Journal of Education for Humanities

The world today is witnessing rapid transformations due to the technological revolution, most notably artificial intelligence, which has become a strategic tool that can be employed across various sectors. At the same time, humanity faces common global challenges related to sustainable development, such as combating poverty, mitigating climate change, and promoting health and education. Hence, the importance of research into the relationship between artificial intelligence and international cooperation as a key approach to enhancing opportunities for achieving the Sustainable Development Goals.
This research aims to examine how artificial intelligence can be used as a tool to support international cooperation and analyze its role in accelerating progress towards the Sustainable Development Goals, focusing on the experiences of some countries and international organizations. The study relied on a descriptive, analytical, and comparative approach, in addition to a prospective approach to monitoring future prospects. The research findings are expected to contribute to providing a practical framework and recommendations for enhancing integration between technology and international policies, thus supporting the construction of a more just and sustainable future

We shall redefine privacy, democracy, individual rights, power, state sovereignty, security, dependability, and conflict. It appears that the situation is remarkably unclear because it led some of the world's greatest thinkers, like Henry Kissinger, Stephen Hawking, Elon Musk, and others, to label artificial intelligence as a weapon of the end of the world. Perhaps one of the tools with events is artificial intelligence. In addition to the international system, there has been a significant transformation in all aspects of human life. Since the discovery of agriculture, the beginning of the industrial revolution, and the employment of firearms in conflicts to develop nuclear weapons, However, the change at this point will be profound since artificial intelligence will be incorporated into practically every new technology developed in the fields of industry, agriculture, weaponry, medical, engineering, and the rest of the sciences. By removing nations that rely on their traditional power from the leadership system and creating a new international order, it would alter the terms of the international game

Artificial intelligence technologies have become a fundamental pillar in cyberspace, acting as a double-edged sword. They can be exploited by actors-particularly terrorist groups-to spread extremism, carry out denial-of-service attacks, and manipulate media content in ways that are difficult to detect, conversely, artificial intelligence can serve as an effective tool in combating cyber terrorism through technologies such as facial recognition, blockchain, and the Internet of things. This duality presents a significant challenge to cybersecurity, necessitating, as well as legal and ethical frameworks, to ensure the enhancement of cybersecurity, Furthermore, international cooperation is essential to develop policies capable of addressing Al-enabled threats

This research seeks to explore the transformative role of artificial intelligence techniques, particularly deep learning and digital image analysis, in the automatic detection of basic rhetorical figures (simile, metaphor, metonymy) in Arabic poetry from the pre-Islamic era to the modern era. The study aims to overcome the limitations facing traditional rhetorical analysis, which suffers from subjective interpretation and the time required, hindering the conduct of comprehensive quantitative studies of the evolution of rhetorical phenomena throughout history. It also seeks to bridge the gap between Arabic rhetorical heritage and modern computational tools by presenting an applied methodology that enhances literary and linguistic research with data-driven analyses.
The study adopted a quantitative analytical approach based on deep learning techniques, following a series of meticulous steps to ensure the accuracy of the results. The work began by collecting a large database of poetic texts, covering ancient poetry (from the pre-Islamic era to the Abbasid era) and modern poetry (from the Renaissance era to the present day), relying on reliable digital sources and verified texts. These texts then underwent a rigorous linguistic processing process, which included:
Removing errors and impurities from the texts.
Unifying the spelling of hamzas and alifs.
Removing redundant diacritics that do not affect the meaning.
Dividing the texts into analytical units (verses or semantic segments).
The critical stage: Building the labeled database
To ensure classification accuracy, three Arabic rhetoric experts manually classified 20,000 poetic verses, setting detailed guidelines to ensure consistency in evaluation. The degree of agreement between classifiers was also measured using statistical measures to ensure data reliability.
Advanced deep learning models were developed, focusing on natural language processing techniques, specifically the "AraBERT" model, which is tailored to the Arabic language. The models relied on representing texts with rich contextual vectors, incorporating additional linguistic features to improve performance. It is worth noting that image analysis techniques (computer vision) have not proven highly effective in this task, due to its complex semantic nature. Training also included the use of advanced techniques to prevent overfitting, such as early stopping and random dropout.
The results showed that the model achieved high accuracy in recognizing similes and performed well in detecting metaphors, while it encountered greater difficulties in identifying metonymy, given its close association with cultural context and external knowledge. The study also revealed clear differences in the patterns of rhetorical imagery usage between ancient and modern poetry. The study recommends the following:
Expanding the Arabic rhetorical database to include more diverse texts.
Improving the models' ability to understand metonymy by incorporating contextual knowledge.
Developing more transparent models for interpreting results rhetorically.
Conducting comparative studies to analyze the evolution of rhetorical techniques across the ages.
Expanding the scope of research to include other rhetorical images, such as metonymy and antithesis

This research aims to demonstrate the importance of information and communications technology (ICT) capabilities in achieving strategic readiness, through an applied study at the Al Kafeel Information Technology Center. The research problem arose from the question of the extent to which information technology capabilities continue to enhance the ability to focus on integration with primary target customers. The research included a comprehensive analytical description, and data was collected through a questionnaire distributed to a group of (120) employees. (110) valid questionnaires were retrieved for statistical analysis. This was achieved through the use of a set of statistical programs.
The research seeks to demonstrate the importance of ICT capabilities in achieving strategic readiness, as they are characterized by their ability to generate technological information that contributes significantly and significantly to achieving strategic readiness. This is due to their technical characteristics that contribute to meeting individual needs and enhancing the ability to identify effective requirements for challenges and changes. It also indicates a strong relationship between investment in technological information and increasing the center's absorptive capacity. A study has already been conducted to develop the center's IT capabilities, focusing on continuous training of human resources and adopting the latest efforts. This includes ensuring the center's readiness to achieve key technological milestones, including enhancing its strategic readiness

This research aims to provide an in-depth critical analysis of the phenomenon of employing artificial intelligence to uncover symbolism and hidden meanings in Arabic literary texts. This is achieved by exploring the conceptual framework of literary symbolism, analyzing the computational methodologies and techniques used in this process, and ultimately evaluating the critical quality of the automated analysis. The research adopted a descriptive-analytical methodology, analyzing the most prominent computational applications and models in the field of literary text processing, with a focus on the challenges posed by the rhetorical and linguistic rules of the Arabic language. The study reached several key conclusions, the most important of which is that advanced artificial intelligence models are capable of adhering to the formal rules of texts and identifying linguistic and semantic patterns, but they still lack the interpretive depth and artistic and aesthetic originality that characterize human criticism. Based on these findings, the research presented a set of recommendations calling for the necessity of investing in the creation of accurately annotated critical corpora and developing hybrid models that combine rhetorical rules with the flexibility of deep learning. The research also proposed several areas for future research, most notably the study of Explainable AI in literary criticism and its use in developing linguistic and creative skills

This research aims to examine the role of artificial intelligence technologies in bridging the educational gap between countries, focusing on international experiences and exploring lessons learned that can be applied in developing countries. The research discusses the theoretical framework of artificial intelligence and the educational gap, reviews the most prominent applications of artificial intelligence in education, and the opportunities and challenges associated with employing this technology.
It also analyzes the experiences of China, Finland, and the UAE in smart education and deduces policies and strategies applicable in emerging educational contexts. The research finds that artificial intelligence offers significant potential to improve the quality of education, provide personalized learning, and enhance critical and creative thinking, provided the digital infrastructure is developed, teachers are qualified, and practical projects are integrated that meet the needs of the local community

The current research aimed to use the \\"Expert\\" educational system to teach interior design to develop the technical skills of interior design students, using appropriate artificial intelligence. The study applied the system to a sample for the 2023/2024 academic year.
The researchers used an experimental approach with two groups: an experimental and a control group, with pre- and post-tests. The research sample consisted of (44) male and female students from the third year in the Interior Design Department. The researchers prepared a skill test measured using an assessment form, and then verified its validity and reliability. Several statistical methods were used to process the data, and the results showed that the experimental group outperformed the post-skill test. This was attributed to the educational experiences included in the expert educational system and the presentation of skills according to their skill sequence in the interior design subject.

The rapid integration of Artificial Intelligence (AI) into diverse fields has reinforced the critical role of English as both a global lingua franca and a medium for technological advancement· This study, Bridging Minds and Machines: The Role of English in Advancing AI Technology, investigates how English functions as the dominant linguistic framework for AI research, programming, and human- computer interaction· The research highlights the centrality of English in major AI hubs such as OpenAI (San Francisco, USA), DeepMind (London, UK), and Google AI (Mountain View, USA), where English underpins the design of large language models (LLMs), including GPT-5 and Gemini· It further examines how English-based corpora, such as the Common Crawl and Wikipedia, form the backbone of AI training datasets, while acknowledging the challenges of linguistic bias, marginalization of low-resource languages, and the need for more inclusive multilingual models· By drawing on case studies from Iraq and the broader Middle East, the study contextualizes how English proficiency among researchers and students influences access to AI scholarship, coding communities (e·g·, GitHub, Kaggle), and open-source collaborations· Additionally, it explores pedagogical

implications, particularly the integration of English for Specific Purposes (ESP) in university curricula to prepare future generations of Iraqi scholars and developers to engage with global AI discourses· The findings argue that while English continues to be the dominant bridge between human minds and intelligent machines, a critical approach is required to balance this dominance with the promotion of linguistic diversity· This study contributes to both applied linguistics and digital studies by showing how English is not only a communication tool but also an epistemic gatekeeper in the age of AI