Mediating role of artificial intelligence in the relationship between higher education quality and scientific research ethics among faculty members: A Study in carrying out the study, specific research objectives were derived, and based on the derived objectives, null hypotheses were formulated and tested for the study. This study, thus, employed survey research design. This study’s population comprised postgraduate students from Middle Eastern University, Jordan, with 1200 students. Using the population, a sample size of 291 respondents was selected based on Krecie and Morgan The students in the sample completed Google Forms questionnaires. The data were statistically processed, and the analysis’s most significant level was 0.25. The research questions were analyzed using descriptive statistics, and the null hypothesis was tested using Pearson Product Moment Correlational Analysis (PPMC). Also, the study showed a significant relationship between artificial intelligence and the quality of higher education and the relationship of significance between artificial intelligence and ethics in scientific research. The researcher suggested a need for ongoing education, cross-discipline cooperation, and the development of solid ethical frameworks for the integration ethics of AI academia.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.

The need to expand the range of banking services in Ukraine is stipulated with technological progress, the European integration processes and the legal regime of martial law introduced in the country. Under the conditions of war, the need to strengthen the security of banking activities and protect the banking system from the influence of any internal and external factors gains meaning. The topical direction of economic and legal research of scientists today is the possibility to introduce digital technologies with elements of artificial intelligence (AI) into the banking activity in Ukraine to improve its protection. The AI law as an independent branch of the Ukrainian law has not been developed so far. The sources of AI law, its functions, tasks, scope, risks and limits of legal responsibility for prohibited practices of artificial intelligence have not been defined. The purpose of the article is to analyze the theoretical and legal provisions that underpin the regulation of AI application in Ukrainian banking. The comparative legal method made it possible, considering the provisions of the draft law on AI of the European Union, to determine the trends in the development of the legal regulation of AI in Ukraine. Following the study, proposals to the legislation of Ukraine were formulated, which will contribute to the legal regulation of banking activities using digital technologies with elements of AI.

The development of artificial intelligence (AI) and 5G network technology has changed the production and lifestyle of people. AI also has promoted the transformation of talent training mode under the integration of college industry and education. In the context of the current transformation of education, AI and 5G networks are increasingly used in the education industry. This paper optimizes and upgrades the training mode of skilled talents in higher vocational colleges by using its advanced methods and technologies of information display. This means is helpful to analyze and solve a series of objective problems such as the single training form of the current talent training mode. This paper utilizes the principles and laws of industry university research (IUR) collaboration for reference to construct and optimize the talent training mode based on the analysis of the requirements of talent training and the role of each subject in talent training. Then, the ecological talent training environment can be realized. In the analysis of talent training mode under the cooperation of production and education, the correlation coefficients of network construction, environment construction, scientific research funds, scientific research level, and policy support were 0.618, 0.576, 0.493, 0.785, and 0.451, respectively. This showed that the scientific research level had the greatest impact on talent training in the talent training mode of IUR collaboration, while policy support had less impact on talent training compared with other factors. The combination of AI and 5G network technology with the talent training mode of IUR cooperation can effectively analyze the influencing factors and problems of the talent training mode. The hybrid method is of great significance to the talent training strategy and fitting degree.

The study aims to explore the role of artificial intelligence in enhancing the efficiency of public relations practitioners in Jordanian telecommunication companies. This study belongs to the category of descriptive research and adopted a survey methodology. The study surveyed (86) individuals representing the community of public relations practitioners and customer service personnel in the Jordanian telecommunication companies Zain and Orange.The study findings revealed that less experienced public relations personnel in Zain and Orange, with less than five years of experience, exhibit greater acceptance and enthusiasm for using artificial intelligence applications compared to their more experienced counterparts. The study also indicated that most public relations practitioners in Zain and Orange perceive artificial intelligence applications to have a moderate to significant contribution to achieving public relations functions and enhancing their work, reflecting technological advancement and the need to adapt to rapid changes in the business environment. Moreover, the study also discussed the limits, including that artificial intelligence can analyze large amounts of data related to the market and the audience, which provides further research and study.