The Utilization of Artificial Intelligence in the Service of the Noble Qurʾān and Its Sciences

AI Applications in Health Sector: Use of Artificial Intelligence in Covid-19 Crisis and Impacts of Medical Robots on Global Economy

The digital transformation in modern libraries employs Artificial Intelligence (AI) to enhance scientific literacy. However, the implementation of AI presents various legal and ethical challenges that must be addressed to ensure its responsible and fair use. This study utilizes a narrative literature review method, analyzing and synthesizing various relevant sources. This method is flexible, covering diverse types of literature, and is useful for developing theoretical or conceptual models. Regulations for AI in Indonesia are still incomplete, although some aspects are regulated by existing laws. Key challenges include privacy, bias, discrimination, and AI regulation. Ethical principles such as transparency, honesty, and accountability are crucial in AI utilization. Ethical guidelines and regulations must be implemented to ensure fairness and accountability. Librarians play a vital role in enhancing users' scientific literacy through training and digital resource curation. AI implementation can improve library service efficiency and quality but also requires careful attention to ethical and privacy issues. AI holds significant potential for enhancing scientific literacy and operational efficiency in libraries, but the existing legal and ethical challenges must be addressed seriously. More specific regulations and clear ethical guidelines are essential to ensure the safe and responsible application of AI. The application of AI in libraries can significantly enhance scientific literacy and service efficiency, but stricter regulations and the implementation of ethical guidelines are needed to address the existing legal and ethical challenges. This study provides guidance for libraries in adopting AI technology safely and ethically.

This study investigates the utilization of Artificial Intelligence (AI) in digital learning as a key innovation for advancing 21st-century education within the context of Society 5.0. Using a descriptive-exploratory mixed-methods approach, the research integrates both qualitative and quantitative data: a comprehensive literature review and a survey of 183 educators, including teachers, supervisors, and madrasah principals. Findings reveal that although awareness of AI tools (such as ChatGPT, Grammarly, and adaptive learning platforms) is moderate, consistent application in classrooms remains limited, with only 27.2% of educators frequently using such technologies. Major challenges identified include insufficient infrastructure, limited professional development, and a lack of confidence in integrating AI tools effectively. Despite these barriers, most educators acknowledge AI's potential to enhance learning effectiveness, personalize instruction, and streamline administrative tasks. The study concludes that successful AI integration requires targeted strategies, including sustained teacher training, equitable access to digital infrastructure, clear ethical guidelines, and institutional support. Rather than replacing educators, AI should be positioned as a complementary tool that enhances pedagogical practices and strengthens human-centered learning. These findings contribute to the broader discourse on digital transformation in education, offering practical insights for policymakers, school leaders, and educators aiming to leverage AI-driven innovations to equip students with critical 21st-century competenciesKeywords: Artificial Intelligence; Digital Learning; 21st-Century Education; Educational Innovation; Teacher Training; Society 5.0

The concept of this study is centred around clarifying the rulings pertaining to the utilisation of artificial intelligence (AI) applications in scholarly research, while the importance of this study lies in the significance of both scholarly research and artificial intelligence (AI), and contributes towards enriching the corpus of Islamic jurisprudence, while clarifying contemporary matters and recurrent inquiries along with the rulings of Islamic jurisprudence related to them. The problem of the study is embodied in the extent to which utilising (AI) applications in scholarly research is permissible, and identifying what the guidelines in Islamic jurisprudence that ensure the sound utilisation of artificial intelligence (AI) in scholarly research. This study aims to clarify the extent to which utilising (AI) applications in scholarly research is permissible and clarifying the role of Islamic jurisprudence in regulating and supporting the procedures of utilising artificial intelligence (AI) applications in the field of scholarly research. The nature of this study necessitated following the descriptive, analytical methodological approach. This study reached to include: By default according to Islamic law (Sharīˁah) it is permissible to utilise (AI) in scholarly research, as long as the scriptural rulings and restrictions are adhered to. The study also clarified that is not permissible to utilise (AI) applications to compose the body text of the study on behalf of the researcher while attributing it to the researcher, whereas it is allowed to utilise (AI) applications to complement scholarly research. The researcher of this paper holds the view that it is vital to combine between the technologies of artificial intelligence (AI) and human effort in scholarly research.

This study explored the ethical boundaries and data-sharing practices in artificial intelligence (AI)-enhanced nursing from the perspective of Arab nurses. Although AI offers advancements in clinical decision-making and operational efficiency, it also presents challenges such as ethical dilemmas, data privacy concerns, and technical issues. These challenges are being addressed through continuous education, the development of robust ethical guidelines, and the implementation of transparent data-sharing practices METHODS: A qualitative approach was employed, adhering to the Standards for Reporting Qualitative Research (SRQR) guidelines. Fourteen registered nurses from healthcare facilities in Abha City, Saudi Arabia, were selected through purposive sampling. Data were collected through semistructured interviews, observational data and document analysis. Thematic analysis was used to analyze the data. Nurses reported that AI technologies enhance clinical decision-making and efficiency by automating routine tasks. However, they also highlighted ethical challenges, including conflicts between AI recommendations and patient preferences, the need for continuous training, and resource constraints. The importance of maintaining human interaction and empathy in nursing practice was emphasized. The findings align with existing literature on the benefits and challenges of AI in nursing. Ethical dilemmas, particularly related to data privacy and informed consent, require careful management. Continuous education and adequate resources are essential for successful AI integration. AI in nursing not only offers significant benefits but also presents ethical and practical challenges. Clear ethical guidelines, continuous education, and adequate resources are crucial for optimizing AI integration. AI can enhance clinical decision-making and efficiency, allowing nurses to focus on patient interaction and critical thinking. Develop robust ethical frameworks and data protection regulations. Implement continuous professional development programs and ensure adequate resources for AI integration in healthcare.

The emergence and proliferation of artificial intelligence (AI) tools has left the realm of science fiction and the province of computer science research and has reached the everyday activities of academics and various support staff. AI promises to automate and facilitate a range of research tasks and increase scientific productivity, and can thus be expected to raise new questions and dilemmas that might challenge the systems of accountability currently in place to safeguard academic integrity. This poster presents preliminary results of an analysis of seven prominent ethical guidelines (international and Norwegian): the Vancouver protocol, ALLEA guidelines, NENT and NESH guidelines, professional codes of ethics from IFLA, ALA, and the Norwegian Union of Librarians. EBLIDA and LIBER were consulted, but do not offer their own ethical guidelines. The main research question is: to what extent do current ethical guidelines support researchers and librarians in dealing with ethical questions brought about by the proliferation of new AI tools? The concern that emergent technologies tend to challenge values, norms, and practices in academia is not new. For example, ALLEA (2017) acknowledges that the values and principles they lay out are “affected by social, political or technological developments and by changes in the research environment” (p.3). Nonetheless, only the Vancouver protocol (updated in May 2023) provides explicit recommendations on AI; it essentially prescribes that authors/reviewers disclose if and how they used AI tools. The other documents, ranging from 2008 to 2022, mention neither AI nor the possibility of automation technologies in academic/library work. Despite the absence of advice on AI, the analysis revealed interesting issues on ethical guidelines and emergent technologies. ALA (2017) makes extensive recommendations about social media, both as a tool for libraries’ own work and as a demand from patrons who require their expertise. Similar needs for new competencies and responsibilities can be expected from AI. Also, the Norwegian Union of Librarians (2008) encourages the adoption of free software, open standards, and open source codes; this can gain new momentum with the emergence of proprietary tools and algorithms, particularly if they are trained on public data curated by i.a. libraries. Ethical guidelines are general; they state a commitment to certain values and how they should guide certain tasks and practices. They do not prescribe how concrete tools should be employed. In this regard, the current ethical guidelines do offer a sound basis upon which new ethical questions can be assessed. Yet, unlike other types of tools employed in research and library work, AI poses challenges to things that are taken for granted by ethical guidelines, such as what constitutes information, or whether non-human entities can be considered authors, sources, or neither. In conclusion, it might be beneficial to revise ethical guidelines, less so because AI requires concrete recommendations, and more because they challenge substantive assumptions upon which guidelines rely. Also, new possibilities afforded by AI might put pressure on certain values, such as reproducibility and academic craftsmanship. Assuming that academia/library communities consider these important to preserve, it might be beneficial to reaffirm these values in light of the changing landscape.

The article examines the evolutionary relationship between the development of science, human intellect, and modern digital technologies, with a particular focus on artificial intelligence as a key driver of transformation in research and higher education. Science is considered a social institution, a form of purposeful activity, and a structured system of knowledge that continuously evolves under the influence of technological progress. Special attention is given to the rapid integration of artificial intelligence tools into academic environments, which simultaneously enhances research efficiency and generates new ethical, legal, and methodological challenges. The study analyzes the main advantages of artificial intelligence, including the automation of large-scale data processing, support for analytical and predictive tasks, optimization of research experiments, and the personalization of educational processes. At the same time, the article emphasizes the risks associated with excessive reliance on AI technologies, including violations of academic integrity, reduced independence in critical thinking, ambiguity in authorship, reliability issues, and potential algorithmic bias in research outcomes. Key concepts, including artificial intelligence, neural networks, intelligent systems, and chatbots, are systematized in accordance with contemporary academic discourse and current regulatory frameworks. The paper argues that artificial intelligence represents a logical stage in the development of post-non-classical science, in which information flows and cognitive processes become central elements of knowledge production. The authors conclude that maintaining academic integrity in the digital era requires responsible, transparent, and critically reflective use of artificial intelligence technologies. The implementation of clear institutional policies, ethical guidelines, and regulatory mechanisms is essential to balance technological innovation with the preservation of originality, credibility, and trust in scientific research and higher education. Keywords: small business; rural communities; innovation-investment mechanism; entrepreneurial activity; investment support; innovation; socio-economic development.

Integrating Artificial Intelligence (AI) into managerial decision-making raises significant ethical concerns, particularly regarding the attribution of responsibility and decision-making in moral dilemmas. This study examines how different forms of human–AI collaboration influence responsibility and managers’ behavior in ethically questionable scenarios. Across three hypothetical vignette experiments involving 587 marketing managers, we investigate the effects of AI recommendation systems, as opposed to background automation or natural language processing, on ethical decision-making. Results suggest that working solely with AI recommendations may increase perceived personal responsibility, discouraging unethical actions (Study 1). In contrast, collaboration with human and AI teams tends to diffuse responsibility and increase the likelihood of unethical behavior. The severity of ethical violations further shapes these effects. For moderate violations, responses vary by collaboration type, whereas for severe violations, heightened moral clarity supersedes these differences (Study 2). Study 3 shows that benefit-focused AI communication poses particular risks. When AI highlights potential benefits, managers report lower personal responsibility and greater willingness to engage in unethical actions, such as using sensitive customer data. This effect is most potent among managers who heavily rely on AI in their daily work. These findings highlight the dual impact of AI recommendation systems in managerial contexts. While such systems have the potential to enhance accountability, benefit-oriented framing and overreliance on AI may undermine the ethical standards. The study highlights the importance of establishing clear accountability frameworks and ethical guidelines when implementing AI in high-stakes decision-making.

Significant developments in information technology gave rise to artificial Intelligence (AI). Its existence seeks to help human activities be effective and efficient. AI is a technology that allows computers and machines to simulate human Intelligence and problem-solving abilities. The use of AI in Indonesia, based on existing data, is widely used by banks, health institutions, and e-commerce. The existence of AI has both positive and negative impacts. Therefore, there needs to be regulations governing the existence and use of AI. Until now, (1) There is no regulatory instrument that regulates the ethics and policies of responsible development and utilization of artificial Intelligence in Indonesia. (2) There is no supervisory institution to oversee and control the development and utilization of artificial Intelligence in society. (3) There are not enough regulations on the issue of data and sharing infrastructure that will be used publicly and openly by the community for research and innovation development needs. (4) There is no national standard for artificial Intelligence in Indonesia. Using a socio-legal research approach and empirical data collection, the study develops a policy framework aimed at restricting AI use in contexts where misuse may harm public interest, morality, or legal order. The findings show that AI restrictions must be tailored to specific sectors. For example, in the educational field, AI should be prohibited from generating scientific papers, as this undermines academic integrity. Such sector-based limitations must be formalized through legislation to ensure legal certainty and prevent unethical or unlawful behaviour. The research concludes that Indonesia urgently requires a comprehensive legal framework for AI governance. This includes establishing ethical principles, regulatory instruments, oversight institutions, data governance mechanisms, and national AI standards. Clear legal restrictions—such as banning AI-generated academic writing— should be codified to ensure responsible utilization and protect societal values. Without legal safeguards, AI’s rapid expansion risks creating gaps in accountability, ethics, and public trust.

In the current economic context, marked by a significant acceleration of digital transformation, artificial intelligence (AI) is increasingly integrated into business processes, including audit activities. This paper aims to analyze the challenges of using AI in the audit process within companies. Through this research, we aimed to conduct a bibliometric analysis of the literature on the use of AI in auditing. This study performs mapping analyses using VOSviewer software starting from the concepts of “audit” and “artificial intelligence”. The analysis was performed through a quantitative research methodology applied to a sample of a total of 422 research documents published between 1992 and 2024, extracted from the Web of Science (WOS) online database. Recent academic publications highlight three main themes: the presence of artificial intelligence (AI), its role in audit work and concerns about the limits of technology in audit. This study provides information for policy makers, researchers, students and auditors on how AI can be integrated into audit activities, providing findings and suggestions for its application. The paper contributes to the audit literature on AI by highlighting its ability to analyze large data sets. However, it also highlights the lack of clear limitations and ethical guidelines, which are necessary to prevent AI from making independent decisions. Although AI learns autonomously and adapts, it lacks human ethics, being linked to the goals and conditions set by humans. Thus, responsibility should be shared between humans and AI. Research suggests that the use of AI in auditing needs to be adapted to ensure ethical decision making.

This study explores the transformative potential of integrating artificial intelligence with business intelligence to enhance decision-making effectiveness in modern enterprises. Using a quantitative approach, the research focuses on the case of Pakistan Telecommunication Company Limited, a leading internet services provider in Pakistan, to examine the synergistic relationship between artificial and BI. Key factors analyzed include artificial intelligence integration, business intelligence tool usage, and data processing speed, with findings indicating that these variables collectively explain a significant 41.2% variance in decision-making effectiveness. The results highlight artificial intelligence's capability to enhance predictive and prescriptive analytics, business intelligence's utility in data visualization, and the critical role of real-time data processing. Recommendations emphasize strategic artificial and business intelligence integration, robust data governance, user training, and ethical considerations to maximize organizational benefits and maintain competitive advantage. This research provides actionable insights for stakeholders and contributes to the growing discourse on artificial and business intelligence integration in business strategy.

With the ever-increasing integration of artificial intelligence (AI) into health care, it becomes imperative to gain an in-depth understanding of how health care professionals, specifically nurse practitioners, perceive and approach this transformative technology. This study aimed to gain insights into nurse practitioners' perceptions and attitudes toward AI adoption in health care. This qualitative research employed a descriptive and phenomenological approach using in-depth interviews. Data were collected through a semi-structured questionnaire with 37 nurse practitioners selected through purposive sampling, specifically Maximum Variation Sampling and Expert Sampling techniques, to ensure diversity in characteristics. Trustworthiness of the research was maintained through member checking and peer debriefing. Thematic analysis was employed to uncover recurring themes and patterns in the data. The thematic analysis revealed nine main themes that encapsulated nurse practitioners' perceptions and attitudes toward AI adoption in health care. These included nurse practitioners' perceptions of AI implementation, attitudes toward AI adoption, patient-centered care and AI, quality of health care delivery and AI, ethical and regulatory aspects of AI, education and training needs, collaboration and interdisciplinary relationships, obstacles in integrating AI, and AI and health care policy. While this study found that nurse practitioners held a wide range of perspectives, with many viewings AI as a tool to enhance patient care. This research provides a valuable contribution to the evolving discourse surrounding AI adoption in health care. The findings underscore the necessity for comprehensive education and training in AI, accompanied by clear and robust ethical and regulatory guidelines to ensure the responsible integration of AI in health care practice. Furthermore, fostering collaboration and interdisciplinary relationships is pivotal for the successful incorporation of AI in health care. Policymakers should also address the challenges and opportunities that AI presents in the health care sector. This study enhances the ongoing conversation on AI adoption in health care by shedding light on the perspectives of nurses, thereby shaping future strategies for AI integration.

Background: Artificial Intelligence (AI) has emerged as a transformative force in higher education, particularly in programming instruction where students often struggle with computational thinking and problem-solving. Advancements in AI technologies such as adaptive learning platforms, generative assistants, and automated feedback systems show strong potential to enhance student engagement and improve learning outcomes. However, research on AI integration in programming education remains fragmented with limited consolidated evidence on its pedagogical implications. This scoping review aims to integrate current studies to identify AI’s pedagogical functions within programming education and highlight the key challenges and opportunities in this evolving field. Method: A scoping review was systematically conducted using the Scopus and Web of Science databases to identify the nature of existing research on AI in programming education and to determine the pedagogical roles reported across studies. Guided by Arksey and O’Malley’s framework and the PRISMA-ScR guidelines, the search process identified 598 records, of which 15 met the inclusion criteria for thematic analysis. Result: The review identified five pedagogical roles of AI in programming education: (i) enhancer of adaptive learning and engagement, (ii) facilitator of personalized learning pathways, (iii) assessor providing automated feedback and evaluation, (iv) scaffolder supporting problem-solving and computational thinking, and (v) personalizer tailoring content to learner needs. While AI was found to improve student confidence, creativity, and instructional design, critical concerns were also highlighted, including over-reliance on AI tools, ethical risks such as plagiarism and bias, and the lack of structured pedagogical frameworks. Conclusion: This scoping review consolidates emerging evidence and emphasizes the dual role of AI as both a pedagogical partner and a source of challenges. The findings call for structured professional development, clear ethical guidelines, and competency-based pedagogical frameworks to ensure sustainable and responsible AI integration in programming education

Utilization of artificial intelligence (AI) technology is very important in helping English. This research aims to explore the utilization of artificial intelligence (AI) technology in helping English Literature Study Program students complete their final projects at university level. The research design used is a qualitative approach. The population in this study were students from the English Literature Study Program who were completing their final projects, with a sample of 10 students selected purposively. Data was collected through interviews using Google Form which contained five questions related to the utilization of AI in the final project. Data analysis was carried out by referring to the points contained in the interviews to answer the research objectives. The research results show that AI really helps students in completing their final projects, especially in terms of finding ideas, understanding concepts, and improving English language skills. However, some students also realize the limitations of AI in terms of source validity and accuracy of information provided. The conclusion of this research is that the utilization of AI must be balanced with critical evaluation of the information and sources provided to ensure the quality and acceptability of students’ final projects. This research provides a deeper understanding of the role of AI in supporting students’ final assignment completion, as well as the importance of vigilance in verifying information obtained from this technology.

The study aimed to evaluate the nursing students’ perception and attitudes toward utilization of Artificial Intelligence in Health care. Descriptive research design. The study was conducted at Vision Medical College, Jeddah. KSA. Two hundred and six students registered in the nursing program were included in the study by using convenience sampling. Three tools were used for data collection, Self-Administered questionnaire, Covered student nurses' demographic characteristics, Perception toward Artificial Intelligence Questionnaire and Students’ attitudes towards Artificial Intelligence Questionnaire. The majority of participants responded that they are familiar with Artificial Intelligence 79.6%, there was a significant positive correlation between student nurse’ demographic characteristics (Living Location, education, Self-Assessment of Technological Competence and Familiarity with Artificial Intelligence) and their attitudes toward using the artificial intelligence. The mean score of the attitude scale was (M= 3.29, SD = 0.76), while the mean scale score of the perception scale was (M= 3.43, SD = 0.69). Likewise, a significant positive association was observed between perception of students and their attitudes towards artificial intelligence (β = 0.855, p < 0.001). The current study revealed that the students most likely held positive attitudes towards AI utilization and had a favorable perception toward utilization of artificial intelligence in health care. Integration of artificial intelligence technology and their utilization in nursing practice as a partner for improving patient outcomes in the health care field.