Non-dual awareness (NDA) refers to a shift in consciousness in which the usual distinction between subject and object dissolves, and experience is no longer structured by conceptual mediation or goal-directed regulation. Meling enactivist model describes NDA as a meditative disclosure of groundlessness-the recognition of emptiness (śūnyatā), that all phenomena lack intrinsic nature. While enactivism explains autonomy through process closure, this article argues that constraint closure, as developed by Nave, extends that framework by making explicit how autonomy is sustained through the continual regeneration of its own relational conditions. This refinement prevents process-closure models from being read in substantialist terms when applied to complex cognitive systems, where stability arises through ongoing transformation rather than fixed organization. Nave's account builds on Juarrero theory of constraint causality, which replaces intrinsic forces with relational conditions-a view that parallels Nāgārjuna's Madhyamaka analysis of dependent origination. Integrating these perspectives, I propose that NDA corresponds to a shift from decoupled to precarious constraints, revealing that cognition and awareness persist not through intrinsic foundations but through the dynamic regeneration of interdependent relations.
Modeling non-dual awareness via constraint closure: a reinterpretation of groundlessness
Abstract. Non-dual awareness (NDA) refers to a shift in consciousness in which the usual distinction between subject and object dissolves, and experience i
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.
We speak often of AI as if it were a future event. But it is already here in the fabric of our being. What Karl Ove Knausgaard captures with devastating clarity in his recent essay ‘The Reenchanted… | Kenneth Mikkelsen | 19 comments
We speak often of AI as if it were a future event. But it is already here in the fabric of our being. What Karl Ove Knausgaard captures with devastating clarity in his recent essay ‘The Reenchanted World’ is the departure of the real. “We live in a virtual world, as if the world had been lifted out of itself, into the air, like a giant roof suspended above the ground,” he writes. It is an existential condition. Across philosophy, from Heidegger to Baudrillard, from Don DeLillo to Debord, a singular thread weaves: the world, once our shelter from the self, has become self-referential. Where once we encountered beings in our Zuhandensein—ready-to-hand, intimate, meaningful—we now face a procession of Vorhandensein: inert, objectified, mediated. Simulation replaces encounter. Perception is swallowed by spectacle. And the digital era, in Knausgaard’s terms, “distances culture from the body”. “It is not just the body that disappears—it is the awareness that we are dying,” he writes. What we face is not merely technological change, but what I would call existential dissonance: the erosion of resonance between our inner world, our social world, and the material world. It is the tension that arises when the way one lives, acts, and relates is misaligned with one’s deeper sense of meaning, reality, and value. It manifests itself as a disturbance in being — an unease that is not merely emotional, but rooted in a felt gap between one’s existence as it is and as it could or should be. It is the voice of the self calling from within the noise of the world. This is why Knausgaard’s essay matters for anyone working in, with, or around AI. Because the question isn’t: What can these systems do? It is: What do they undo? “We can explain everything. But we understand nothing,” he writes. Manipulated constructions of truth, in such a time, becomes a currency. As shown in recent events—from Francesca Gino’s research fraud at Harvard to Bezos’ all-female crew venture into space, and Trump’s detention camp —truth is no longer that which corresponds with reality, but that which performs and sells. As Baudrillard warned, the simulation no longer hides the real—it becomes it. And yet, something remains. Knausgaard writes not to despair, but to stay. In the body. In death. In silence. In the concrete. If you seek to understand what is happening—not just in AI, but in the very metaphysics of modern life—I suggest we begin not with data, but with dissonance. With the feeling that something vital is slipping from view, and that “being in the world” now requires resistance. “We are surrounded by mystery. And yet we act as if everything were known,” he writes. AI will never understand this. But we must. Knausgaard’s full essay from Harper’s Magazine can be read via link in comments. | 19 comments on LinkedIn
The science of consciousness does not need another theory, it needs a minimal unifying model
Abstract. This article discusses a hypothesis recently put forward by Kanai et al., according to which information generation constitutes a functional basi
A Philosopher’s One-Word Theory to Explain Why the World Feels So Weird
Once you learn what the "uni-context" is, you won't stop seeing it everywhere
Verbalizable Representations Form a Global Workspace in Language Models
If the mind is an ocean, we spend our lives floating at the surface. Beneath us, an enormous amount of processing takes place without our knowledge: our visual systems parsing the contours of a face, our motor circuits maintaining our posture. At any given moment, only a small fraction of this neural activity is accessible to us. Yet it is this privileged sliver of activity that we rely on to reason deliberately: to plan what ingredients to buy for a recipe, or to puzzle out why an engine won’t start. Such thoughts can be articulated out loud, deliberately held in mind, and brought to bear on whatever task the moment demands. This distinction, between our accessible thoughts and our unconscious processing, is perhaps the most striking feature of human cognition.
Verbalizable Representations Form a Global Workspace in Language Models
If the mind is an ocean, we spend our lives floating at the surface. Beneath us, an enormous amount of processing takes place without our knowledge: our visual systems parsing the contours of a face, our motor circuits maintaining our posture. At any given moment, only a small fraction of this neural activity is accessible to us. Yet it is this privileged sliver of activity that we rely on to reason deliberately: to plan what ingredients to buy for a recipe, or to puzzle out why an engine won’t start. Such thoughts can be articulated out loud, deliberately held in mind, and brought to bear on whatever task the moment demands. This distinction, between our accessible thoughts and our unconscious processing, is perhaps the most striking feature of human cognition.
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.
Thinking through other minds: A variational approach to cognition and culture
The processes underwriting the acquisition of culture remain unclear. How are shared habits, norms, and expectations learned and maintained with precision and reliability across large-scale sociocultural ensembles? Is there a unifying account of the mechanisms involved in the acquisition of culture? Notions such as “shared expectations,” the “selective patterning of attention and behaviour,” “cultural evolution,” “cultural inheritance,” and “implicit learning” are the main candidates to underpin a unifying account of cognition and the acquisition of culture; however, their interactions require greater specification and clarification. In this article, we integrate these candidates using the variational (free-energy) approach to human cognition and culture in theoretical neuroscience. We describe the construction by humans of social niches that afford epistemic resources called cultural affordances. We argue that human agents learn the shared habits, norms, and expectations of their culture through immersive participation in patterned cultural practices that selectively pattern attention and behaviour. We call this process “thinking through other minds” (TTOM) – in effect, the process of inferring other agents’ expectations about the world and how to behave in social context. We argue that for humans, information from and about other people's expectations constitutes the primary domain of statistical regularities that humans leverage to predict and organize behaviour. The integrative model we offer has implications that can advance theories of cognition, enculturation, adaptation, and psychopathology. Crucially, this formal (variational) treatment seeks to resolve key debates in current cognitive science, such as the distinction between internalist and externalist accounts of theory of mind abilities and the more fundamental distinction between dynamical and representational accounts of enactivism.
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.
The Care of the Self within a Biopolitical Paradigm: Integrating Cognitive Psychology to resist Subjectification
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.
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.
Cognitive Surrender and Tri-System Theory · Today I Learned
How AI can support, displace, or bypass human deliberation
Alexander Lerchner, The Abstraction Fallacy: Why AI Can Simulate But Not Instantiate Consciousness - PhilPapers
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 ...
