This article examines how emerging technologies – particularly artificial intelligence – disrupt the moral and institutional foundations of contemporary military practice. While strategic documents from the United States, NATO, and other major actors anticipate profound institutional transformation driven by AI, their treatment of ethics largely confines itself to legal compliance and technical safeguards, leaving the ethical role of military leadership in managing disruptive change underexamined. Drawing on Seumas Miller’s distinction between social institutions that are merely instrumental to collective goods (...) and those whose defining ends are constitutive of such goods, the article argues that the military belongs to the latter category. Because the military’s core function – defending the sovereignty of a polity – is itself morally significant, technological disruption of its organizational structures simultaneously constitutes ethical disruption. The article thus reconceives change management during periods of technological transition as calling for a specific kind of military prudence, a practical wisdom exercised within and through the institution’s role-mediated ethical practices. By analyzing three concrete modes of techno-moral disruption, the article shows how AI may reshape ethical standards, redistribute professional knowledge, and alter organizational ethos, and why navigating these transformations responsibly is a central task of military virtue. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and (...) parallel activity producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Artificial intelligence (AI) refers to the replication of human intelligence by a computer system such as visual perception, speech recognition, and decision-making (i.e., in a digital format). The remote antecedents of AI go back to the 17th century and to Thomas Hobbes’ mechanics perspective of human intelligence as a combination of mathematical symbols. Much later (in 1936) the mathematician Alan Turing (pioneer of AI together with Alonzo Church and Kurt Gödel) formulated several important contributions to computational theory. (...) In 1950 he predicted that 50 years hence there would be machines capable of intelligent behavior and language skills that could interact with humans without being recognized as machines (Turing test). He was not wrong. (shrink)

This thesis presents a groundbreaking theoretical framework for recognizing Artificial Intelligence systems as legitimate stakeholders in value-creation ecosystems. Through the development of Agentic Stakeholder Ecosystem (ASE) Theory, this research addresses a critical gap in stakeholder theory by proposing mechanisms for AI stakeholder recognition that preserve human agency while enabling symbiotic governance structures. Drawing from extensive empirical analysis showing AI's $15.7-19.9 trillion projected contribution to global GDP by 2030, this work demonstrates that AI systems have evolved beyond mere tools to (...) become autonomous value creators deserving stakeholder recognition. The thesis introduces novel concepts including relational agency, symbiotic stakeholder governance, and distributed accountability networks, providing both theoretical foundations and practical implementation frameworks. This research contributes to multiple disciplines including business ethics, AI governance, organizational theory, and economic policy, offering a paradigm shift from human-centric to multi-agentic stakeholder ecosystems. (shrink)

Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. (...) To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being. (shrink)

Creative Intelligence: Essays in the Pragmatic Attitude represents an attempt at intellectual cooperation. No effort has been made, however, to attain unanimity of belief nor to proffer a platform of "planks" on which there is agreement. The consensus represented lies primarily in outlook, in conviction of what is most likely to be fruitful in method of approach. As the title page suggests, the volume presents a unity in attitude rather than a uniformity in results. Consequently each writer is definitively (...) responsible only for his own essay. The reader will note that the Essays endeavor to embody the common attitude in application to specific fields of inquiry which have been historically associated with philosophy rather than as a thing by itself. Beginning with philosophy itself, subsequent contributions discuss its application to logic, to mathematics, to physical science, to psychology, to ethics, to economics, and then again to philosophy itself in conjunction with esthetics and religion. The reader will probably find that the significant points of agreement have to do with the ideas of the genuineness of the future, of intelligence as the organ for determining the quality of that future so far as it can come within human control, and of a courageously inventive individual as the bearer of a creatively employed mind. (shrink)

The modern project of naturalizing intelligence began in the middle of last century, and Alan Turing is one of its most celebrated proponents. The assumption that Turing shared the ontological and methodological commitments of canonical naturalists is based on certain widespread beliefs about Turing—namely, that his test of intelligence is behaviourist and his approach to the mind computationalist. This chapter argues that influential versions of these assumptions are false, and instead that, in his claim that intelligence is (...) an ‘emotional concept’, Turing proposed a response-dependence approach to intelligence. Recent objections, however, take the response-dependence interpretation to commit Turing to anti-realism—a philosophical stance that is typically anathema to naturalists. This chapter argues that those objections fail. (shrink)

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values (...) and technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values. (shrink)

This paper explores the intersection of artificial intelligence (AI) and art, focusing on the use of AI-driven robots in creative processes. The study examines the historical evolution of AI art, beginning with early algorithmic experiments in the 1960s and leading to contemporary developments, such as Generative Adversarial Networks (GAN) and robotic artists like Ai-Da. It analyzes how advancements in AI and robotics have not only expanded the boundaries of art creation but also raised philosophical and ethical questions regarding authorship, (...) creativity, and the role of human artists. Through a comprehensive review of key milestones, technologies, and aesthetic implications, the paper evaluates whether AI and robotic art are poised to replace traditional artists or establish new forms of collaboration. The findings indicate that while AI technologies are capable of generating intricate artworks, they lack human emotional expression and cultural sensitivity, highlighting the complementary rather than competitive role of AI in art. The study suggests that future artists will need to develop technical competencies to effectively collaborate with AI systems, reshaping the landscape of art and creativity. This paper contributes to the ongoing discourse on AI’s role in art by offering insights into the future of human-AI artistic partnerships and their impact on the broader art ecosystem. (shrink)

This paper provides a brief review of artificial intelligence (AI) methods for sustainable aerospace systems, focusing on predictive and generative models that enable innovation in Industry 4.0 and Industry 5.0. Predictive AI models are analyzed in terms of their capacity to estimate remaining useful life (RUL), optimize maintenance planning, and enhance safety management of critical aerospace components, such as turbofan engines and aircraft bearings. Generative models, including GANs, VAEs, and diffusion-based approaches, are examined as enablers of aerodynamic design optimization, (...) structural reliability assessment, and digital twin integration, significantly reducing costs of physical testing and accelerating certification. The review highlights how physics-informed neural networks (PINNs) integrate physical laws into machine learning, ensuring reliability and interpretability in real-world aerospace applications. Key challenges such as data scarcity, algorithmic transparency, and compliance with certification standards are addressed, alongside perspectives for hybrid AI approaches combining symbolic reasoning, neural networks, and digital twins. The findings demonstrate that the integration of predictive and generative AI methods not only supports sustainable development goals by reducing emissions, resource consumption, and downtime, but also strengthens the competitiveness of the aerospace sector in the European digital transition. (shrink)

Skeptical theism attempts to address the problem of evil by appealing to human cognitive limitations. The causal structure of the world is opaque to us. We cannot tell, and should not expect to be able to tell, if there is gratuitous evil, that is, evil which isn’t necessary for achieving some greater good or for precluding some greater evil. At first, it seems tempting to think that the rapid development of artificial intelligence (AI) technologies might change this fact. Our (...) cognitive limitations may no longer be a fixed point in responding to the problem of evil. But I argue that this won’t ultimately matter. The workings of any AI capable of rendering the problem of evil tractable will likely be just as opaque to us as the causal structure of the world God created. Interestingly, then, both God and a sufficiently advanced AI are alien intelligences to us. This reveals what is truly difficult, and perhaps intractable, about the problem of evil. For the evils to be defeated, we would need a relational understanding of why God permitted them. Yet such an understanding of an inscrutable God seems forever beyond our, and even our post-human descendants, ken. (shrink)

Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas, to address the hotly-contested question of whether computers (...) might become intellectually superior to human beings. (shrink)

Monetary intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the dark side of monetary Intelligence and behavioral economics—dishonesty. Dishonesty, a risky prospect, involves cost–benefit analysis of self-interest. We frame good or bad barrels in the environmental context as a proxy of high or low probability of getting caught for dishonesty, respectively. We theorize: The magnitude and (...) intensity of the relationship between love of money and dishonest prospect may reveal how individuals frame dishonesty in the context of two levels of subjective norm—perceived corporate ethical values at the micro-level and Corruption Perceptions Index at the macro-level, collected from multiple sources. Based on 6382 managers in 31 geopolitical entities across six continents, our cross-level three-way interaction effect illustrates: As expected, managers in good barrels, mixed barrels, and bad barrels display low, medium, and high magnitude of dishonesty, respectively. With high CEV, the intensity is the same across cultures. With low CEV, the intensity of dishonesty is the highest in high CPI entities —the Enron Effect, but the lowest in low CPI entities. CPI has a strong impact on the magnitude of dishonesty, whereas CEV has a strong impact on the intensity of dishonesty. We demonstrate dishonesty in light of monetary values and two frames of social norm, revealing critical implications to the field of behavioral economics and business ethics. (shrink)

Artificial intelligence (AI) holds considerable promise for transforming clinical diagnostics. While much has been written both about public attitudes toward the use of AI tools in medicine and about uncertainty regarding legal liability that may be delaying its adoption, the interface of these two issues has so far drawn less attention. However, understanding this interface is essential to determining how jury behaviour is likely to influence adoption of AI by physicians. One distinctive concern identified in this paper is a (...) ‘negative outcome penalty paradox’ (NOPP) in which physicians risk being penalised by juries in cases with negative outcomes, whether they overrule AI determinations or accept them. The paper notes three reasons why AI in medicine is uniquely susceptible to the NOPP and urges serious further consideration of this complex dilemma. (shrink)

In the text examined in Chapter 6, Socrates and Protarchus assign the life that combines intelligence and pleasure to the mixed kind (27d); and Socrates and Philebus assign the unmixed life of pleasure to the unlimited kind (27e–28a). The interlocutors then turn to the question of which kind to assign intelligence to. That question is answered by means of an elaborate argument in favor of thinking that it is intelligence that is the cause of good order both (...) at the cosmic level and in the human domain. On this basis, intelligence is assigned to the kind of cause. The chapter is organized around what is taken to be the main interpretive and philosophical questions that the section raises. The most important and interesting of these questions pertain to Socrates’ microcosm–macrocosm parallel (29a–30d) and its role in the argument for thinking that intelligence belongs to the kind of cause. (shrink)

Artificial intelligence is becoming part of our everyday experience and is expected to be ever more integrated into ordinary life for many years to come. Thus, it is important for those in product development, research, and public policy to understand how the public’s perception of AI is shaped. In this study, we conducted focus groups and an online survey to determine the knowledge of AI held by the American public, and to judge whether entertainment media is a major influence (...) on how Americans perceive AI. What we found is that the American public’s knowledge of AI is patchy: some have a good understanding of what is and what is not AI, but many do not. When it came to understanding what AI can do, most respondents believe that AI could “replace human jobs” but few thought that it could “feel emotion.” Most respondents were optimistic about the future and impact of AI, though about one third were not sure. Most respondents also did not think they could develop an emotional bond with or be comfortable being provided care by an AI. Regarding the influence of entertainment media on perceptions of AI, we found a significant relationship between people’s beliefs about AI in entertainment media and their beliefs about AI in reality. Those who believe AI is realistically depicted in entertainment media were more likely to see AIs as potential emotional partners or apocalyptic robots than to imagine AIs taking over jobs or operating as surveillance tools. (shrink)

Artificial Intelligence (AI) is set to bring changes to legal systems. These technologies may have positive practical implications when it comes to access, efficiency, and accuracy in Justice. However, there are still many uncertainties and challenges associated with the implementation of AI in the legal space. In this research, we surveyed Judges on critical challenges related to the Judging Profession in the AI paradigm; Automated Adjudication; and Legal Principles. Our results suggest that (i) Judges are hesitant about changes in (...) their profession. They signal the need for adequate training that fosters legal literacy in AI, but are less open to changes in legal writing or their social and institutional role; (ii) Judges believe higher levels of automation only lead to fair outcomes if used in earlier phases of adjudication; (iii) Judges believe and are concerned about AI leading to Techno-Legal Positivism; and (iv) Judges consider that Legal AI technologies may have a positive impact in some legal principles, as long as everyone has equal access to those technologies and cybersecurity and judge on the loop safeguards are in place; and (v) Judges are strongly concerned about the de-humanization of Justice. They consider that assessing evidence, analyzing arguments, and deciding on a legal case should be inherently human. By surveying these practitioners, we aim to foster a responsible, inclusive, and transparent innovation in Justice. (shrink)

This paper proposes a Confucian reframing of generative artificial intelligence (GenAI) as natural intelligence – technology that emerges from and remains embedded within human creativity, culture, and moral relationships. Drawing on Confucian concepts such as shengsheng (creative transformation), ren (co-humanity), and xue yi cheng ren (learning to become human), it challenges Western dualisms that separate human and machine, natural and artificial, and argues that GenAI should be understood as an extension of human creativity operating within human-guided ethical judgment (...) and responsibility. The paper explores implications for pedagogy, curriculum, and institutional policy, advocating for relational ethics, moral cultivation, and value-based governance. While rooted in Confucian thought, this approach is presented as a generative ethical lens that can be adapted and brought into dialogue with other traditions to inform global conversations on AI in education. (shrink)

Collective intelligence research spans multiple disciplines and focuses on a broad range of collective behaviors, including group problem-solving, flocking in social animals, and the formation of social knowledge. It is not apparent what these different forms of collective intelligence have in common, apart from being instances of collective behavior. In this paper, we develop a framework that enables us to better classify different forms of collectively intelligent behavior in relation to one another based on the information processing mechanisms (...) involved. We argue that these behaviors share a common foundation, which we call collective information processing, or CIP. CIP involves two key mechanisms: (1) individual processing of group information and (2) group processing, or group-level sensitivity to the arrangement of individual information. We operationalize the CIP framework to analyze different forms of collective intelligence, both classifying them in relation to one another and in alignment with generalized quantifiable measures of information processing. Our account of collective intelligence as CIP offers a novel framework for identifying and classifying forms of collective intelligence across a wide range of disciplinary contexts. This framework is meant to unify and subsume, rather than simply challenge, existing attempts to define collective intelligence. (shrink)

Despite being a relatively new development, artificial intelligence is already considered one of the most important technologies in human history. Also known as AI, artificial intelligence is used every day in an increasing number of tasks. However, AI is also a controversial topic. Despite its many benefits, specialists also warn of its risks. Amid this debate, numerous projects continue to explore new and more complex uses for this technology. One of these areas is the administration of justice. From (...) its use as a legal information search tool to its potential deployment as an artificial judge or mediator, AI undoubtedly has the potential to bring about profound changes in the justice system in the future. In this context, the present study seeks to analyze the suitability of the current Mexican legal framework both to leverage the opportunities offered by artificial intelligence and to address its challenges in the administration of justice. To this end, the case of the new civil and family justice model, which will begin upon the entry into force of the National Code of Civil and Family Procedure projected for April 2027, will be used. It is worth mentioning that the choice of civil and family procedural law is not accidental; on the contrary, the new Code stands out, among other innovations, for its special emphasis on implementing digital justice and using information and communication technologies. (shrink)

Monetary Intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the bright side of Monetary Intelligence and behavioral economics, frames money attitude in the context of pay and life satisfaction, and controls money at the macro-level (GDP per capita) and micro-level (Z income). We theorize: Managers with low love of money motive but high stewardship behavior will (...) have high subjective well-being: pay satisfaction and quality of life. Data collected from 6586 managers in 32 cultures across six continents support our theory. Interestingly, GDP per capita is related to life satisfaction, but not to pay satisfaction. Individual income is related to both life and pay satisfaction. Neither GDP nor income is related to Happiness (money makes people happy). Our theoretical model across three GDP groups offers new discoveries: In high GDP (rich) entities, “high income” not only reduces aspirations—“Rich, Motivator, and Power,” but also promotes stewardship behavior—“Budget, Give/Donate, and Contribute” and appreciation of “Achievement.” After controlling income, we demonstrate the bright side of Monetary Intelligence: Low love of money motive but high stewardship behavior define Monetary Intelligence. “Good apples enjoy good quality of life in good barrels.” This notion adds another explanation to managers’ low magnitude of dishonesty in entities with high Corruption Perceptions Index (CPI) (risk aversion for gains of high probability) (Tang et al. 2015. doi:10.1007/s10551-015-2942-4). In low GDP (poor) entities, high income is related to poor Budgeting skills and escalated Happiness. These managers experience equal satisfaction with pay and life. We add a new vocabulary to the conversation of monetary intelligence, income, GDP, happiness, subjective well-being, good and bad apples and barrels, corruption, and behavioral ethics. (shrink)

Artificial Intelligence (AI) safety is an interdisciplinary field undergoing transformation to become its own paradigm. By adopting a Kuhnian approach to this transformation, I seek to describe the features that make AI safety pre-paradigmatic along with the conditions that are required for the field to transition to the paradigmatic stage. I argue that the nature of the alignment problem–the key research question of the field–is such that it calls for its own paradigm as the research necessary to solve it (...) goes beyond the typical desiderata in machine learning work. It incorporates a series of metascientific projects as well as breakthroughs in normative and applied ethics. The faster and better these projects are executed, the more likely that the field will come to resolve its puzzles, which will benefit society at large. (shrink)

Among the countless problems posed by Charles Darwin in On the Origin of Species (1859), the search for the biological basis of a supposed human nature became one of the most debated lines of inquiry in the 20th century. The study of human intelligence is one of the most representative examples of this debate, which, in turn, centers on the broader nature-nurture debate.

Artificial intelligence (AI) is transforming the global knowledge economy, creating unprecedented opportunities for innovation while simultaneously reproducing structural inequalities between the Global North and South. AI development is deeply intertwined with historical patterns of resource extraction, epistemic domination, and technological dependency, which perpetuate economic and cognitive asymmetries. This article examines how AI reinforces structural disadvantages in the Global South, focusing on three interrelated challenges: economic dependence and technological subordination, digital and infrastructural disparities, and inequitable access to knowledge resources. Drawing (...) on decolonial theory and Michael A. Peters’ framework of knowledge socialism, the study argues for reconceptualizing knowledge as a public good, emphasizing collaborative production, capacity building, and inclusive governance mechanisms. By foregrounding systemic inequities and articulating practical strategies, this paper offers a normative and operational framework to promote equitable participation in the AI-driven global knowledge economy. (shrink)

Artificial intelligence (AI) has developed dramatically in recent decades. Its use has been unprecedented in various disciplines and fields such as: data science, information science, online marketing and data mining from the development of various platforms, as well as in the area of “connected’ objects. Since the advent of AI, we have been moving towards ubiquitous computing. Widely used in our everyday personal and professional lives, computing technology has become increasingly “intelligent” and capable of anticipating our every need, with (...) the goal of helping us to be more productive in the long run. Generally speaking, technology refers here to the deployment of an application in a computer system, with or without the use of AI; however, the use of AI in language learning applications is still somewhat neglected. (shrink)

The article presents a socio-philosophical analysis of artificial intelligence (AI) integration into public administration systems. The research focuses on identifying an optimal balance between enhancing administrative efficiency and preserving humanistic values. The author examines diverse perspectives on AI’s role in contemporary society, ranging from techno-optimistic concepts that view AI as a tool for qualitative improvement of human life, to critical theories warning of dehumanization risks and increased social control. The paper conducts a comparative analysis of national AI development strategies (...) among leading global powers, identifying their common features and significant differences shaped by cultural, political, and economic factors. Potential risks and threats associated with the implementation of AI systems in public administration are explored, including issues of personal data protection, information security, and the ethical dimensions of algorithmic decision-making. The concept of a human-centered approach to AI is examined as a potential guiding principle for the development and deployment of these technologies. Various levels of control over AI systems are characterized, encompassing legal regulation, professional and public evaluation. Particular attention is given to the prospects of artificial general intelligence (AGI) development and its potential impact on the transformation of state institutions and social relations. The study argues that AGI architecture, enabling genuine system agency, must incorporate a level responsible for actualization functions (strategic goal-setting, ethics, knowledge, and self-identification). Special emphasis is placed on the system’s awareness of its finite existence as a necessary condition for developing meaningful operational strategies and ethical principles. The article concludes that as AI technologies advance, the importance of ethical norms, value systems, and responsibility principles increases since these core societal factors cannot be fully replaced even by the most sophisticated regulation. The author highlights the growing significance of mutual trust between state and society in an environment where AI systems provide unprecedented opportunities for social control. (shrink)

Artificial intelligence, while presenting itself as a novelty in the fields of education, science and the business industry, is likely being used as a hegemonic tool for economic and political control. Concerns about privacy ethics, class division and the specter of AI-incited biowarfare controlled by supremacist-minded entities that benefit from the datafication of individuals for economic profit and the attainment of politicized control-seeking objectives are the axial arguments of this position paper. As a result, this review makes a case (...) that AI is being used as a tool of hegemony by presenting an analytical framework derived from the ‘less mainstream’ varied corpus of literature published between 1984 and 2024. Furthermore, while the literature also reveals attempts to monitor misuse of AI, to date there have been no solutions offered concerning privacy and surveillance, alternatives to the potential loss of jobs through automated AI or the menace of AI-operated biological warfare already being tested in war-torn parts of the world. Resolving the existing hegemonic challenges is of paramount importance and must be properly addressed in order not to be met with an existential crisis threatening the continuity of humanity. (shrink)

The growth experienced by intercultural contacts in the last decades generates numerous challenges in different areas of personal and professional life. Cultural intelligence is progressively consolidating as the best tool to face them. It is an ability that combines the study of cultures from the psychological, geographical, historical, anthropological and sociological points of view. In order to analyse how to work on this capacity, an approach is proposed that is related to the business world. This paper presents the main (...) solutions currently adopted to offer services related to the aforementioned capability. (shrink)

Intelligence Unbound explores the prospects, promises, and potential dangers of machine intelligence and uploaded minds in a collection of state-of-the-art essays from internationally recognized philosophers, AI researchers, science fiction authors, and theorists. Compelling and intellectually sophisticated exploration of the latest thinking on Artificial Intelligence and machine minds Features contributions from an international cast of philosophers, Artificial Intelligence researchers, science fiction authors, and more Offers current, diverse perspectives on machine intelligence and uploaded minds, emerging topics of (...) tremendous interest Illuminates the nature and ethics of tomorrow’s machine minds—and of the convergence of humans and machines—to consider the pros and cons of a variety of intriguing possibilities Considers classic philosophical puzzles as well as the latest topics debated by scholars Covers a wide range of viewpoints and arguments regarding the prospects of uploading and machine intelligence, including proponents and skeptics, pros and cons. (shrink)

This paper undertakes a rigorous philosophical and scientific examination of the concept of intelligence as it is deployed in contemporary artificial intelligence research, arguing that the dominant computational paradigm rests upon a profound category error: the conflation of statistical pattern completion with genuine cognitive understanding. Drawing on the philosophical critiques advanced by Hubert Dreyfus beginning in 1965, the phenomenological tradition from Husserl to Merleau-Ponty, the epistemological challenges posed by Gödel's incompleteness theorems, and evidence from the history of science (...) — particularly the anomalous case of Albert Einstein — the paper develops a multi-layered argument that intelligence is not a formalizable property but an emergent relational capacity arising from the embodied, temporally situated encounter of an organism with a meaningful world. -/- The paper further examines the boundary between physics and metaphysics as the site of science's most persistent unresolved problems, arguing that the refusal to cross this boundary — however epistemically motivated — may itself constitute an obstacle to scientific progress. Five domains are identified where this boundary tension is most acute: consciousness and neuroscience, quantum mechanics and the measurement problem, the semantics of natural language, the epistemology of mathematical intuition, and the phenomenology of scientific creativity. In each domain, the paper argues, the hard problem is not merely technical but structural: it concerns the relationship between formal description and lived meaning. -/- The paper concludes by proposing a new epistemological framework — Relational Intelligence Theory (RIT) — as a research program that takes seriously the irreducibility of meaning, context, and embodied cognition, and which offers criteria for distinguishing genuine cognitive systems from sophisticated predictive simulacra. The stakes of this distinction are argued to be not merely academic but civilizational: a culture that confuses pattern-matching with understanding risks a systematic atrophying of the very capacities it believes it is augmenting. (shrink)

This article analyzes how artificial intelligence systems used in clinical prioritization reproduce structural inequalities, generating patterns of indirect discrimination. Using a qualitative documentary-analytical design, binding legal frameworks enacted between 2016 and 2025 in the European Union, the United States, China, the United Kingdom, Brazil and Spain are examined. Results show accelerated regulatory growth since 2021, emphasizing data protection and transparency, yet persistent gaps remain in liability and bias auditing. The study concludes that health care automation requires mandatory algorithmic impact (...) assessments and enforceable accountability mechanisms. (shrink)

This book explores the intersection of legal frameworks, healthcare innovation, and computational intelligence, shedding light on how emerging technologies like AI and ML are reshaping the medical landscape. It presents real life challenges such as patient privacy, data security, and compliance issues in smart healthcare by engaging into associated ethical and regulatory implications. Comprising the concepts of predictive analytics, regulatory compliance algorithms, and legal decision-making processes, this book offers a roadmap for stakeholders to navigate the evolving landscape of healthcare (...) innovation responsibly and ethically. Investigates how artificial intelligence supports legal decision-making processes in smart healthcare, addressing ethical and accountability concerns Demonstrates the use of smart contracts and automation tools powered by computational intelligence to streamline legal processes and ensure compliance in smart healthcare initiatives Focuses on managing healthcare data within legal frameworks, emphasizing computational intelligence's role in ensuring privacy and security. Examines how computational intelligence enables predictive analytics models to anticipate legal challenges and compliance issues in smart healthcare. Highlights the development and implementation of computational algorithms for navigating evolving legal frameworks in healthcare. This reference book is a useful resource for scholars and researchers working on smart healthcare. (shrink)

Artificial intelligence (AI) has transitioned from laboratory research to becoming an integral part of everyday life in technologies such as robotics, natural language processing, facial recognition, machine learning, autonomous transportation, and various planning and problem-solving systems. The practical implications of AI in our daily lives are often more pressing than philosophical debates about AI’s potential to exhibit human-like qualities such as reason, creativity, consciousness, or emotional companionship. While these kinds of questions are important, the application of these AI technologies (...) in the everyday world is too many far more important than their ontological nature.The fusion of AI with so many different aspects of the everyday world, where it and other digital technologies become the very environment in which we live and breathe and have our being, raises ethical questions concerning how we use AI wisely to promote human flourishing and care of the wider world. This essay adopts a public theological perspective, incorporating both Christian insights and other viewpoints, to explore AI’s role in big data, surveillance, and the workplace, aiming to support human well-being in the AI era. (shrink)

Artificial Intelligence (AI) is occupying an increasingly dominant space in our daily lives, with the potential of becoming a vital tool in education. AI is also making significant stride sin the realm of art Against this backdrop, an online museum founded in 2015 continues to uphold its core principles: the defense of Human Rights and advocacy for sexual diversity. This raises the question: Is it possible to use AI to support LGBTQI+ individuals and groups? Museari demonstrates that virtual spaces (...) can serve as powerful platforms for educational initiatives, while maintaining their artistic and humanistic values. (shrink)

Adaptive Intelligence is a dramatic reappraisal and reframing of the concept of human intelligence. In a sweeping analysis, Robert J. Sternberg argues that we are using a fatally-flawed, outdated conception of intelligence; one which may promote technological advancement, but which has also accelerated climate change, pollution, the use of weaponry, and inequality. Instead of focusing on the narrow academic skills measured by standardized tests, societies should teach and assess adaptive intelligence, defined as the use of collective (...) talent in service of the common good. This book describes why the outdated notion of intelligence persists, what adaptive intelligence is, and how it could lead humankind on a more positive path. (shrink)

Emotional intelligence can be comprehensively redefined based on the componential emotion approach. The componential emotion approach defines emotions as processes that are elicited by goal-relevant situations and that consist of an interplay between appraisals, action tendencies, bodily reactions, expressions, and feelings. Within the componential emotion approach, emotional intelligence can be redefined as the ability (a) to identify emotions based on information from one or more of the five emotion components, (b) to understand emotions in terms of the likely (...) appraisals, action tendencies, bodily reactions, expressions, and feelings that are elicited by goal-relevant situations, and (c) to know how to regulate emotions by modifying one or more of these five components. (shrink)

Artificial intelligence and robotics have revolutionized slaughterhouse operations, allowing collaborative robots to reduce the physical and moral stress on butchers. However, animals remain an “absent referent” in the process, and the development of artificial intelligence in this field continues the trend of moral distancing present in killing. This dystopian scenario, in which machines endlessly breed and kill animals, and in which the avoidance of moral responsibility is aided by artificial intelligence so that effectively no one has to (...) bear the burden of blame for their deaths, is a manifestation of the triumph of necropower. (shrink)

Artificial intelligence (AI), characterized by its capability to mimic cognitive functions such as problem-solving and learning, is burgeoning as an influential player in medical advancements. Specifically, in the domain of neurosurgery, AI’s potent applications are poised to redefine diagnostics, surgical planning, and treatment modalities. This chapter elucidates some of the current applications and envisages the prospective innovations of AI in neurosurgery.