Artificial Intelligence Concepts Research Articles

Assessing the disconnect between student interest and education in artificial intelligence in medicine in Saudi Arabia

BackgroundAlthough artificial intelligence (AI) has gained increasing attention for its potential future impact on clinical practice, medical education has struggled to stay ahead of the developing technology. The question of whether medical education is fully preparing trainees to adapt to potential changes from AI technology in clinical practice remains unanswered, and the influence of AI on medical students’ career preferences remains unclear. Understanding the gap between students’ interest in and knowledge of AI may help inform the medical curriculum structure.MethodsA total of 354 medical students were surveyed to investigate their knowledge of, exposure to, and interest in the role of AI in health care. Students were questioned about the anticipated impact of AI on medical specialties and their career preferences.ResultsMost students (65%) were interested in the role of AI in medicine, but only 23% had received formal education in AI based on reliable scientific resources. Despite their interest and willingness to learn, only 20.1% of students reported that their school offered resources enabling them to explore the use of AI in medicine. They relied mainly on informal information sources, including social media, and few students understood fundamental AI concepts or could cite clinically relevant AI research. Students who cited more scientific primary sources (rather than online media) exhibited significantly higher self-reported understanding of AI concepts in the context of medicine. Interestingly, students who had received more exposure to AI courses reported higher levels of skepticism regarding AI and were less eager to learn more about it. Radiology and pathology were perceived to be the fields most strongly affected by AI. Students reported that their overall choice of specialty was not impacted by AI.ConclusionFormal AI education seems inadequate despite students’ enthusiasm concerning the application of such technology in clinical practice. Medical curricula should evolve to promote structured, evidence-based AI literacy to enable students to understand the potential applications of AI in health care.

Integration of artificial intelligence in national science curricula

This study investigates the integration of artificial intelligence (AI) in national science curricula across 21 countries, including Australia, Cyprus, Estonia, France, Finland, Greece, Hong Kong, India, Iceland, Ireland, Nepal, New Zealand, Norway, Ontario (Canada), Poland, Singapore, South Africa, South Korea, Sweden, the United Kingdom, and the United States. By analyzing these curricula, the research identifies the presence of AI-related knowledge, skills, and attitudes, providing a comprehensive understanding of how AI is embedded in educational frameworks. The findings reveal a strong emphasis on practical AI skills, interdisciplinary knowledge, ethical considerations, and societal impacts, preparing students to thrive in an AI-driven future. This comprehensive approach highlights AI’s transformative potential in education. The study emphasizes AI’s role in fostering problem-solving skills and active learning, underscoring the need for practical AI applications and comprehensive teacher training in AI concepts. The analysis also identifies gaps in the explicit mention of “artificial intelligence” itself, suggesting a broader focus on related concepts. Notably, AI is not frequently mentioned explicitly in the curricula but is often approached under the umbrella of information and communication technology in relation to science. Recommendations for enhancing AI integration include comprehensive teacher training, continuous curriculum evaluation, and the inclusion of the ethical and societal implications of AI. This research provides valuable insights for educators and policymakers, highlighting the need for a well-rounded curriculum that prepares students for the future challenges and opportunities presented by AI technologies.

The Significance of Artificial Intelligence in Learning and Education Management in the Light of Philosophy of Education: A Critical Appraisal

The integration of Artificial Intelligence (AI) into the framework of education has spelt out a remarkable landmark in the history of educational revolution. Both in teaching-learning methodologies and management practice, AI is rapidly becoming a pivotal indispensability. Employing qualitative methods of conceptual frame, content analysis and literature review, this paper critically evaluates the significance of AI in learning and education management in the light of philosophy of education. The highlights of the paper include the concepts of AI, learning, education management, and philosophy of education. Philosophical perspectives and ethical considerations in implementing AI technology are also discussed. The capacity of AI to inform personalized learning, enhance intelligent learning, and facilitate data-driven decision making is critically examined. The paper, going forward, explores the transformational role of teachers amid the reality of the AI environmental permeation and centrality, with a focus on the need for teachers to be adequately equipped with requisite skills that promote critical thinking, creativity and innovation. In the process of the critical appraisal, it is discovered that AI has great potentials to engender harmonized and customized learning experiences. It is also discovered that it equally brings, in its wake, hordes of challenges and concerns with regard to the possibility of stripping the human face of education in terms of depersonalization, ethical concerns, danger of data privacy and algorithmic bias. On the basis of the findings, the paper recommends, among others, that stakeholders in education should adopt a balanced approach to the issue of AI in learning and education management. In this model of approach, AI is to be given an ancillary position as a source of information and knowledge in the process of education. In this way, AI will play a complementary role to the time-tested traditional values through which education strives to offer and achieve a comprehensive development of the learner. This will go a long way in addressing the challenges associated with AI, thereby harnessing its transformative potentials in learning and education management.

Artificial Intelligence and its Impact on Social Policy-Making

This study aims to analyze the role of artificial intelligence (AI) in shaping social policies, focusing on its impacts on poverty, unemployment, education, and healthcare. The research explores the concept, origins, types, and dimensions of AI, as well as the stages of social policymaking. It highlights how AI technologies contribute to building simulation models that support governmental decision-making and enhance civic engagement through interactive platforms that allow citizens to express their opinions and participate in policymaking. Additionally, AI facilitates monitoring and analyzing social trends, enabling governments to respond swiftly to social and economic changes and crises, such as pandemics and natural disasters. The study concludes that AI plays a crucial role in improving transparency, building trust in governments, and offering innovative solutions to social challenges.

Artificial Intelligence Revolution in Pharmaceutical Sciences: Advancements, Clinical Impacts, and Applications.

Artificial intelligence (AI) is a rapidly transforming drug discovery and development process, significantly impacting the pharmaceutical industry and enhancing human health. This review article examines the tremendous role of AI in analyzing complex biological data, optimizing research processes, and reducing costs of production. Implementation of AI in the pharmaceutical sector can store a vast dataset of manufacturing processes, identify potential disease targets, simulate physiological conditions, and predict drug interactions. The review article also discusses the AI concepts and their applications, particularly in developing solid dosage forms. Advanced algorithms optimize formulation processes, predict pharmacokinetics profiles, and assess drug toxicity profiles, facilitating a more efficient pathway from pilot study to market. Additionally, this review highlights the advancements in 3D printing technologies of dosage forms that have the ability to provide personalized treatment to different individuals. Furthermore, the article explores the opportunities and challenges of AI in healthcare, focusing on applications such as disease diagnosis, digital therapy, and epidemic forecasting. Prominent AI technologies like deep learning and neural networks are examined for their roles in predicting outbreaks of diseases like influenza and COVID-19. As the pharmaceutical landscape evolves, AI is poised to redefine traditional methods. This paves the way for more efficient healthcare solutions. By harnessing the interplay of technology and science, AI not only increases productivity; but it also promotes a new era of precision medicine tailored to the needs of each patient.

AI and the Cognitive Sense of Self

This article explores the development of a cognitive sense of self within artificial intelligence (AI), emphasizing the transformative potential of self-awareness in enhancing AI functionalities for sophisticated interactions and autonomous decision-making. Rooted in interdisciplinary approaches that incorporate insights from cognitive science and practical AI applications, the study investigates the mechanisms through which AI can achieve self-recognition, reflection, and continuity of identity—key attributes analogous to human consciousness. This research is pivotal for fields such as healthcare and robotics, where AI systems benefit from personalized interactions and adaptive responses to complex environments. The concept of a self-aware AI involves the ability for systems to recognize themselves as distinct entities within their operational contexts, which could significantly enhance their functionality and decision-making capabilities. Further, the study delves into the ethical dimensions introduced by the advent of self-aware AI, exploring the profound questions concerning the rights of AI entities and the responsibilities of their creators. The development of self-aware AI raises critical issues about the treatment and status of AI systems, prompting the need for comprehensive ethical frameworks to guide their development. Such frameworks are essential for ensuring that the advancement of self-aware AI aligns with societal values and promotes the well-being of all stakeholders involved.

Artificial Intelligence and its Perspectives in Dentistry: A Review

Artificial Intelligence (AI) is the ability of machines to perform various tasks with smart work that normally requires human intelligence. It is not a new concept as it was introduced back in the 1950s. However, it has not become the practical tool until two decades ago. Artificial intelligence (AI) has obtained large interest and has long past via a transition level from being a pure statistical tool to being one of the main drivers of modern dentistry. In dentistry, the employment of synthetic intelligence continues to be at its start. Many radiographs are used to decide illnesses with the aid of using displaying the whole shape of the enamel and a few dental troubles that cannot be visible at once with the aid of using the human eye. The concepts of AI, including convolutional neural networks and/or synthetic neural networks, have proven a selection of applications in dentistry, forecasting the viability of stem cells. The dental pulp, measuring operating lengths, pinpointing root fractures and periapical lesions and forecasting the achievement of retreatment procedures. AI has established accuracy and precision in detection, evaluation and prediction. Thus, this review narrates the history, classification and its applications in dentistry.

الذكاء الاصطناعي في مجال التعليم

This research paper was titled: (Artificial Intelligence in Education), and through it, the researchers sought to explore the main role that artificial intelligence represents as a modern and advanced technical achievement in the fields of education and learning at its various stages. The paper was divided into six sections, the first of which represents the methodological framework of the research, the second on the concept of artificial intelligence in education and its importance, the third included applications of artificial intelligence in education, the fourth shed light on the use of artificial intelligence in education and the challenges, controls, effects and ethical concerns that accompany it, the fifth was devoted to future trends in artificial intelligence in education in the Kingdom, and the sixth contained the results, recommendations and references. The researchers concluded with a number of results, the most prominent of which are: the importance of combining artificial intelligence and teachers to achieve the best educational results, the positive impact that artificial intelligence-supported tools achieve in improving the quality of education, and the role of artificial intelligence in reducing routine burdens on teachers and enabling them to focus on aspects of creative teaching.

Applications of Generative Artificial Intelligence in Medicine: Opportunities and Ethical Considerations

Generative Artificial Intelligence (AI) has emerged as a transformative tool in various domains, including medical sector. Generative AI models like ChatGPT offer unparalleled potential in diagnostics, prognostications, and research assistance. However, their integration necessitates careful scrutiny of risks, including privacy violations and the propagation of inaccuracies. Establishing clear guidelines for their use in academic medicine and research is imperative for the responsible use of these tools. This article explores the foundational concepts of generative AI, highlights its applications in medicine, research, and academia, and addresses ethical and practical concerns.

Superficial Fungal Infections and Artificial Intelligence: A Review on Current Advances and Opportunities: REVISION.

Superficial fungal infections are among the most common infections in world, they mainly affect skin, nails and scalp without further invasion. Superficial fungal diseases are conventionally diagnosed with direct microscopy, fungal culture or histopathology, treated with topical or systemic antifungal agents and prevented in immunocompetent patients by improving personal hygiene. However, conventional diagnostic tests can be time-consuming, also treatment can be insufficient or ineffective and prevention can prove to be demanding. Artificial Intelligence (AI) refers to a digital system having an intelligence akin to a human being. The concept of AI has existed since 1956, but hasn't been practicalised until recently. AI has revolutionised medical research in the recent years, promising to influence almost all specialties of medicine. An increasing number of articles have been published about the usage of AI in cutaneous mycoses. In this review, the key findings of articles about utilisation of AI in diagnosis, treatment and prevention of superficial fungal infections are summarised. Moreover, the need for more research and development is highlighted. Fifty-four studies were reviewed. Onychomycosis was the most researched superficial fungal infection. AI can be used diagnosing fungi in macroscopic and microscopic images and classify them to some extent. AI can be a tool and be used as a part of something bigger to diagnose superficial mycoses. AI can be used in all three steps of diagnosing, treating and preventing. AI can be a tool complementary to the clinician's skills and laboratory results.

Generative AI and Its Potential Impact on Humanity

ABSTRACTThis study explores the evolving circumstances of generative artificial intelligence (AI) and its implications for humanity. A central question guides this exploration: “What is humanity in a world with human‐like machines?” as proposed by Suleyman (2023). Multiple streams of literature have been integrated to employ a holistic approach. This includes an extensive literature review and analysis of recent developments, incorporating insights from various sources and experts in key domains such as AI, AI singularity, ethics, digital transformation, human‐machine collaboration, and societal implications. While rapid advancements in generative AI have captured widespread attention, with a particular emphasis on its positive potential, it is equally vital to address its potential negative impacts, including human displacement, lower wages, and increased power and income inequality (Farina, Yu, and Lavazza 2024). Despite varying scholarly perspectives on the concept of generative AI, there is a consensus that it significantly impacts humans and society and requires careful consideration. The National Institute of Standards and Technology (NIST) and the European Parliament highlight the global significance of addressing its challenges. From a practical perspective, these insights have enormous implications for governments, business leaders, scholars, and society.

Artificial intelligence technologies in the Russian educational context: educators views

Introduction. Intelligent technologies for processing and generating natural language, machine learning and deep learning have the potential to qualitatively change both teaching methods and techniques and the education management system. Meanwhile, there is a question of whether the teaching community is ready for the conscious and effective implementation of artificial intelligence (AI) in educational programs. The purpose of the study is to examine the degree of educators’ awareness about modern intelligent technologies, to understand their attitude towards AI and their proficiency in these technologies. Materials and Methods. Data collection was carried out by means of a survey. The questionnaire was completed by 132 respondents including university professors of humanities (13%), schools teachers (15%) and pre-school and kindergarten educators (72%). Based on the survey data, the researchers conducted a content analysis of responses to open-ended questions and a quantitative analysis of responses to closed- ended questions. In addition, the chi-squared test was employed to identify the relationship between the age category and the level of AI competence. Results. The study demonstrates that the majority of respondents do not have a clear understanding of the concept of artificial intelligence and do not have the competencies and experience sufficient to effectively implement AI in the educational process, which is especially typical for respondents over 40 years of age. Artificial intelligence is perceived as something interesting, promising and useful, although complex and requiring solutions to respond to negative cognitive and emotional impact on learners. Only 11% of respondents rate their level of competence as high, while the majority consider it average (56%), below average (19%) or low (14%). Statistical analysis shows a significant relationship between the age of respondents and the level of competence (χ 2 =8.852; the critical value of χ 2 at the significance level of p=0.05 is 7.815). The younger generation (20-40 years old) is more likely than the older generation (41-60 years old) to assess their level of AI competence as high. The study shows that the use of AI in teaching practice is unsystematic and often experimental in nature due to the lack of knowledge and practical skills, which might be explained by the novelty of the AI technologies as well as the scarcity of research-based and tested pedagogical models for their implementation. Practical Significance. The results of the study will have practical application in training and professional development programs for educators, as well as in improving digitalization of education. Further research should be aimed at creating and testing methods and techniques for integrating AI into educational programs of all levels and forms.

ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ И ОЦЕНКА ИЗМЕНЕНИЙ ОТ ЕГО ВНЕДРЕНИЯ В ЭКОНОМИКЕ

Artificial intelligence methods are becoming one of the most relevant topics in the scientific and business environment. The article examines the concept of artificial intelligence, the main stages of its development and the types of tasks it solves. The penetration of new technologies into various spheres of life around the world makes economists think about assessing its impact on GDP, how this impact is achieved, and whether there are only positive aspects in the implementation of new methods.

Do people prefer AI-generated patient educational materials over traditional ones?

This study aimed to assess people's preference between traditional and Artificial Intelligence (AI)-generated colon cancer staging Patient Education Materials (PEMs). We assessed preference among patients and companions being seen for a non-cancer diagnosis at the UT Health Austin Colon and Rectal Surgery Clinic. Participants were blinded to the study concept of AI and generation method of PEMs (Traditional: National Cancer Institute and the American Cancer Society; AI-generated: ChatGPT and Google Bard). Participants completed an anonymous demographic survey and ranked their PEM preference for randomized, de-identified materials. We hypothesized that there would be no difference in preference between the AI-generated and traditional PEMs. This study is IRB approved (STUDY00005203). 35 participants were recruited, ages 27-79 years (mean 46; SD 14 years) and 57 % female. 54 % were four-year college graduates. Among the participants, 51 % ranked the traditional PEMs as most preferred, while 49 % ranked the AI-generated PEMs as most preferred (p = NS). People do not have a dominant preference for AI-generated or traditional PEMs. Further investigation on the use of AI for PEM generation is warranted. AI may be capable of generating PEMs that incorporate the strengths of traditional PEMs while also reducing the required resources for PEM generation.

AI Literacy for Young Learners: Engaging Muhibbah School Students in the Future of Technology

Artificial intelligence (AI) is a set of technologies that allow computers to imitate human intelligence and perform complex tasks, such as (1) Understanding language (2) Analyzing data (3) Recognizing images (4) Writing (5) Making predictions. The presence of AI today cannot be avoided but must be wise in utilizing it in daily activities. This community service program is the first step in an effort to prepare the younger generation in Sarawak to be able to compete in the digital era. By collaborating with SK Mubibbah Sarawak, this service hopes to make a significant contribution to improving the quality of education in Indonesia and Malaysia in the border areas of the two countries through sharing Knowledge, especially the Padang State Polytechnic with I-Cats Malaysia and the University of Malaysia Sarawak (UNIMAS). The teaching method used in this activity is very interactive and fun. The learning process is carried out through interesting games and simulations, so that students can more easily understand the concept of AI without feeling burdened. Students are invited to actively participate and be directly involved in simple experiments that show how AI can be applied in everyday life. This program also shows the commitment of Padang State Polytechnic, Unimas and I-Cats Malaysia in expanding the role of higher education not only domestically but also internationally, especially in the field of technology which continues to develop rapidly

Protection of AI Created Works under IPR Regime, Its Impact and Challenges: An Analysis

Artificial Intelligence (AI) is one of the upcoming fields of computer science which deals with the development of intelligent tools and techniques for accomplishing different tasks that require effort and intelligence of a human being. It is considered as one of the biggest achievements, which has the potential to revolutionize diverse aspects of life. The concept of AI can be read together with Intellectual Property (IP) as it refers to the developments of the mind which include literary works, inventions, designs, trademarks etc which are governed under different laws. AI can create different types of IP assets and assist in its management including licensing of the invented creations, enforcement, analysis and so on. The issue that has been raised at multiple platforms is with regard to the use of AI and its impact on IP as there are high chances of exploitation of those assets along with other legal and ethical challenges. The ownership of the creations, patentability, protection of data and information, infringement of symbols or any other copyright issues etc have become issues of concern which require careful consideration and proper analysis. On one hand, AI is playing a huge role in creating advanced types of IP assets which is effective in developing diverse business models and on the other hand, it can be seen that it is creating issues concerning ownership, patentability, infringement etc. which is having an impact on the Intellectual Property Rights (IPR). This paper aims to analyse the challenges raised by AI with regard to the developments in the IP sector and infringement of IPR along with its legal and ethical implications. The research will focus on the impact of AI on IPR and the issues arising out of the interventions by AI tools in IP assets. The policy frameworks which are required to address such challenges and bring in effective alternatives will be discussed in the paper along with the recommendations to be provided to the policymakers, legal scholars and other professionals.

Deep Guard-IoT: A Systematic Review of AI-Based Anomaly Detection Frameworks for Next-Generation IoT Security (2020-2024)

The emergence of IoT devices has complicated the landscape of cybersecurity in ways that had never been experienced before, thereby, giving raise to the need for more developed methods that can assist in threat evaluation and deterrent. The work in the international scope analyses the particulars of the artificial intelligence-based anomaly detection in the IoT technology implementation including the perspectives of recent period between 2020 and 2024 of the various architectures’ effectiveness and their use in low-resource IoT environments. In this review, as well as in many other recent works carried out by other authors, it is observed that deep learning methods, such us Long Short-Term Memory (LSTM) networks and GRU-LSTM hybrid models, achieved the most accurate performance, ranging from 96% up to 99.9% correct detection. Our examination focuses on several aspects of IoT security, such as challenges at the device level, issues related to security at the network level, data security, and facets related to artificial intelligence concepts and architectures capable of addressing the challenges. The results of the study state that the AI techniques tend to be more efficient and have a high performance than the conventional methods before but have drawbacks for realistic application owing to lack of adequate resources, absence of standard practices and sophistication of new threats. The study also highlights the gaps that exist in addressing the current approaches and makes suggestions on what is to be done, such as the importance of developing

Intelligent Control Systems for Mechanical Engineering Technology Tasks

The article is devoted to solving the main tasks set in the work with the aim of analyzing and substantiating the implementation of intelligent control systems in technological processes of mechanical engineering, with an emphasis on increasing efficiency, accuracy, and reliability of production. The use of multi-agent systems and decentralized control systems, which significantly enhance the flexibility and adaptability of production, is analyzed. Special attention is paid to the role of physics-informed neural networks in fault diagnosis, which ensures increased reliability and reduced maintenance costs for equipment. The effectiveness of applying machine learning algorithms to optimize production processes, particularly in material processing and equipment maintenance, is evaluated. The impact of integrating intelligent control systems on production performance and quality, especially in the processes of milling and bonding large parts, is considered. Practical recommendations have been developed for the implementation of an adaptive intelligent production management system (AIPMS), which combines multi-agent systems, neural networks, digital twins, and innovative materials. The implementation of the artificial intelligence concept in production processes will contribute to the further development of mechanical engineering from a technological perspective, enabling enterprises to adopt innovations more rapidly, increase automation, and enhance the adaptability of technological processes, which in turn will lead to significant improvements in product quality and competitiveness. The use of such systems allows optimizing technological processes, reducing the number of defects, lowering energy consumption, and improving environmental efficiency

Structural and semantic features of English eponyms in the “artificial intelligence” terminology system

The paper is focused on the structural and semantic characteristics of eponyms in the sublanguage “Artificial Intelligence” in English. The study’s relevance is determined by the rapid advancement of artificial intelligence systems and information technology in almost all spheres of human activities, which in turn leads to the creation of new lexical units. This finding highlights the necessity of conducting both theoretical and applied studies in this area of lexicology.We have found that in the sublanguage “Artificial Intelligence”, the names and surnames of individuals who have made significant contributions to the formation and development of this field of knowledge are used as a productive basis for creating new terms. We have also succeeded in revealing that anthroponyms can both undergo certain morphological transformations during the deonymization process and be used in their initial form. The most productive word-formation models are the use of an eponym in the possessive case and the formation of an eponym-based adjective. In contrast to anthroponyms, toponyms and names of literary and mythological characters shift into the category of common nouns without changing their form, but acquiring a new meaning. The study’s findings highlight the significance of eponyms as fundamental components of the language of science and technology and their impact on the way artificial intelligence concepts are understood.

Artificial Intelligence Technologies and Their Significance in Enhancing the Quality of Adaptive E-Learning

The continuous advancement of artificial intelligence (AI) technology is driving a profound transformation in educational systems, which are crucial in shaping societal development and future trends. AI plays a pivotal role in advancing social progress by developing programs and devices that replicate human behaviors and cognitive functions, leading to a revolutionary change in learning methodologies and an enhancement in the interaction between learners and educational content. This research paper explores the role of AI in improving the quality of adaptive e-learning. It begins by defining fundamental concepts of AI and its educational technologies, then clarifies the concept of adaptive e-learning, and reviews the latest AI applications in this field. Additionally, the paper demonstrates how AI can be utilized to enhance the educational environment and improve educational quality, while also assessing notable international experiences in this context. The study’s key findings indicate that AI enhances educational quality by providing personalized learning experiences, effectively analyzing learner data, and offering flexible virtual learning environments and advanced digital tools to enhance interaction