family health education by conducting a questionnaire on students’ family education and analyzing the results of the questionnaire. And it designs database and performance analysis experiments to improve the artificial intelligence-based family health education public service system designed in this paper. Finally, a comparative experiment between the family health education public service system based on artificial intelligence and the traditional health education method will be carried out. The experimental results show that the family health education public service system based on artificial intelligence has improved by 21.74% compared with the traditional family health education method; compared with the traditional family health education method, the health education effect of the family health education public service system based on artificial intelligence has increased by 13.89%. (shrink)

The text examines how the integration of technology and artificial intelligence into school education fundamentally alters classical notions of the role and functions of education held by representatives of various scientific disciplines. The literature review is structured around the following research questions: 1) How do technology (including artificial intelligence) reshape the sociologist Emile Durkheim's thesis on the authority of the teacher and their role in the socialization of students?; 2) How does the presence of (...) "superintelligent" technology relate to psychologist Abraham Maslow's theory of motivation and self-actualization?; and 3) How do technology weaken the role of school education in addressing societal inequalities – an idea, advocated by the philosopher John Dewey and his daughter and educator Evelyn Dewey? The report aims to serve as a starting point for future interdisciplinary empirical research in school education, with the goal of finding comprehensive and effective solutions for how technology and artificial intelligence can positively impact school education. (shrink)

Recent advancements in artificial intelligence make its use in education more likely. In fact, existing learning systems already utilize it for supporting students’ learning or teachers’ judgments. In this perspective article, we want to elaborate on the role of humans in making decisions in the design and implementation process of artificial intelligence in education. Therefore, we propose that an artificial intelligence-supported system in education can be considered a closed-loop system, which includes (...) the steps of data recording, pattern detection, and adaptivity. Besides the design process, we also consider the crucial role of the users in terms of decisions in educational contexts: While some implementations of artificial intelligence might make decisions on their own, we specifically highlight the high potential of striving for hybrid solutions in which different users, namely learners or teachers, are provided with information from artificial intelligence transparently for their own decisions. In light of the non-perfect accuracy of decisions of both artificial intelligence-based systems and users, we argue for balancing the process of human- and AI-driven decisions and mutual monitoring of these decisions. Accordingly, the decision-making process can be improved by taking both sides into account. Further, we emphasize the importance of contextualizing decisions. Potential erroneous decisions by either machines or humans can have very different consequences. In conclusion, humans have a crucial role at many stages in the process of designing and using artificial intelligence for education. (shrink)

This hands-on guide offers clear explanations of fuzzy logic along with practical uses and detailed examples. Written by an award-winning engineer and experienced author, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and skills in students and professionals alike. Inside, you will discover how to apply fuzzy logic and migrate to a new man-machine relationship in the context of pervasive digitization and big data across emerging technologies. The book lays out (...) real-world applications in intelligent energy systems with demand response, smart homes, electrification of transportation, supply chain efficiencies, smart cities, e-commerce, education, healthcare, and decarbonization. (shrink)

This groundbreaking proceedings volume explores the integration of Artificial Intelligence (AI) across key domains—healthcare, finance, education, robotics, industrial and other engineering applications —unveiling its transformative potential and practical implications. With a multidisciplinary lens, it transcends technical aspects, fostering a comprehensive understanding while bridging theory and practice. Approaching the subject matter with depth, the book combines theoretical foundations with real-world case studies, empowering researchers, professionals, and enthusiasts with the knowledge and tools to effectively harness AI. Encompassing diverse AI (...) topics—machine learning, natural language processing, computer vision, data analytics and supervisory control — the volume showcases state-of-the-art techniques propelling AI advancements. Structured into four parts: Part 1: Artificial Intelligence (AI), explores evolving deep neural networks, reinforcement learning, and explainable AI, providing a deep dive into the technical foundations of AI advancements. Part 2: Robotics and Control Systems, delves into the integration of AI in robotics and automatic control, addressing supervisory control, automated robotic movement coordination, anomaly detection, dynamic programming, and fault tolerance, offering insights into the evolving landscape of intelligent automation. Part 3: AI and Society, examines the societal impact of AI through chapters on ethical considerations, economic growth, environmental engagements, and hazard management, providing a holistic perspective on AI's role in shaping society. Part 4: PhD Symposium, presents the future of AI through cutting-edge research, covering legal and ethical dimensions, privacy considerations, and computationally efficient solutions, offering a glimpse into the next generation of AI advancements. Catering to a diverse audience—from industry leaders to students—the volume consolidates the expertise of renowned professionals, serving as a comprehensive resource for navigating the ever-evolving AI landscape. An essential reference for those staying at the forefront of AI developments. (shrink)

Our synthetic review of the relevant and related literatures on the ethics and effects of using AI in education reveals five qualitatively distinct and interrelated divides associated with access, representation, algorithms, interpretations, and citizenship. We open our analysis by probing the ethical effects of algorithms and how teams of humans can plan for and mitigate bias when using AI tools and techniques to model and inform instructional decisions and predict learning outcomes. We then analyze the upstream divides that feed (...) into and fuel the algorithmic divide, first investigating access and then representation. After that, we analyze the divides that are downstream of the algorithmic divide associated with interpretation and citizenship. At present, lacking ongoing reflection and action by learners, educators, educational leaders, designers, scholars, and policymakers, the five divides collectively create a vicious cycle and perpetuate structural biases in teaching and learning. However, increasing human responsibility and control over these divides can create a virtuous cycle that improves diversity, equity, and inclusion in education. We conclude the article by looking forward and discussing ways to increase educational opportunity and effectiveness for all by mitigating bias through a cycle of progressive improvement. (shrink)

Our social relations are changing, we are now not just talking to each other, but we are now also talking to artificial intelligence (AI) assistants. We claim AI assistants present a new form of digital connectivity risk and a key aspect of this risk phenomenon is related to user risk awareness (or lack of) regarding AI assistant functionality. AI assistants present a significant societal risk phenomenon amplified by the global scale of the products and the increasing use in (...) healthcare, education, business, and service industry. However, there appears to be little research concerning the need to not only understand the changing risks of AI assistant technologies but also how to frame and communicate the risks to users. How can users assess the risks without fully understanding the complexity of the technology? This is a challenging and unwelcome scenario. AI assistant technologies consist of a complex ecosystem and demand explicit and precise communication in terms of communicating and contextualising the new digital risk phenomenon. The paper then argues for the need to examine how to best to explain and support both domestic and commercial user risk awareness regarding AI assistants. To this end, we propose the method of creating a risk narrative which is focused on temporal points of changing societal connectivity and contextualised in terms of risk. We claim the connectivity risk narrative provides an effective medium in capturing, communicating, and contextualising the risks of AI assistants in a medium that can support explainability as a risk mitigation mechanism. (shrink)

This paper studies the relationship of Artificial Intelligence to the study of language and the representation of the underlying knowledge which supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession of a few general and uniform principles. The paper also provides a unifying thread to a variety of recent approaches to natural language comprehension. We (...) conclude with a brief discussion of how Artificial Intelligence may have a radical impact on education if the principles which it utilizes to explore the representation and use of knowledge are made available to the student to use in his own learning experiences. (shrink)

The evolution in the quality of teaching for preschool education is worth studying. In this article, we solved the qualitative problems in the comprehensive quality evaluation by suggesting a method of quantitative combination and establishing a set of indicators suitable for the comprehensive quality evaluation of students in the kindergarten. According to the experience summed up by previous scholars, the weight of each index is obtained by an analytic hierarchy process. This study analyzed the defects and causes of fuzzy (...) comprehensive evaluation and the neural network model in the construction of early childhood and preschool education's comprehensive quality evaluation model and propose a Feedforward Neural Network model. FNN combined with neural network and fuzzy logic characteristics introduces fuzzy concepts and fuzzy inference rules into neural networks of neurons, the connection power, and network learning. It improves the learning ability of NN and fuzzy evaluation of the power of expression and effectively exerts the advantages of fuzzy logic and neural network to make up for their shortcomings. However, the convergence speed is very slow. To solve this problem, the similarity measure was used to improve the number of hidden layer nodes of the network. The effectiveness and feasibility of the FNN improved hidden layer nodes are verified by an example so as to realize the automation of comprehensive quality evaluation. (shrink)

Intolerance, abuse, calling of names because of differences of opinion about religion or politics or business, as well as because of differences of race, color, wealth or degree of culture are treason to the democratic way of life. Merely legal guarantees of the civil liberties of free belief, free expression, free assembly are of little avail if the give and take of ideas, facts, experiences, is choked by mutual suspicion, by abuse, by fear and hatred.Without some kind of oversight, the (...) golem, not God, might emerge from machines … it is naïve to believe that government is competent, let alone in a position to control the development and deployment of robots, self-generating algorithms, and artificial intelligence.... (shrink)

With the rapid development of big data, artificial intelligence teaching systems have gradually been developed extensively. The powerful artificial intelligence teaching systems have become a tool for teachers and students to learn independently in various universities. The characteristic of artificial intelligence teaching system is to get rid of the constraints of traditional teaching time and space and build a brand-new learning environment, which is the mainstream trend of future learning. As the carrier of students’ (...) autonomous learning, the artificial intelligence teaching system provides a wealth of learning resources and learning tools on the one hand, and on the other hand, it gradually accumulates more and more learning behaviors, learning status, and other large amounts of data, which is an in-depth study of online learning and provides valuable and generative dynamic resources. Based on relevant researches on domestic and foreign related learning analysis and common big data analysis methods, combined with actual learning evaluation goals, this paper proposes an artificial intelligence teaching system using big data analysis methods and a modeling process framework for online learning evaluation and uses student data to carry out predictive evaluation modeling to evaluate student learning outcomes. The evaluation results can enable teachers to predict whether students can successfully complete the course of learning after a period of teaching. Through the final evaluation, students’ learning problems can be discovered in time based on the evaluation results, and targeted interventions can be made for students who are at risk. The scientific and objective learning evaluation obtained in this study through data analysis can not only provide teachers with relevant information and provide personalized guidance to students, but also improve the adaptive and personalized service functions of the learning platform of the artificial intelligence teaching system, greatly reducing teachers teaching burden. Artificial intelligence teaching evaluation can help educators understand the problems in teaching, adjust teaching strategies in time, and improve teaching results. (shrink)

Artificial intelligence (AI) national strategies provide countries with a framework for the development and implementation of AI technologies. Sixty countries worldwide published their AI national strategies. The majority of these countries with more than 70% are developed countries. The approach of AI national strategies differentiates between developed and developing countries in several aspects including scientific research, education, talent development, and ethics. This paper examined AI readiness assessment in a developing country (Palestine) to help develop and identify the (...) main pillars of the AI national strategy. AI readiness assessment was applied across education, entrepreneurship, government, and research and development sectors in Palestine (case of a developing country). In addition, it examined the legal framework and whether it is coping with trending technologies. The results revealed that Palestinians have low awareness of AI. Moreover, AI is barely used across several sectors and the legal framework is not coping with trending technologies. The results helped develop and identify the following five main pillars that Palestine’s AI national strategy should focus on: AI for Government, AI for Development, AI for Capacity Building in the private, public and technical and governmental sectors, AI and Legal Framework, and international Activities. (shrink)

The experience of organizing the educational process during the quarantine caused by the COVID-19 pandemic is considered. Using of interactive technologies that allow organizing instant audio communication with a remote audience, as well as intelligent tools based on artificial intelligence that can help educational institutions to work more efficiently. Examples of sufficient use of artificial intelligence in distance learning are given. Particular attention is paid to the development of intelligent chatbots intended for use in communications with (...) students of online courses of educational web portals. The use of technologies of ontology formation based on automatic extraction of concepts from external sources is offered, what can lead to greater acceleration of construction of the intellectual component of chatbots. Artificial intelligence tools can become an essential part of distance learning during this global COVID-19 pandemic. While educational institutions are closed to quarantine and many of them transitioned to distance learning lecturers and schoolteachers, as well as students and schoolchildren faced with the necessity to study in this new reality. The impact of these changes depends on people's ability to learn and on the role that the education system will play in meeting the demand for quality and affordable training. The experience of organizing the educational process at the University of Education Management of the National Academy of Pedagogical Sciences of Ukraine in the quarantine caused by the COVID-19 pandemic showed that higher and postgraduate institutions were mostly ready to move to distance learning. However, most distance learning systems, on whatever platform they are organized, need to be supplemented: the ability to broadcast video, providing fast transmission of various types of information, receiving instant feedback when voting, polls and more. The structure of each section of the training course for the online learning system should fully cover the training material and meet all the objectives of the course. Appropriate language should be used, and wording, syntax, and presentation of tasks should be considered. One of the areas of application of artificial intelligence technologies in online learning is the use of chatbots which are characterrized by the following properties. It is advisable to use computer ontologies to ensure the intellectualization of chatbots. In this case, the metadata must be understandable to both humans and software and meet the requirements of modern standards in the field of information technology. The extraction of concepts from external data sources was carried out to build the ontology. (shrink)

PurposeThis paper aims to demonstrate the relevance of worldviews of the global south to debates of artificial intelligence, enhancing the human rights debate on artificial intelligence (AI) and critically reviewing the paper of UNESCO Commission on the Ethics of Scientific Knowledge and Technology (COMEST) that preceded the drafting of the UNESCO guidelines on AI. Different value systems may lead to different choices in programming and application of AI. Programming languages may acerbate existing biases as a people’s (...) worldview is captured in its language. What are the implications for AI when seen from a collective ontology? Ubuntu (I am a person through other persons) starts from collective morals rather than individual ethics.Design/methodology/approachLiterature overview on the African philosophy of Ubuntu as applied to artificial intelligence. Application of it to the United Nations Educational, Scientific and Cultural Organisation (UNESCO) debates on establishing guidelines to the ethics of artificial intelligence.FindingsMetaphysically, Ubuntu and its conception of social personhood (attained during one’s life) largely rejects transhumanism. When confronted with economic choices, Ubuntu favors sharing above competition and thus an anticapitalist logic of equitable distribution of AI benefits, humaneness and nonexploitation. When confronted with issues of privacy, Ubuntu emphasizes transparency to group members, rather than individual privacy, yet it calls for stronger (group privacy) protection. In democratic terms, it promotes consensus decision-making over representative democracy. Certain applications of AI may be more controversial in Africa than in other parts of the world, like care for the elderly, that deserve the utmost respect and attention, and which builds moral personhood. At the same time, AI may be helpful, as care from the home and community is encouraged from an Ubuntu perspective. The report on AI and ethics of the UNESCO World COMEST formulated principles as input, which are analyzed from the African ontological point of view. COMEST departs from “universal” concepts of individual human rights, sustainability and good governance which are not necessarily fully compatible with relatedness, including future and past generations. Next to rules based approaches, which may hamper diversity, bottom-up approaches are needed with intercultural deep learning algorithms.Research limitations/implicationsThere is very few existing literature on AI and Ubuntu. Therefore, this paper is of an explorative nature.Practical implicationsThe ethics of Ubuntu offers unique vantage points in looking at the organization of society and economics today, which are also relevant for development of AI, especially in its tenet of relatedness rather than individuality (and practical use of AI for individuals), taking responsibility for society as a whole (such as analyzing the benefit of AI for all strata of society), and embodying true inclusiveness. Whether looking at top-down guidelines for the development and implementation of AI or the bottom-up ethical learning process of AI (deep learning), ethics of the Global South can have an important role to play to combat global individualist tendencies and inequity, likely reinforced by AI. This warrants far more research.Social implicationsApplications of AI in Africa are not contextualized, do not address the most pressing needs of the African continent, lead to cybersecurity issues and also do not incorporate African ethics. UNESCO’s work in this regard is important but expert inputs are largely centered around Western “universal” principles and Organisation for Economic Cooperation and Development and EU precedence. African ethics have, so far, a small role to play in global ethics and philosophy and therefore risk to be overlooked in the discussion on AI and ethics. This is why the consultation process of UNESCO on ethics of AI was of paramount importance. However, it does not automatically lead to consultation of African philosophers or sages, as many are educated in Western (ized) education systems. See further details under practical implications.Originality/valueThis is a new area of research in which little work has been done so far. This paper offers the opportunity to widen the debate on AI and ethics beyond the conventional discourse, involving multiple worldviews, of which Ubuntu is just one. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article discusses the (...) applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us (...) in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you. (shrink)

This project has been supported by the Australian Government through the Australian Research Council (project number CS170100008); the Department of Industry, Innovation and Science; and the Department of Prime Minister and Cabinet. ACOLA collaborates with the Australian Academy of Health and Medical Sciences and the New Zealand Royal Society Te Apārangi to deliver the interdisciplinary Horizon Scanning reports to government. The aims of the project which produced this report are: 1. Examine the transformative role that artificial intelligence may (...) play in different sectors of the economy, including the opportunities, risks and challenges that advancement presents. 2. Examine the ethical, legal and social considerations and frameworks required to enable and support broad development and uptake of artificial intelligence. 3. Assess the future education, skills and infrastructure requirements to manage workforce transition and support thriving and internationally competitive artificial intelligence industries. (shrink)

This study is based on the background of how artificial intelligence technology is applied to the field of creativity and design education to improve the design vision, teaching methods, and actual design productivity of practitioners. The purpose of the research is to compare traditional design education and new design education methods combined with AI technology. Taking the Technological Pedagogical Content Knowledge technology integration model as the starting point, a comprehensive evaluation is selected for different types (...) of research to explore the animation design professional courses in design education, the content of students’ perception preferences, and the evaluation of ease of learning so as to conduct research and analyze AI technology. Design new education strategies and practice methods under the background. In the research, a comparative experimental study was conducted on 40 first-year students majoring in animation design. The results show that through online design studio project practice, with personalized project learning guidance, the learning needs of students to show a better trend, and customized learning and project practice content can enhance the learning experience and performance of students. In the future, we can further expand the scope of analysis, include more case studies, and conduct more comprehensive research, including how to deal with the expansion of the platform for students’ learning of design in situations similar to coronavirus disease 2019 that profoundly affects our lives, and how the project is applied in practice. (shrink)

This study provided a content analysis of studies aiming to disclose how artificial intelligence has been applied to the education sector and explore the potential research trends and challenges of AI in education. A total of 100 papers including 63 empirical papers and 37 analytic papers were selected from the education and educational research category of Social Sciences Citation Index database from 2010 to 2020. The content analysis showed that the research questions could be classified (...) into development layer, application layer, and integration layer. Moreover, four research trends, including Internet of Things, swarm intelligence, deep learning, and neuroscience, as well as an assessment of AI in education, were suggested for further investigation. However, we also proposed the challenges in education may be caused by AI with regard to inappropriate use of AI techniques, changing roles of teachers and students, as well as social and ethical issues. The results provide insights into an overview of the AI used for education domain, which helps to strengthen the theoretical foundation of AI in education and provides a promising channel for educators and AI engineers to carry out further collaborative research. (shrink)

This study aims to explore new educational strategies suitable for the mental health education of college students. Big data and artificial intelligence are combined to evaluate the mental health education of college students in sports majors. First, the research status on the mental health education of college students is introduced. The internet of things on mental health education, a structure based on big data and convolutional neural network, is constructed. Next, the survey design and (...) questionnaire survey are carried out. Finally, the questionnaire data are analyzed and compared with the mental health status under traditional education. The results show that the CNN model has good accuracy and ability to distinguish symptoms, so it can be applied to the existing psychological work in colleges. In the symptom comparison survey, under the traditional education and big data network, the number of college students with mild mental health problems is found to be 158 and 170, respectively. It indicates that the number of college students with moderate mental health problems decreases significantly. In the comparative investigation of the severity of mental problems, the number of students with normal mental health, subhealth, and serious mental health problems under the background of traditional mental health education is 125, 56, and 5, respectively. The mental health status of college students under the influence of big data networks on mental health education is better than that of traditional mental health education. There are 140 students with normal mental health, a year-on-year increase of 16.7%. In the comparative survey of specific mental disorders, students with obsessive-compulsive symptoms under traditional mental health education account for 22.0% of the total sample, having the largest proportion. In the subhealth psychological group under the big data network on mental health education, the number of hostile students decreases by 7, which is the psychological factor with the most obvious improvement. Hence, the proposed path of mental health education is feasible. (shrink)

The article describes the possibilities of using and modifying existing machine learning technologies in the field of natural language processing for the purpose of designing a system for automatically generating control and test tasks (CTT). The reason for such studies was the limitations in generating theminimumrequired amount ofCTtomaintain student engagement in game-based learning formats, such as quizzes, and others. These limitations are associated with the lack of time resources among training professionals for manual generation of tests. The article discusses the (...) applied research of the Large Language Model (LLM) and Generative pre-trained transformer (GPT) technologies for the development of a system for automatic generation of tests for the purpose of its implementation in the BoxBattle gamified learning platform. The result of such applied research can be a system for automatic generation of tests, which will reduce the time for developing tests. As a result, this will allow teachers to free up time to implement a personalized approach to teaching and develop students’soft skills. (shrink)

As the use of artificial intelligence (AI) technologies, particularly generative AI (Gen AI), becomes increasingly prevalent in nursing education, it is paramount to address the ethical implications of their implementation. This article explores the realm of cyberethics (a field of applied ethics that focuses on the ethical, legal, and social implications of cybertechnology), highlighting the ethical principles of autonomy, nonmaleficence, beneficence, justice, and explicability as a roadmap for facilitating AI integration into nursing education. Research findings suggest (...) that ethical dilemmas that challenge these five principles can emerge within the context of nursing education; however, adherence to these very principles, which is essential to improving patient care, can offer solutions to these dilemmas. To ensure the ethical and responsible use of Gen AI in nursing education, these principles must be woven into the fabric of curricula, and appropriate guidelines must be developed. Nurse educators have a pivotal role in strategizing comprehensive approaches for ethical AI integration, establishing clear guidelines, and instilling critical thinking among students. Fostering lifelong learning and adaptability is key to ensuring that future nurses can successfully navigate the constantly evolving landscape of health care technology. Future research should investigate the long-term impacts of AI utilization on learning outcomes and ethical decision-making. (shrink)