هوش مصنوعی

This article is a speculative essay on the future of the teaching profession, offering a new perspective for reflection in this area. The author argues that under certain conditions, teaching cannot be entrusted to machines. The subtle differences between the actions of a teacher and a pseudo teacher lie within these conditions. If these conditions, based on the theories presented in the article, are used as the criteria for judgment, artificial intelligence and machines cannot replace teachers but will instead act as catalysts alongside them. However, if we move away from the realities of actual teaching practice, not only can machines perform this role and even replace teachers, but such a replacement should be embraced as a smart policy. The article also distinguishes between two states of teaching—namely, true teaching and pseudo teaching—using the expressions "teacher as nurturer" and "teacher as instructor", respectively. It concludes that for longevity in the teaching profession, practitioners must adopt a "teacher as nurturer" approach and strengthen their qualities in this area. Concepts such as the teacher as a curriculum maker and the teacher resistant to artificial intelligence are also introduced to expand this perspective.

The current and expected prospects for the development of artificial intelligence algorithms, especially in military applications, and the research conducted on their application in the field of civilian life are the core focus of this article. In recent years, more attention was paid to the use of artificial intelligence algorithms in cyber security, object detection, military logistics and robotics. This article discusses the related problems and how artificial intelligence can help solve them. It also briefly presents mathematical structures and explanations for ART, CNN and SVM networks, as well as expectation maximization algorithms and Gaussian mixture models used in solving the discussed problems. It also addresses the society's attitude towards the use of neural network algorithms in military applications and finally discusses the basic problems related to ethics in the use of artificial intelligence and issues related to the responsibility of errors caused by independent systems.

This paper aims to provide a detailed overview of the most recent methods and strategies used for detecting fake news, especially in the context of rapid advancements in artificial intelligence and machine learning. With the widespread reach of fake news across social media and other digital platforms, this review focuses on identifying and evaluating effective approaches that can help tackle this growing problem. Given the importance of detecting fake news, this paper reviews and compares various approaches utilized in this field. To this end, by studying articles published in online libraries and document repositories such as IEEE, Scopus, Elsevier, and others, we first explore different methods for detecting fake news. Then, we compare the various approaches of human-based detection with those of automated detection. The review shows that while conventional techniques like feature extraction and rule-based systems offer a good starting point, they often fall short when dealing with the complexity of modern disinformation. Deep learning models trained on large datasets have demonstrated promising results in detecting fake news, yet they still struggle with the subtlety of human-generated content and real-time applications. This highlights the need for more comprehensive solutions that can address these challenges. The findings suggest that an integrated approach—one that combines language analysis, machine learning, and network-based methods—is essential for building effective fake news detection systems. As the field progresses, future research should focus on improving hybrid models, refining data quality, and incorporating user-centric insights to combat the spread of disinformation better. Combining large language models (LLMs) with context-aware systems offers a promising path for achieving higher precision in detecting both machine-generated and human-created fake news.

This research delves deeply into the issues and challenges associated with artificial intelligence (AI) and moral judgment, seeking to answer the fundamental question of how AI can play a role in human moral decision-making. 

The study employs an analytical-descriptive approach, utilizing library research to examine existing literature and resources related to AI, ethics, and moral judgment. 

AI, through complex algorithms and machine learning, is capable of processing information and making decisions across various domains. The application of AI in moral judgment offers benefits such as increased accuracy, speed, and impartiality. However, several challenges persist, including a lack of understanding of moral nuances, bias, and a deficiency in creativity and innovation. 

Currently, fully entrusting moral judgment to AI is unreliable. AI can serve as a tool to assist humans in the moral judgment process, but final decision-making should remain with humans.

This research examines the functions of new media equipped with artificial intelligence in the field of religion. The main objective of the study is to understand the potential impacts of artificial intelligence on religious beliefs and practices, as well as its role in shaping and reproducing religious concepts. Additionally, it evaluates the challenges and opportunities that artificial intelligence may create in providing information and answering religious questions.

Methodology of the Research: 

This research is qualitative and was conducted with an analytical and descriptive approach. Data were collected by posing specific questions to artificial intelligence bots related to internet media. This approach helped researchers to study more deeply the impact of artificial intelligence in responding to religious questions and to examine the potential for changes in this area.

The findings of the research indicate that the use of artificial intelligence can significantly impact responses to religious questions and the interpretation of religious texts. Given the rapid advancements in this technology, assessing its capabilities and effects as a widely used tool for addressing religious inquiries and teachings appears to be essential.

The results indicate that the use of artificial intelligence bots can create challenges related to the quality and manner of user interaction with religious information. These interactions involve how users engage with Chatbots and the impact of these interactions on users' critical thinking and their understanding of religious information. The emergence and expansion of artificial intelligence in the field of religion have raised new questions about its role in reproducing and changing religious beliefs. The findings of this research clarify that artificial intelligence can have a significant impact on shaping religious concepts and practices. Accordingly, various scenarios that may arise from the continued integration of this technology into religious practices and beliefs were examined, highlighting that improving responsiveness and enhancing cognitive depth regarding religious concepts through this technology requires sustained continuity and knowledge enhancement in this area.

In recent years, the prediction of traffic density and the use of artificial intelligence in it has become a growing research field, and today, considering artificial intelligence as an advanced technology, it is possible to provide innovative and effective solutions for urban traffic management, and past experiences have shown that not using these technologies, increases traffic problems day by day. Therefore, the use of these technologies to solve traffic problems is of great importance.
  In this research identifies and prioritizes the requirements of using artificial intelligence in traffic management, and then provides solutions for the future of these requirements. The data of this research was obtained from the studies of previous works, experience of the authors, and also through in-depth interviews with 20 of the main experts in the qualitative phase and 45 of the intermediate experts through a researcher-made questionnaire in the quantitative phase, which are the statistical population experts of scientific centers, specialized police officers experts with at least bachelor's education in fields related to artificial intelligence and traffic and several years of activity related to this field. In order to determine its validity, were used the opinions of experts, and the reliability of the questionnaire was determined with Cronbach's alpha coefficient and its value was 0.88, and Friedman's test was used for prioritization.
By collecting and coding the information, a conceptual model was presented to identify the requirements for the use of artificial intelligence, and the authors were able to present a practical framework in five main dimensions and 43 components, which according to Friedman's test importunes factor are related to data with 84.71% and education and human were identified with the lowest factor load.
According to the existing situation of the responsible organizations in the management of traffic, in order to achieve the acquired requirements and reach the desired state, should be train the forces continuously and comprehensively and at the international level in the fields of artificial intelligence, and continuously equip the guidance centers, and analysis of extracted data, and executive the maneuvers, and evaluating the actions taken and fixing the observed defects, concluding multilateral international contracts to provide various infrastructure services, etc

The aim of this article is to examine and measure the position of religion and its relationship with artificial intelligence within the framework of new media, and to investigate the connection between the potential capacities of religion and artificial intelligence technology in new media contexts.

This article adopts a research approach and is conducted using documentary-library methods and descriptive-analytical techniques.

Today, internet platforms, AI-based algorithms, and various religious sources such as sacred texts, sermons, and worship materials activate according to individual preferences and beliefs. Technologies like virtual reality (metaverse) enable individuals to participate in virtual pilgrimages, religious ceremonies, and public worship, creating a new environment for the utilization of new media sciences in service of religious followers in the digital age.

The relationship between the position of religion and artificial intelligence in the context of new media can lead to a healthy and fruitful use for followers and those concerned with the fields of religion and media. Additionally, defined artificial intelligence in various media tools can be utilized for various religious practices and rituals. It is essential to leverage new opportunities in today's world to enhance the position of religion and to confront challenges in a correct, specialized, and scientific manner.

This article, titled "The Future of Media Management in Light of the Impact of Artificial Intelligence and New Media on Religion," has been written to address a novel topic. Given the significant advancements in the field of artificial intelligence and new media technologies, the role and impact of these two factors on religion and media management are of high importance. This research aims to achieve effective and useful results for individuals and organizations involved in media management by addressing the mentioned issues.Research

The research employs a qualitative method using future scenario writing to explore the impact of artificial intelligence and new media on religion and the future of media management. Discussing its challenges will also assist media managers in finding the best strategies for utilizing artificial intelligence and new media in media management, thereby contributing to knowledge development in this area.

Based on the findings, with the rapid and increasing growth of technology in the near future, it seems we will witness an interdependence and influence among media. In other words, we will observe the impact and utilization of this technology (artificial intelligence) in most information sources and communication channels for transmitting various types of messages (both religious and non-religious) to target audiences through different media channels.

Ultimately, this article aims to provide guidance for future media managers by examining and referencing the applications or functions of artificial intelligence across various media industries, while also suggesting recommendations for other researchers.

Today, we are witnessing a wide range of concerns about the jeopardy of the human position in relation to artificial intelligence-based technologies. The study field of human-centricity artificial intelligence was established in response to these concerns, as it was necessary for human involvement in the development of these systems. The current research is an endeavor to encourage and fortify the convergence of two potential study forces—sociology and artificial intelligence—in order to establish the human-centricity concept.A systematic review of the existing literature was implemented in this investigation. The projectile sampling strategy was implemented to conduct the sampling. The primer set and articles were selected in accordance with the PRISMA guidelines. To analyze the data, we used Double Diamond innovative design framework.The research findings were categorized into eight levels, including: Human-centricity artificial intelligence; Problems of human-centricity artificial intelligence in the production of social sciences and sociology; Interdisciplinary research on the human-centricity concept in sociological studies of artificial intelligence; The position of human-centricity artificial intelligence in the methodology of social sciences; Principles and regulations governing the explainability of artificial intelligence; The significance of the human-centricity concept in the comprehension and perception of artificial intelligence by actors; Artificial intelligence and human interaction; Specific disciplines of study that are oriented toward human artificial intelligence.Two problems related to artificial intelligence and three problems related to humans (in the general sense) were identified through the systematic review of the existing literature. The coexistence of the issues, as well as the adoption of varying perspectives by the articles under investigation in relation to the aforementioned issues, has resulted in the development of 22 distinct approaches to addressing these issues.

The public sector is facing diverse and complex challenges in the current era. Solving these challenges, which are often related to the development of communication and data, will not be possible except by benefiting from the capacities created by these technologies and realizing data-driven governance. Artificial intelligence technology is one of the revolutionary technologies in the current era that can be used to improve the quality of governance. In order to apply this technology, it is necessary to first consider possible obstacles and challenges in a conscious way. Therefore, in the current research, after a systematic review of the literature, 16 obstacles and challenges of using artificial intelligence in the public sector have been identified and prioritized using the fuzzy simple weighting method(FSAW). According to the findings, "access to data and its quality" have been identified as the most important obstacle, and "ignoring public and social considerations" as the most important challenge. Finally, the identified cases are placed in 6 economic, social, political, managerial, technological and ethical categories, and policy recommendations are proposed according to each category and relevant stakeholders.

The rapid advancements in artificial intelligence (AI) are reshaping various industries, and journalism is no exception. As a cornerstone of democratic societies, journalism plays a vital role in informing the public, shaping opinions, and holding power to account. However, the increasing integration of AI into journalistic practices brings both opportunities and challenges. AI enables the automation of content production, enhances data-driven journalism, and improves audience engagement through personalized content. On the flip side, it raises concerns about ethics, accuracy, trust, and employment in the media sector. This paper explores the future of journalism in the age of AI using the Pillkan model, which provides a structured approach to futures studies by analyzing constants, trends, uncertainties, wildcards, and images of the future.

This study aims to investigate the profound impact of AI on journalism and media content through a comprehensive exploration of the factors shaping its future. The objectives include:Identifying constants and trends in journalism influenced by AI. Analyzing uncertainties and potential wildcards that may disrupt the field.Exploring desired and undesired images of the future to inform strategic decisions in journalism. Methods. The research adopts a qualitative approach rooted in futures studies, utilizing the Pillkan model as the primary framework. Data were analyzed systematically across the model’s five key factors. For each factor, key findings were derived from credible sources, including scientific studies, industrial reports, and expert insights. These sources provided a robust basis for identifying the constants, trends, uncertainties, wildcards, and images shaping the future of journalism in the AI era.

The analysis revealed several key findings across the five factors:Constants: Core values such as ethical standards, transparency, public trust, and the supervisory role of journalism were identified as enduring foundations. These elements serve as guiding principles for integrating AI into media practices.Trends: The growing use of AI in automating content production, the rise of data-driven journalism, and the personalization of media content are shaping the future of journalism. These trends highlight AI's potential to increase efficiency and audience satisfaction.Uncertainties: Key uncertainties include the regulatory landscape for AI in journalism, audience acceptance of AI-generated content, and the economic implications of automation. These factors present challenges that require adaptive strategies.Wildcards: Potential disruptions such as the emergence of Artificial General Intelligence (AGI), large-scale cyberattacks on media systems, and environmental crises due to AI's energy demands could drastically alter the trajectory of journalism.Images of the Future: Desired images include improved audience engagement, higher content accuracy, and the democratization of information through AI. Conversely, undesired images involve reduced public trust, ethical breaches, and the monopolization of AI technologies by a few powerful corporations.

The findings underscore the dual nature of AI's impact on journalism. On one hand, AI offers tools to enhance productivity, accuracy, and audience connection. For instance, AI-driven tools can analyze large datasets in seconds, enabling journalists to uncover stories that would otherwise remain hidden. However, ethical concerns surrounding bias in algorithms, loss of human jobs, and potential misuse of AI for spreading misinformation remain significant challenges.Strategically, media organizations must embrace AI while safeguarding human creativity and ethical standards. Policymakers should implement regulatory frameworks to ensure AI transparency and fairness. Moreover, investing in AI literacy among journalists is crucial to striking a balance between technological advancement and journalistic integrity.

This study provides a comprehensive framework for understanding the interplay between AI and journalism, revealing a nuanced landscape of opportunities and challenges. While AI holds immense potential to transform journalism, its integration requires careful management of ethical, economic, and societal factors. By navigating uncertainties and leveraging AI's strengths, the media industry can ensure a sustainable and innovative future.

Higher education, as one of the most crucial societal institutions, requires innovation in teaching methods to respond to the rapid and complex changes of the modern world. This study aims to identify the dimensions and components of innovative teaching methods in higher education.

This qualitative study was conducted using a content analysis approach. Data were collected through semi-structured interviews with experts and faculty members of Tehran universities during the academic year 2022-2023. Data analysis was performed using NVivo software and thematic analysis.

Five main themes were identified in this study: innovative teaching, artificial intelligence in educational innovation, smart innovation management, innovation and entrepreneurship development, and information technology. Each of these themes was divided into various components and concepts.

The study results indicated that innovation in teaching methods can enhance the quality of education and learning in universities. Additionally, challenges such as technical issues and the need for cultural changes were highlighted. To achieve desirable outcomes, it is necessary for all members of the academic community to participate in the innovation process and leverage each other's experiences and knowledge.

Media is one of the most affected industries by technological changes. The applications of artificial intelligence in the media industry encompass a wide range. On the other hand, AI can also have many negative consequences. In fact, anything that is fully automated can be subject to misuse. One of the organizational protective measures against the dangers of AI, and perhaps the most critical first step to prevent these outcomes, is the ethics of artificial intelligence. This paper first examines the ethical challenges in the media industry and then explores strategies for addressing these ethical challenges. 

This article adopts a review-analytical approach, providing evidence and analysis of the subject. Data were collected through library methods and by referring to academic and electronic sources. The analysis of the data was based on structured reasoning and inference. 

The review indicates the ethical challenges facing the media industry in relation to artificial intelligence, which include: privacy preservation, data monitoring and protection, bias (lack of neutrality)., contributing to the occurrence of riots and jeopardizing public security, elimination of media jobs, devaluation of human worth, economic power monopolization, disputes over ownership of media products, and the proliferation of deepfakes and misinformation. 

Identifying ethical challenges alone is not sufficient; it is essential to devise solutions for them. Drafting enforceable laws, conducting ethical audits, and utilizing digital media literacy are considered as strategies to address the ethical challenges of artificial intelligence.

In today's world, Artificial Intelligence (AI) is considered one of the most advanced technologies and plays a crucial role in the development and enhancement of police forces. With the increasing complexity of crimes and security challenges, law enforcement agencies require intelligent and efficient solutions to address new threats. This paper examines the diverse applications of AI in law enforcement, including crime prediction, traffic monitoring, and facial recognition systems. AI, with its capabilities in data processing, pattern recognition, and information analysis, helps police forces respond more effectively and swiftly to threats. For example, machine learning solutions can identify crime patterns and assist law enforcement in having a more significant presence in high-risk areas. However, this innovative technology also comes with challenges, such as privacy issues, algorithm accuracy, and the need for appropriate infrastructure. This paper analyzes these challenges and applications and provides strategies for optimal utilization of AI in law enforcement. Given the importance of this topic, it is expected that the results and recommendations presented in this paper will guide officials and decision-makers in enhancing security, public order, and organizational efficiency. Ultimately, by using AI, law enforcement can effectively contribute to improving community order and security and address new security challenges.

Artificial intelligence (AI), as a transformative technology, holds significant potential for addressing the complex challenges of drugrelated issues. This paper explores the role of AI in combating drug trafficking and abuse through three main aspects: identification, prevention, and intervention.

this article is a descriptive- analytical one.

The findings show that the role of AI in combating drug trafficking and abuse is through three main aspects: identification, prevention, and intervention. In the identification phase, AI utilizes big data analytics and computer vision to detect and track drug trafficking networks. These technologies are capable of analyzing financial transactions, spatiotemporal data, and social network information to identify trafficking patterns. In the prevention phase, AI leverages genetic analysis and technologies such as virtual reality (VR) and augmented reality (AR) to identify atrisk individuals and deliver preventive educational programs. Additionally, chatbots and intelligent systems play a crucial role in reducing drug demand by providing counseling and psychological support. In the intervention phase, AI employs machine learning and AIequipped drones to enable early detection of addiction, personalize treatment programs, and enhance border surveillance. These technologies improve the accuracy and speed of security operations, playing a key role in reducing drug production and distribution.

Although AI has a unique role in combatting drug crimes, However, challenges such as high costs, ethical concerns, and the need for accurate data limit the widespread adoption of these technologies.

Since the past, innovations have dramatically changed people's quality of life and played an important role in all aspects of humans' lives. The internet, social media, and e-books are well-known examples of current worldwide innovative breakthroughs. Despite innovations' advantages, they can lead to some negative consequences or harmful effects such as online fraud, copyright infringements and privacy violations which need to be regulated by law. In fact, the law seeks to regulate innovations in a way that protects users' rights while reducing risks. Every country have passed numerous laws to regulate the online sphere and the European Union is a legislative body which has created various laws on different topics in its European member states.“The European Union” was established after the Second World War in the European region according to “the treaty of Maastricht”. Human dignity, freedom, equality, human rights, and the rule of law are the values of the European Union (The EU). Generally, the EU has four main institutions with important responsibilities. “The European commission” offers new laws and “The Parliament” and “The European Council” enact them in forms of directives and regulations. Additionally, the Commission monitors member states to ensure that rules are implemented correctly. The Court of Justice of the European Union (CJEU) interprets EU laws to ensure that they are applied uniformly in all EU countries, and resolves legal disputes between national governments and EU institutions. Therefore, EU has been active in making laws and implementing them. Therefore, since the emergence of new technologies, in particular the Internet, the EU has been constantly trying to solve the internet legal problems. In 2017, the Commission stated that digitization provides many benefits in terms of innovation, employment, growth and cultural diversity. Taking advantage of these opportunities requires a collective response to some of the challenges caused by digital transformation and a review of policies affected by digitalization. The EU has enacted many laws such as General Data Protection Regulation (GDPR) for protecting natural person’s data, the Digital Markets Act (DMA) with the aim of reaching potential economic growth in a coherent manner and the Digital Services Act (DSA) for safe and secure activities in the digital space.  Now, the complicated innovation “Artificial Intelligence” (AI) has brought new legal problems. AI is not a new innovation. Actually, AI has been rooted in the previous century, when Alan Turing, a British mathematician, made The Bomb to encode the Enigma code which was used by the German army in the Second World War. After its successful function, working on AI has continued to grow with all of its ups and downs. Now, AI tries to simulate the function of  human’s brain and on the ground of using new technologies, improved scientific methods and developed computer science, AI has improved and become generative. Generally, Generative AI works based on a complicated process which consists of deep learning, machine learning, natural language processing (NLP) and artificial neurons. These parts work completely related together to analyze and organize input data to answer users’ requests clearly and exactly. So, this function is like the human's brain function and has its difficulties, ambiguity and complexity. Also, artificial intelligence functions are broad and complex. This is used for a variety of purposes, from recipe suggestions to complex math problems and if it has mistaken, it can learn from them to correct its mistakes and improve its abilities. This technology helps human beings a lot in various majors such as medical diagnosis, automatic translations and natural disaster predictions. However, due to its game-changing nature, it poses new challenges for law enforcement and policymakers. Specifically, the European Union has tried to regulate Artificial intelligence with current laws and new policies. In 2018, In addition to emphasizing the guarantee of data protection and ethical standards, with the aim of preventing the risks of artificial intelligence and using its benefits, artificial intelligence was aligned with the legislative priorities of the European Union. In 2020, European Union published a report on "the European approach to excellence and trust" in artificial intelligence, which emphasized the existence of clear rules and a safe environment to build people's trust in artificial intelligence, with supporting the artificial intelligence growth and development. In order to synchronize laws related to artificial intelligence, a single and comprehensive law on artificial intelligence was reviewed by the European Commission, the Council of the European Union and the European Parliament. The draft was proposed by the European Commission in 2021 and approved by the European legislators in 2023. Despite the definitions and purposes in this draft, the risks of using AI systems are introduced and regulated. The use of AI systems to create or expand facial recognition databases, recognize people's emotions in workplaces and educational institutions, and using “biometric classification systems'' are all examples of the inhibited risks of AI which are fortunately prohibited unless the law specifically allows for these risks.  Additionally, there are high AI risks associated with AI systems in products. These products are protected by General Product Safety Directive (GPSD) 2001/95/EC and the new AI regulations. In addition, intelligence systems used in administrative, employment, immigration, asylum, and border management must be recorded in the EU data repositories. However, all challenges are not limited to risks. About copyright, directives and regulations have been in force since 1991 and now Directive 2019/790 contains provisions on the protection of copyright in the digital field. Therefore, when generative AI uses a lot of data for text and data mining (TDM) or other purposes, this data collection input must be used with their authors’ authorization. Additionally, after the content is produced, it must be shown that the content was created by artificial intelligence so that users can know whether the creator is human or not.In conclusion, this article endeavors to explain the history of the European Union and its groundbreaking legislative measures in different subjects, specifically in artificial intelligence. Some provisions of the draft of the AI Act are analyzed which are new in the world and they can affect other countries’ legislations in the AI field.