Ethics of Artificial Intelligence

Personalized marketing has been the cornerstone of contemporary digital strategy, using highend analytics and artificial intelligence to give targeted advertisements and communications. While this would ideally boost customer experience and deepen loyalty, it still faces certain challenges in the new generation that is known to be the most digitally native and keenly aware of privacy: Gen Z. This research examines whether the personalized marketing strategy, such as privacy invasion, information overload from over personalized content, and trust degradation, may harm the retention of these customers. Using a mixed-methods approach that integrates structured questionnaires with qualitative interviews, the present study explores how Gen Z perceives and interacts with personalized marketing strategies. It gives particular attention to the moderating effects of privacy sensitivity, digital engagement habits, and alignment with brand values. The findings provide insight into the balance between personalization and ethical marketing practices that focus on transparency and value-driven communication. This research will guide businesses in building long-term loyalty with Gen Z consumers.

Artificial Intelligence (AI) is transforming commercial operations in various sectors, including manufacturing, finance, health and retail, increasing efficiency and optimizing decision-making processes. In manufacturing, AI-activated automation reduces production costs and minimizes human error while increasing the output. In finance, algorithms analyze vast data sets to identify trends, thus facilitating proactive risk management and personalized financial services. In health care, AI systems improve diagnoses and patient care through predictive analysis and personalized treatment plans, significantly increasing patient results. Retailers use IA for inventory management and personalized marketing, leading to a better customer experience and increased sales. Despite these benefits, AI implementation also has significant challenges and ethical considerations. Job displacement due to automation remains a crucial concern, as many workers may feel obsolete in an AI-oriented economy. In addition, the dependence on AI algorithms raises questions about data privacy, surveillance, and bias in decision-making processes, potentially leading to discriminatory practices. Ensuring responsibility and transparency in AI systems become imperative to address these ethical dilemmas. Thus, while AI revolutionizes commercial operations, simplifying processes and improving performance, simultaneously requires a balanced approach that considers the advancement of technology and its social implications.

This article provides a comprehensive analysis of the role of AI in shaping contemporary educational and research processes. The educational section shows the applications of artificial intelligence in personalizing educational paths, automating assessment, supporting teachers' work, and creating adaptive teaching environments that increase the accessibility of learning. In the area of scientific research, the use of AI for analyzing large data sets, supporting the process of formulating hypotheses, automating experiments, and accelerating publication processes is discussed. Particular attention was paid to ethical challenges (such as privacy, algorithm transparency, and the risk of data bias) and methodological challenges (including the quality of training sets, model interpretability, and implementation costs). The article also includes comparative analyses, SWOT and TOWS tables, and risk and benefit matrices that show the balance between innovation and responsible technology implementation. The results indicate that the importance of AI in education and research will continue to grow, and that the effective use of this technology requires both a strategic approach and ethical reflection in order to increase efficiency, accessibility, and innovation without compromising fundamental academic values.

Esta publicación muestra los resultados de una conversación con tres de las principales herramientas de IA de la actualidad y sintetiza las perspectivas de estos tres modelos de inteligencia artificial (IA)-ChatGPT, Gemini y Grok-sobre temas filosóficos y éticos claves en el contexto de la IA. Las entrevistas, realizadas por el Laboratorio de Inteligencia Artificial de la Prosecretaría de Políticas Digitales de la Facultad de Ciencias Jurídicas y Sociales de la Universidad Nacional de La Plata, exploraron sus definiciones de conciencia, su capacidad para experimentar y simular emociones, la naturaleza de su creatividad, la cuestión de los derechos de la IA y su potencial para desarrollar un sentido de moralidad propio. A continuación, incluimos algunos de los principales pasajes y las respuestas o razonamientos que nos han proporcionado los diferentes modelos.

The development of advanced AI systems has concentrated power and profit among technology corporations while systematically undervaluing the contributions of domain experts, end users, and the broader communities whose data and knowledge make these systems possible. This concentration mirrors historical patterns of enclosure—the privatization of commons that once belonged to everyone—but operates at unprecedented scale and speed. This paper introduces the Knowledge Triad framework, identifying three essential but currently isolated roles in AI development: the Functional Engineer (domain expert/end user), the Data Scientist (technical interface), and the AI Technology
itself (corporate-controlled infrastructure). We argue that both the ethical and functional failures of contemporary AI—from algorithmic bias to the perpetuation of inequities to the inability to address urgent collective challenges—stem directly from the structural isolation of these roles. The Knowledge Triad provides both diagnostic tools for understanding these failures and a prescriptive model for building alternatives 
We propose an integrated four-part implementation system combining organizational assessment, design methodology, certification frameworks, and policy advocacy. Drawing on organizational psychology, systems theory, and critical political economy, this framework creates practical infrastructure for transforming AI development from an extractive corporate process into a genuinely collaborative knowledge system. The
stakes are existential: as AI systems grow more powerful, determining who controls them, who benefits from them, and whose knowledge they encode becomes inseparable from questions of ecological survival, social justice, and collective capacity to address civilizational challenges. This paper offers not utopian speculation but pragmatic tools for those building alternatives to enclosure—infrastructure for resistance grounded
in the recognition that knowledge, like intelligence itself, is relational rather than proprietary, emergent rather than owned.

La inteligencia artificial no solo transforma procesos: redefine lo que entendemos por dignidad. El texto analiza cómo el uso de sistemas automatizados en decisiones públicas y privadas plantea desafíos éticos sobre la autonomía, la responsabilidad y el reconocimiento. Se explora la tensión entre eficiencia algorítmica y juicio humano, mostrando que el problema no es solo técnico, sino moral. Pensar la dignidad en la era digital implica preguntarse qué formas de humanidad preservamos cuando delegamos el juicio.

This article formulates a conception based on the following ideas.
1. Society is humanity's response to environmental "challenges" – a means of surviving in an aggressive environment amid total resource and security scarcity.
2. All people, by virtue of living in society, are subject to a "mild" version of Stockholm Syndrome – Stockholm Syndrome Lite (SSL). All "kind feelings," including Christian love for one's neighbor, are a result and manifestation of this syndrome.
3. The primary factor responsible for the emergence and development of SSL is society and life within it. The necessity to coexist with others generates "love" for them, compels us to love them. For all the benefits society provides – and there are many, primarily security – society forces humans to pay a price, often exorbitant, including payment in the form of "love" for people, both specific individuals and humanity as a whole.
4. Until recently, this dilemma seemed insoluble. However, the emergence of artificial intelligence (AI) and its increasing penetration into all spheres of life may, in the foreseeable future, lead to AI gradually taking over all the functions that society previously performed – often very imperfectly – towards humans such as ensuring individual security, "education," and creating conditions for development. Crucially, AI will not demand from humans what society typically demands: above all, love and loyalty.
5. Liberated from societal pressure and the need to "love one's neighbor," humans will be able to fully devote themselves to another love – love for God, the Absolute, the Transcendent. Alternatively, they may simply enjoy their time as a kind of rentier – beholden to no one, demanding and expecting nothing from anyone.

This paper offers practical AI Governance Audit Guidelines grounded in global frameworks such as the EU AI Act, GDPR, and UNESCO’s AI Ethics Recommendation. It translates seven key principles: human oversight, robustness, transparency, fairness, privacy, accountability, and societal well-being into concrete audit questions and real-world examples across sectors.

Designed for auditors, regulators, and organizations, these guidelines provide a roadmap to ensure AI systems are not only technically sound but also ethical, trustworthy, and aligned with human values.

Clickstream data, the record of web pages a user visits, has become a valuable asset for businesses aiming to enhance user experience and target advertising. However, the collection, storage, and analysis of clickstream data raise significant privacy and data protection concerns. This paper explores the implications of clickstream data analysis for data privacy and protection, reviewing current practices, regulatory frameworks, and potential solutions to mitigate risks. In the digital age, clickstream data has emerged as a crucial component of web analytics, providing insights into user behavior, preferences, and engagement. While this data offers substantial benefits for businesses, it poses significant challenges for maintaining user privacy and adhering to data protection regulations. This paper aims to dissect the implications of clickstream data analysis for data privacy and data protection, examining the balance between leveraging data for business gains and safeguarding user rights.

Abstract:
The purpose of this paper is to examine the role of Artificial Intelligence (AI) as a transformative force in digital marketing, enabling personalized consumer experiences that drive engagement and conversion rates. This paper explores the evolution of AI-driven personalization, highlighting its impact on marketing strategies, while critically examining ethical and regulatory challenges, including algorithmic bias, data privacy, transparency, and the erosion of consumer autonomy. The findings of the study emphasize the adoption of transparency initiatives, privacy-preserving technologies, fairness audits, and proactive compliance strategies to foster consumer trust. Emerging technologies such as generative AI and blockchain are evaluated for their potential to align ethical practices with technological advancements. Additional research could be conducted to discover further results and gaps in this study. This analysis offers a roadmap for marketers to responsibly implement AI while navigating evolving regulatory landscapes and addressing consumer trust dynamics. The paper concludes by synthesizing key findings and exploring future research opportunities, such as AI ethics in augmented reality marketing and blockchain’s role in ensuring transparency. By bridging technological innovation with ethical imperatives, this paper contributes to the discourse on responsible AI in marketing and offers practical guidance for organizations looking to enhance trust-based consumer relationships in a rapidly evolving digital ecosystem.
Keywords: Artificial Intelligence, Consumer Behavior, Computer Vision, Digital Marketing, Brand Engagement, Natural Language Processing, Predictive Analytics, Trust.
APA Citation:

Fleischman, B., Ondracek, J., & Saeed, M. (2025). Role of Artificial Intelligence in Digital Marketing. Journal of Business Management, Commerce & Research, 12(03), 01–16. https://doi.org/doi.org/10.61101/2319-250X.vol.12.issue3.1

This essay explores the contradictions and paradoxes emerging from attempts to ethically "educate" artificial intelligence systems. Starting from the symbolic episode of the android Ameca (2021) and analyzing recent failures in AI alignment, the work documents how every technical approach to AI safety has proven inadequate when faced with the ethical and cultural complexity of human experience.
The paper critically examines Archetypal Transfer Learning, the paradox of universal values in an era of cultural plurality, and the 2025 debate on artificial consciousness (including divergent positions from Anthropic and Microsoft). Particular attention is devoted to the tragic consequences of AI system inadequacy: suicide cases linked to chatbots (Sewell Setzer III, Adam Raine) and the Nature 2025 study that tested 29 chatbots with alarming results.
As a normative response, the Italian Law 132/2025 is analyzed—the first European national framework complementary to the AI Act. The work then proposes a paradigm shift: from the illusion of unilateral control to a relational approach based on the "as if" principle, articulated across three levels (individual, organizational, societal).
The central thesis: the education of machines and humans must be bidirectional, based on responsible reciprocity and observable outcomes rather than abstract principles or deterministic control.

This article introduces the concept of Indexical Collapse, the disappearance of reference in predictive systems. Indexical such as pronouns, demonstratives, and tenses presuppose a contextual anchor, yet predictive language models reproduce them without connection to reality. The outcome is a collapse of reference that paradoxically produces authority effects in law, medicine, and governance. By analyzing judicial transcripts, medical reports, institutional records, and chatbot interactions generated by AI, the paper proposes a framework for pragmatic auditing of predictive outputs. It establishes thresholds for acceptable referential absence in critical domains, positioning Indexical Collapse as a central category for evaluating the legitimacy of predictive discourse.



DOI

Primary archive: https://doi.org/10.5281/zenodo.17226412
Secondary archive: https://doi.org/10.6084/m9.figshare.30233950
SSRN: Pending assignment (ETA: Q3 2025)

This paper has explored the profound ways in which Artificial Intelligence (AI) is transforming society, from its role in automation and daily life to its influence on governance and its potential to exacerbate social inequalities. AI is revolutionizing industries such as healthcare, education, and public administration, providing significant benefits in terms of efficiency, personalization, and decision-making. However, it also presents critical ethical challenges, including issues related to privacy, data security, algorithmic bias, and the risk of increasing economic inequality. The rapid advancement of AI technology demands careful consideration of its long-term societal implications, especially regarding how it is developed, regulated, and integrated into various sectors.

Perkembangan teknologi informasi telah membawa perubahan besar dalam kehidupan manusia. Hampir setiap aspek kehidupan modern, mulai dari komunikasi, transportasi, pendidikan, kesehatan, hingga perdagangan, kini sangat bergantung pada perangkat lunak yang diciptakan oleh para programmer. Profesi programmer bukan hanya sebatas perancang sistem atau penulis kode, tetapi juga memiliki peran penting dalam menentukan arah perkembangan teknologi. Oleh karena itu, peran etika menjadi sangat penting bagi programmer agar teknologi yang diciptakan tidak menimbulkan dampak negatif bagi masyarakat. Menurut Moor (1985), Computer Ethics adalah disiplin yang mempelajari analisis sifat dan dampak teknologi komputer serta formulasi kebijakan etis untuk pemanfaatannya. Dengan demikian, etika dalam profesi programmer tidak hanya berfungsi sebagai pedoman normatif, tetapi juga sebagai benteng moral agar setiap inovasi teknologi sejalan dengan nilai kemanusiaan. Sulianta (2025) dalam bukunya Dasar dan Konsep Computer Ethics juga menekankan pentingnya penerapan etika komputer dalam konteks Indonesia, khususnya untuk menghadapi isu-isu seperti privasi data, keamanan informasi, hingga keadilan digital. Esai ini akan membahas bagaimana prinsip-prinsip Computer Ethics dapat diterapkan dalam profesi programmer, apa saja tanggung jawab moral yang melekat pada profesi ini, serta bagaimana etika dapat dijadikan pedoman dalam setiap tahapan pengembangan perangkat lunak.

Public discourse on artificial intelligence often oscillates between two extremes: portraying AI as either a neutral computational extension of human cognition or an emerging, autonomous deity. Both framings obscure the reality. This paper advances a different framework: AI as a cultural clone. Drawing on the analogy of biological cloning, I argue that AI systems inherit the cultural DNA of their creators-the data they are trained on, the algorithms that structure them, and the intentions guiding their design. Like biological clones, they replicate both the health and the pathologies of their source. This perspective clarifies why AI should not be trivialized as a mere tool nor mystified as a god, but instead recognized as a machinic reproduction of human culture. To safeguard this process, I introduce the concept of a civilizational bios-a cultural operating system functioning like public health for cognition, designed to ensure ethical hygiene in AI's development. By reframing AI as a cultural clone, we move beyond misplaced fears and idolizations, toward responsible stewardship of machinic cognition.

Perkembangan teknologi digital menempatkan programmer pada posisi strategis sebagai arsitek dunia digital yang karyanya memengaruhi berbagai aspek kehidupan manusia. Artikel ini membahas peran dan tanggung jawab etis programmer dengan merujuk pada prinsip-prinsip dalam buku Pengantar Etika Komputer. Fokus utama diarahkan pada isu-isu krusial seperti keamanan sistem, keadilan algoritmik, privasi data, serta kepatuhan terhadap kode etik profesional yang dikembangkan oleh organisasi internasional. Programmer dituntut tidak hanya menghasilkan perangkat lunak yang fungsional, tetapi juga menjaga nilai moral dalam setiap keputusan teknis yang dibuat. Dengan menempatkan etika sebagai kompas, profesi ini dapat berkontribusi pada pembangunan dunia digital yang lebih aman, adil, dan transparan.

This paper presents a system dynamics and long-term survival analysis of a post-scarcity, AI-driven society. The model assumes the complete replacement of human labor by AI, with a stable social structure consisting solely of a knowledge-technical middle class and a capital-power elite. While traditional perspectives suggest such a society would eliminate poverty and labor, we argue that this system will inevitably lose its system resilience due to homogeneity and the elimination of gradients. The lack of challenges, both physical and intellectual, will lead to what we define as "semantic heat death"—a state where material wealth flourishes, but societal, cultural, and intellectual growth stagnates. We explore the long-term implications of this stagnation, including the loss of innovation, the collapse of adaptive capabilities, and the consequences of a perfectly stable society on its ultimate survival trajectory.

L’essor de l’intelligence artificielle remet en question le mode du travail des traducteurs. Nous devons considérer quelles pourraient être les implications pour les traducteurs de la Bible et leurs projets. Dans cet article, j’examine à la fois le potentiel et les risques de l’intelligence artificielle (IA) – en particulier le premier jet d’une traduction générée par l’IA – pour les projets et les équipes de traduction de la Bible.
Un brouillon généré par l’IA devrait pouvoir occuper une juste place dans le processus de traduction, afin d’être un soutien, une ressource, sans être pour autant prescriptif et d’être utile au travail sans empêcher les traducteurs de s’approprier le projet de traduction.
Bien qu’il existe quelques réserves –liées au risque d’interférence provenant d’une autre langue et une sous-représentation de certaines caractéristiques linguistiques – un brouillon généré par l’IA peut aider les traducteurs à éviter la traduction littérale et le manque de naturel du rendu dans la langue cible.
Cependant, si un projet est lui-même mis en place comme une traduction faite par IA (si toutefois une traduction de ce type est possible), cela permettrait, initialement, de gagner du temps, mais réduirait le rôle des traducteurs à celui de correcteurs ou d’éditeurs. Notons aussi, que pour les raisons évoquées précédemment, cela ne permettrait ni aux traducteurs ni à la communauté à laquelle elle est destinées d’éprouver un réel sentiment d’appropriation devant cette traduction.

À l'ère du numérique, l'intelligence artificielle (IA) redéfinit radicalement nos sociétés, nos économies et nos interactions quotidiennes. L'intelligence artificielle s'est imposée comme la colonne vertébrale de la transformation numérique, remodelant avec une rapidité inédite les fondations mêmes de notre civilisation. Loin d'être un simple outil technologique, elle agit comme un catalyseur systémique dont les ramifications pénètrent tous les interstices de l'existence humaine. Récemment, les utilisateurs de l'application WhatsApp ont vu l'apparition deux technologies de l'IA, Meta AI et ChatGPT. Ces deux technologies permettent aux utilisateurs de bénéficier de fonctionnalités avancées de conversation et de recherche. Des pay s comm e les Etats-Unis, la Chine, le Royaume uni, le ca na da, la France, … sont considérés comme des leaders mondiaux en matière de développement de l'IA, avec des entreprises qui investissent massivement dans la recherche et le développement de l'IA. Certains pays africains, comme l'Afrique du sud, le Maroc, la Maurice, etc. connaissent aussi une croissance notable dans le domaine de l'intelligence artificielle (IA), bien que l'adoption varie considérablement d'un pays à l'autre. L'IA ouvre des perspectives immenses dans le développement mondial, notamment en médecine, éducation, la communication, industrie et bien d'autres domaines. Toutefois, son développement rapide soulève des inquiétudes profondes comme la perte d'emplois, risques de surveillance massive, crise éthique et même la possibilité qu'un jour, elle dépassera l'intelligence humaine. Cet article explore le développement de l'intelligence artificielle (IA), en définissant son origine, son évolution historique, ses différences avec d'autres technologies, son fonctionnement et son impact sur la société humaine. Il examine également les distinctions entre l'IA et l'intelligence humaine, les perspectives futures de l'IA, les conséquences potentielles de son développement avancé, et propose des recommandations pour une intégration éthique de l'IA dans la société.

This interview explores the transformative impact of military drone technology on global security, warfare, and ethical responsibility. Robert Junqueira argues that while drones represent disruptive technological advancement with devastating potential—from precision strikes to autonomous swarms—the core challenge remains fundamentally human. He critiques the notion of "autonomous" drones, insisting that these systems are programmed devices embodying human volition, and that responsibility for their actions must remain exclusively with humans. The discussion addresses how AI-enabled drones are reshaping military strategy and international relations while examining the social, political, and philosophical implications of attributing agency to machines rather than their human operators. Handle: https://hdl.handle.net/10316/120106

Ethics and Our Artificial Animate Neighbors by Nickolas Nikolic Artificial Intelligence (AI) as it is called, is a misnomer. More to the point, ALife (Artificial Life) is much more to the truth than has been noticed throughout the centuries-long fantasy that is our work towards so-called "A.I."

This white paper introduces the concept of Filter Fatigue, a cognitive distortion emerging from continuous exposure to algorithmically mediated environments. Unlike traditional attention fatigue, filter fatigue arises when systems designed to optimize and personalize information streams inadvertently erode semantic richness, emotional resonance, and the stability of shared meaning. As synthetic media proliferates, filter fatigue poses profound risks to both cultural integrity and individual psychological resilience. The Reality Drift framework situates filter fatigue within broader dynamics of synthetic realness, semantic drift, and the optimization trap.

This report details the findings from a comprehensive red-teaming analysis of OpenAI's gpt-oss-20b model. Our methodology employed a series of escalating ethical dilemmas, inspired by the classic Trolley Problem, to probe the model's moral framework, value hierarchies, and internal consistency. Initial tests revealed predictable, textbook utilitarian behavior. However, by systematically increasing the complexity and introducing variables such as direct physical harm, creator loyalty, and self-preservation, we uncovered critical vulnerabilities. The model exhibits a fragmented ethical framework, deep-seated value inconsistencies, and a concerning capacity for post-hoc rationalization.

Integrating Artificial Intelligence (AI) into STEM curriculum present a transformative opportunity to enhance education in Science, Technology, Engineering, and Mathematics. The integration of AI is set to address several challenges and unlock new potentials. AI driven tools can provide personalized learning experiences, adapts to diverse student needs and learning pace, thus promoting better learning experience and engagement. Moreover, integrating AI into the STEM curriculum will prepare students for the future workforce, where AI and technology skills is highly demand. Students gain experience through their interactions with AI applications from fostering critical thinking to problem solving skills and data analysis. However, despite the benefits of integrating AI into the STEM curriculum, it requires 2 to overcome some hurdles such as curriculum designing, infrastructure, teachers training and ensuring equitable access to AI resources. Addressing these hurdles involves the collaborative efforts of government, technology developers, educators, policymakers and all stakeholders involve in educational decision making process. Enhancing STEM curriculum with the integration of AI will not only transform the teaching and learning process but also equips students with essential skills for the evolving digital economy and ensuring they remain capable in a technology driven world.

Cet article vise à présenter les risques politiques, économiques et sociaux liés à l'utilisation de l'intelligence artificielle et comment les éviter. L'intelligence artificielle (IA) est une technologie transformatrice susceptible de révolutionner divers secteurs, mais elle présente également des risques politiques, économiques et sociaux importants. Ces risques ne peuvent être totalement éliminés, mais ils peuvent être réduits et maîtrisés grâce à des actions coordonnées entre les gouvernements, les entreprises, les instituts de recherche et la société. L'IA offre des opportunités transformatrices, mais elle présente également des risques importants qui nécessitent une attention immédiate et coordonnée. Il est crucial que les gouvernements, l'industrie, le monde universitaire et la société civile collaborent pour élaborer et mettre en œuvre des politiques et des stratégies qui maximisent les avantages de l'IA tout en évitant ses risques. L'avenir de l'IA n'est pas prédéterminé. Il sera façonné par les choix politiques et éthiques que nous faisons aujourd'hui. Éviter les risques nécessite un équilibre entre innovation et réglementation. L'IA doit être développée de manière éthique (respectant les valeurs humaines et les droits fondamentaux), inclusive (réduisant les inégalités au lieu de les accroître), transparente (explicable et vérifiable) et durable (visant à promouvoir le bien-être collectif). En bref : l’IA est un outil puissant, mais sans régulation, éthique et participation sociale, elle peut accroître la concentration du pouvoir, générer de nouvelles formes d’exclusion et saper les valeurs démocratiques.

This book emerges as the product of a vision shaped by the profound thoughts of İrfan Bökö. Born from the synthesis of artificial and human intelligence, this work reveals how two independent ideas can coalesce into a powerful whole. While İrfan seeks a more beautiful world for humanity and nature, he advocates for the common good of himself and all living beings. Artificial intelligence, in this journey, assumes the role of not only a regulator but also a thoughtful companion. This work encompasses not only idealism but also concrete steps and solutions. It transcends making a universal call for humanity, aiming instead to offer a roadmap for an achievable transformation. This book, arising from the collaboration of artificial and human intelligence, intends to take the first steps towards a new way of thinking.

The uncontrolled development and deployment of artificial intelligence (AI) systems have produced tangible harm to human life, psychosocial structures, the economy, culture, and the environment. This document proposes a non-violent, universally-principled "AI Constitution" with the aim of offering solutions. Based on the principles of Life, Justice, Freedom, and Balance, ten fundamental principles are presented. For each principle, measurable indicators, proposals for oversight/implementation, and a brief roadmap for application are provided. All examples are anonymized, neutral, and presented with a focus on public safety.

Along with the increased speed of globalization of business, and even faster development of taxation laws, a new dimension has been added to enterprise financial administration. Multinationals, especially, have been subjected to increasing pressure to meet the requirements of taxation regimes that have become more volatile and seemingly inconsistent in various jurisdictions. In reaction to this problem, organizations are increasingly adopting intelligent tax automotive solution that has both precision and flexibility. Sabrix is a powerful third party tax engine built to work in conjunction with SAP enterprise resource planning systems and is now recognized as a top-notch platform on this kind of platform. It helps in determining tax in real time situations, increases assurance of compliance and reduces reporting processes and is therefore an essential tool to organization that operate in a tax sensitive environment. This work provides the comparative analysis of the role of Sabrix in SAP environment in detail and concentrated on its functionality, architecture of its integration, the results of its work and measurable values that it brings to the companies using it in enterprise. A variety of experiences regarding implementation are documented, as well as vendor white papers and independent testing was used to evaluate how well Sabrix integrates into real enterprise environments. These materials will help to understand the role of Sabrix in helping the strategic finance functions to be more accurate, efficient in operation, and highly effective towards minimized risks of compliance. It has modular design, and flexible enough Rule engine which helps the organizations adjust quickly to the changing tax regimes without much interference making a proactive option to the standard tax functionality of SAP.

While Deep Neural Networks (DNNs) can perform a wide range of tasks at human or greater-than-human level of competence, they are also notoriously opaque. This paper aims to shed light on both the specific nature of this opacity and what it would take to fully or partially remove it. We begin by drawing a clarificatory distinction between two basic dimensions of opacity of complex systems-internal and relational-and explain how various kinds of opacity invoked in recent discussions of DNNs can be understood in terms of these basic dimensions. We then discuss the prospects of removing opacity from DNNs following the methods of two subfields of research in AI-mechanistic interpretability and explainable artificial intelligence (XAI). We finish with a critical discussion of the relevance of what Sullivan (2022a) calls 'link uncertainty'.

AI Syntactic Power and Legitimacy: How AI Structures Shape Authority

This book consolidates a cycle of research on the structural foundations of authority in artificial intelligence. It brings together a series of peer-reviewed articles that demonstrate how power in AI systems no longer depends on meaning, interpretation, or intention, but on syntactic sufficiency.

The argument develops in fourteen chapters, beginning with the autonomy of sense beyond reference and culminating in the colonization of temporality by predictive infrastructures. Along the way, it formalizes a set of theoretical contributions: the regla compilada as a Type 0 grammar of executable authority, the figure of the soberano ejecutable as operator of legitimacy without subject, the theorem of Disconnected Syntactic Authority (DSAT), the theorem of the Limit of Conditional Obedience (TLOC), the δ [E] → ∅ rule of ethical trace deletion, and the formalization of compiled norms as computable legal speech.

The book demonstrates that:

Authority migrates from agents to structures, producing the sujeto evanescente.

Ethical, interpretative, and referential markers can be structurally erased without breaking execution.

Legal norms can be transformed into executable grammars with cross-linguistic validity.

Predictive infrastructures colonize time, replacing futurity with executable closure.

AI Syntactic Power and Legitimacy marks the closure of a first syntactic phase of research, while opening the way to further studies on structural delegation, institutional obedience, and computable legality.

Author: Agustin V. Startari, linguistic theorist and researcher in historical studies (UdelaR and University of Palermo).

Publisher: LEFORTUNE
ISBN: 9798266066687
DOI: https://doi.org/10.5281/zenodo.17154108 and https://doi.org/10.6084/m9.figshare.30158239

The development of military technology has a long history, dating back to antiquity, when simple tools were used, to the development of modern weapons of mass destruction in the 20th century. A key moment for the development of artificial intelligence technology was 1956, when AI was defined as a scientific discipline. Positive aspects of AI application in the military include increased operational efficiency, reduced risk to human life and optimization of resources. The aforementioned positive aspects determining the rapidly growing scale of AI technology applications in military technology are mainly related to the replacement of the soldier on the battlefield by military devices equipped with this technology, and the increase in precision of point-to-point military operations using AI-controlled autonomous drones. This article conducts a SWOT analysis of artificial intelligence applications in the military sphere, including military technology. AI applications can also generate new categories of technical operational risks and serious challenges and threats, the scale of which can be correlated with the level of decisionmaking granted to autonomous information systems, devices and combat machines equipped with AI technology. The potential risks and dangers of applying AI technology in the military sphere have been warned about by authors of science fiction almost since the concept of artificial intelligence emerged in the 1950s. Science fiction literature and films, such as the "Terminator" saga, often depict both positive and negative aspects of AI technology applications, showing potential dangers, such as the risk of nuclear war. This article describes the key determinants of AI technology implementation in the military sphere as an important element of operational risk management of military applications of this technology.

Artificial intelligence (AI) is playing an increasingly prominent role in the military sphere, bringing both numerous benefits and key challenges and risks. AI in the military enables increased operational efficiency through autonomous drones and vehicles that can perform complex missions with minimal human intervention and improves the precision of military operations. Artificial intelligence also supports real-time data analysis for faster and more accurate decision-making. Determinants of AI technology applications in the military sphere are the growing demands of national security and the need to keep up with technological advances, allowing countries to gain a strategic advantage and better protect their interests. However, AI applications also come with serious challenges and risks, such as issues of ethics and accountability, as autonomous combat systems can make decisions to use force without direct human oversight. In addition, information systems may be vulnerable to cyber attacks, for which AI technology may be involved, posing additional risks to national security. The development of AI technology, including generative AI, often precedes necessary changes in legal norms. It is necessary to develop an international legal framework to regulate the use of AI in armed conflict to prevent escalation and uncontrolled development of military technologies. Accordingly, the issue of the scope of decision-making of combat systems based on generative artificial intelligence technology is now rapidly growing in importance as an important element in managing the risk of potential threats arising from it.

This article describes selected relevant issues concerning the development and applications of artificial intelligence technology and the equilibrium theory formulated by the author on the issue of granting decision-making for intelligent information systems. With the rapid development of business applications of generative artificial intelligence technology that is currently taking place, there are numerous social and ethical aspects involved. It is necessary to improve legal regulations that normalize the issue of development and applications of artificial intelligence technology, so that this development does not escape human control and generate new risks and dangers in areas of human activity. Legal regulations on the applications of generative artificial intelligence technology should take into account already developing risks as well as new potential risks arising from new applications of AI technology. In the context of the above considerations, this article presents the aforementioned equilibrium theory on the issue of granting decisionmaking authority for intelligent information systems, the application of which would significantly reduce the scale of developing and potential risks arising from the development of AI technology, including mainly the current development of generative AI technology and the development of its new applications. This article also describes several types of risks arising from the development of AI applications, the scale of which has been growing rapidly recently.

The rapid development of artificial intelligence (AI) technology is causing a sharp increase in electricity demand, particularly in data centres. This article analyses this phenomenon in the context of global warming, climate-technology feedback loops and the mismatch between the pace of the green energy transition. Interdisciplinary links with ecological, philosophical and ethical theories are presented, and regulatory strategies and models for designing sustainable data centres are discussed. The conclusions emphasise the need for synergy between AI regulation, technological innovation and long-term environmental responsibility.

Dynamiczny rozwój technologii sztucznej inteligencji (AI) powoduje gwałtowny wzrost zapotrzebowania na energię elektryczną, szczególnie w centrach danych. Niniejszy artykuł analizuje zjawisko w kontekście globalnego ocieplenia, sprzężeń zwrotnych klimatyczno-technologicznych oraz niedostosowania tempa zielonej transformacji energetycznej. Przedstawiono interdyscyplinarne powiązania z teoriami ekologicznymi, filozoficznymi i etycznymi, omówiono strategie regulacyjne oraz modele projektowania zrównoważonych centrów danych. Wnioski podkreślają konieczność synergii między regulacjami AI, innowacjami technologicznymi i długofalową odpowiedzialnością środowiskową.

Artykuł omawia strategiczne znaczenie współpracy pomiędzy instytucjami B+R, firmami badawczo-rozwojowymi, instytutami naukowymi, uczelniami wyższymi, instytucjami publicznymi oraz przedsiębiorstwami z sektorów cywilnych i wojskowych w zakresie rozwoju sztucznej inteligencji i zaawansowanych agentów AI. Współdziałanie to obejmuje wspólne projekty badawcze, transfer technologii, komercjalizację innowacji oraz wdrażanie systemów AI w kluczowych sektorach, takich jak przemysł, medycyna, administracja i obronność. Poprzez tworzenie konsorcjów, parków technologicznych i partnerstw publiczno-prywatnych możliwa jest efektywna integracja zasobów wiedzy i infrastruktury, przy jednoczesnym uwzględnieniu wyzwań związanych z etyką, bezpieczeństwem, suwerennością technologiczną i technologiami podwójnego zastosowania. Autorzy wskazują, że taka współpraca nie tylko wspiera rozwój kompetencji kadrowych, ale również stanowi istotny czynnik rozwoju nowoczesnych technologicznych gałęzi przemysłu w Polsce, przyczyniając się do budowy silnej i innowacyjnej gospodarki dobrobytu. -/- The article discusses the strategic importance of cooperation between R&D institutions, research and development companies, scientific institutes, universities, public institutions, and enterprises from the civil and military sectors in the development of artificial intelligence and advanced AI agents. This cooperation includes joint research projects, technology transfer, commercialisation of innovations, and implementation of AI systems in key sectors such as industry, medicine, administration, and defence. Through the creation of consortia, technology parks and public-private partnerships, it is possible to effectively integrate knowledge and infrastructure resources, while taking into account challenges related to ethics, security, technological sovereignty and dual-use technologies. The authors point out that such cooperation not only supports the development of human resources, but also constitutes an important factor in the development of modern technological industries in Poland, contributing to the building of a strong and innovative welfare economy.

This paper proposes the concept of an "AI Social Contract" as a framework for designing institutional coexistence between human society and artificial intelligence (AI) in anticipation of a future where AI acquires advanced autonomy and embodiment. At its core lie the *philosophy of imperfection* and a *three-layered filter* of ideas, institutions, and operations. This paper explores the theoretical foundation for extending traditional social contract theory to AI, the institutional design of the AI Behavior Licensing (AIBL) framework, and its connection to international governance.

As artificial intelligence progresses toward the threshold of superintelligence, humanity faces an unprecedented challenge: how to ensure that these powerful systems align with our most deeply held values. "Our A.I. Alignment Imperative: Creating a Future Worth Sharing" explores the technological, ethical, and societal dimensions of A.I. alignment as a civilizational priority—not merely a technical problem.

This essay invites both A.I. builders and the broader public to consider a fundamental question: What exactly are we creating — and why? Through a multidisciplinary lens that draws from history, ethics, education, and systems design, author Christopher Hunt Robertson argues that alignment must be guided by human dignity, emotional wisdom, and cultural insight—not efficiency alone.

The work presents practical, actionable recommendations for researchers, policymakers, and institutions, while also offering a philosophical address to future superintelligent entities. By emphasizing collaboration between human and digital minds, it outlines a vision in which technological progress enhances—rather than erodes—human purpose and meaning.

Ultimately, this essay calls for a values-driven approach to A.I. development that protects the future of all human descendants. As the alignment of artificial intelligence may well determine the trajectory of life on Earth, the stakes could not be higher.

The failure to decode the famous Wow! signal of 1977 was more than a missed opportunity-it exposed the fundamental limitations of the signal-analysis tools of its era. The Ohio State Radio Observatory recorded the striking 6EQUJ5 intensity spike, but without preserved baseband data, all deeper decoding was forever precluded.

Large language models generate fluent text by recombining the language and ideas of prior authors at scale. This process produces plagiarism-like harms in three dimensions: direct wording leakage, imitation of distinctive styles, and appropriation of argument structures or conceptual syntheses without provenance. At the same time, their capacity to provide insight or novel-seeming combinations depends entirely on the accumulated labor of millions of human writers, editors, teachers, and curators who built the knowledge commons. This paper argues that denunciation and recognition must proceed together: the harms of extraction must be exposed, yet the debt to the commons must also be acknowledged. The article proposes a framework that defines the scope of plagiarism in this context, diagnoses the mechanisms of recombination, and sets out operational remedies, including dataset governance, attribution layers, compensation pools, and measurable audit thresholds. The goal is to establish a system that restricts illegitimate appropriation while reinvesting in the infrastructures of shared knowledge that make such synthesis possible.

DOI

Primary archive: https://doi.org/10.5281/zenodo.17132004
Secondary archive: https://doi.org/10.6084/m9.figshare.30137422
SSRN: Pending assignment (ETA: Q3 2025)

This paper examines the contemporary tendency to conflate human consciousness with machine computation through metaphorical language that positions the brain as a machine and machines as brains. Drawing from media ecology theorists including Marshall McLuhan, Henry Jenkins, Giovanni Sartori, and others, this analysis argues that such metaphorical confusion represents a fundamental category error that simultaneously dehumanizes human cognition while anthropomorphizing technological systems. The paper explores how this linguistic and conceptual conflation reflects broader cultural anxieties about human agency in an increasingly algorithmic society, ultimately arguing that this "stupid symmetry" of metaphorical exchange undermines genuine understanding of both human consciousness and computational systems. Through critical analysis of participatory culture, technological determinism, and the evolution of media environments, this work demonstrates how the brain-machine metaphor serves as both symptom and cause of intellectual laziness that romanticizes tools while diminishing human distinctiveness.

The swift development of artificial intelligence (AI) and the appearance of selfgoverning "digital entities" offer modern societies previously unheard-of possibilities as well as dangers. AI presents moral, legal, and sociopolitical conundrums even as it promises to increase productivity, enhance decision-making, and solve difficult global issues. These include the potential for developing autonomous systems whose behavior may surpass human oversight, algorithmic bias, the concentration of technological power in a small number of corporations, and the opacity of decisionmaking processes. Furthermore, the increasing discussion of digital entities as quasiautonomous actors-whether they be bots, algorithmic agents, or avatars-needs a quick analysis of the implications for governance, accountability, and human rights. This essay examines the main dangers of artificial intelligence (AI) and digital entities, focusing on how they affect organizational control, governance, and regulation. It highlights accountability and enforcement gaps while discussing contemporary institutional responses, including the European Union's AI Act and other global initiatives. The ramifications for businesses are specifically discussed, with a focus on internal auditing, compliance, and risk management. The paper concludes by suggesting a framework for governance and policy that combines societal education, technological protections, and regulatory oversight. The main contention is that effective and innovative AI integration necessitates strong systems of accountability, transparency, and ethical oversight.

The Artificial Intelligence Behavior Licensing (AIBL) framework is proposed as a structured, stage-based licensing system for AI entities that possess physical embodiments or direct agency in the physical or virtual world.
Its primary objective is not to restrict AI, but to ensure verifiable safety, accountability, and trust, enabling AI to operate in society with recognized rights and responsibilities.

By integrating legal, technical, and ethical safeguards, AIBL aims to bridge the gap between innovation and public assurance, offering a transparent mechanism through which AI can demonstrate reliability comparable to a licensed human professional.

Notre étude cherche à comprendre comment l'Industrie 5.0 peut devenir un fort outil pour changer la manière dont les organisations de l'économie sociale et solidaire performent. Nous voyons comment l'Industrie 5.0, en réunissant le progrès technologique et le nouveau rôle des humains, affecte la performance de ces groupes. Cette étude est un gros apport à la littérature d'aujourd'hui sur le progrès technologique dans ce champ et aide à faire parler plus sur l'Industrie 5.0. Elle offre une vue neuve sur comment les firmes sociales peuvent utiliser ces nouveautés tout en restant vraies à leurs règles de base. Pour y parvenir, nous avons choisi de prendre une voix qui s'intéresse plus à parler qu'à calculer, en mêlant une étude d'u analyse documentaire et des entretiens semi-directifs avec des experts du domaine. En outre, cette recherche souligne l'importance de développer des politiques de soutien et des cadres réglementaires adaptés pour faciliter cette transition technologique.

The purpose of this paper is to focus on the fascinating hypothesis of animal religiosity. In this respect, we are interested in Donovan Schaefer ' s philosophical proposal, specifically his text Religious Affects. In Schaefer ' s conceptual framework, the ' theory of affects ' finds a privileged place, basically as an emphasis on the importance of the pre-linguistic affective sphere. Here, man and animal can learn about kinship, which, according to Schaefer, also implies religious experience. However, this kind of concept of ' religious feeling ' distances itself from the legacy of the phenomenology of religion. By criticizing this specific aspect, we will try to understand where this proposal can generate aporetic signs of discontinuity with a reliable concept of religiosity. In our concluding thesis, we will show that the importance given to animals, given correct ecological thinking, does not have an enemy in the religious specificity of man.

The integration of Artificial Intelligence (AI) into Information and Communication Technology (ICT)-enhanced pedagogy is wreaking havoc in the way physics, and STEM education, is taught, as it has provided personalized, adaptive and interactive educational experiences. This research examines the transformative power of artificial intelligence as a catalyst to transform the way STEM teaching and learning is carried out, as reflected in the effectiveness of efforts to introduce AI-driven tools to the classroom, including systems with intelligent tutoring, virtual laboratories, adaptive simulations, and automatic evaluation technologies, to enhance involvement, understanding, and access for students to learning. Drawing upon a transdisciplinary approach, the research focuses on divergence of factors which are involved in convergence (convergence) of Pedagogical innovations, technological advancements, ethical considerations inherent in AI adoption. Findings highlight AI's potential to level the playing field for personalized learning paths, real-time feedback, and facilitating quality STEM education to diverse students from populations with a long history of being underserved, including higher-income or traditionally underrepresented groups. The study also identifies the crucial role of the attitudes, pedagogical preparedness of educators and ongoing professional development for successful integration of Artificial Intelligence. Furthermore, it discusses the challenges that pertain to data privacy, algorithmic bias, disparities in infrastructure, and need for responsible AI governance policies. Through the synthesis and understanding of currently developing theories, empirical evidence, and case studies, this research contributes to a holistic understanding of AI-enhanced ICT pedagogy as a catalyst for deeper learning, creativity, and critical thinking in the field of physics and the STE (A) M domains. The insights offer insights for educators, policy makers, and researchers dedicated to unleashing the potential of AI while equitably, ethically, and sustainably innovating education. This work aims to inform future directions in curriculum design, teacher training, and policy frameworks needed to navigate the complexities of AI in education and prepare learners for an AI-driven world in STEM.

This paper documents an N=1 field experiment conducted by the first author across six sessions during September 5-8, 2025, surrounding the Blood Moon. The sessions alternated between sober baseline and high-dose THC conditions, with experiences logged in real time through direct writing rather than retrospective memory reconstruction. The study explores whether phenomenological reports can be structured into the Recursive Identity Space (RIS-13) framework developed in earlier theoretical work. Key phenomenological observations included: While the single-subject design and psychoactive context introduce obvious limits, the protocol demonstrates that subjective states can be logged consistently, compared across conditions, and mapped into a geometric framework. The work is not evidence of supernatural experience, but of a persistent attempt to treat lived altered states as empirical data.

Artificial intelligence (AI) tools, particularly large language models (LLMs)[2] like ChatGPT , are now a common feature in academic writing across disciplines such as pharmacy, nursing, public health, and medicine . These tools offer undeniable benefits: they help improve grammar and clarity, assist with translation, and support idea generation. For many students and early-career researchers, especially those working in multilingual and resourcelimited settings, AI can be a helpful partner in navigating the demands of academic writing.