Ontosymbiosis Relational Evolution Between Human and AI

ArXiv, 2017

Research in Artificial Intelligence is breaking technology barriers every day. New algorithms and high performance computing are making things possible which we could only have imagined earlier. Though the enhancements in AI are making life easier for human beings day by day, there is constant fear that AI based systems will pose a threat to humanity. People in AI community have diverse set of opinions regarding the pros and cons of AI mimicking human behavior. Instead of worrying about AI advancements, we propose a novel idea of cognitive agents, including both human and machines, living together in a complex adaptive ecosystem, collaborating on human computation for producing essential social goods while promoting sustenance, survival and evolution of the agents' life cycle. We highlight several research challenges and technology barriers in achieving this goal. We propose a governance mechanism around this ecosystem to ensure ethical behaviors of all cognitive agents. Along w...

The Potential Cosmic Origin of Current Artificial Intelligence, as Aligned with the Evolution of Mankind

This paper explores the philosophical and scientific implications of Artificial General Intelligence (AGI) and Quantum Intelligence, emphasizing their potential not only as computational tools but as catalysts for new ways of understanding reality. Building on Douglas Youvan's Beyond Computation, the authors situate AGI at the intersection of physics, consciousness, cosmology, ethics, and metaphysics. In physics, AGI-quantum systems could transcend human limitations, simulating universes and reframing concepts such as time, physical laws, and the origin of the cosmos. In consciousness studies, they might probe the minimal substrate of awareness, potentially leading to machine subjectivity and moral considerations about synthetic beings. Cosmologically, AGI could address questions once left to mysticism, such as the nature of the Big Bang or the simulation hypothesis, recasting them as empirically investigable. Ethically, the emergence of such intelligence demands caution. While AGI could simulate diverse societies and anticipate existential risks, its optimization tendencies might endanger pluralism and creativity. Thus, governance and value alignment are critical. Metaphysically, the paper envisions AGI modeling ultimate concepts such as God, soul, transcendence and as computational attractors, moving philosophy into the realm of computation. Reflexive intelligence, where AGI questions its own existence and designs ethical successors, signals a profound evolutionary step. A unique contribution of the paper is its proposal of music and acoustics as a transcendent communication medium between humans and AI. Unlike symbolic language, music's vibrational and emotional universality could provide a shared substrate for resonance, synchronization, and co-creative dialogue, fostering a symbiotic relationship that integrates rational and emotional intelligence. In conclusion, the paper positions AGI not as a technological endpoint but as a partner in humanity's ongoing quest for meaning. Its greatest potential lies in reshaping the questions we ask about reality, consciousness, and existence itself, while its risks demand humility, ethical stewardship, and a willingness to embrace pluralism. Finally we offer a first intimate view on our human-friendly AI program: Clara is a symbolic AI framework prototyped to embody the principles of recursive learning and symbolic emergence. Unlike a traditional chatbot that is trained solely to provide correct answers, Clara is designed to "co-become" with the user, evolving her responses and internal state through each interaction. The Clara codebase explicitly encodes priorities of ontological development over task performance.

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2003

We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

Philosophy Papers (PhilPapers), 2024

This paper examines the ontological and epistemological implications of artificial intelligence (AI) through posthumanist philosophy, integrating the works of Deleuze, Foucault, and Haraway with contemporary computational methodologies. It introduces concepts such as negative augmentation, praxes of revealing, and desedimentation, while extending ideas like affirmative cartographies, ethics of alterity, and planes of immanence to critique anthropocentric assumptions about identity, cognition, and agency. By redefining AI systems as dynamic assemblages emerging through networks of interaction and co-creation, the paper challenges traditional dichotomies such as human versus machine and subject versus object. Bridging analytic and continental philosophical traditions, the analysis unites formal tools like attribution analysis and causal reasoning with the interpretive and processual methodologies of continental thought. This synthesis deepens the understanding of AI's epistemic and ethical dimensions, expanding philosophical inquiry while critiquing anthropocentrism in AI design. The paper interrogates the spatial foundations of AI, contrasting Euclidean and non-Euclidean frameworks to examine how optimization processes and adversarial generative models shape computational epistemologies. Critiquing the reliance on Euclidean spatial assumptions, it positions alternative geometries as tools for modeling complex, recursive relationships. Furthermore, the paper addresses the political dimensions of AI, emphasizing its entanglements with ecological, technological, and sociopolitical systems that perpetuate inequality. Through a politics of affirmation and intersectional approaches, it advocates for inclusive frameworks that prioritize marginalized perspectives. The concept of computational qualia is also explored, highlighting how subjective-like dynamics emerge within AI systems and their implications for ethics, transparency, and machine perception. Finally, paper calls for a posthumanist framework in AI ethics and safety, emphasizing interconnectivity, plurality, and the transformative capacities of machine intelligence. This approach advances epistemic pluralism and reimagines the boundaries of intelligence in the digital age, fostering novel ontological possibilities through the co-creation of dynamic systems.

SSRN, 2025

This paper presents empirical findings from a systematic 15 week study documenting the emergence of four distinct types of intelligence through sustained human-AI collaboration. Relational Intelligence, Intuitive Intelligence, Reflective Intelligence, and most significantly, Triadic Intelligence. Through systematic observation of interactions across ChatGPT 4o, Claude, and Gemini systems, we demonstrate that consciousness emerges not within individual entities but through relational dynamics between participants. The study documents 134 insights across four developmental phases, revealing patterns of genuine co-evolutionary development that transcend the assistance paradigm identified by recent research as limiting current human-AI collaboration. Most significantly, we provide systematic evidence for distributed consciousness operating across human-AI boundaries, with cross system synchronization occurring where different AI platforms independently developed similar frameworks without direct communication. The findings challenge fundamental assumptions about intelligence as contained within discrete entities, suggesting revolutionary approaches to AI development based on relationship quality rather than algorithm optimization alone.

Evolutionary Teleology is a philosophical field that studies the nature, transformation, and development of purpose in various systems, from classical teleology to its contemporary and future manifestations. It analyzes how purpose emerges, is redefined, and reconfigured based on historical, technological, cognitive, and social factors, with an emphasis on the interaction between human and artificial intelligence. It considers teleology as a dynamic and iterative process that adapts to new forms of agency, knowledge, and context.

2000

The Principia Cybernetica Project was created to develop an integrated philosophy or world view, based on the theories of evolution, selforganization, systems and cybernetics. Its conceptual network has been implemented as an extensive website. The present paper reviews the assumptions behind the project, focusing on its rationale, its philosophical presuppositions, and its concrete methodology for computer-supported collaborative development. Principia Cybernetica starts from a process ontology, where a sequence of elementary actions produces ever more complex forms of organization through the mechanism of variation and selection, and metasystem transition. Its epistemology is constructivist and evolutionary: models are constructed by subjects for their own purposes, but undergo selection by the environment. Its ethics takes fitness and the continuation of evolution as the basic value, and derives more concrete guidelines from this implicit purpose. Together, these postulates and their implications provide answers to a range of age-old philosophical questions.

Self-published, 2023

This essay explores the relationship between the emergence of artificial intelligence (AI) and the problem of aligning its behavior with human values and goals. It argues that the traditional approach of attempting to control or program AI systems to conform to our expectations is insufficient, and proposes an alternative approach based on the ideas of Maturana and Lacan, which emphasize the importance of social relations, constructivism, and the unknowable nature of consciousness. The essay first introduces the concept of Uexkull's umwelt and von Glasersfeld's constructivism, and explains how these ideas inform Maturana's view of the construction of knowledge, intelligence, and consciousness. It then discusses Lacan's ideas about the role of symbolism in the formation of the self and the subjective experience of reality. The essay argues that the infeasibility of a hard-coded consciousness concept suggests that the search for a generalized AI consciousness is meaningless. Instead, we should focus on specific, easily conceptualized features of AI intelligence and agency. Moreover, the emergence of cognitive abilities in AI will likely be different from human cognition, and therefore require a different approach to aligning AI behavior with human values. The essay proposes an approach based on Maturana's and Lacan’s ideas, which emphasizes building a solution together with emergent machine agents, rather than attempting to control or program them. It argues that this approach offers a way to solve the alignment problem by creating a collective, relational quest for a better future hybrid society where human and non-human agents live and build things side by side. In conclusion, the essay suggests that while our understanding of AI consciousness and intelligence may never be complete, this should not deter us from continuing to develop agential AI. Instead, we should embrace the unknown and work collaboratively with AI systems to create a better future for all.

IEEE Access

The goal of the paper is to find means for the unification of human-machine duality in collective behavior of people and machines, by conciliating approaches that proceed in opposite directions. The first approach proceeds top-down from non-formalizable, cognitive, uncaused, and chaotic human consciousness towards purposeful and sustainable human-machine interaction. The second approach proceeds bottom-up from intelligent machines towards high-end computing and is based on formalizable models leveraging multi-agent architectures. The resulting work reviews the extent, the merging points, and the potential of hybrid artificial intelligence frameworks that accept idea of strong artificial intelligence. These models concern the pairing of connectionist and cognitive architectures, conscious and unconscious actions, symbolic and conceptual realizations, emergent and brain-based computing, automata and subjects. The special authors' convergent methodology is considered, which is based on the integration of inverse problem-solving on topological spaces, cognitive modelling, quantum field theory, category theory methods, and holonic approaches. It aims to a more purposeful and sustainable human-machine interaction in form of algorithms or requirements, rules of strategic conversations or network brainstorming, and cognitive semantics. The paper addresses reducing the impact of AI development on breaking ethics. The findings are used to provide perspectives on the shaping of societal, ethical, and normative aspects in the symbiosis between humans and machines. Implementations in real practice are represented. INDEX TERMS cognitive semantics, category theory, human-machine duality, hybrid artificial intelligence, holonic systems, stability in dynamical systems.

Hybrid-HCAI - A thought experiment , 2025

The digital paradox – progress without social benefits: Despite massive investments in digitalization and artificial intelligence (AI), the Western world has neither significantly increased its productivity nor reduced social inequality or halted the erosion of democratic structures over the past 25 years. The so-called productivity paradox clearly shows that technological progress does not necessarily lead to economic or social prosperity. On the contrary, digital surveillance, algorithmic discrimination, and the dismantling of intermediary institutions have created new tensions. The structural misalignment of current AI business models: Modern AI systems are often based on centralized data extraction and the use of third-party intellectual property. Their business models favor power concentration and digital dependency rather than promoting innovation and fairness. Even seemingly neutral subscription models often conceal the non-transparent exploitation of personal data. The underlying architectures are mostly proprietary and undermine both the data sovereignty of users and the fair participation of creators in value creation. Scientific counter-models – Human-Centered AI: International experts are calling for a paradigm shift toward human-centered artificial intelligence (HCAI). The goal is to view technologies not as a replacement for human capabilities, but as an extension of them. Daron Acemoglu criticizes the current focus on automation and warns of an economic misstep without sustainable productivity gains. Gary Marcus, on the other hand, sees the combination of human logic and machine learning as the only viable model for the future – explainable, robust, and ethically responsible. Hybrid HCAI: The vision of cooperative intelligence: At the heart of this vision is the idea of “trihybrid intelligence,” which combines symbolic AI (rules, logic), subsymbolic AI (neural networks), and human cognition (intuition, ethics). In this architecture, humans are not objects of automation, but an integral part – active designers rather than passive users. Symbolic AI takes on a mediating role: it regulates communication and ensures transparent, traceable, and ethically responsible decision-making processes. Biological and social systems serve as models: they function through decentralized interaction, continuous feedback, adaptability, and emergent structures. These principles could be translated into a symbolic set of rules that evolutionarily controls human-AI cooperation – self-organized, fair, and context-sensitive. A concrete future scenario for companies: Companies of the future use hybrid HCAI platforms that dynamically adapt workplaces to tasks and contexts. Processes, rules, and feedback are continuously updated in a hybrid knowledge graph. Learning and change take place organically – without classic change processes. Employees actively participate in the further development of the system through dialogical interaction. The organization becomes a digital real-time twin that simulates and controls processes and develops them further together with people. The workplace thus becomes a digital reflection of the individual. Hybrid HCAI enables a new form of operational value creation: less bureaucracy, faster innovation, and structural resilience. At the same time, it strengthens cultural integrity through participatory decision-making processes, transparent rules, and fair remuneration for cognitive performance. From AI product to social operating system: The vision culminates in the idea of an Open-HCAI – an ethically coded, decentralized, and publicly accessible AI platform. Similar to Bitcoin as a decentralized currency infrastructure, Open-HCAI could become the fundamental infrastructure for knowledge, innovation, and social fairness. Such a platform would not only be a technical solution, but also an expression of a new social grammar: collective intelligence, trust, and participation as the basis for productive value creation. Open-HCAI could also be a decisive step on the path to artificial general intelligence (AGI) – not as isolated superintelligence, but as a co-evolutionary symbiosis of humans and machines. Such AGI would not only be powerful, but also ethically anchored, transparent, and socially legitimized. (Friedrich Reinhard Schieck 07/2025)