Artificial Intelligence

Background: Throughout history, humans have consistently developed groundbreaking technologies, from fire and the wheel to modern computing, showcasing their ability to innovate and control their creations. The rise of artificial intelligence has sparked renewed concerns about whether machines might eventually surpass human intelligence and autonomy.Aims: This study aims to critically assess AI’s role in human society, particularly addressing concerns that it may surpass human control and agency. It seeks to demonstrate that while AI is a powerful tool, it lacks autonomy, self-augmentation, and intentionality, making it unlikely to replace human decision-making. Additionally, the paper examines historical technological advancements, showing how humans have always adapted and controlled new innovations.Methodology: Employing a historical-comparative methodology, this study traces the evolution of computing technologies from early tally systems to quantum computing. It incorporates philosophical analysis through the works of Hubert Dreyfus, John Searle, and Michael Tomasello, assessing AI’s limitations in replicating human cognition.Findings: The study finds that despite AI’s rapid advancements, it remains fundamentally dependent on human input, lacks true understanding, and is incapable of independent self-enhancement. The historical trajectory of technological progress demonstrates that while new technologies can disrupt societies, humans have consistently adapted and maintained control. Philosophical critiques of AI further reinforce the argument that intelligence is not solely computational but deeply rooted in embodiment, intuition, and shared intentionality—qualities that AI lacks.Conclusions: Concerns about AI overwhelming human agency are largely misplaced. Just as humanity has managed previous technological revolutions—including writing, mechanization, and computing—AI will be integrated and regulated according to human needs and ethical considerations. While vigilance is necessary, the myth of AI autonomy is exaggerated.

Background: The nature of scholarly research has undergone a profound transformation in recent decades, transitioning from traditional, library-based inquiry to digitally mediated and increasingly AI-assisted methodologies. This article reflects on that evolution through an autoethnographic lens, drawing upon the author’s personal academic trajectory and long-standing engagement with satire. Aims: This article explores the evolving landscape of research, communication, and authorship in the digital age, with a particular focus on the transformative role of Artificial Intelligence. Methodology: The study employs a reflective, autoethnographic methodology combined with AI-assisted literature synthesis. Drawing on personal academic experiences and outputs from ChatGPT and Claude, the author critically examines artificial intelligence’s role in communication research and satire. This qualitative approach blends narrative inquiry with theoretical analysis to explore the epistemological and ethical implications of AI in scholarly authorship. Discussion: Reflecting on a shift from traditional library-based scholarship to AI-assisted inquiry, the author critically examines how tools like ChatGPT and Claude reshape academic and journalistic practices. The manuscript considers the integration of AI across domains such as human communication, media, sentiment analysis, and translation, while addressing ethical concerns including privacy, authorship, and misinformation. Through both anecdotal reflection and synthesized research, the text interrogates the promises and pitfalls of AI in content generation, especially in the context of satire—a long-standing interest of the author. Conclusion: Drawing on personal experience and historical theories of satire from figures like Northrop Frye, Juvenal, and Linda Hutcheon, the article positions AI not just as a technological tool but as a cultural force influencing narrative forms and critical thought. While acknowledging AI's generative capabilities, the author emphasizes the enduring need for human discernment, intellectual ownership, and critical interpretation in both academic and creative contexts.

The finance sector is experiencing substantial technological disruption as Quantum Computing and Artificial Intelligence (AI) continue to advance at a rapid pace. This study employs bibliometric analysis, specifically VOS Viewer, to investigate the academic environment at the intersection of financial risk, AI, and quantum computation. From 2014 to 2023, a comprehensive bibliometric analysis was performed on a total of 145 journal articles that were published in Scopus and Web of Sciences (WoS). Articles are categorized based on their homogeneity in the disciplines of Quantum Computing, Financial Risk, and AI, as well as their interdisciplinary compositions. The results, which include authorship trends, keyword dynamics, and linked works, are analyzed and presented. This extensive bibliometric analysis offers critical insights into contemporary research and pinpointing areas necessitating further exploration. As quantum computers and AI algorithms become more sophisticated, this paper investigates the potential weaknesses and issues that financial institutions may encounter. By analyzing the intersection of two transformative technologies, the report offers critical insights into the discourse surrounding the safeguarding of financial systems in the quantum era. The analysis not only enhances the quality of the review but also directs researchers to significant papers and identifies regions of publications, thereby facilitating a more comprehensive understanding of the research environment.

The current paper reviews the present literature in the most known scientific databases in the management and business fields about artificial intelligence (AI) and digital transformation within organizations. The main objective is to extract related research axes and uncover gaps in this emergent topic. The methodology used is a systematic literature review with RStudio software based on 36 selected papers from the Scopus and Web of Science (WOS) databases in the period of 2019-2024. The main axes identified are AI potential for organizations’ performance, innovation and AI potentials, and AI adoption determinants. Regarding the discussion and analysis of the results, future directions are projected to cover all sides of digital transformation through AI tools. The main contribution of this paper is to provide researchers and practitioners with current advancements and changes in Al tools utilized to facilitate digital transformation within evolving economic and social landscapes for companies.

Purpose: The primary objective of this research was to integrate ChatGPT, an advanced artificial intelligence language model, into distance science education. By addressing the specific challenges inherent in online learning environments, this study aims to investigate how technological advancements, such as ChatGPT, can effectively enhance the management and overall quality of distance education experiences. Method: This qualitative, exploratory study aimed to provide a comprehensive understanding of the potential applications of ChatGPT in distance science education. This study identifies the various interactions that can occur in distance education and describes and evaluates the input and output instructions associated with each interaction. The chat bot used is https://chatbot.theb.ai and A biology tutoring platform uses ChatGPT to provide personalized support to students working on biology issues or concepts. Findings: Based on the results, the artificial intelligence can play an important role in improving distance science education. Furthermore, this study highlights the importance of developing metacognitive skills among learners and encourages educators to seek professional development opportunities to enhance the quality and engagement of distance science education. This study emphasizes the need for careful planning, research, design, evaluation, management, and responsible application of AI technology in distance education. Conclusion: This study was concluded that ChatGPT could be very useful for both learners and educators in distance education. This research showcases the innovative results facilitated by ChatGPT and provides valuable insights and practical guidance for educators, researchers, and policy makers on the effective use of AI technologies in distance science education.

Purpose: The purpose of the current research is to extract the components and dimensions of digital transformation and determine the levels and sequence of dimensions in Iran's education and upbringing, for the planning and implementation roadmap.Method: This research has a mixed approach (qualitative-quantitative). The qualitative section was able to extract the components of digital transformation by searching for authentic Persian and English articles published in the last ten years. With the help of seven experts, the digital transformation components were classified into eight dimensions in the form of 109 identified sub-components using the ISM method. Dimension levels were determined by SSIM matrix calculations in the quantitative part. MICMAC software version 5.3.0 was used to calculate the impact of relationships.Findings: Based on the opinion of experts and the results of ISM calculations, the identified dimensions including: institutional, education, technology, infrastructural, social, cultural and economic were placed in four levels.Conclusion: According to experts, the institutional dimension, being placed at the fourth level, has the greatest impact on digital transformation in Iran's education. Therefore, it is one of the key dimensions to achieve digital educational transformation that is placed at the first level of the model. According to the results of ISM, the economic and cultural dimensions were placed at the third level. Also, in analyzing the impact of relationships between dimensions using MICMAC software, the results indicate that the institutional dimension has a significant impact on infrastructure development.

The purpose of this study is to investigate the impact of digital transformation on audit efficiency in companies listed on the Iranian capital market. Audit delay is used as a key measure to evaluate audit efficiency. To assess digital transformation, an index based on the frequency of keywords related to digital technologies, such as "Internet of Things," "Artificial Intelligence," "Cloud Computing," and "Big Data," in annual reports of companies is calculated. Control variables include company size, financial leverage, board independence, ownership concentration, Return on Assets (ROA), company losses, and CEO duality.This research is applied and descriptive survey in nature, and data were collected from financial reports of companies listed on the Tehran Stock Exchange between 2018 and 2022. Data analysis was performed using linear regression and the Eviews software, with the study adopting a panel data methodology.The results indicate that digital transformation negatively affects audit efficiency, leading to increased audit report delays. Additionally, companies with higher levels of digital transformation experienced more significant audit delays. These effects were particularly evident in firms with higher financial leverage and lower ownership concentration.This study highlights that digital transformation presents new challenges for the auditing profession, emphasizing the need for enhanced skills and the adoption of relevant technologies in the audit process

This article provides a philosophical analysis of identity within the context of artificial intelligence, from the perspective of Transcendent Philosophy (especially the views of Mulla Sadra) and contemporary philosophy. With the rapid advancements in artificial intelligence as one of the most significant innovations in computer science, issues such as the reconstruction of human identity and its comparison with natural intelligence have come to the fore. The paper examines the philosophical capacities and limitations of this phenomenon, exploring the perspectives of Mulla Sadra and John Searle, and offers a comparative analysis of their views on identity and consciousness in machines and artificial intelligence. According to the views of these two thinkers, artificial intelligence, despite its advancements, cannot achieve human identity, as it lacks essential characteristics such as consciousness, intentionality, and abstraction. Searle argues that artificial systems will never be able to attain genuine consciousness because understanding meaning and consciousness are intrinsic to the human brain and mind, qualities that cannot be attributed to machines. He consistently supports this belief through the Chinese Room experiment and various critiques of artificial systems.

Introduction: The concept of the “responsibility gap” in artificial intelligence (AI) was first raised in philosophical discussions to reflect concerns that learning and partially autonomous technologies may make it more difficult or impossible to attribute moral blame to individuals for adverse events. This is because in addition to designers, the environment and users also participate in the development process. This ambiguity and complexity sometimes makes it seem that the output of these technologies is beyond the control of human individuals and that no one can be held responsible for it, which is known as the “responsibility gap”. In this article, the issue of the responsibility gap in artificial intelligence technologies will be explained and strategies for the responsible development of artificial intelligence that prevent such a gap from occurring as much as possible are presented. Material and Methods: The present article examined responsibility gap in AI. In order to achieve this goal, related articles and books were examined. Conclusion: There have been various responses to the issue of the responsibility gap. Some believe that society can hold the technology responsible for its outcomes. Others disagree. Accordingly, only the human actors involved in the development of these technologies can be held responsible, and they should be expected to use their freedom and awareness to shape the path of technological development in a way that prevents undesirable and unethical events. In summary, the three principles of routing, tracking, and engaging public opinion and attention to public emotions in policymaking can be useful as three effective strategies for the responsible development of AI technologies.

Purpose of this research is Predicting Stock Price Crash Risk with a Deep Learning Approach from Artificial Intelligence and Comparing its Efficiency with Classical Predicting Methods. This research is post-event correlation type and practical in terms of purpose. The research data were extracted from the website of the Stock Exchange Organization and Codal website. The risk variable of crashing stock prices was introduced as a predictor. 3200 obser-vations were obtained from 10-year data of 320 companies between 2012 and 2021. In the following, 29 variables were identified as variables that can affect the risk of crashing stock prices. Statistical methods such as unit root test, composite data, Hausman test and variance heterogeneity test were used. Next, the top 10 algorithms in the field of deep learning were selected and used to model the mentioned variables with the CNN method. Python, Eviews and Excel software were used in this research. Examining the performance of different deep learning algorithms shows that the convolutional neural network method performs better compared to other algorithms and can improve the prediction accuracy. Therefore, it is suggested to use this algorithm in reviewing econometric data and especially predicting the risk of crashing stock prices.

based on the peculiarities of developing AI technology, learning English among EFL learners has become easier and the significance of studying the way English skills interact with AI technology such as Chat-GPT, and EFL learners’ internal and social factors have become highly important. Social factors include may greatly affect the problem-solving skills of the students. It might also lead to a decline in students' writing skills as they rely on the model to generate content rather than developing their own communication abilities. Social factors might include issues related to job or individual growth. Adopting a transformative learning ground, the present study attempted to use a qualitative-method approach to investigate how EFL learners experience AI, on one hand, and how they perceive Chat-GPT in this process through understanding changes in their job, attitudes toward themselves and etc, on the other hand. This study is based on a detailed investigation of the learning experiences of 46 Iranian EFL learners (intermediate and upper intermediate level) from Qom and Tehran provinces; selected based on convenience sampling procedure. Semi-structured interviews were used as the primary data collection method. Thematic analysis was used to analyze the recorded and transcribed data and theme extraction, which combined with an abductive approach helped derive broader meaning. The results indicated an overall positive perception of Chat-GPT among the participants

Since reflective practice is regarded as a significant professional learning tool for teachers to change, modify, and reform their educational practices, it is important for teachers to move towards a more creative use of reflection. Thus, imaginative and creative reflective practice can serve as a new approach to enhance teaching efficiency, originality, reflectivity, and practicality. Additionally, teachers can utilize Artificial Intelligence (AI) tools to implement reflective practice in creative and imaginative ways to support innovative reflections and address complex teaching challenges. Accordingly, this study employed imaginative and creative reflective practice with a Chat Generative Pre-Trained Transformer (ChatGPT) as a novel AI tool. This study explored how imaginative and creative AI-oriented reflective practice could contribute to the professional development of EFL teachers within a complex educational system. To this end, the perspectives of six novice and experienced EFL teachers were examined through semi-structured interviews, classroom observations, and post-class discussions within a qualitative case study framework. The findings indicated that teachers were able to transform and reform their belief systems by learning new concepts, reflecting on their practices, innovating knowledge and practice, and initiating change through imaginative and creative AI-oriented reflective practice. The study concludes with suggestions on how to engage language teachers in imaginative and creative AI-oriented reflective practices.

Artificial Intelligence (AI) is increasingly transforming the landscape of education, particularly within the domain of language learning, as evidenced by a growing body of research published in computer-assisted language learning (CALL) journals. These studies have examined the application of various AI technologies, including natural language processing (NLP), AI-driven educational platforms, automatic speech recognition, and chatbots, in facilitating language acquisition. The present study investigated the perceptions of 386 Iranian high school EFL students, utilizing the Students’ Perceived EFL Teacher Support Scale to evaluate the impact of AI-powered speaking assistance technologies, educational level, and learning setting on perceived teacher support. The findings revealed a tri-factorial structure underlying EFL teacher support, highlighting the compatibility of AI technologies with traditional pedagogical methods. This suggests that the integration of AI-powered tools into classroom instruction can enhance the overall effectiveness of language teaching and learning. To ensure optimal outcomes, educators are encouraged to strategically incorporate AI within pedagogically sound frameworks that maintain human-centered support. The study offers important implications for sustaining and enhancing teacher support in technology-enriched learning environments and underscores the need for further empirical research in this evolving area of applied linguistics and educational technology.

Extensive research has been conducted on the intersection of digital games and AI, exploring how it impacts the diverse variables of education, such as proficiency, vocabulary, and motivation. However, there is a lack of studies that have comprehensively assessed the combined impact of digital games and AI applications on enhancing six aspects of vocabulary. This study focused on finding the possible effect of using the combination of digital games and the Artificial Intelligence Chat GPT application technique (AIGames) on developing the 7th-grade EFL learners’ vocabulary acquisition and their attitude toward such a technique. Based on an experimental and descriptive design, a quantitative approach was used. The participants were assigned to two groups randomly: the experimental group, which studied using this technique, and the control group, which was taught using the regular instruction method. The study used two instruments: a pre-posttest and an attitude scale (questionnaire). The findings revealed statistically significant differences between the experimental and control groups in vocabulary learning due to using the AIGames technique in favor of the experimental group. The post-test results (Table 2) revealed significant improvements across all six vocabulary aspects, with the largest gains in denotation (experimental group: M=7.82 vs. control: M=4.56) and spelling (M=7.59 vs. 5.38). Pronunciation showed the slightest improvement (M=5.41 vs. 3.69), suggesting that the AIGames technique was less effective for this aspect. The study also showed that most participants in the experimental group had a positive attitude towards using the new technique in learning vocabulary. Moreover, the study revealed no correlation between the experimental students’ achievement in vocabulary and their perception of using the AIGames technique.

Artificial intelligence (AI) is changing language education through personalized and interactive practice. However, its impact on language achievement and emotional aspects of learning is unclear. Therefore, this mixed-methods study investigated the effects of Chatbot-Assisted Language Learning (CHALL) on learners’ English language achievement and sense of metavolvement—the deepest level of metacognitive engagement. In phase 1, the Sense of Metavolvement Scale (SOMS) was developed and validated. In phase 2, following a quasi-experimental design, 44 intermediate Iranian EFL learners were divided into an experimental group (n=22, using the AI chatbot Pi) and a control group (n=22, receiving conventional classroom instruction). Both groups had pre- and post-tests for language achievement and metavolvement, and the experimental group sat for semi-structured interviews post-intervention. There were significant gains in the experimental group’s in-class metavolvement and language achievement. There were also significant differences between the two groups in post-test metavolvement, while there was no significant difference in their post-test language achievement. Furthermore, interview data illustrated CHALL as a low-anxiety practice context with cultural and pragmatic limitations. Therefore, CHALL can complement but not replace conventional instruction.

Artificial Intelligence has emerged as a transformative technology with implications for global security. This article using descriptive-analytic method aims to explore the US and China’s Competition for AI supremacy and its security consequences for global security. The research main question is that “what ramifications do the US and China’s competition for AI supremacy have for global security?” This article argues that the competition between China and the U.S in the realm of AI technologies has significant ramifications for global security, with implications spanning economic, military, and geopolitical spheres. This multifaceted competition casts a profound shadow over the contemporary international landscape and necessitates a nuanced understanding of its consequences. This article also discusses that international collaboration, dialogue, and the establishment of norms and regulations are crucial in harnessing the benefits of AI while mitigating its risks. The final section of this article addresses recommendations to robust AI systems that prioritize human rights. By embracing a responsible approach to AI, we can strive towards a safer and more secure world.

This study investigates EFL teachers’ perceptions of ChatGPT as a tool for English language instruction, focusing on its perceived benefits, challenges, and pedagogical implications. Using a qualitative phenomenological approach, data were collected through semi-structured interviews with ten EFL teachers currently working in different language-related educational centers in Iran. Participants represented diverse educational contexts, including universities, public schools, and private language centers. Thematic analysis of the interview data revealed that while teachers generally expressed positive attitudes toward ChatGPT, recognizing its flexibility, time-saving capabilities, and potential to enhance students’ writing skills and learner autonomy, they also voiced concerns regarding overreliance, inaccuracies, ethical challenges related to academic dishonesty, and limitations in supporting listening and speaking skills. The findings suggest that ChatGPT is viewed as a supplementary educational tool rather than a replacement for traditional pedagogy. Teachers emphasized the necessity of critical supervision, ethical guidelines, and professional development to ensure effective and responsible integration of AI technologies in EFL instruction. This study contributes to the growing body of research on AI integration in education, offering practical insights for teachers, policymakers, and researchers seeking to harness the potential of AI in language learning while mitigating its challenges.

Introduction: The widespread penetration of artificial intelligence technology in various aspects of human life raises major concerns regarding the degree to which these technologies adhere to ethical standards. Therefore, the aim of the present study is to identify key ethical concepts for using artificial intelligence in digital technologies. Material and Methods: In the present study, a literature review was used as a research methodology. Articles published in the field of ethics and artificial intelligence were examined. Conclusion: Based on the review of the existing literature, ethical considerations of digital ethics, including: human dignity, safety, sustainability, understandability, responsibility, self-organization, promotion of happiness and well-being, cohesion and solidarity, democratic participation, fairness, diversity, privacy, security, regulatory-supervisory effect, financial-economic effect, and individual-social effect, were raised, which should be considered in the use of artificial intelligence.

Introduction: Given the expansion of numerous applications of artificial intelligence in the daily activities of human societies and the ethical obstacles that may arise in this direction, the need for a detailed and comprehensive examination of these issues is felt more than ever. Therefore, this study was developed with the aim of examining the challenges of ethical use of artificial intelligence technology. Material and Methods: This study is applied in terms of purpose and descriptive-survey in terms of data collection. Library methods, searching through electronic sources, and field study were used to collect data. In the field method, a questionnaire was used. The research community is experts and specialists in the field of artificial intelligence, 15 of whom were selected through purposive sampling (snowball sampling). By reviewing the literature, 6 obstacles related to the ethical use of artificial intelligence were identified; the DEMATEL method and Excel and MATLAB software were used to analyze the data and evaluate the cause-and-effect relationships between the obstacles. Results: The results show that among the 6 identified barriers (lack of accountability, lack of transparency, lack of legal regulations, possibility of bias and discrimination, violation of data privacy, and violation of social justice and livelihood of individuals), the barrier of lack of transparency, followed by the lack of legal regulations, are considered to be the most important and influential barriers to the ethical use of AI. Also, the barriers of data privacy violation and violation of social justice and livelihood of individuals were identified as the most influential barriers among the aforementioned barriers. Conclusion: The findings of this study indicate the importance and causal relationships governing the existing barriers to the ethical use of AI and can help experts and managers in this field in designing AI systems and making decisions in order to comply with ethical principles.

The traditional anthropocentric understanding of human rights is undergoing a profound re-evaluation in contemporary legal discourse. While historically focused on the individual human being, recent developments in international and regional human rights law reveal a nascent yet significant trend towards extending rights and protections to non-human entities. This article examines the legal basis and implications of recognizing "rights of nature" and considering the human rights dimensions of artificial intelligence, arguing that these emerging subjects challenge and reshape foundational concepts within human rights law. Abstract: The traditional anthropocentric understanding of human rights is undergoing a profound re-evaluation in contemporary legal discourse. While historically focused on the individual human being, recent developments in international and regional human rights law reveal a nascent yet significant trend towards extending rights and protections to non-human entities. This article examines the legal basis and implications of recognizing "rights of nature" and considering the human rights dimensions of artificial intelligence, arguing that these emerging subjects challenge and reshape foundational concepts within human rights law. Abstract: The traditional anthropocentric understanding of human rights is undergoing a profound re-evaluation in contemporary legal discourse. While historically focused on the individual human being, recent developments in international and regional human rights law reveal a nascent yet significant trend towards extending rights and protections to non-human entities. This article examines the legal basis and implications of recognizing "rights of nature" and considering the human rights dimensions of artificial intelligence, arguing that these emerging subjects challenge and reshape foundational concepts within human rights law.