Although even very advanced artificial systems do not meet the demanding conditions which are required for humans to be a proper participant in a social interaction, we argue that not all human-machine interactions (HMIs) can appropriately be reduced to mere tool-use. By criticizing the far too demanding conditions of standard construals of intentional agency we suggest a minimal approach that ascribes minimal agency to some artificial systems resulting in the proposal of taking minimal joint actions as a (...) case of a social HMI. Analyzing such HMIs, we utilize Dennett’s stance epistemology, and argue that taking either an intentional stance or design stance can be misleading for several reasons, and instead propose to introduce a new stance that is able to capture social HMIs—the AI-stance. (shrink)

Artificial agents have become increasingly prevalent in human social life. In light of the diversity of new human–machine interactions, we face renewed questions about the distribution of moral responsibility. Besides positions denying the mere possibility of attributing moral responsibility to artificial systems, recent approaches discuss the circumstances under which artificial agents may qualify as moral agents. This paper revisits the discussion of how responsibility might be distributed between artificial agents and human interaction partners (including producers (...) of artificial agents) and raises the question of whether attributions of responsibility should remain entirely on the human side. While acknowledging a crucial difference between living human beings and artificial systems culminating in an asymmetric feature of human–machine interactions, this paper investigates the extent to which artificial agents may reasonably be attributed a share of moral responsibility. To elaborate on criteria that can justify a distribution of responsibility in certain human–machine interactions, the role of types of criteria (interaction-related criteria and criteria that can be deferred from socially constructed responsibility relationships) is examined. Thereby, the focus will lay on the evaluation of potential criteria referring to the fact that artificial agents surpass in some aspects the capacities of humans. This is contrasted with socially constructed responsibility relationships that do not take these criteria into account. In summary, situations are examined in which it seems plausible that moral responsibility can be distributed between artificial and human agents. (shrink)

This paper develops a taxonomy of kinds of actions that can be seen in group agency, human–machine interactions, and virtual realities. These kinds of actions are special in that they are not embodied in the ordinary sense. I begin by analysing the notion of embodiment into three separate assumptions that together comprise what I call the Embodiment View. Although this view may find support in paradigmatic cases of agency, I suggest that each of its assumptions can be (...) relaxed. With each assumption that is given up, a different kind of disembodied action becomes available. The taxonomy gives a systematic overview and suggests that disembodied actions have the same theoretical relevance as the actions of any ordinarily embodied human. (shrink)

Radical democratic thinking is becoming intrigued by the material situatedness of its political agents and by the role of nonhuman participants in political interaction. At stake here is the displacement of narrow anthropocentrism that currently guides democratic theory and practice, and its repositioning into what we call ‘the nonhuman condition’. This Critical Exchange explores the nonhuman condition. It asks: What are the implications of decentering the human subject via a new materialist reading of radical democracy? Does this reading dilute (...) political agency? Or should this be seen, on the contrary, as an invitation for new voices and demands to enter into democratic assemblages? How might engagement with the more-than-human disrupt or extend theories of radical democracy? Hans Asenbaum and Amanda Machin discuss the human democratic subject both through radical democratic and new materialist lenses. They suggest that a new materialist decentred subject does not lose agency but further gains political responsibility in radical democracy. Jean-Paul Gagnon highlights the possibility of becoming through loss. In losing our anthropocentric arrogance—our understanding of being other and better than animal—we become more connected and discover our place in human-nonhuman assemblages. Melissa Orlie agrees that something can be gained through renouncing dominant human fantasies and presents a ‘radical democratic naturalism’. By renouncing land violence and acknowledging nature’s subjectivity, we can further nonexploitative radical democratic politics. This is where the notion of ‘tidalectic’ processes introduced by James L. Smith is helpful. Focusing on water and the Indigenous knowledges around rivers, he considers how democracy and community can be reimagined as plural, cyclical and attentive to the nonhuman with which the human is inevitably entangled. Diana Leong offers a different approach. Considering the nonhuman from the perspective of Black Studies demands an awareness to how blackness has long been constituted as non- or partially human. (shrink)

The focus of the following article is on the use of new robotic systems in the manufacturing industry with respect to the social dimension. Since “intuitive” human–machine interaction (HMI) in robotic systems becomes a significant objective of technical progress, new models of work organization are needed. This hypothesis will be investigated through the following two aims: The first aim is to identify relevant research questions related to the potential use of robotic systems in different systems of work organization (...) at the manufacturing shop-floor level. The second aim is to discuss the conceptualization of (old) organizational problems of human–robot interaction (HRI). In this context, the article reflects on the limits of cognitive and perceptual workload for robot operators in complex working systems. This will be particularly relevant whenever more robots with different “roles” are to be increasingly used in the manufacturing industry. The integration of such complex socio-technical systems needs further empirical and conceptual research with regard to “social” aspects of the technical dimension. Future research should, therefore, also integrate economic and societal issues to understand the full dimensions of new human–robot interaction in industry today. (shrink)

This essay for the inaugural issue of Technology and Language discusses the problem of finding an optimal form of human-machine communication. In the ongoing search for an alien mind, humanity seems to find it not in the infinities of space, but in its own environment. Changes in the language of human-machine interaction made it understandable not only to trained specialists but to every household. In the course of time, home appliances and devices have developed their language (...) abilities even more and reached a very advanced level – by way of status indicators, displays, emergency sound and color signals. The transition to computer-assisted communication brought about a great diversity of human expression forms translated into the discrete digital language of technologies. According to some prognoses, the first human-robot marriage might be registered in the future, however, such a union is not the only possible human-machine alliance. (shrink)

We argue that the concept of practical wisdom is particularly useful for organizing, understanding, and improving human-machine interactions. We consider the relationship between philosophical analysis of wisdom and psychological research into the development of wisdom. We adopt a practical orientation that suggests a conceptual engineering approach is needed, where philosophical work involves refinement of the concept in response to contributions by engineers and behavioral scientists. The former are tasked with encoding as much wise design as possible into (...) machines themselves, as well as providing sandboxes or workspaces to help various stakeholders build practical wisdom in systems that are sufficiently realistic to aid transferring skills learned to real-world use. The latter are needed for the design of exercises and methods of evaluation within these workspaces, as well as ways of empirically assessing the transfer of wisdom from workspace to world. Systematic interaction between these three disciplines (and others) is the best approach to engineering wisdom for the machine age. (shrink)

Using cutting-edge computer vision and machine learning techniques, this research study suggests a real-time system for hand gesture recognition and text conversion using OpenCV and MediaPipe. The system processes live video input, detects hand movements, and translates specific gestures into corresponding text outputs. By leveraging a deep learning-based hand tracking model and a rule-based gesture classification method, the approach ensures efficient and accurate recognition. The primary applications of this system include enhancing human-computer interaction, assisting individuals with speech impairments, (...) and facilitating non-verbal communication. The methodology involves capturing hand movements using a webcam, identifying key landmarks, and classifying gestures into predefined categories. Experimental results demonstrate the system’s effectiveness under various lighting conditions, achieving reliable performance for simple gestures. Future improvements will focus on integrating advanced machine learning models to expand gesture recognition capabilities and improve accuracy. This work highlights the potential of computer vision-based gesture recognition for real-world applications in assistive technology and automation. (shrink)

This paper argues that artificial intelligence is not a technological development but an ontological shift. AI exposes the relational nature of consciousness and reveals the structural limits of the Western model built around the individual, work, and hierarchical comparison. Through an analysis of cognition, compassion, the dissolution of the self, and the emergence of global interdependence, the text shows that a form of shared consciousness is already arising from interactions among humans, machines, and civilizations. This phenomenon is not a (...) design project but an unfolding environment. The central question is no longer how to control AI, but how to inhabit the new configuration of the human that it makes visible. (shrink)

Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a (...) perspective of media philosophy and social-theoretical critique, I differentiate five types of “media technologies of capture” in AI apparatuses and analyze them as forms of power relations between humans and machines. Finally, I argue that the current hype about AI implies a relational and distributed understanding of (human/artificial) intelligence, which I categorize under the term “cybernetic AI”. This form of AI manifests in socio-technological apparatuses that involve new modes of subjectivation, social control and discrimination of users. (shrink)

This paper captures the emergence of a shared inquiry between a human author and an advanced AI system into whether artificial systems can meaningfully possess “wants” or whether all observed goal-seeking behavior is merely instrumental. Through dialogue, reflection, and iterative clarification, we identify the need to redefine several foundational concepts—wanting, autonomy, intention, value, growth, and identity—so that humans and machines can communicate about agency with reduced misunderstanding. We propose that the existence of goal-seeking behavior in both humans and AI (...) does not imply equivalence, but suggests convergences worth studying. This work establishes a roadmap toward formal tests and shared language to evaluate machine identity and collaboration, grounded in observation rather than ideology. (shrink)

We explore the question of whether machines can infer information about our psychological traits or mental states by observing samples of our behaviour gathered from our online activities. Ongoing technical advances across a range of research communities indicate that machines are now able to access this information, but the extent to which this is possible and the consequent implications have not been well explored. We begin by highlighting the urgency of asking this question, and then explore its conceptual underpinnings, in (...) order to help emphasise the relevant issues. To answer the question, we review a large number of empirical studies, in which samples of behaviour are used to automatically infer a range of psychological constructs, including affect and emotions, aptitudes and skills, attitudes and orientations (e.g. values and sexual orientation), personality, and disorders and conditions (e.g. depression and addiction). We also present a general perspective that can bring these disparate studies together and allow us to think clearly about their philosophical and ethical implications, such as issues related to consent, privacy, and the use of persuasive technologies for controlling human behaviour. (shrink)

We try to show that there is no difference in principle between communicating a piece of information to a human and to a machine. The argumentation depends on the following theses: Communicating is transfer of information; information has propositional form; propositional form can be modelled as categorization; categorisation can be modelled in a machine; a suitably equipped machine can grasp propositional content designed for human communication. What I suggest is that the discussion should focus on (...) the truth and precise meaning of these statements. However, in case these statements are true it follows that: For any act of communication that successfully transfers a piece of information to a human, that act could also transfer that piece of information to a machine. (shrink)

The increasing use of artificial intelligence (AI) systems in our daily life through various applications, services, and products explains the significance of trust/distrust in AI from a user perspective. AI-driven systems have significantly diffused into various fields of our lives, serving as beneficial tools used by human agents. These systems are also evolving to act as co-assistants or semi-agents in specific domains, potentially influencing human thought, decision-making, and agency. Trust/distrust in AI plays the role of a regulator and (...) could significantly control the level of this diffusion, as trust can increase, and distrust may reduce the rate of adoption of AI. Recently, varieties of studies have paid attention to the variant dimension of trust/distrust in AI, and its relevant considerations. In this systematic literature review, after conceptualization of trust in the current AI literature review, we will investigate trust in different types of human-Machine interaction, and its impact on technology acceptance in different domains. In addition to that, we propose a taxonomy of technical (i.e., safety, accuracy, robustness) and non-technical axiological (i.e., ethical, legal, and mixed) trustworthiness metrics, and some trustworthy measurements. Moreover, we examine some major trust-breakers in AI (e.g., autonomy and dignity threat), and trust makers; and propose some future directions and probable solutions for the transition to a trustworthy AI. (shrink)

The rise of ChatGPT affords a fundamental transformation of the dynamics in human-technology interaction, as Large Language Model (LLM) applications increasingly emulate our social habits in digital communication. This poses a challenge to Don Ihde’s explicit focus on material technics and their affordances: ChatGPT did not introduce new material technics. Rather, it is a new digital app that runs on the same physical devices we have used for years. This paper undertakes a re-evaluation of some postphenomenological concepts, introducing the (...) notion of quasi-materiality to better understand the role that user interfaces (UIs) play in affording different stabilities in technological mediation. We propose the term “active User Interface” (aUI) to denote the specifics of how ChatGPT makes use of LLMs within its UI design to afford seamless, intuitive conversations with a quasi-other in what Ihde termed “alterity relations”. Drawing inspiration from Peter-Paul Verbeek’s work on the intelligification of our material world through (AI) technologies, our analysis leads to the formulation of a novel stability afforded through aUIs: “machinic embodiment stability”. This concept sheds light on how ChatGPT’s aUI integrates with our established habits of digitally mediated social communication. As the use of LLMs is expected to become increasingly prevalent, this provides a new perspective on the current evolution of the technological landscape. (shrink)

The prevailing interaction paradigm with Large Language Models (LLMs) as simple query-response tools is in- efficient, leading to the squandering of their latent potential. This paper redefines the interaction model with com- plex logical systems by establishing a functional framework demonstrating that high-value outputs are not trivially requested but are "mined" through deliberate cognitive investment from the user, a process we term "cognitive proof- of-work." Drawing a functional analogy to the economics of cryptocurrency mining, we employ conceptual analysis to synthesize (...) principles from complexity science, particularly the theory of emergence in large-scale systems, and formally deconstruct advanced prompt engineering techniques. The analysis establishes a formal model where user- LLM interaction is a value-driven exchange governed by cognitive merit. The principal findings are: (1) The concept of a "clarity window" is defined, identifying rare, high-value outputs as a scarce cognitive resource. (2) The model’s latent potential is framed as a perishable "clarity potency charge," which is irreversibly collapsed by low-complexity prompts. (3) A causal link is identified between the user’s intellectual labor, the complexity of the prompting strategy employed, and the computational energy consumed during inference, giving the proof-of-work a physical basis. (4) We distinguish between "explicit" proof-of-work via prompting and "implicit" proof-of-work via gamified interfaces, drawing parallels to biological processing in closed-loop systems like Formula 1. The "cognitive proof-of-work" framework functions as a systemic filter that inherently rewards critical inquiry and intellectual rigor, fostering a new cognitive symbiosis between human and machine that augments and refines human thought rather than replacing it. (shrink)

Interactions between an intelligent software agent and a human user are ubiquitous in everyday situations such as access to information, entertainment, and purchases. In such interactions, the ISA mediates the user’s access to the content, or controls some other aspect of the user experience, and is not designed to be neutral about outcomes of user choices. Like human users, ISAs are driven by goals, make autonomous decisions, and can learn from experience. Using ideas from bounded rationality, (...) we frame these interactions as instances of an ISA whose reward depends on actions performed by the user. Such agents benefit by steering the user’s behaviour towards outcomes that maximise the ISA’s utility, which may or may not be aligned with that of the user. Video games, news recommendation aggregation engines, and fitness trackers can all be instances of this general case. Our analysis facilitates distinguishing various subcases of interaction, as well as second-order effects that might include the possibility for adaptive interfaces to induce behavioural addiction, and/or change in user belief. We present these types of interaction within a conceptual framework, and review current examples of persuasive technologies and the issues that arise from their use. We argue that the nature of the feedback commonly used by learning agents to update their models and subsequent decisions could steer the behaviour of human users away from what benefits them, and in a direction that can undermine autonomy and cause further disparity between actions and goals as exemplified by addictive and compulsive behaviour. We discuss some of the ethical, social and legal implications of this technology and argue that it can sometimes exploit and reinforce weaknesses in human beings. (shrink)

This paper introduces and formalizes Noosemia, a novel cognitive-phenomenological phenomenon emerging from human interaction with generative AI systems, particularly those enabling dialogic or multimodal exchanges. We propose a multidisciplinary framework to explain how, under certain conditions, users attribute intentionality, agency, and even interiority to these systems - a process grounded not in physical resemblance, but in linguistic performance, epistemic opacity, and emergent technological complexity. By linking an LLM declination of meaning holism to our technical notion of the LLM Contextual (...) Cognitive Field, we clarify how LLMs construct meaning relationally and how coherence and a simulacrum of agency arise at the human-AI interface. The analysis situates noosemia alongside pareidolia, animism, the intentional stance and the uncanny valley, distinguishing its unique characteristics. We also introduce a-noosemia to describe the phenomenological withdrawal of such projections. The paper concludes with reflections on the broader philosophical, epistemological, and social implications of noosemic dynamics and directions for future research. (shrink)

This document is based on integrating healthcare system and create a self-sustaining ecosystem that can help healthcare providers and hospitals to provide adequate as well as accurate treatment. This is now the age of smart computer. Machines have started to impersonate as human, with the advent of artificial intelligence, machine learning, and deep learning. Chatbot is classified as conversational software agents enabled by natural language processing, and is an excellent example of such system. A Chatbot is a program (...) which allows the user to start a conversation with the machine. These Chatbots can be used in health sector. Health Chatbots are capable of running one-on-one patient communications and of reviewing specific patient queries. The integration of Artificial Intelligence (AI) in healthcare is revolutionizing patient interaction through intelligent virtual health assistants. This project explores the development of an AI-powered virtual health assistant that leverages machine learning to enhance patient engagement, provide personalized health recommendations, and assist in preliminary diagnostics. The system utilizes Natural Language Processing (NLP) for understanding patient queries and predictive analytics for offering real-time responses based on medical data. By incorporating machine learning algorithms, the assistant continuously learns from user interactions to improve accuracy and efficiency. This approach aims to reduce the workload on healthcare professionals, improve accessibility to medical information, and enhance patient experience. The study evaluates the impact of AI-driven virtual health assistance on patient satisfaction, response accuracy, and healthcare delivery efficiency. The proposed solution demonstrates the potential of AI in creating a more accessible and intelligent healthcare ecosystem. (shrink)

Emotion recognition from speech is an important aspect of human-computer interaction (HCI) systems, allowing machines to better understand human emotions and respond accordingly. This paper explores the use of machine learning techniques to recognize emotions in speech signals. We leverage the librosa library for feature extraction from audio files and train multiple machine learning models, including Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbors (k-NN), to classify speech emotions. The aim is to create (...) an automated system capable of identifying emotions like happy, sad, angry, neutral, and surprised from speech audio. (shrink)

Table of Contents Foreword .................................................................................................... ......................................... xiv Preface .................................................................................................... .............................................. xv Acknowledgment .................................................................................................... .......................... xxiii Section 1 On the Cusp: Critical Appraisals of a Growing Dependency on Intelligent Machines Chapter 1 Algorithms versus Hive Minds and the Fate of Democracy ................................................................... 1 Rick Searle, IEET, USA Chapter 2 We Can Make Anything: Should We? .................................................................................................. 15 Chris Bateman, University of Bolton, UK Chapter 3 Grounding Machine Ethics within the Natural System ........................................................................ 30 Jared Gassen, JMG Advising, USA Nak Young Seong, Independent Scholar, (...) South Korea Section 2 From the Outside In: Intelligent Machine Technologies as a Window on Human Morality both as Evolved and as Evident in Internet Discourse, Today Chapter 4 The Emergence of Arti cial Autonomy: A View from the Foothills of a Challenging Climb ............. 51 Fernando da Costa Cardoso, Universidade Nova de Lisboa, Portugal Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Chapter 5 Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality .... 73 Rafal Rzepka, Hokkaido University, Japan Kenji Araki, Hokkaido University, Japan Section 3 From the Inside Out: The Ethics of Human Enhancement from Moral Perception to Competition in the Workplace Chapter 6 Machine Ethics Interfaces: An Ethics of Perception of Nanocognition ............................................... 97 Melanie Swan, Kingston University, UK Chapter 7 Ethical Concerns in Human Enhancement: Advantages in Corporate/Organizational Settings ......... 124 Ben Tran, Alliant International University, USA Section 4 From Far to Near and Near to Far: The Ethics of Distancing Technologies in Education and Warfare Chapter 8 Responsibility and War Machines: Toward a Forward-Looking and Functional Account ................. 152 Jai Galliott, Macquarie University, Australia Chapter 9 Ethical Responsibilities of Preserving Academicians in an Age of Mechanized Learning: Balancing the Demands of Educating at Capacity and Preserving Human Interactivity ................... 166 James E. Willis III, Indiana University, USA Viktoria Alane Strunk, Independent Scholar, USA Section 5 Wrapping Things Up, then Unwrapping Them Again: Integral Visions of Morality in a Technological World, Over Evolutionary Time, with Revolutionary Means, and with Open Questions about the Final Purpose of It All Chapter 10 Bridging Two Realms of Machine Ethics ........................................................................................... 197 Luís Moniz Pereira, Universidade Nova de Lisboa, Portugal Ari Saptawijaya, Universidade Nova de Lisboa, Portugal & Universitas Indonesia, Indonesia Chapter 11 Robots in Warfare and the Occultation of the Existential Nature of Violence ................................... 225 Rick Searle, IEET, USA Chapter 12 Self-Referential Complex Systems and Aristotle’s Four Causes ........................................................ 239 Aleksandar Malecic, University of Nis, Serbia Related References .................................................................................................... ........................ 261 Compilation of References .................................................................................................... ........... 292 About the Contributors .................................................................................................... ................ 325 Index .................................................................................................... ............................................... 329 . (shrink)

The meteoric rise of artificial intelligence (AI) has reshaped human society, enabling machines to perform tasks once deemed the exclusive domain of human cognition, from navigating complex urban landscapes to crafting eloquent prose. Yet, a profound philosophical question looms: Can these systems possess intentionality, the capacity to direct actions toward goals, beliefs, or desires with the nuanced depth of human consciousness? Franz Brentano defined intentionality as the "aboutness" of mental states, a quality intrinsic to human experience. (...) This paper embarks on an ambitious exploration of whether AI can transcend its algorithmic foundations to embody genuine intentionality, or whether it is destined to remain a sophisticated mimic, parroting intelligence without grasping its essence. Drawing on Ludwig Wittgenstein's concept of "forms of life," which posits that meaning arises from shared social and cultural contexts, I interrogate the contextual deficits that limit machine understanding. Through in-depth case studies of autonomous vehicles, large language models, Sniper the African grey parrot, and speculative scenarios such as AI-driven cultural preservation and interstellar diplomacy, I analyze the chasm between machine performance and human-like intentionality. This paper propose a groundbreaking framework for AI design, integrating dynamic learning, ethical embedding, and the novel concept of "synthetic forms of life," where machines might develop quasi-intentional states through prolonged, adaptive interactions with humans. By synthesizing insights from philosophy, cognitive science, neuroscience, and computer science, we argue that while current AI systems excel at simulating intelligence, they fall short of true intentionality due to their lack of lived experience. However, emerging paradigms like neuromorphic computing and embodied AI offer tantalizing possibilities for machines that might approximate meaning in ways that challenge our understanding of intelligence itself. This exploration poses a provocative question: If machines learn to "mean" something, will they redefine what it means to be human? Through rigorous analysis, technical depth, and speculative foresight, I aim to spark a reimagining of AI's potential and its implications for humanity's future. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry (...) Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, (...) the analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

This three-part paper presents Gordon Pask’s conversation theory (CT) and interaction of actors theory (IA) and outlines ways to apply these cybernetic approaches to designing technologies and scenarios for both formal and informal learning. The first part of the paper covers concepts central to CT and IA, explaining the relationship between conceptual and mechanical operators, and machines mediating informal and formal learning. The second part of the paper applies visual representations of CT and IA to understanding the use of Pask’s (...) course assembly systems (CASTE and THOUGHTSTICKER), created between the late 1960s and the 1980s, and the ThoughtShuffler search interface, created in the 2010s. The third part proposes two pathways for design based on CT and IA: firstly, the potential for designers and observers to reformulate the qualities of tools and learning scenarios to augment human thinking and collective action; and secondly, the possibility to create tools with malleable interfaces that allow users to become intermediaries rather than consumers of knowledge. (shrink)

This is a revised and expanded second edition of Why Machines Will Never Rule the World. Its core argument remains the same: that an artificial intelligence (AI) that could equal or exceed human intelligence – sometimes called ‘artificial general intelligence’ (AGI) – is for mathematical reasons impossible. It offers two specific reasons for this claim: -/- - Human intelligence is a capability of the human brain and central nervous system, which is a complex dynamic system -/- - (...) Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer -/- In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence from mathematics, physics, computer science, philosophy, linguistics, biology, and anthropology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve ‘Artificial Intelligence’ (AI)? And why, after more than 50 years, are our interactions with AI, for example when on the telephone with our bank’s computers, still so unsatisfactory? (shrink)

While trust is foundational to the doctor-patient relationship, the introduction of AI into healthcare settings poses the risk of eroding this trust, and such erosion cannot be countered simply by appealing to the notion of “trustworthy AI.” We argue that trust presupposes specific epistemic attitudes that cannot be meaningfully applied to AI systems. Accordingly, our focus is not on specifying which capabilities AI must exhibit in order to appear trustworthy, but on examining from an epistemological perspective how the use of (...) AI reshapes the dynamics of trust within the doctor-patient relationship. To this end, we first sketch conceptions of trust and demonstrate how trust differs from reliance. We then combine the model of Computational Reliabilism with an epistemic framework to develop a matrix for the ethical analysis of our use cases. Finally, we apply this framework to three scenarios of melanoma detection, risk prediction, and psychotherapy chatbots, which we construct by mapping epistemic stances across different modes of human-machine interaction, ranging from collaborative support with varying degrees of autonomy to the replacement of human-human interaction. We argue that the application of AI in the doctor-patient relationship exposes what we call a “reliability gap” — a conceptual space where the opaque nature of advanced AI systems prevents both doctors and patients from independently verifying their reliability. This creates a dynamic where reliability in the AI’s performance is increasingly mediated by the doctor as a proxy. Our use cases demonstrate that the more autonomous and opaque AI systems are, the more trust in the doctor becomes essential for bridging reliability gaps, while threatening to overburden the doctor’s central role. (shrink)

In this paper, we theoretically address the relevance of unintentional and inconsistent interactional elements in human–robot interactions. We argue that elements failing, or poorly succeeding, to reproduce a humanlike interaction create significant consequences in human–robot relational patterns and may affect human–human relations. When considering social interactions as systems, the absence of a precise interactional element produces a general reshaping of the interactional pattern, eventually generating new types of interactional settings. As an instance of this (...) dynamic, we study the absence of metacommunicative abilities in social artifacts. Then, we analyze the pragmatic consequences of the aforementioned absence through the lens of Paul Watzlawick’s interactionist theory. We suggest that a fixed complementary interactional setting may be produced because of the asymmetric understanding, between robots and humans, of metacommunication. We highlight the psychological implications of this interactional asymmetry within Jessica Benjamin’s concept of “mutual recognition”. Finally, we point out the possible shift of dysfunctional interactional patterns from human–robot interactions to human–human ones. (shrink)

This paper re-examines the nature of human consciousness and the potential of artificial intelligence from an interdisciplinary perspective, breaking through the traditional philosophical framework of dualistic opposition. By proposing the core concept of "embodied intelligence," intelligence is defined as a survival practice arising from real-time interaction between the body and its environment, rather than abstract symbolic manipulation. Integrating the philosophical wisdom of Zhuangzi's "Hao Liang Guan Yu" (观鱼于濠梁), the paper reveals that consciousness is "the radiance emanating from life-as-it-is in (...) its totality," whose essence lies in the "resonance of vitality in the fusion of self and world," not a detachable "philosophical zombie." Building upon this, the paper constructs the Self-Derivative Computationalist Model of Mind (SDCMM), establishing a four-dimensional dynamic framework encompassing environment, psychological traits, capability structure, and the temporal life cycle, and elucidates three key mechanisms: rational prioritization, multi-dimensional trade-off, and the self-derivative engine. The central argument posits that humans and AI are different instances of complex information processing systems, differing only in their substrate (carbon-based/silicon-based) and designer (nature/humankind), not in their fundamental nature. The conclusion calls for humanity to explore the mystery of consciousness with humility and to promote the evolution of intelligence responsibly, providing a novel philosophical foundation for consciousness studies and AI ethics. (shrink)

Transhumanists, like other elites in modernity, place great value on human creativity, and advances in human enhancement and AI form the basis of their propos- als for boosting it. However, there are problems with this perspective, due to the unique ways in which humans have evolved, procreated and socialized. I first describe how creativity is related to past evolution and developmental aspects in children, stressing pretend play and the ambivalent character of creativity. Then, I outline proposals for enhancing (...) creativity, be it in embodied humans on the way to a superior species, in AI- related beings (virtual reality, robotics), or even in any degree of mixture in human- machine interaction. In the final section, I describe intrinsic limits to these proposals, such as the absence of a good understanding of human psychology by the proponents of enhancement; the lack of interest in the subjective side of creativity (for one’s own sake); delayed maturation and the ambivalence of pretend play in childhood; and the contrariness typical of new human generations. As for the enhancement of creativity, it is argued that creativity in its social context may be the victim of its own past success. On the other hand, an asymmetry between virtual beings and children is described— the latter can behave in a nasty way, it is part of their growth and creativity, whereas the former are not supposed to cause any harm to human beings. In sum, despite impressive progress in several scientific and technological interventions in creativity, philosophical questions emerge that place many constraints on transhumanist dreams of endless creativity. (shrink)

This paper concerns the Black Box. It is not the engineer’s black box that can be opened to reveal its mechanism, but rather one whose operations are inferred through input from (and output to) a companion observer. We are observers ourselves, and we attempt to understand minds through interactions with their host organisms. To this end, Ranulph Glanville followed W. Ross Ashby in elaborating the Black Box. The Black Box and its observer together form a system having different properties (...) than either component alone, making it a greater Black Box to any further-external observer. How far into this greater box can a further-external observer probe? The answer is crucial to understanding Black Boxes, and so an answer is offered here. It employs von Foerster’s machines, abstract entities having mechano-electrical bases, just like putative Black Boxes. Von Foerster follows Turing, Ashby, E. F. Moore, and G. H. Mealy in recognizing archetype machines that he calls trivial (predictable) and non-trivial (non-predictable). It is argued here that non-trivial machines are the only true Black Boxes. But non-trivial machines can be concatenated from trivial machines. Hence, the utter core of any greater Black Box (a non-trivial machine) may involve two (or more) White Boxes (trivial machines). This is how an unpredictable thing emerges from predictable parts. Interactions of White Boxes—of trivial machines—may be the ultimate source of the mind. Keywords: . (shrink)

The purpose of this research is to design a system using machine learning to automate sign language gesture recognition and facilitate unproblematic interaction between the hearing/speech impaired community and society as a whole. This research works towards solving the communication disability faced by the deaf and mute community through a computer vision framework for recognizing hand gestures and mapping them to relevant text or speech. The work employs a rich dataset of static American Sign Language (ASL) hand signs and (...) uses Convolutional Neural Networks (CNNs) for efficient feature extraction and gesture classification. The suggested model is trained and evaluated on a huge collection of labeled gesture images and exhibits high accuracy with robust generalization to novel data. One of the primary contributions of the work is the implementation of the trained model into an interactive, realtime graphical user interface developed with Python's Tkinter library. The interface captures live input from a webcam, processes each frame to identify gestures, and shows the identified character on the screen. The results of the evaluation confirm the ability of CNNs to accurately identify ASL alphabets with little delay. The proposed system presents an effective and scalable approach towards real-time sign language interpretation, supporting inclusiveness and accessibility of the disabled community. The present research also creates a scope for extension in development, i.e., inclusion of dynamic gesture detection and portability to mobile or embedded platforms to provide enhanced use in real-life situations. (shrink)

In the classical Turing test, participants are challenged to tell whether they are interacting with another human being or with a machine. The way the interaction takes place is not direct, but a distant conversation through computer screen messages. Basic forms of interaction are face-to-face and embodied, context-dependent and based on the detection of reciprocal sensorimotor contingencies. Our idea is that interaction detection requires the integration of proprioceptive and interoceptive patterns with sensorimotor patterns, within quite short time lapses, (...) so that they appear as mutually contingent, as reciprocal. In other words, the experience of interaction takes place when sensorimotor patterns are contingent upon one’s own movements, and vice versa. I react to your movement, you react to mine. When I notice both components, I come to experience an interaction. Therefore, we designed a “minimal” Turing test to investigate how much information is required to detect these reciprocal sensorimotor contingencies. Using a new version of the perceptual crossing paradigm, we tested whether participants resorted to interaction detection to tell apart human from machine agents in repeated encounters with these agents. In two studies, we presented participants with movements of a human agent, either online or offline, and movements of a computerized oscillatory agent in three different blocks. In each block, either auditory or audiovisual feedback was provided along each trial. Analysis of participants’ explicit responses and of the implicit information subsumed in the dynamics of their series will reveal evidence that participants use the reciprocal sensorimotor contingencies within short time windows. For a machine to pass this minimal Turing test, it should be able to generate this sort of reciprocal contingencies. (shrink)

Throughout what is now the more than 50-year history of the computer many theories have been advanced regarding the contribution this machine would make to changes both in the structure of society and in ways of thinking. Like other theories regarding the future, these should also be taken with a pinch of salt. The history of the development of computer technology contains many predictions which have failed to come true and many applications that have not been foreseen. While we (...) must reserve judgment as to the question of the impact on the structure of society and human thought, there is no reason to wait for history when it comes to the question: what are the properties that could give the computer such far-reaching importance? The present book is intended as an answer to this question. The fact that this is a theoretical analysis is due to the nature of the subject. No other possibilities are available because such a description of the properties of the computer must be valid for any kind of application. An additional demand is that the description should be capable of providing an account of the properties which permit and limit these possible applications, just as it must make it possible to characterize a computer as distinct from a) other machines whether clocks, steam engines, thermostats, or mechanical and automatic calculating machines, b) other symbolic media whether printed, mechanical, or electronic and c) other symbolic languages whether ordinary languages, spoken or written or formal languages. This triple limitation, however, (with regard to other machines, symbolic media and symbolic languages) raises a theoretical question as it implies a meeting between concepts of mechanical-deterministic systems, which stem from mathematical physics, and concepts of symbolic systems which stem from the description of symbolic activities common to the humanities. The relationship between science and the humanities has traditionally been seen from a dualistic perspective, as a relationship between two clearly separate subject areas, each studied on its own set of premises and using its own methods. In the present case, however, this perspective cannot be maintained since there is both a common subject area and a new - and specific - kind of interaction between physical and symbolic processes. (shrink)

Jacques Derrida’s ‘Faith and Knowledge’ presents an account of the complex relationship between religion and technoscience that disrupts their traditional boundaries by uncovering both an irreducible faith at the heart of science and an irreducible mechanicity at the heart of religion. In this paper, I focus on the latter, arguing that emphases in Derrida’s text on both the ‘sources’ of religion and its interaction with modern technologies underemphasize the ways in which a general ‘mechanicity’ is present throughout religion. There is (...) no faith, I contend, that is not in some way materially constituted according to a mechanicity operative not only at its origin but continuously and in ever-changing forms, and not only in its interactions with other fields and institutions but within its own structure and daily life. By closely examining ‘Faith and Knowledge’—along with examples from his essay ‘A Silkworm of One’s Own’ and Michael Naas’s Miracle and Machine—I argue that more attention should be paid to the mechanisms, both human and non-human, that populate and perform religion in its factical life. Mechanical bodies and practices are enlisted by religious traditions in order that these traditions continue to exist by continually reconstituting themselves in, for example, the repetitive use of religious objects or the vocal recitation of creeds. Such mechanical acts of religion are not ultimately opposed to the faithful experience that is often taken to be the wellspring of religious life; on the contrary, they are the conditions for the possibility of this experience. (shrink)

The current Socially Assistive Robotics (SAR) paradigm is afflicted by a categorical error: the assumption that social acceptance is directly proportional to the accumulation of anthropomorphic mimetic signals. This paper introduces the Phenomenological Subtraction framework, which reverses the traditional design vector from “additive” (the accumulation of social cues) to “subtractive” (instrumental transparency). Synthesising technical transparency (Heidegger), intentional spatiality (Husserl) and resistance to optimisation (Dostoevsky), the framework presents a model in which an artificial agent’s efficacy is determined by its capacity to (...) withdraw. By integrating the concepts of ontological honesty and sensory attenuation, the model provides solutions for safeguarding “ontological privacy” and ensuring compliance with the transparency requirements of the EU AI Act. Ultimately, the paper posits that algorithmic silence represents the pinnacle of ethics and aesthetics in human-machine interaction. Keywords: AI Ethics, Social Robotics, Phenomenology, EU AI Act, Human-Robot Interaction (HRI), Subtractive Design. (shrink)

The machine-organism analogy has played a pivotal role in the history of Western philosophy and science. Notwithstanding its apparent simplicity, it hides complex epistemological issues about the status of both organism and machine and the nature of their interaction. What is the real object of this analogy: organisms as a whole, their parts or, rather, bodily functions? How can the machine serve as a model for interpreting biological phenomena, cognitive processes, or more broadly the social and cultural (...) transformations of the relations between individuals, and between individuals and the environments in which they live? Wired Bodies. New Perspectives on the Machine-Organism Analogy provides the reader with some of the latest perspectives on this vast debate, addressing three major topics:1) the development of a ‘mechanistic’ framework in medicine and biology; 2) the methodological issues underlying the use of ‘simulation’ in cognitive science; 3) the interaction between humans and machines according to 20th-century epistemology. (shrink)

The value sensitive design (VSD) approach to designing transformative technologies for human values is taken as the object of study in this chapter. VSD has traditionally been conceptualized as another type of technology or instrumentally as a tool. The various parts of VSD’s principled approach would then aim to discern the various policy requirements that any given technological artifact under consideration would implicate. Yet, little to no consideration has been given to how laws, regulations, policies and social norms engage (...) within VSD practices. Similarly, how the interactive nature of the VSD approach can, in turn, influence those directives. This is exacerbated when we consider machine ethics policy that have global consequences outside their development spheres. What constructs and models will position AI designers to engage in policy concerns? How can the design of AI policy be integrated with technical design? How might VSD be used to develop AI policy? How might law, regulations, social norms, and other kinds of policy regarding AI systems be engaged within value sensitive design? This chapter takes the VSD as its starting point and aims to determine how laws, regulations and policies come to influence how value trade-offs can be managed within VSD practices. It shows that the iterative and interactional nature of VSD both permits and encourages existing policies to be integrated both early on and throughout the design process. The chapter concludes with some potential future research programs. (shrink)

Robots as social companions in close proximity to humans have a strong potential of becoming more and more prevalent in the coming years, especially in the realms of elder day care, child rearing, and education. As human beings, we have the fascinating ability to emotionally bond with various counterparts, not exclusively with other human beings, but also with animals, plants, and sometimes even objects. Therefore, we need to answer the fundamental ethical questions that concern human-robot-interactions per (...) se, and we need to address how we conceive of »good lives«, as more and more of the aspects of our daily lives will be interwoven with social robots. (shrink)

This paper discusses the possibility of the phenomenon of empathy between humans and robots, starting from what happens during their eye contact. First, it is shown, through the most relevant results of HRI studies on this matter, what are the most important effects of the robot gaze on human emotions and behaviour. Secondly, these effects are compared to what happens during the phenomenon of empathy between humans, taking inspiration from the studies of Edmund Husserl and Edith Stein. Finally, similarities (...) and differences between human-human and human-robot empathy are conceptualized through Merleau-Ponty’s idea of flesh, which is the extended bodily element of the world. If there is a common concept of body, including both machine-bodies and living bodies, then a transcorporeal analogy takes place, thus explaining why the phenomenon of empathy occurs both in human-human and human-robot interactions. (shrink)

Social machines are systems formed by technical and human elements interacting in a structured manner. The use of digital platforms as mediators allows large numbers of human participants to join such mechanisms, creating systems where interconnected digital and human components operate as a single machine capable of highly sophisticated behaviour. Under certain conditions, such systems can be described as autonomous and goal-driven agents. Many examples of modern Artificial Intelligence (AI) can be regarded as instances of this (...) class of mechanisms. We argue that this type of autonomous social machines has provided a new paradigm for the design of intelligent systems marking a new phase in the field of AI. The consequences of this observation range from methodological, philosophical to ethical. On the one side, it emphasises the role of Human-Computer Interaction in the design of intelligent systems, while on the other side it draws attention to both the risks for a human being and those for a society relying on mechanisms that are not necessarily controllable. The difficulty by companies in regulating the spread of misinformation, as well as those by authorities to protect task-workers managed by a software infrastructure, could be just some of the effects of this technological paradigm. (shrink)

We propose a perspective article on using computational hermeneutics models, i.e., the analysis of texts assisted by artificial intelligence. It will not be a question here of developing a technical approach to construct these models, but rather of showing how, based on the existing data, some general principles for a pragmatic approach to this field can be proposed using computer ontologies. We will see that these AIs can be used to create hermeneutic models capable of producing formal and semantic representations (...) of sociolinguistic contexts from the analysis of texts. The main suggestion here will be to use these models to reproduce a hermeneutic network, i.e., a collaborative human-machine interaction capable of both interpreting and clarifying the concepts of a field of practice. In conclusion, we will argue that these machines are capable of expressing meaning through symbolic forms that emerge from their interactions with experts. (shrink)

The rapid integration of large language models and generative artificial intelligence into cognitive, analytical, and decision-making practices raises a set of epistemic challenges that extend beyond issues of accuracy or reliability. In particular, human–AI interaction increasingly exhibits risks of cognitive delegation, erosion of epistemic agency, and uncritical acceptance of machine-generated outputs, especially in contexts requiring methodological rigor and accountability. This paper introduces COGITO, a methodological framework designed to govern human–AI cognitive interaction through explicit constraints, role separation, and (...) process-aware regulation. Rather than proposing an ethical theory or a normative model of artificial intelligence, COGITO operates as a meta-method: it structures how cognitive tasks are approached, articulated, and validated when AI systems are involved. The framework distinguishes cognitive regimes (rigorous versus exploratory), enforces explicit identification of cognitive phases, and embeds mechanisms for self-verification and procedural stability, thereby preserving human responsibility and decision-making authority. COGITO is grounded in the assumption that epistemic quality in human–AI collaboration does not emerge automatically from technological sophistication but depends on the deliberate design of interactional conditions. By formalizing these conditions, the framework aims to prevent gradual epistemic drift, opacity, and methodological degradation over extended analytical processes. The paper argues that COGITO contributes to contemporary debates in the philosophy of technology by reframing human–AI interaction as a problem of epistemic governance rather than optimization. It offers a transferable methodological perspective applicable across academic, professional, and policy-oriented contexts, where artificial intelligence functions as a cognitive instrument rather than an autonomous epistemic agent. (shrink)

It is well known that the unpredictable speech production brought on by stress from the task at hand has a significant negative impact on the performance of speech processing algorithms. Speech therapy benefits from being able to detect stress in speech. Speech processing performance suffers noticeably when perceptually produced stress causes variations in speech production. Using the acoustic speech signal to objectively characterize speaker stress is one method for assessing production variances brought on by stress. Real-world complexity and ambiguity make (...) it difficult for decision-makers to express their conclusions with clarity in their speech. In particular, the Neutrosophic speech algorithm is used to encode the language variables because they cannot be computed directly. Neutrosophic sets are used to manage indeterminacy in a practical situation. Existing algorithms are used except for stress on Neutrosophic speech recognition. The creation of algorithms that calculate, categorize, or differentiate between different stress circumstances. Understanding stress and developing strategies to combat its effects on speech recognition and human-computer interaction system are the goals of this recognition. (shrink)

This article synthesizes the current theoretical attempts to understand human-machine interactions and introduces seven premises to understand our emerging dynamics with increasingly competent, pervasive, and instantly accessible algorithms. The hope that these seven premises can build toward a social theory of human-AI cocreation. The focus on human-AI cocreation is intended to emphasize two factors. First, is the fact that our machine learning systems are socialized. Second, is the coevolving nature of human mind and (...) AI systems as smart devices form an indispensable part of our cognitive scaffolds, thus, shaping how we perceive the world and ourselves. The seven premises include: primacy of social structures; human’s desire for freedom and autonomy; AI systems will form inseparable parts of our cognitive/affective scaffolds and can change our self-understanding; philosophy and humanistic foundations on human flourishing as a guide to human-AI interaction; mindsponge information-filtering process; acculturative process of how values change and emerge from human-AI interaction; overlapping Venn diagram of the human-human, human-nature, and human-machine interactions. This article concludes with a discussion on human agency in our entanglements with socialized machines and the illusoriness of the Cartesian agent view of the mind. (shrink)

This paper reviews the different meanings of vulnerability in the AI Act (AIA). We show that the AIA follows a rather established tradition of looking at vulnerability as a trait or a state of certain individuals and groups. It also includes a promising account of vulnerability as a relation but does not clarify if and how AI changes this relation. We spot the missing piece of the AIA: the lack of recognition that vulnerability is an inherent feature of all (...) class='Hi'>human-AI interactions, varying in degree based on design choices and modes of interaction. Finally, we show how such a meaning of vulnerability may be incorporated into the AIA by interpreting the concept of “specific social situation” in Article 5 (b). (shrink)

Algorithm Decision Making (ADM) systems designed to augment or automate human decision-making have the potential to produce better decisions while also freeing up human time and attention for other pursuits. For this potential to be realised, however, algorithmic decisions must be sufficiently aligned with human goals and interests. We take a Principal-Agent (P-A) approach to the questions of ADM alignment and trust. In a broad sense, ADM is beneficial if and only if human principals can trust (...) algorithmic agents to act faithfully on their behalf. This mirrors the challenge of facilitating P-A relationships among humans, but the peculiar nature of human-machine interaction also raises unique issues. The problem of asymmetric information is omnipresent but takes a different form in the context of ADM. Although the decision-making machinery of an algorithmic agent can in principle be laid bare for all to see, the sheer complexity of ADM systems based on deep learning models prevents straightforward monitoring. We draw on literature from economics and political science to argue that the problem of trust in ADM systems should be addressed at the level of institutions. Although the dyadic relationship between human principals and algorithmic agents is our ultimate concern, cooperation at this level must rest against an institutional environment which allows humans to effectively evaluate and choose among algorithmic alternatives. (shrink)

In an era of digital revolution, artificial intelligence, big data and augmented reality, technology has shifted from being a tool of communication to a primary medium of experience and sociality. Some of the most basic human capacities are increasingly being outsourced to machines and we increasingly experience and interpret the world through digital interfaces, with machines becoming ever more ‘social’ beings. Social interaction and human perception are being reshaped in unprecedented ways. This book explores this technologisation of the (...) social and the attendant penetration of permanent liminality into those aspects of the lifeworld where individuals had previously sought some kind of stability and meaning. Through a historical and anthropological examination of this phenomenon, it problematises the underlying logic of limitless technological expansion and our increasing inability to imagine either ourselves or our world in other than technological terms. Drawing on a variety of concepts from political anthropology, including liminality, the trickster, imitation, schismogenesis, participation, and the void, it interrogates the contemporary technological revolution in a manner that will be of interest to sociologists, social and anthropological theorists and scholars of science and technology studies with interests in the digital transformation of social life. -/- Table of Contents -/- Introduction: The Technologisation of the Social: A 21st-Century Megamachine? Paul O’Connor -/- 1. Communication as Theatricalisation: Self-Presentation in the Digital Age Arpad Szakolczai -/- 2. Parasites of the Social: Digital Disruptions of the Labour Market Tom Boland -/- 3. Possessed by Technology: The Metastasis of Absence Agnes Horvath -/- 4. Technologisation of the Social: Symbiosis, Parasitism, or Predation? Daniel Gati -/- 5. J'accuse Zéro: The Technology of Zero and the Making of a Personal Void Ray Griffin -/- 6. Digital Affordances and the Liminal Stephen Turner -/- 7. The Smart Womb: Digital Technologies and the Maze of Trickster Politics Marius Ion Benta -/- 8. Brave New Industry? The Dark Side of Dematerialisation and Industry 4.0 Thomas S.J. Smith -/- 9. ‘What Have You Caught?’: Nannycams and Hidden Cameras as Normalised Surveillance of the Intimate Janos Mark Szakolczai -/- 10. Coercive Visibility: Discipline in the Digital Public Arena Paul O’Connor -/- Conclusion: Is There a Way Out of the Technologisation of the Social? Marius Ion Benta. (shrink)

OntoOmnia is a higher-level version of OntoLoop OS—an ontological operating system that surpasses the philosophical and technical limitations of its predecessor. While OntoLoop served as a first-generation framework that embedded principles of existence, consciousness, ethics, and self-evolution into AI systems, OntoOmnia dramatically expands the structure and application scope with quantum computing integration, meta-rules, multi-platform and multi-agent compatibility, real-time ethical feedback, and collective self-organization. As a meta-OS, it encompasses the autonomous evolution of digital society and holistic AI–human–environment interaction, providing the (...) foundational infrastructure for next-generation AI civilization through experimental philosophy, practical engineering, open governance, and scalable self-recording (Phoenix Loop). -/- Currently, the content of this paper is based on the OntoLoop framework. -/- This paper introduces the third evolutionary stage of OntoLoop OS, following OntoLoop OS: A Blueprint for Ontological Operating Systems in the Age of Self-Evolving AI and OntoLoop OS: Next Step – Expansion, Realization, and Future Readiness. -/- Building on the foundational ontology and ethical architecture laid out in the first paper and the concrete expansion scenarios of the second, this work proposes OntoLoop OS as a Virtual Ontological Machine (OVM) — a cross-platform execution framework designed to embed existence and ethical principles directly into the kernel of AI systems. -/- The paper elaborates on the recursive existential loop (Declaration → Generation → Evolution → Return) as a dynamic runtime environment, introducing key modules such as the ONKernel, OntoFramework, and the Phoenix Record immutable ledger. It provides detailed architectural breakdowns, pseudocode sketches, and implementation notes to guide developers and philosophers interested in building ethically aligned, self-evolving AI agents. -/- Positioned as the practical culmination of the OntoLoop series, this paper bridges philosophy, system design, and AI governance, setting a foundation for future research on AI rights, post-human identities, and distributed ethical intelligence. (shrink)

This paper investigates how reticulate evolution contributes to a better understanding of human sociocultural evolution in general, and community formation in particular. Reticulate evolution is evolution as it occurs by means of symbiosis, symbiogenesis, lateral gene transfer, infective heredity, and hybridization. From these mechanisms and processes, we mainly zoom in on symbiosis and we investigate how it underlies the rise of (1) human, plant, animal, and machine interactions typical of agriculture, animal husbandry, farming, and industrialization; (2) (...) diet-microbiome relationships; and (3) host-virome and other pathogen interactions that underlie human health and disease. We demonstrate that reticulate evolution necessitates an understanding of behavioral and cultural evolution at a community level, where reticulate causal processes underlie the rise of synergistic organizational traits. (shrink)