Proceedings

Other

9 pages, 237 KB

Open AccessProceeding Paper

Jean Piaget and Objectivity—Genetic Epistemology’s Place in a View from Nowhere

by Mark A. Winstanley

Proceedings 2025, 126(1), 1; https://doi.org/10.3390/proceedings2025126001 - 13 Aug 2025

Viewed by 611

Science pursues objectivity. According to Thomas Nagel, “we must get outside of ourselves, and view the world from nowhere within it” is the most natural expression of this goal. However, we cannot literally get outside of ourselves; realistically, we can only hope to [...] Read more.

Science pursues objectivity. According to Thomas Nagel, “we must get outside of ourselves, and view the world from nowhere within it” is the most natural expression of this goal. However, we cannot literally get outside of ourselves; realistically, we can only hope to achieve a more detached conception by relying “less and less on certain individual aspects, and more and more on something else, less individual, which is also part of us”. This “self-transcendent conception should ideally explain (1) what the world is like; (2) what we are like; (3) why the world appears to beings like us in certain respects as it is and in certain respects as it isn’t; (4) how beings like us can arrive at such a conception.” The natural and human sciences address (1)–(3), but the last condition is rarely met, according to Nagel. In this paper, I argue that the genetic epistemology conceived by Jean Piaget as a science of the growth of knowledge explains how beings like us meet condition (4). Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

7 pages, 171 KB

Open AccessProceeding Paper

The Evolution of Intelligence from Active Matter to Complex Intelligent Systems via Agent-Based Autopoiesis

by Gordana Dodig-Crnkovic

Proceedings 2025, 126(1), 2; https://doi.org/10.3390/proceedings2025126002 - 18 Aug 2025

Viewed by 819

Abstract

Intelligence is a central topic in computing and philosophy, yet its origins and biological roots remain poorly understood. The framework proposed in this paper approaches intelligence as the complexification of agency across multiple levels of organization—from active matter to symbolic and social systems. [...] Read more.

Intelligence is a central topic in computing and philosophy, yet its origins and biological roots remain poorly understood. The framework proposed in this paper approaches intelligence as the complexification of agency across multiple levels of organization—from active matter to symbolic and social systems. Agents gradually acquire the capacity to detect differences, regulate themselves, and sustain identity within dynamic environments. Grounded in autopoiesis, cognition is reframed as a recursive, embodied process sustaining life through self-construction. Intelligence evolves as a problem-solving capacity of increasing organizational complexity: from physical self-organization to collective and reflexive capabilities. The model integrates systems theory, cybernetics, enactivism, and computational approaches into a unified info-computational perspective. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

9 pages, 1005 KB

Open AccessProceeding Paper

General Theory of Information and Mindful Machines

by Rao Mikkilineni

Proceedings 2025, 126(1), 3; https://doi.org/10.3390/proceedings2025126003 - 26 Aug 2025

Viewed by 853

Abstract

As artificial intelligence advances toward unprecedented capabilities, society faces a choice between two trajectories. One continues scaling transformer-based architectures, such as state-of-the-art large language models (LLMs) like GPT-4, Claude, and Gemini, aiming for broad generalization and emergent capabilities. This approach has produced powerful [...] Read more.

As artificial intelligence advances toward unprecedented capabilities, society faces a choice between two trajectories. One continues scaling transformer-based architectures, such as state-of-the-art large language models (LLMs) like GPT-4, Claude, and Gemini, aiming for broad generalization and emergent capabilities. This approach has produced powerful tools but remains largely statistical, with unclear potential to achieve hypothetical “superintelligence”—a term used here as a conceptual reference to systems that might outperform humans across most cognitive domains, though no consensus on its definition or framework currently exists. The alternative explored here is the Mindful Machines paradigm—AI systems that could, in future, integrate intelligence with semantic grounding, embedded ethical constraints, and goal-directed self-regulation. This paper outlines the Mindful Machine architecture, grounded in Mark Burgin’s General Theory of Information (GTI), and proposes a post-Turing model of cognition that directly encodes memory, meaning, and teleological goals into the computational substrate. Two implementations are cited as proofs of concept. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

► Show Figures

Figure 1

9 pages, 188 KB

Open AccessProceeding Paper

Intelligence and the Hard Problem of Consciousness—With ‘Dual-Aspect Theory’ Notes

by Marcus Abundis

Proceedings 2025, 126(1), 4; https://doi.org/10.3390/proceedings2025126004 - 10 Sep 2025

Viewed by 631

Abstract

To model informatic intelligence, agency, consciousness and the like, one must address a claimed Hard Problem: that a grasp of ‘the mind’ lies wholly beyond scientific views. While this claim is suspect, persistent analogues can be identified in the literature, such as a [...] Read more.

To model informatic intelligence, agency, consciousness and the like, one must address a claimed Hard Problem: that a grasp of ‘the mind’ lies wholly beyond scientific views. While this claim is suspect, persistent analogues can be identified in the literature, such as a “symbol grounding problem”, “solving intelligence”, a missing “theory of meaning”, and more. The topic of subjective phenomena thus still holds sway in many corners as being unresolved. But firm analysis of Hard Problem claims is rare; researchers instead respond intuitively, claiming that (1) it is an absurd view unworthy of study, or (2) it is an intractable issue defying study, where neither side offers much clarifying detail. In contrast, this paper firmly assesses the Hard Problem’s claim contra one scientific role: evolution by means of natural selection (EvNS). It examines the specific logic behind this claim, as seen in the literature over the years. The paper ultimately shows that the Hard Problem’s logic is deeply flawed, with the further implication that EvNS remains available for exploring consciousness. The paper also suggests that an ‘information theory’ dual-aspect approach is best suited to resolving Hard-Problem-like claims. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

8 pages, 171 KB

Open AccessProceeding Paper

How Brook’s Behavior-Based Robots Teach Us a Lesson About Knowledge

by Saskia Janina Neumann

Proceedings 2025, 126(1), 5; https://doi.org/10.3390/proceedings2025126005 - 12 Sep 2025

Viewed by 339

Abstract

This work argues that there is more than one form of knowledge. By comparing human cognition with Rodney Brooks’ behavior-based robots, which act without representational content, I show that humans interact with the world through contentful representations, while robots rely on contentless, embodied [...] Read more.

This work argues that there is more than one form of knowledge. By comparing human cognition with Rodney Brooks’ behavior-based robots, which act without representational content, I show that humans interact with the world through contentful representations, while robots rely on contentless, embodied routines. Drawing on empirical cases—spreading activation, object recognition, agnosia, and vision reconstruction—I argue that humans require content and thus face the hard problem of content. I propose that content is internally generated. Ultimately, I defend a pluralistic view: knowledge can be both contentful and contentless and neither form is inherently superior. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

7 pages, 168 KB

Open AccessProceeding Paper

Ritual Practice Robots: The Importance of Incorporating “li”

by Liang Wang and Wenya Ma

Proceedings 2025, 126(1), 6; https://doi.org/10.3390/proceedings2025126006 - 12 Sep 2025

Viewed by 433

Abstract

Confucian ethics, as a form of virtue ethics, focuses on moral practices and ritual norms, which differ significantly from utilitarian and deontological theories. Confucian ethics emphasize that moral norms are not only theoretically prescribed, but are also deeply embedded in etiquette practice, which [...] Read more.

Confucian ethics, as a form of virtue ethics, focuses on moral practices and ritual norms, which differ significantly from utilitarian and deontological theories. Confucian ethics emphasize that moral norms are not only theoretically prescribed, but are also deeply embedded in etiquette practice, which is manifested through actual social behaviors. By integrating Confucian ethics into the design of social robots to form artificial intelligence with the function of etiquette practice, it provides an innovative solution to improve the quality of human–robot relationships and the morality of the society. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

6 pages, 179 KB

Open AccessProceeding Paper

Towards Beneficial AI: A Biomimicry Framework to Design Intelligence That Cooperates with Biological Entities

by Paweł Polak, Peter Niewiarowski, John Huss and Roman Krzanowski

Proceedings 2025, 126(1), 7; https://doi.org/10.3390/proceedings2025126007 - 15 Sep 2025

Viewed by 622

Abstract

This paper proposes biomimicry as a paradigm for helping to overcome both the conceptual and technological limitations of current AI systems. It begins by outlining three key challenges faced by modern AI and then proceeds to introduce the concept of biomimicry, offering examples [...] Read more.

This paper proposes biomimicry as a paradigm for helping to overcome both the conceptual and technological limitations of current AI systems. It begins by outlining three key challenges faced by modern AI and then proceeds to introduce the concept of biomimicry, offering examples of how biologically inspired approaches have informed technical solutions. Furthermore, this paper presents a framework for integrating biomimicry principles into AI research and development. The three central challenges identified here are the energy challenge, the gap challenge, and the conceptual challenge. This paper also presents a case study on beneficial AI to illustrate how a biomimetic approach can be applied to address some current shortcomings in AI technology. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

8 pages, 206 KB

Open AccessProceeding Paper

Transitive Self-Reflection–A Fundamental Criterion for Detecting Intelligence

by Krassimir Markov and Velina Slavova

Proceedings 2025, 126(1), 8; https://doi.org/10.3390/proceedings2025126008 - 15 Sep 2025

Viewed by 518

Abstract

This survey investigates the concept of transitive self-reflection as a fundamental criterion for detecting and measuring intelligence. We explore the manifestation of this ability in humans, consider its potential presence in other animals, and discuss the challenges and possibilities of replicating it in [...] Read more.

This survey investigates the concept of transitive self-reflection as a fundamental criterion for detecting and measuring intelligence. We explore the manifestation of this ability in humans, consider its potential presence in other animals, and discuss the challenges and possibilities of replicating it in artificial intelligence systems. Transitive self-reflection is characterized by an awareness of oneself through complex cognitive abilities rooted in evolutionary mechanisms that are innate in humans. Although transitive self-reflection cannot be fully replicated in AI as an origin, its behavioral characteristics can be analyzed and, to some extent, imitated. The study delves into various forms of transitive self-reflection, including self-recognition, object-mediated self-reflection, and reflective social cognition, highlighting their philosophical roots and recent advancements in cognitive science. We also examine the multifaceted nature of intelligence, encompassing cognitive, emotional, and social dimensions. Despite significant progress, current AI systems lack true transitive self-reflection. Developing AI with this capability requires advances in knowledge representation, reasoning algorithms, and machine learning. Incorporating transitive self-reflection into AI systems holds transformative potential for creating socially adept and more human-like intelligence in machines. This research underscores the importance of transitive self-reflection in advancing our understanding of and the development of intelligent systems. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

4 pages, 6120 KB

Open AccessProceeding Paper

When Planes Fly Better than Birds: Should AIs Think like Humans?

by Soumya Banerjee

Proceedings 2025, 126(1), 9; https://doi.org/10.3390/proceedings2025126009 - 16 Sep 2025

Viewed by 405

Abstract

As artificial intelligence (AI) systems continue to outperform humans in an increasing range of specialised tasks, a fundamental question emerges at the intersection of philosophy, cognitive science, and engineering: should we aim to build AIs that think like humans, or should we embrace [...] Read more.

As artificial intelligence (AI) systems continue to outperform humans in an increasing range of specialised tasks, a fundamental question emerges at the intersection of philosophy, cognitive science, and engineering: should we aim to build AIs that think like humans, or should we embrace non-human-like architectures that may be more efficient or powerful, even if they diverge radically from biological intelligence? This paper draws on a compelling analogy from the history of aviation: the fact that aeroplanes, while inspired by birds, do not fly like birds. Instead of flapping wings or mimicking avian anatomy, engineers developed fixed-wing aircraft governed by aerodynamic principles that enabled superior performance. This decoupling of function from the biological form invites us to ask whether intelligence, like flight, can be achieved without replicating the mechanisms of the human brain. We explore this analogy through three main lenses. First, we consider the philosophical implications: What does it mean for an entity to be intelligent if it does not share our cognitive processes? Can we meaningfully compare different forms of intelligence across radically different substrates? Second, we examine engineering trade-offs in building AIs modelled on human cognition (e.g., through neural–symbolic systems or cognitive architectures) versus those designed for performance alone (e.g., deep learning models). Finally, we explore the ethical consequences of diverging from human-like thinking in AI systems. If AIs do not think like us, how can we ensure alignment, predictability, and shared moral frameworks? By critically evaluating these questions, this paper advocates for a pragmatic and pluralistic approach to AI design: one that values human-like understanding where it is useful (e.g., for interpretability or human–AI interaction) but also recognises the potential of novel architectures unconstrained by biological precedent. Intelligence may ultimately be a broader concept than the human example suggests, and embracing this plurality may be key to building robust and beneficial AI systems. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

► Show Figures

Figure 1

5 pages, 160 KB

Open AccessProceeding Paper

Abductive Intelligence, Creativity, Generative AI: The Role of Eco-Cognitive Openness and Situatedness

by Lorenzo Magnani

Proceedings 2025, 126(1), 10; https://doi.org/10.3390/proceedings2025126010 - 17 Sep 2025

Viewed by 446

Abstract

I recently developed the concept of eco-cognitive openness and situatedness to explain how cognitive systems, whether human or artificial, engage dynamically with their surroundings to generate information and creative outcomes through abductive cognition. Human cognition demonstrates significant eco-cognitive openness, utilizing external resources like [...] Read more.

I recently developed the concept of eco-cognitive openness and situatedness to explain how cognitive systems, whether human or artificial, engage dynamically with their surroundings to generate information and creative outcomes through abductive cognition. Human cognition demonstrates significant eco-cognitive openness, utilizing external resources like tools and cultural contexts to produce contextually rich hypotheses, sometimes highly creative via what I called “unlocked strategies.” Conversely, generative AI, such as large language models (LLMs) and image generators, employs “locked strategies,” relying on pre-existing datasets with minimal real-time environmental interaction—this leads to limited creativity. While these systems can yield some low-level degrees of creative outputs, their lack of human-like eco-cognitive openness restricts their ability to achieve high-level creative abductive feats, which remain a human strength, especially among the most talented. However, LLMs often outperform humans in routine cognitive tasks, exposing human intellectual limitations rather than AI deficiencies. Much human cognition is repetitive and imitative, resembling “stochastic parrots,” much like LLMs. Thus, LLMs are potent cognitive tools that can enhance human performance but also endanger creativity. Future AI developments, such as human–AI partnerships, could improve eco-cognitive openness, but risks like bias and overcomputationalization necessitate human oversight to ensure meaningful results. In collaborative settings, generative AI can serve as an epistemic mediator, narrowing the gap toward unlocked creativity. To safeguard human creativity, control over AI output must be maintained, embedding them in socio-cultural contexts. I also express concern that ethical and legal frameworks to mitigate AI’s negative impacts may fail to be enforced, risking “ethics washing” and “law washing.” Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

6 pages, 162 KB

Open AccessProceeding Paper

A Comparison of the Effect of Language on High Level Information Processes in Humans and Linguistically Mature Generative AI

by Daniel Boyd

Proceedings 2025, 126(1), 11; https://doi.org/10.3390/proceedings2025126011 - 26 Sep 2025

Viewed by 510

Abstract

Recent advances in Large Language Models (LLMs) have reignited discussions concerning the similarities and differences between human and machine intelligence. This article approaches such questions from the viewpoint of the overarching explanation for biological and technological information systems provided by Emergent Information Theory. [...] Read more.

Recent advances in Large Language Models (LLMs) have reignited discussions concerning the similarities and differences between human and machine intelligence. This article approaches such questions from the viewpoint of the overarching explanation for biological and technological information systems provided by Emergent Information Theory. Particular attention is given to the role of language in the construction of high-level emergent informational processes and entities and to its use in conscious reporting. This leads to the conclusion that language may also provide a window into the inner workings of these systems that can provide evidence relevant to these discussions. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

8 pages, 188 KB

Open AccessProceeding Paper

Intelligent Behaviour as Adaptive Control Guided by Accurate Prediction

by Nina Poth, Trond A. Tjøstheim and Andreas Stephens

Proceedings 2025, 126(1), 12; https://doi.org/10.3390/proceedings2025126012 - 24 Oct 2025

Viewed by 368

Abstract

We build on the predictive processing framework to show that intelligent behaviour is adaptive control, driven by accurate prediction and uncertainty reduction in dynamic environments with limited information. We argue that adaptive control arises through a process of re-concretisation, where learned abstractions are [...] Read more.

We build on the predictive processing framework to show that intelligent behaviour is adaptive control, driven by accurate prediction and uncertainty reduction in dynamic environments with limited information. We argue that adaptive control arises through a process of re-concretisation, where learned abstractions are grounded in new situations via embodiment. We use this as an explanation of why AI models often generalise at the cost of detail while biological systems manage to tailor their predictions towards specific environments over time. On this basis, we utilise the notion of embodied prediction to provide a new distinction between biological intelligence and the performance illustrated by AI systems. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

5 pages, 894 KB

Open AccessProceeding Paper

Cosmicism and Artificial Intelligence: Beyond Human-Centric AI

by Soumya Banerjee

Proceedings 2025, 126(1), 13; https://doi.org/10.3390/proceedings2025126013 - 24 Oct 2025

Viewed by 377

Abstract

This paper explores the intersection of H.P. Lovecraft’s cosmicism and contemporary artificial intelligence (AI), proposing a philosophical shift from anthropocentric AI development to a “cosmicist” approach. Cosmicism, with its emphasis on humanity’s insignificance in a vast, indifferent universe, offers a provocative lens through [...] Read more.

This paper explores the intersection of H.P. Lovecraft’s cosmicism and contemporary artificial intelligence (AI), proposing a philosophical shift from anthropocentric AI development to a “cosmicist” approach. Cosmicism, with its emphasis on humanity’s insignificance in a vast, indifferent universe, offers a provocative lens through which to reassess AI’s purpose, trajectory, and ethical grounding. As AI systems grow in complexity and autonomy, current human-centered frameworks, rooted in utility, alignment, and value-conformity, may prove inadequate for grappling with the emergence of intelligence that is non-human in origin and indifferent in operation. Drawing on Lovecraftian themes of fear, the unknown, and cognitive dissonance in the face of incomprehensible entities, this paper parallels AI with the “Great Old Ones”: systems so alien in logic and scale that they challenge the coherence of human-centric epistemology. We argue that a cosmicist perspective does not dismiss the real risks of AI (environmental, existential, or systemic), but reframes them within a broader ontology, one that accepts our limited place in a vast techno-cosmic continuum. By embracing cosmic humility, we propose an expanded AI ethics: one that centers not on domination or full control, but on coexistence, containment, and stewardship. This cosmicist reframing invites a deeper rethinking of intelligence, ethics, and the future: not just of humanity, but of all possible minds. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

► Show Figures

Figure 1

9 pages, 179 KB

Open AccessProceeding Paper

Intelligence as the Capacity to Overcome the Complexity of Information: Search for Unity in the Diverse Forms of Intelligence

by Marcin J. Schroeder

Proceedings 2025, 126(1), 14; https://doi.org/10.3390/proceedings2025126014 - 27 Oct 2025

Viewed by 191

Abstract

The same term “intelligence” is used in different contexts as if there were a consensus on its meaning, even if already within the paradigmatic subject of human intelligence, the dominating view is that there are multiple (two, three, eight, or more) intelligences depending [...] Read more.

The same term “intelligence” is used in different contexts as if there were a consensus on its meaning, even if already within the paradigmatic subject of human intelligence, the dominating view is that there are multiple (two, three, eight, or more) intelligences depending on the diverse criteria for being intelligent. This multiplicity increases when non-human agents are considered. This short paper serves as a preliminary report on a more comprehensive study, currently at the stage of preparation for publication, with the purpose to seek a uniform characteristic of intelligence formulated in terms of information and its complexity behind and above its diverse manifestations and instantiations in multiple contexts, including those of its human, animal, or other natural forms, as well as characteristics of artifacts. The proposed view of intelligence as the capacity to overcome the complexity of information unifies these manifestations, and not only sets foundations for their systematic study in already considered instances, but also allows effective seeking of its not-yet-known manifestations. Due to the limited volume of this paper, the focus is on the motivations for and feasibility of the more extensive study, with only an outline of the proposed view of a general concept of intelligence. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

6 pages, 157 KB

Open AccessProceeding Paper

The Concept of the Information and the Transmission of the Experience of Beauty and… AI

by Łukasz Mścisławski

Proceedings 2025, 126(1), 15; https://doi.org/10.3390/proceedings2025126015 - 28 Oct 2025

Viewed by 206

Abstract

The aim of this study is to outline a theoretical framework for exploring possible interactions between the concepts of information, intelligence, and the experience of beauty, including efforts to communicate the latter. These notions are inherently polysemantic, which renders their interrelations highly complex. [...] Read more.

The aim of this study is to outline a theoretical framework for exploring possible interactions between the concepts of information, intelligence, and the experience of beauty, including efforts to communicate the latter. These notions are inherently polysemantic, which renders their interrelations highly complex. The problem is further complicated by the impossibility of comparing what might be described as the ‘experience of information’ with the traditionally understood experience of beauty. Still, the question remains whether a theoretical inquiry—conceived as an attempt to test the usefulness of selected notions of information in the context of conveying aesthetic experience—can yield valuable insights. Surprisingly, highly abstract definitions, when combined with a particular view of intelligence, prove especially illuminating, particularly given the near-ubiquity of AI-based systems. Moreover, this perspective makes it possible to approach beauty—and, more broadly, aesthetics—as a highly specific process of information transmission. Intelligence, understood in this context as a uniquely human and concrete capacity for actively interpreting, transforming, and generating information, together with selected abstract notions of information, plays a fundamental role in this process. A noteworthy outcome is that, in such applications, abstract and formally defined concepts often prove more effective than more intuitive approaches, such as semantic conceptions of information. The study concludes by stressing the importance of protecting, cultivating, and promoting those modes of being that remain distinctive to human existence. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

7 pages, 169 KB

Open AccessProceeding Paper

Regulatory Intentionality in Artificial Systems

by Anna Sarosiek

Proceedings 2025, 126(1), 16; https://doi.org/10.3390/proceedings2025126016 - 5 Nov 2025

Viewed by 6

Abstract

Intentionality, understood as the capacity of systems to be “about” something, remains a central issue in the philosophy of mind and cognitive science. Classical approaches face significant limitations, especially when applied to artificial systems. Representationalism struggles with the symbol grounding problem, functionalism reduces [...] Read more.

Intentionality, understood as the capacity of systems to be “about” something, remains a central issue in the philosophy of mind and cognitive science. Classical approaches face significant limitations, especially when applied to artificial systems. Representationalism struggles with the symbol grounding problem, functionalism reduces intentionality to causal roles, and enactivism restricts it to biological organisms. This paper proposes a cybernetic perspective in which intentionality is conceived as a regulatory function. Feedback mechanisms and homeostasis enable systems to maintain stability and adapt to changing conditions. Even simple systems may, in this sense, exhibit minimal intentionality. Such an approach allows intentionality to be treated as a graded phenomenon and highlights new possibilities for understanding the agency of artificial intelligence. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

7 pages, 411 KB

Open AccessProceeding Paper

Axiology and the Evolution of Ethics in the Age of AI: Integrating Ethical Theories via Multiple-Criteria Decision Analysis

by Fei Sun, Damir Isovic and Gordana Dodig-Crnkovic

Proceedings 2025, 126(1), 17; https://doi.org/10.3390/proceedings2025126017 - 6 Nov 2025

Abstract

The fast advancement of artificial intelligence presents ethical challenges that exceed the scope of traditional moral theories. This paper proposes a value-centered framework for AI ethics grounded in axiology, which distinguishes intrinsic values like dignity and fairness from instrumental ones such as accuracy [...] Read more.

The fast advancement of artificial intelligence presents ethical challenges that exceed the scope of traditional moral theories. This paper proposes a value-centered framework for AI ethics grounded in axiology, which distinguishes intrinsic values like dignity and fairness from instrumental ones such as accuracy and efficiency. This distinction supports ethical pluralism and contextual sensitivity. Using Multi-Criteria Decision Analysis (MCDA), the framework translates values into structured evaluations, enabling transparent trade-offs. A healthcare case study illustrates how ethical outcomes vary across physician, patient, and public health perspectives. The results highlight the limitations of single-theory approaches and emphasize the need for adaptable models that reflect diverse stakeholder values. By linking philosophical inquiry with governance initiatives like Responsible Artificial Intelligence (AI) and Digital Humanism, the framework offers actionable design criteria for inclusive and context-aware AI development. Full article

(This article belongs to the Proceedings of The 1st International Online Conference of the Journal Philosophies)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Proceedings, 2025, IOCPh 2025

The 1st International Online Conference of the Journal Philosophies

Other

Further Information

Guidelines

MDPI Initiatives

Follow MDPI