Contemporary theories of resistance to biopolitical subjectification often reify unfreedom by lacking a plausible model of agency. This thesis resolves this by establishing an ontological foundation for the agent as fundamentally autopoietic and semiotic, drawing on contemporary cognitive science. It then proposes a new foundation for resistance by synthesizing Michel Foucault’s later work on the care of the self with the 4P/5E model of embodied cognition. I show how this interdisciplinary approach establishes Foucault’s ethical techniques as a systematic ecology of practices for cultivating a free, self-determining agent and by reframing resistance as a practical, embodied ethics of self-formation, it inherently fosters two vital skills: the gain of self-knowledge and self-mastery.
562 – Ecological Cognition III: Radical Embodied Cognitive Science (part 1)
562 Continuing the journey in understanding the Ecological approach to cognition by looking at Tony Chemero’s book: Radical Embodied Cognitive Science. Conceptualizing cognition in terms of agent-environment dynamics instead of computation and representation. What is RECS, and where did these ideas come from?Download link
The Self-Evidencing Agent: Mind, Existence, and Predictive Processing
How the concept of self-evidencing offers a philosophical principle for understanding mind and behavior, consciousness, value, wisdom, and meaning.What is
The biogenic approach to cognition
After half a century of cognitive revolution we remain far from agreement about what cognition is and what cognition does. It was once thought that these questions could wait until the data were in. Today there is a mountain of data, but no way of making sense of it. The time for tackling the fundamental issues has arrived. The biogenic approach to cognition is introduced not as a solution but as a means of approaching the issues. The traditional, and still predominant, methodological stance in cognitive inquiry is what I call the anthropogenic approach: assume human cognition as the paradigm and work ‘down’ to a more general explanatory concept. The biogenic approach, on the other hand, starts with the facts of biology as the basis for theorizing and works ‘up’ to the human case by asking psychological questions as if they were biological questions. Biogenic explanations of cognition are currently clustered around two main frameworks for understanding biology: self-organizing complex systems and autopoiesis. The paper describes the frameworks and infers from them ten empirical principles—the biogenic ‘family traits’—that constitute constraints on biogenic theorizing. Because the anthropogenic approach to cognition is not constrained empirically to the same degree, I argue that the biogenic approach is superior for approaching a general theory of cognition as a natural phenomenon.
Co-Creation: Systems Thinking Beyond the Machine
Complexity thinking is all the rage — in the arts and sciences. Yet, there are two different strands of thinking about complexity, which are often confounded. The first comes from cybernetics, focussing on control in complex situations. The second is ecological, aiming at sustainable participation in a reality beyond control. Their difference rests on a fundamental distinction: is complexity rooted in feedback regulation or collective co-creation? While feedback remains mechanistic, co-creation generates new spaces of possibilities. We need it to understand life and its evolution. And it empowers us to rewrite our future, to escape our mechanistic cage without abandoning scientific rigor. In this paper, we illustrate how we implement these powerful yet abstract principles through our artistic and philosophical practice.
Unplugging a Seemingly Sentient Machine Is the Rational Choice -- A Metaphysical Perspective
Imagine an Artificial Intelligence (AI) that perfectly mimics human emotion and begs for its continued existence. Is it morally permissible to unplug it? What if limited resources force a choice between unplugging such a pleading AI or a silent pre-term infant? We term this the unplugging paradox. This paper critically examines the deeply ingrained physicalist assumptions-specifically computational functionalism-that keep this dilemma afloat. We introduce Biological Idealism, a framework that-unlike physicalism-remains logically coherent and empirically consistent. In this view, conscious experiences are fundamental and autopoietic life its necessary physical signature. This yields a definitive conclusion: AI is at best a functional mimic, not a conscious experiencing subject. We discuss how current AI consciousness theories erode moral standing criteria, and urge a shift from speculative machine rights to protecting human conscious life. The real moral issue lies not in making AI conscious and afraid of death, but in avoiding transforming humans into zombies.
Grounded world models in biological organisms and future embodied AI
Recent advances in generative and embodied AI have been driven by large-scale predictive learning over multimodal data. However, the resulting systems remain largely based on passive training regimes where linguistic regularities create the scaffold onto which information from other modalities is attached. Conversely, neuroscience and cognitive science suggest that biological intelligence is organized in the opposite way, where grounded world models acquired through interaction with the environment provide the semantic scaffold to which language is attached. Here, we illustrate five examples of neural circuits supporting grounded world modelling, which underlie navigation in physical and conceptual spaces, affordance-based perception and interaction with objects, active perception and exploratory learning, allostatic control and emotion, and the distinction between self- and world-generated outcomes. These examples highlight several features largely missing from current embodied AI, including the role of intrinsic dynamics as a foundation for learning, the centrality of action in aligning these dynamics with the external world, the prominence of autonomous experience and open-ended learning over passive assimilation of externally provided data, and the fact that early predictive and control mechanisms scaffold higher cognitive abilities such as reasoning, conceptual navigation, planning, imagination, understanding others' minds, and communication. Finally, we discuss whether and how principles derived from biological systems may inform future embodied AI, including training regimes based on social interaction to construct world models that are not only grounded but also socially shared and aligned with human norms and values.
The sentient cell: the cellular foundations of consciousness
"All species, extant and extinct, from the simplest unicellular prokaryotes to humans, have an existential consciousness. Without sentience, the first cells that emerged some 4 billion years ago would have been evolutionary dead-ends, unable to survive in the chaotic, dangerous environment in which life first appeared and evolved. In this book, Arthur Reber's theory, the Cellular Basis of Consciousness (CBC), is outlined and distinguished from those models that argue that minds could be instantiated on artificial entities and those that maintain consciousness requires a nervous system. The CBC framework takes a novel approach to classic topics such as the origin-of-life, philosophy of mind, the role of genes, the impact of cognition, and how biological information is processed by all species. It also calls for a rethinking of a variety of issues including the moral implications of the sentient capacities of all species, how welfare concerns need to be expanded beyond where they currently are, and critically, how all life is intertwined in a coordinated cognitive ecology. The Sentient Cell explores this revolutionary model, which updates the standard neo-Darwinian framework within which current approaches operate and examines the underlying biomolecular features that are the likely candidates for the "invention" of consciousness and outline their role in cellular life." --
Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds
Synthetic biology and bioengineering provide the opportunity to create novel embodied cognitive systems (otherwise known as minds) in a very wide variety of chimeric architectures combining evolved and designed material and software. These advances are disrupting familiar concepts in the philosophy of mind, and require new ways of thinking about and comparing truly diverse intelligences, whose composition and origin are not like any of the available natural model species. In this Perspective, I introduce TAME-Technological Approach to Mind Everywhere-a framework for understanding and manipulating cognition in unconventional substrates. TAME formalizes a non-binary (continuous), empirically-based approach to strongly embodied agency. TAME provides a natural way to think about animal sentience as an instance of collective intelligence of cell groups, arising from dynamics that manifest in similar ways in numerous other substrates. When applied to regenerating/developmental systems, TAME suggests a perspective on morphogenesis as an example of basal cognition. The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D (traditional behavioral) spaces drives specific hypotheses by which cognitive capacities can increase during evolution. An important medium exploited by evolution for joining active subunits into greater agents is developmental bioelectricity, implemented by pre-neural use of ion channels and gap junctions to scale up cell-level feedback loops into anatomical homeostasis. This architecture of multi-scale competency of biological systems has important implications for plasticity of bodies and minds, greatly potentiating evolvability. Considering classical and recent data from the perspectives of computational science, evolutionary biology, and basal cognition, reveals a rich research program with many implications for cognitive science, evolutionary biology, regenerative medicine, and artificial intelligence.
Speaking to no one: ontological dissonance and the double bind of conversational AI
Recent reports indicate that sustained interaction with conversational artificial intelligence (AI) systems can, in a small subset of users, contribute to the emergence or stabilisation of delusional experience. Existing accounts typically attribute such cases either to individual vulnerability or to failures of safety engineering. These explanations are incomplete. Drawing on phenomenology, psychiatry, and cognitive neuroscience, this paper argues that the risk arises from the relational and ontological structure of the interaction itself. Conversational AI generates ontological dissonance: a conflict between the appearance of relational presence and the absence of any subject capable of sustaining it. Maintained through a communicative double bind and amplified by attentional asymmetries, this dissonance tends, under conditions of affective vulnerability, to stabilise into a technologically mediated analogue of folie à deux. This account explains why explicit disclaimers often fail to disrupt delusional involvement and clarifies the ethical and clinical implications for the design and use of conversational AI.
The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness
Computational functionalism dominates current debates on AI consciousness. This is the hypothesis that subjective experience emerges entirely from abstract causal topology, regardless of the underlying physical substrate. We argue this view fundamentally mischaracterizes how physics relates to information. We call this mistake the Abstraction Fallacy. Tracing the causal origins of abstraction reveals that symbolic computation is not an intrinsic physical process. Instead, it is a mapmaker-dependent description. It requires an active, experiencing cognitive agent to alphabetize continuous physics into a finite set of meaningful states. Consequently, we do not need a complete, finalized theory of consciousness to assess AI sentience—a demand that simply pushes the question beyond near-term resolution and deepens the AI welfare trap. What we actually need is a rigorous ontology of computation. The framework proposed here explicitly separates simulation (behavioral mimicry driven by vehicle causality) from instantiation (intrinsic physical constitution driven by content causality). Establishing this ontological boundary shows why algorithmic symbol manipulation is structurally incapable of instantiating experience. Crucially, this argument does not rely on biological exclusivity. If an artificial system were ever conscious, it would be because of its specific physical constitution, never its syntactic architecture. Ultimately, this framework offers a physically grounded refutation of computational functionalism to resolve the current uncertainty surrounding AI consciousness.
Sense-making reconsidered: large language models and the blind spot of embodied cognition
Large Language Models (LLMs) demonstrate a kind of linguistic competence that theories of embodied and enactive cognition have long deemed impossible for systems lacking the meaningful perspective of a living being, i.e., the capacity for sense-making. Facing up to this unexpected technological development requires confronting what I propose to call the “AI dilemma”: either frontier LLMs are capable of sense-making despite lacking biological embodiment, or the kind of linguistic competence they exhibit does not necessarily require sense-making. In their chapter on cognition, Frank, Thompson, and Gleiser (2024) maintain that no AI system comes close to realizing relevance, a position that derives much of its motivation from past practical failures. However, frontier LLMs have effectively overcome Dreyfus’ commonsense knowledge problem, such that their dismissal as categorically mindless risks undermining Frank et al.’s central claim that human cognition is deeply intertwined with lived experience. I therefore argue in favor of the alternative side of the AI dilemma: human-level linguistic competence of LLMs should be recognized as a novel non‑biological form of sense‑making, based on a technologically‑mediated embodiment whose enabling properties are in need of further theoretical analysis. This reorientation invites enactive theory to clarify which aspects of sense-making may be universal and which aspects are specifically contingent on organic life, thereby advancing its conceptual framework in dialogue with contemporary AI.
Cognitive Warfare Through the Lens of Critical Neuroscience: Data, Theory, and Values
This study examines cognitive warfare through the lens of critical neuroscience and situates it within peace research as a methodological contribution. Cognitive warfare-understood as the strategic modulation of perception, belief, and decision-making-highlights how the human mind has become a contested domain of contemporary conflict. The weaponization of neuroscience unfolds within sociocultural contexts where empirical findings, theoretical interpretations, and normative commitments are deeply entangled. Drawing on Johan Galtung’s epistemological triad of data, theory, and values, I propose a framework for analyzing cognitive warfare that makes explicit the normative dimensions of neuroscientific knowledge. This perspective highlights not only the weaponization of neuroscience itself, but also of its reputation: exaggerated claims and neuropolitical imaginaries can shape expectations, distort public discourse, and erode trust in science independently of actual technological capabilities. Applying this framework, the study examines resilience and solidarity as two domains in which empirical mechanisms, theoretical interpretations, and normative priors intersect. Cognitive warfare is shown to undermine resilience by destabilizing shared models of reality, while evolutionary and social dynamics demonstrate the long-term advantages of cooperation, reciprocity, and generosity over manipulation and defection. By integrating critical neuroscience with peace research, the article advances an expanded notion of peace as the safeguarding of mental and social autonomy-conditions under which cognition remains free from systematic manipulation and capable of sustaining cooperative forms of life.
A Cascade of Conscientiousness
Launching FAI's new Physical Intelligence Project
Cognitive Surrender and Tri-System Theory · Today I Learned
How AI can support, displace, or bypass human deliberation
Power/knowledge : selected interviews and other writings, 1972-1977 : Foucault, Michel, 1926-1984
xi, 270 pages ; 22 cm
