The study explores the emerging role of Artificial Intelligence (AI) in mathematics education by systematically reviewing recent empirical and conceptual research published between 2020 and 2025. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, fourteen relevant articles were selected through defined screening and evaluation procedures. The review identifies three major applications of AI in mathematics education— personalized learning, problem-solving support, and content generation—and three major benefits, namely enhanced learning engagement and motivation, deeper conceptual understanding, and improved accessibility and convenience. Likewise, three critical challenges are recognized: issues of accuracy and reliability, reduced human interaction, and misalignment with existing curricula. The findings suggest that while AI presents transformative potential in mathematics teaching and learning, its integration should be grounded in pedagogical reflection, ethicalawareness, and curriculum innovation. The study concludes that AI, when thoughtfully integrated with human intelligence, can reshape mathematics education toward more interactive, inclusive, and learner-centered practices.

The following research Article describes a gender centered account of the exemplary operational strategies of the Israeli intelligence facilitation firm the Mossad through the documented life of two women i.e., Sylvia Rafael and Catherine Perez-Shakdam. Based on archival information, memoirs, declassified records, and reliable media investigations, the paper will analyze the use of gender and identity construction and ideological orientation in human intelligence (HUMINT) operations. One of the participants of the Cold War, the undercover Israeli campaign after the Munich massacre was Sylvia Rafael who worked under the alias of a journalist to help locate the desired targets. Catherine Perez-Shakdam is a contemporary political commentator who was a contributor to Iranian state media, subsequently publicly denounced her religious identity, raising concerns with the manipulation and control of ideology and access. It does not make speculative conclusions, yet the paper presents patterns in the use of gendered identity in intelligence that can be verified. It forms part of the critical research in the field of intelligence in wondering how the traditional and non traditional facets of espionage become grown-up reliant on the performative identity within the notionally sensitive political set ups.

ABSTRACT This study examines public perceptions of the risks associated with Generative Artificial Intelligence (GenAI), focusing on its potential ‘epistemic power’ – i.e., its capacity to redefine knowledge production – including its ability to blur the boundaries between real and fully synthetic content, thereby facilitating misinformation and potentially undermining democratic stability. We posit that social media use, GenAI familiarity, and the ability to discern synthetic content result in asymmetric risk perception patterns through mechanisms of digital habituation, agency, control, and fear. An online survey experiment (N = 1,800) shows that social media use and tech-savviness lower perceived risks, while unfamiliarity heightens ‘epistemic fear’. Priming with GenAI political content increases risk sensitivity, especially among less AI-savvy respondents. By demonstrating the asymmetric role of exposure in modulating risk perceptions and bringing attention to the complex interplay between human agency and artificial intelligence, this study questions deterministic accounts of the epistemic power attributed to Generative AI technologies. Instead, it emphasizes how individuals’ digital trajectories and modes of engagement inform their responses to AI-generated political content, but it also suggests that tech-savvy users may potentially underestimate GenAI’s societal threats due to overconfidence, while less experienced users may overestimate them as a result of digital exclusion and epistemic fear.

How useful is human intelligence for evaluating artificial intelligence?

The author attempted to trace the background, outcome, and consequences of the war between Iran and Israel, which can be described as unexpected but expected. The Iran-Israel war in the summer of 2025 was the most acute, armed form of permanent conflict between these countries, which has lasted for over 45 years. Even before coming to power, Ayatollah Khomeini, the founder and first leader of the Islamic Republic of Iran (IRI), criticized the State of Israel in his articles and speeches, arguing that its existence was illegal and unacceptable, and that its destruction was necessary. This concept has become the core of the state ideology of Iran – Khomeinism or neo-Shiism. There are three distinct stages of confrontation between the two countries. The first was the end of the 80s of the twentieth century, characterized by propaganda confrontation. The second, 2003–2024, saw Iran’s nuclear program become the primary factor, and both sides moved toward more active subversive actions. The third stage, from 2024 to the present, is characterized by direct armed conflict. The Iran-Israel conflict has taken various forms over the course of more than four decades: from information wars, proxy wars, and cyberwars to the “hot” war of 2025. The Iran-Israel war had its own unique characteristics, the most important of which were the distance between the warring parties, the absence of a line of contact, the impossibility of using ground forces, and the priority given to missile forces and drones, as well as human and space intelligence. Thus, the summer of 2025 marked the “moment of truth” for Iran, when the country’s future fate are being resolved.

The transition from Industry 4.0 to Industry 5.0 marks a paradigm shift from automation and digitalization toward a human-centric, sustainable, and resilient industrial ecosystem. This review paper explores the evolving role of <i>Industrial Engineering (IE)</i> within the framework of <i>Industry 5.0</i>, emphasizing the integration of advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), robotics, digital twins, and additive manufacturing with human intelligence and creativity. Unlike its predecessor, which primarily focused on efficiency and productivity through automation, Industry 5.0 aims to <i>restore the human touch in manufacturing</i>, ensuring that technology augments not replaces human capabilities. The paper synthesizes recent scholarly contributions and industrial case studies to identify how Industry 5.0 redefines traditional IE domains including <i>operations optimization, production planning, quality control, ergonomics, and supply chain management</i>. Furthermore, it discusses the alignment of Industry 5.0 with global sustainability goals, circular economy principles, and socio-technical resilience. The review highlights how Industrial Engineers act as key enablers in designing <i>human</i><i>-</i><i>machine symbiotic systems</i>, optimizing smart factories, and ensuring ethical and sustainable deployment of emerging technologies. Finally, the paper outlines research gaps and future directions, advocating for interdisciplinary frameworks that combine <i>engineering, data science, and human factors</i> to achieve a more inclusive and adaptive industrial future. By bridging technology with humanity, Industry 5.0 offers Industrial Engineering a renewed relevance in shaping the factories of tomorrow intelligent, empathetic, and sustainable.

The integration of artificial intelligence (AI) and 3D printing technologies is transforming the field of personalized prosthetic design. It offers solutions that meet the specific needs of different patients. Traditional prosthetics have problems such as long manufacturing cycles, high prices, and inability to meet the specific needs of a small number of patients. However, if AI technology is combined with 3D printing technology, each patient can be given a unique diagnosis, and a personalized diagnosis can be provided. The service of providing customized prosthetic limbs for each patient. Prosthetics play a significant role in restoring the mobility of disabled individuals and improving their quality of life. However, traditional prostheses have limitations, such as long manufacturing cycles (The period of a normal prosthetic limb picking date is about 4 to 8 weeks), high prices (This results in the poor being unable to use prosthetic limbs), and inability to meet the special requirements of specific groups of people. For example, children and athletes often have different prosthetic needs than the general population. Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence. Combining artificial intelligence technology with 3D printing provides solutions to the challenges faced by ordinary prosthetics.

The article offers a comprehensive examination of Open Source Intelligence (OSINT) as one of the key instruments for countering information warfare, disinformation campaigns, and hybrid threats in the contemporary digital environment. The relevance of the research stems from the increasing scale of informational influence, the use of social media to manipulate public opinion, and the growing role of digital technologies in modern military-political conflicts. In light of the challenges triggered by the full-scale armed aggression of the Russian Federation against Ukraine, particular attention is devoted to analysing the analytical potential of OSINT in detecting, documenting, and refuting fake narratives, collecting evidence of war crimes, and strengthening the strategic communications of the state. The study classifies the principal branches of OSINT, including geospatial intelligence (GeoINT), social media intelligence (SOCMINT), technical intelligence (TECHINT), and specific elements of human intelligence (HUMINT), which collectively form a multi-layered system of gathering, verifying, and validating data from open sources. The methodological approaches to information analysis and verification algorithms are elucidated, and contemporary tools for automating data collection using artificial intelligence systems – particularly AI-assisted OSINT – are presented as means of significantly enhancing analytical efficiency. At the same time, the article emphasises the legal and ethical dimensions of open-source intelligence, focusing on the protection of personal data and adherence to the principles of legality, proportionality, and data minimisation, in accordance with the requirements of the EU General Data Protection Regulation (GDPR). Both national and international approaches to the legal regulation of OSINT use in law-enforcement and judicial practice are analysed. The scientific novelty of the study lies in the integration of technological, legal, and ethical dimensions of OSINT application as a tool for evidence gathering and countering informational threats. The paper concludes that the development of unified international standards for the collection and verification of OSINT data is essential to ensure their legitimacy in criminal proceedings, enhance state information security, and promote a culture of responsible and ethical use of open data within democratic societies.

The article analyzes the topic "Modern Society and Artificial Intelligence: Current Philosophical, Cultural, Ethical and Moral Aspects". The purpose of this article is to show the influence of AI on society, to analyze current philosophical aspects of the interaction of society and artificial intelligence. It is stated that the focus of research on Artificial Intelligence (AI) has shifted significantly over the past thirty years: if earlier the essence of the problem was seen by most researchers as whether it is possible to create some artificial analogue of human intelligence, now it has actually turned into a conglomerate of a wide variety of problems and tasks related, for example, to modeling the psyche, thinking, pattern recognition, robotics, automatic proof of theorems, etc. However, such a transformation does not mean that the idea of artificial intelligence as an integral phenomenon has no real content and that we should abandon attempts to solve the problem of the possibility of such an artificial intelligence. However, in order for our attempts to become more fruitful, we should radically reconsider the status of this problem. Until now, it has been classified as "complex", "interdisciplinary", etc. However, in our opinion, it will be much more fruitful to consider it as having a fundamentally philosophical nature, that is, as a purely philosophical problem. To study the problem through the prism of a new scientific direction, such as the philosophy of artificial intelligence. The author also made an attempt to briefly characterize the AI revolution of artificial intelligence, to look at the philosophical reflections that it causes. The article considers the fundamental philosophical-cultural, ethical-moral aspects of the problems arising in society as a result of the use of AI systems. The final section of the article presents the author's recommendations on the topic.

The post-digital era marks a profound shift in the creative disciplines, where human imagination and computational intelligence converge to redefine authorship, aesthetics, and design practice. This research explores this transformation through the lens of WebDraw, a machine learning–driven system for automatic website prototyping. Positioned at the intersection of artificial intelligence, computational creativity, and post-digital design, WebDraw exemplifies how automation can evolve into a form of creative collaboration rather than mere efficiency. By analyzing WebDraw’s architecture, workflows, and cultural implications, the research argues that design in the post-digital condition is characterized by hybrid authorship, distributed among humans, algorithms, and data. The discussion unfolds across theoretical and practical dimensions: first establishing a conceptual foundation in post- digital design and computational creativity; then presenting WebDraw as a case of human–machine co-creation in web design. Aesthetic evaluation, collaboration dynamics, ethical considerations, and sustainability concerns are explored. Based on both quantitative system evaluations and qualitative interviews with web professionals, the research highlights how WebDraw fosters co-creation, democratizes access to design, and challenges traditional notions of origin, authorship, and creative control. Ultimately, the research positions computational design systems as agents of cultural transformation, expanding the boundaries of creativity, reconfiguring professional practice, and calling for new frameworks in design education and ethics. Through the lens of WebDraw, post-digital creativity emerges not as the replacement of human agency but as its extension through intelligent collaboration.

This article provides a definition of the term "bilingualism", highlights various types, stages, conditions for the formation and development of this phenomenon, and considers the socio-communicative component of bilingualism. The article also raises the problem of the tolerant coexistence of two languages and cultures in certain social conditions and the competent use of human intelligence as the main tool for the development of an individual in a bilingual community.

Bloodstain pattern types, such as wipes and swipes, are frequently encountered at crime scenes and can offer critical insight into the sequence of events. However, these pattern types can be difficult to reliably distinguish, highlighting the need for modern, objective approaches to classification that reduce the potential for human error. In this study, 50 participants were asked to classify 40 test bloodstain pattern images (20 wipes and 20 swipes). These same images were subsequently classified using Microsoft Azure Custom Vision (MACV), an artificial intelligence (AI) image recognition platform. The MACV model was trained using 5425 bloodstain pattern images, including impact, expirated, cessation cast-off, wipe, and swipe stains, across a range of background colors. At the 50th training iteration, the AI achieved 100% accuracy in classifying both wipe and swipe patterns, outperforming participants who achieved an average accuracy of 52% (47% for wipes and 57% for swipes), marking a 48% improvement in classification performance. The model was further trained to the 80th iteration using rotated images, achieving 98.75% accuracy on the rotated test set.

The demands of a globalized economy challenge organizations to manage knowledge effectively across diverse cultural landscapes. Traditional knowledge management (KM) systems prioritize efficiency but often lack the cultural adaptability and ethical flexibility required in multicultural contexts. Drawing from Peter Drucker’s management philosophy, this paper introduces a Yin-Yang framework for cross-cultural KM, merging the structured capabilities of artificial intelligence (AI) with the adaptive, ethically guided insights of human intelligence. In this model, AI functions as the “Yin” component, delivering scalable, consistent processing, while human intelligence embodies the “Yang” element, contributing cultural sensitivity and ethical discernment. Synthesizing findings from 35 recent studies, this framework addresses critical limitations in current KM models by embedding cultural intelligence (CQ) into KM practices, enabling organizations to apply AI-driven insights that respect local norms and values. This approach supports sustainable knowledge sharing, ethical decision-making, and an adaptable feedback cycle informed by human input. Practical implications for multinational organizations include improved cross-cultural collaboration and an ethically aligned, responsive KM system. Future research directions are proposed to empirically evaluate the framework’s adaptability and effectiveness across various sectors.

Artificial intelligence (AI), as a unique multi-innovation, is the result of the action of human intelligence in an anthropocentric innovation model. The intensive development of innovative and autonomous capabilities of AI is a challenge for the transformation of the anthropocentric innovation model. The main aim of the research is to highlight the opportunities and challenges in the field of generating and protecting innovations, which will arise as a result of the fusion of human intelligence and AI. By using a proactive approach, the authors offer insights into the fusion of human intelligence and AI, as a brand-new innovation resource that will affect: the emergence of a new hybrid innovation model, changes in the structure of innovations, the emergence of multi-innovations, the redefinition of the concept of innovation portfolio, the conception and implementation of new intellectual property (IP) policies that will permit the establishment of a balance between human autonomy and the absence of discrimination against AI, as well as adequate legal protection for innovations generated by the fusion of human intelligence and AI. The research results show that the fusion of human intelligence and AI simultaneously represents: a stimulus for redefining and improving the innovative capabilities of human intelligence and the continuous development of innovative and autonomous capabilities of AI, as well as a catalyst for positive changes in the innovative model, which still remains focused on humans. In the near future, the fusion of human intelligence and AI will become a framework for research with scientific, economic, legal and political significance, and a radical systemic impact on society as a whole.

Interactive graph search (IGS) has emerged as a powerful paradigm for information retrieval across diverse applications. The goal of IGS is to identify the most appropriate (i.e., deepest) node within a hierarchy for an unknown object, typically leveraging human intelligence such as crowdsourcing as the oracle. Existing IGS algorithms usually rely on reachability queries, such as "is the target node reachable from node x ?", and assume that correct answers are always available. However, in practice, answering such queries is challenging due to the requirement for domain-specific knowledge, resulting in frequent errors in the oracle's responses. As a consequence, the reachability-query-based approaches would perform poorly. In this paper, we propose a practical solution to the IGS problem, leveraging the power of large language models (LLMs) to tackle the issue of reachability queries. Specifically, we formally analyze the inherent properties of real-world hierarchies with the notion of ambiguous nodes and overlapping nodes to debunk the difficulty of reachability queries. In addition, we develop a practical oracle based on LLMs that can answer reachability queries on (near) leaf nodes accurately. Building on the LLM oracle, we propose a similarity-based upward search algorithm, namely SuS, to address the IGS problem. We further enhance SuS with layer-wise search and fast initialization techniques. We evaluate SuS on two real-world datasets against four baseline methods, and the experimental results clearly demonstrate the superiority of our solution.

Abstract The rapid rise of generative artificial intelligence (AI) is transforming the landscape of human cognition, education, and society. This position paper explores the implications of generative AI for human intelligence, creativity, and wisdom, with a particular focus on educational contexts. Drawing on cultural, psychological, and educational theories—especially the framework of adaptive intelligence and the Teaching for Active Concerned Citizenship and Ethical Leadership (ACCEL) model—we argue that AI challenges foundational human cognitive abilities by automating tasks traditionally central to learning and intellectual, creative and ethical development. We examine how AI reshapes the cultural attributes of human intelligence and creativity—context dependence, dynamism, and modifiability—highlighting both the potential for cognitive amplification and the risks of cognitive deskilling. The paper also addresses the erosion of critical thinking and the ethical dilemmas posed by AI’s integration into education. While acknowledging the benefits of AI, such as personalized learning and enhanced productivity, we caution against overreliance and the uncritical adoption of AI-generated outputs. We advocate for an educational response that prioritizes the cultivation of analytical, creative, and ethical reasoning—skills that remain uniquely human and essential for democratic citizenship. The paper concludes by examining the motivational forces driving AI development and adoption, and by calling for a renewed commitment to preserving human autonomy, intellectual integrity, and wisdom in an increasingly machine-mediated world. Ultimately, the future of human intelligence and creativity in the age of AI will depend not only on technological advances but on the values and educational practices we choose to uphold.

This study will turn around the difficulties non-English speaking researchers encounter when they try to communicate their local research in the globalized context of international conferences (such as IIIS), where English is used as <strong><em>lingua franca</em></strong>. The presenter will embroider her presentation around a technical term in English - such as <strong>grid</strong> - and in Modern Greek - such as <strong>θέμα</strong> (: t<em>opic</em> of an essay; t<em>heme</em>, as in 'thematic units'; and i<em>ssue</em>, as in "there is an issue here"), compare them with their equivalent terms in Spanish, French and German and try to systematize the research steps (or advanced translation steps and tools) required for a non-English speaking scientist to find the right term in order to make himself/herself understood by a wider international public who communicates in English. During the discussion, the author of this study will try to show how far the AI can help HI (Human Intelligences or <em>nous</em>) in this kind of research, depending on whether researchers are: (1) aware of the polysemy of scientific discourse (i.e. the non-existence of 1:1 equivalence of terms between at least two different linguistic systems), and (2) trained in using comparative and associative thinking. As the writer of this study will claim, it is finally HI who decides which term(s) s/he is going to use, exercising his/her own judgement after s/he has taken into consideration the scientific and social context of the term.

Natural born intelligence manifesto: Illustrating the dynamic perspective for consciousness.

ABSTRACT This research investigates how the source of a checkout charity appeal—human versus artificial intelligence (AI) agent—interacts with contextual (time pressure) and psychological (persuasion knowledge and access to ulterior motives) factors to shape consumer donation and store patronage intentions. Grounded in the self‐regulatory resource depletion framework and the Persuasion Knowledge Model (PKM), we conducted four, between‐subjects experiments (total N = 898), each designed to isolate a specific boundary condition under which AI versus human appeals differ in effectiveness. Study 1 manipulated situational time pressure and found that AI‐led appeals increased donation intentions under high time constraints due to their lower social demands, whereas human‐led appeals were more effective when time pressure was low. Study 2 extended this effect by treating time pressure as a chronic trait and replicating the interaction in a different retail context. In Study 3, we manipulated persuasion knowledge and showed that high‐knowledge consumers preferred AI appeals due to higher perceived credibility, whereas low‐knowledge consumers favored human appeals. Study 4 introduced access to a retailer's ulterior motives and revealed that AI appeals enhanced store patronage intentions under high transparency, whereas human appeals diminished them. These findings refine existing theory by demonstrating how AI agents can reduce social frictions and enhance trust under resource‐depleting or skeptical conditions. The results offer actionable guidance for retailers and nonprofits: deploy AI‐led appeals in high‐pressure or high‐skepticism settings, and human agents in contexts that reward warmth and relational engagement.

Abstract Background Education for Human Flourishing aims to empower students to develop their full potential to lead a meaningful, autonomous life to the benefit of themselves and society at large. Recent technological developments call for an evaluation of the entanglement of (Education for) Human Flourishing and generative Artificial Intelligence (AI). Following the PRISMA guidelines, this scoping review investigates to what extent the current literature has addressed research desiderata on STEM Education for Human Flourishing in an age of generative AI based on three themes proposed by the OECD (2024b). To this end, 183 eligible publications were analyzed regarding their general characteristics, research themes as well as strengths, weaknesses, opportunities, and threats (SWOTs). Results The scoping literature review reveals a focus on cognitive aspects of STEM education despite the need to broaden human capabilities in the light of generative AI. Ethical aspects are sidelined, although the SWOT analysis shows some significance of these issues, and learning about generative AI is largely neglected. Moreover, there is a lack of research on STEM-specific theoretical models and research is concentrated in the Global North, both of which might undermine an unbiased, culturally diverse development of new solutions for generative AI in secondary STEM education. The majority of current research examines AI-generated content instead of human participants, and publications focus on the performance and development of AI tools instead of their impact and application. This might hinder a human-centered approach to generative AI in secondary STEM education, potentially threatening human identity and meaning and thereby Human Flourishing. Conclusions Based on the results, we show that existing literature has not yet sufficiently addressed research desiderata on STEM Education for Human Flourishing in an age of generative AI. Our findings thus point to future research perspectives necessary to strengthen Human Flourishing in STEM education and ensure a human-centered, meaningful approach to generative AI.