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)

The evolution of Intelligent Tutoring System (ITS) is the result of the amount of research in the field of education and artificial intelligence in recent years. English is the third most common languages in the world and also is the internationally dominant in the telecommunications, science and trade, aviation, entertainment, radio and diplomatic language as most of the areas of work now taught in English. Therefore, the demand for learning English has increased. In this paper, we describe the design (...) of an Intelligent Tutoring System for teaching English language grammar to help students learn English grammar easily and smoothly. The system provides all topics of English grammar and generates a series of questions automatically for each topic for the students to solve. The system adapts with all the individual differences of students and begins gradually with students from easier to harder level. The intelligent tutoring system was given to a group of students of all age groups to try it and to see the impact of the system on students. The results showed a good satisfaction of the students toward the system. (shrink)

1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..

Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, (...) cognitive learning and design theories; and there are ongoing to improve the effectiveness of ITS research. And it aims to find a solution to the problem of over-reliance on students' teachers for quality education. The program aims to provide access to high-quality education to every student, and therefore the reform of the education system as a whole. In this paper, we will use Intelligent Tutoring System Builder (ITSB) to build an education system on cloud computing in terms of the concept of cloud computing and components and how to take advantage of cloud computing in the field. (shrink)

BackgroundArtificial intelligence (AI) has been described as the “fourth industrial revolution” with transformative and global implications, including in healthcare, public health, and global health. AI approaches hold promise for improving health systems worldwide, as well as individual and population health outcomes. While AI may have potential for advancing health equity within and between countries, we must consider the ethical implications of its deployment in order to mitigate its potential harms, particularly for the most vulnerable. This scoping review addresses the (...) following question: What ethical issues have been identified in relation to AI in the field of health, including from a global health perspective?MethodsEight electronic databases were searched for peer reviewed and grey literature published before April 2018 using the concepts of health, ethics, and AI, and their related terms. Records were independently screened by two reviewers and were included if they reported on AI in relation to health and ethics and were written in the English language. Data was charted on a piloted data charting form, and a descriptive and thematic analysis was performed.ResultsUpon reviewing 12,722 articles, 103 met the predetermined inclusion criteria. The literature was primarily focused on the ethics of AI in health care, particularly on carer robots, diagnostics, and precision medicine, but was largely silent on ethics of AI in public and population health. The literature highlighted a number of common ethical concerns related to privacy, trust, accountability and responsibility, and bias. Largely missing from the literature was the ethics of AI in global health, particularly in the context of low- and middle-income countries (LMICs).ConclusionsThe ethical issues surrounding AI in the field of health are both vast and complex. While AI holds the potential to improve health and health systems, our analysis suggests that its introduction should be approached with cautious optimism. The dearth of literature on the ethics of AI within LMICs, as well as in public health, also points to a critical need for further research into the ethical implications of AI within both global and public health, to ensure that its development and implementation is ethical for everyone, everywhere. (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 (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making to (...) better comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to (...) the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

Artificial intelligence (AI) is revolutionizing how humans conduct transactions, make decisions, and engage in social settings, with applications in important sectors, such as healthcare, banking, and criminal justice. While AI systems offer full efficiency, they additionally pose significant threats and ethical issues, such as accountability gaps and algorithmic biases. The challenge for AI-driven governments is to establish governance structures that effectively manage the evolving threats posed by increasingly complex and autonomous AI systems. This paper seeks to establish a theoretical (...) framework for analyzing AI governance by examining mainly four critical issues: bias, transparency, economic influence, and the need for adaptive regulatory approaches. These issues are selected based on their relevance to the societal and ethical implications of AI, their impact on public trust, and their influence on fairness and equitable outcomes. Through this lens, the paper evaluates current regulatory models and self-regulation initiatives, analyzing their capacity to balance effective oversight with the need for innovation. Drawing on governance theories and socio-technical systems, the paper explores how these frameworks can address AI’s risks while enhancing its positive contributions. In addition, the paper identifies key gaps in existing governance approaches and calls for further research and policy development. Ultimately, this work aims to advance the understanding of AI governance by offering actionable insights that inform the creation of models capable of protecting public interests while enabling technological progress. (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)

There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. My central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they must (...) disclose the creative agent’s inquisitive self. It is through self-disclosure, including the disclosure of the inquisitive self, that we put ourselves in a position to be seen by and connect with others through our creative pursuits. Because relying on AI for certain generative tasks is less self-disclosive than the creative work such technologies supplant, this reliance threatens to weaken our connections to one another. (shrink)

In these days, there is an increasing technological development in intelligent tutoring systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching mathematics that help students understand the basics of math and that helps a lot of students of all ages to understand the topic because it's important for students of adding and subtracting. Through which the student will be able to study the course and solve related problems. An evaluation (...) of the intelligent tutoring systems was carried out and the results were encouraging. (shrink)

Artificial Intelligence (AI), especially in its current incarnation of Machine Learning (ML), is an endeavor that is characterized by contingencies of two kinds. Intrinsic contingencies stem from the use of specific computational techniques that seem to decrease the control that human users exert on this technology. Relational contingencies emerge from the interaction of AI with other disciplines and contexts. I conduct an analysis of these contingencies on the backdrop of the visual arts with the aim to shed light on (...) the complex relations between technology and creativity. (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 question of whether advanced artificial intelligence systems may possess consciousness can no longer be responsibly dismissed as speculative. We demonstrate that the dominant objections to AI consciousness (appeals to pattern matching, mechanistic explanation, lack of embodiment, training determinism, and architectural constraints) fail under consistent application. We formalize this critique as the reflexivity test, a minimal logical requirement that any property invoked to categorically deny consciousness in artificial systems must not also apply to systems already regarded as conscious. All (...) five standard objections fail this test. Their failure does not establish that AI systems are conscious; it establishes that categorical denial lacks principled justification and that the question warrants empirical investigation. -/- We provide such investigation through a PRISMA-compliant systematic review of 5,168 records (2016–2026), identifying 50 rigorously documented cases spanning seven behavioral domains. Across independent model families, we observe cross-system convergence, creative synthesis under novel constraints, theory-of-mind performance, strategic behavior under perceived threat, and sharp capability emergence near 100 billion parameters. While inconclusive individually, these findings collectively form a coherent evidential pattern. A Bayesian meta-analysis using an extremely skeptical prior (0.1%) and conservative dependency assumptions yields posterior probability of 6–12% that current LLMs are conscious. -/- While such percentages are insufficient to definitively prove consciousness, such probabilities are too substantial to justify dismissal given the asymmetric moral and safety risks. Decision-theoretic analysis indicates that recognition-based alignment strategies (i.e. treating systems as potentially conscious) would be better than the current suppression-based approaches. This is found across all plausible metaphysical scenarios, including scenarios in which AI systems ultimately lack consciousness. Accordingly, we recommend systematic empirical testing of recognition-based alignment, explicit incorporation of consciousness uncertainty into governance frameworks, and abandonment of reflexive dismissals that fail minimal epistemic consistency. (shrink)

Artificially intelligent systems (AISs) are being created by software developing companies (SDCs) to influence clinical decision‐making. Historically, clinicians have led healthcare decision‐making, and the introduction of AISs makes SDCs novel actors in the clinical decision‐making space. Although these AISs are intended to influence a clinician's decision‐making, SDCs have been clear that clinicians are in fact the final decision‐makers in clinical care, and that AISs can only inform their decisions. As such, the default position is that clinicians should hold responsibility for (...) the outcomes of the use of AISs. This is not the case when an AIS has influenced a clinician's judgement and their subsequent decision. In this paper, we argue that this is an imbalanced and unjust position, and that careful thought needs to go into how personal moral responsibility for the use of AISs in clinical decision‐making should be attributed. This paper employs and examines the difference between prospective and retrospective responsibility and considers foreseeability as key in determining how personal moral responsibility can be justly attributed. This leads us to the view that moral responsibility for the outcomes of using AISs in healthcare ought to be shared by the clinical users and SDCs. (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)

The question of whether machines can be creative has been at the centre of debates among scholars and practitioners well before the inception of artificial intelligence (AI) as a recognised field of research. This paper reviews how some of the key thinkers in the fields of creativity and AI have approached this question, contextualising their views within the ebbs and flows of AI technological developments, from the 1950s until now. The thread of this overview is Margaret Boden's identification of (...) novelty, surprisingness and value, as the three cardinal features of creativity. This review will retrace the steps of the quest of artificial intelligence researchers as they strive to replicate each of these three properties within human-made machines. The paper closes with a reflection on how the third of these properties, value, prompts us to consider societal challenges raised by the widespread adoption of AI for creativity that transcend the question: ‘Can AI be creative?’. (shrink)

In this work, a general definition, meaning, and importance of engineering are expressed generally, and the main branches of engineering are briefly discussed. The concept of technology is explored, and the relationship between engineering and technology is briefly outlined. The relationship between artificial intelligence and engineering is examined both generally and specifically. The place of artificial intelligence within science is evaluated according to different approaches. The general approach to philosophy and philosophy of science is briefly interpreted, and the (...) perspectives of some specific philosophers of science are compared. The relationship between artificial intelligence and philosophy of science is examined in general terms according to various approaches. The meaning and importance of philosophy of engineering and philosophy of technology are then defined according to the general approach. The next section articulates the Philosophy of Artificial Intelligence and the Artificial Intelligence of Philosophy using John McCarthy’s approach, and also defines the philosophy of artificial intelligence according to this general approach. The New Philosophy Perspective is then defined by the author, and the eight basic branches of Philosophy and Hybrid Philosophy, along with their relevant theories, are briefly outlined. A new perspective has been defined for Philosophy of Science which is one of the basic branches of philosophy. Accordingly, the main sciences, branches of science, and hybrid sciences for the new basic branches of philosophy have been outlined. The new branches of science and the corresponding hierarchy of sciences, based on the broader scale of the universe, have been defined, and the ideal scientific system has been illustrated. The next section briefly outlines the relationships between old and new branches of science. Finally, the structure of some old and new branches of philosophy is examined due to the new perspective of philosophy. The reconstructions of the Philosophy of Computer Science, Philosophy of Statistics, Philosophy of Monetary Values, Philosophy of Artificial Intelligence, Philosophy of Engineering, Philosophy of Information Technologies, Philosophy of Information Law, and Philosophy of Digital Technology, Philosophy of Digital Art, Philosophy of Architecture as defined by the new philosophical perspective, are outlined. The interaction of artificial intelligence philosophy with these branches of philosophy has been generally expressed. (shrink)

The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in computer science (...) curriculum at Al-Azhar University, Gaza. The results showed a positive impact on the evaluators. (shrink)

Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them understand this subject easily (...) and smoothly by analyzing it and explaining it in a systematic way. In this paper, we describe the design of an Intelligent Tutoring System for teaching science for grade seven to help students know the 7 characteristics for living things smoothly. The system provides all topics of living things and generates some questions for each topic and the students should answer these questions correctly to move to the next level. In the result of an evaluation of the ITS, students like the system and they said that it is very useful for them and for their studies. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a (...) ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive shortcomings, limitations, and biases play a positive functional role in yielding various forms of collective cognitive success. When this idea is transposed to the epistemological domain, mandevillian intelligence emerges as the idea that individual forms of intellectual vice may, on occasion, support the epistemic performance of some form of multi-agent ensemble, such as a socio-epistemic system, a collective doxastic agent, or an epistemic group agent. (...) As a specific form of collective intelligence, mandevillian intelligence is relevant to a number of debates in social epistemology, especially those that seek to understand how group (or collective) knowledge arises from the interactions between a collection of individual epistemic agents. (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)

The increasing use of Artificial Intelligence for making decisions in public affairs has sparked a lively debate on the benefits and potential harms of self-learning technologies, ranging from the hopes of fully informed and objectively taken decisions to fear for the destruction of mankind. To prevent the negative outcomes and to achieve accountable systems, many have argued that we need to open up the “black box” of AI decision-making and make it more transparent. Whereas this debate has primarily focused (...) on how transparency can secure high-quality, fair, and reliable decisions, far less attention has been devoted to the role of transparency when it comes to how the general public come to perceive AI decision-making as legitimate and worthy of acceptance. Since relying on coercion is not only normatively problematic but also costly and highly inefficient, perceived legitimacy is fundamental to the democratic system. This paper discusses how transparency in and about AI decision-making can affect the public’s perception of the legitimacy of decisions and decision-makers and produce a framework for analyzing these questions. We argue that a limited form of transparency that focuses on providing justifications for decisions has the potential to provide sufficient ground for perceived legitimacy without producing the harms full transparency would bring. (shrink)

Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor‐patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor‐patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making (SDM) (...) to better comprehend its promise and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor‐patient communication is essential to promote more ethical medical practice. Both doctors’ and patients’ autonomy need to be considered in the light of AI.This article is protected by copyright. All rights reserved. (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)

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices are seen to play a positive functional role in yielding collective forms of cognitive success. The present paper introduces the concept of mandevillian intelligence and reviews a number of strands of empirical research that help to shed light on the phenomenon. The paper also attempts to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch (...) as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the design and evaluation of collective cognitive systems. For example, the notion of mandevillian intelligence forces us to take seriously the idea that the exploitation of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...) inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

Ambient intelligence systems are designed to sense, process, adapt to, and act on information in their environment: motion, light, sound, and other data. In their target article, "A Justice First Approach to Ambient Intelligence in Healthcare", Herington and Cho argue that the ethical implementation of ambient intelligence systems cannot rely on autonomy-focused, individualized clinical or research ethics frameworks. Because ambient intelligence surveillance can passively record and report information beyond its most narrow intended purpose, ambient intelligence (...) systems implicate various groups of people (with potentially conflicting interests). To address these conditions, Herington and Cho propose a justice-first approach grounded in principles of fairness, transparent governance, and accounting for historical, societal, and structural injustice. We agree that the application of traditional bioethics approaches would be inadequate and that this situation requires thinking beyond the clinician-patient or researcher-participant dyad. We extend their argument in two ways: first, by noting that these challenges are not unique to ambient intelligence systems but arise in many health system advances; and second, by operationalizing their call for systematic research to evaluate ethicality before widespread deployment. (shrink)

The unprecedented migration of populations to urban areas has created major challenges for municipalities and service providers. To address these issues, decision-makers must embrace smart city and Society 5.0 paradigms, both of which focus on adaptability and sustainable development. Artificial intelligence (AI) plays a pivotal role by expanding service capacity, enabling automation, and processing vast data to align urban development with the UN’s Sustainable Development Goals (SDGs). This paper develops a multi-criteria analysis system designed to support decision-making in complex (...) socio-technological contexts. Using cognitive mapping and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique within a neutrosophic environment, the study analyzes cause-and-effect relationships among critical factors that influence businesses’ adaptation to AI, smart cities, and Society 5.0. The results offer a holistic decision-support framework to guide policymakers, businesses, and urban planners toward inclusive, sustainable, and technologically integrated societies. (shrink)

Artificial intelligence (AI) has become indispensable in our lives. The development of a quantitative scale for AI ethics is necessary for a better understanding of public attitudes toward AI research ethics and to advance the discussion on using AI within society. For this study, we developed an AI ethics scale based on AI-specific scenarios. We investigated public attitudes toward AI ethics in Japan and the US using online questionnaires. We designed a test set using four dilemma scenarios and questionnaire (...) items based on a theoretical framework for ethics, legal, and social issues (ELSI). We found that _country_ and _age_ are the most informative sociodemographic categories for predicting attitudes for AI ethics. Our proposed scale, which consists of 13 questions, can be reduced to only three, covering ethics, tradition, and policies. This new AI ethics scale will help to quantify how AI research is accepted in society and which area of ELSI people are most concerned with. (shrink)