The Counterintuitive Need to Slow Down and Find Spaciousness

I pass on the following edited clips from ChatGPT and Claude condensations of a conversation between Nate Hagens and Iain McGilchrist.  While I think McGilchrist's left-hemisphere/right hemisphere distinctions are a bit simplistic, the take home messages are appropriate regardless of the particular brain activity correlates that are invoked: 

In episode 217 of Nate Hagens's The Great Simplification, Hagens is rejoined by philosopher and neuroscientist Iain McGilchrist — best known for The Master and His Emissary and The Matter With Things — for a wide-ranging conversation about what our current moment of civilizational crisis actually demands of us. The counterintuitive answer is not more urgency, not more optimization, but a deliberate slowing down and an opening toward spaciousness, silence, and wonder. The conversation begins from Hagens’ familiar “metacrisis” frame — ecological, economic, social, and psychological instabilities as interlocking expressions of a deeper human predicament —  McGilchrist’s contribution is to shift the diagnosis inward, toward the style of attention that modern culture rewards.

Left-brain dominance and the obscuring of value

McGilchrist's central argument, developed across his major books, is that Western culture has become increasingly dominated by left-hemisphere modes of cognition — narrow, focused, categorical, explicit, and oriented toward control and manipulation. The right hemisphere, by contrast, attends to the whole, holds ambiguity, and remains open to what is living, relational, and interconnected. The trouble is not that we have a left hemisphere but that it has progressively usurped the role of the right as the governing perspective. This imbalance, McGilchrist argues, is not just a psychological curiosity: it is what underlies our collective inability to perceive and act on what truly matters — truth, goodness, and beauty. When the left hemisphere runs the show, these qualities become invisible, and what fills the vacuum is power, productivity, and the measurable.

Attention as the root of value

A thread running through the conversation is that attention is not neutral: what we attend to shapes what we value, and what we value shapes what we attend to. McGilchrist draws on the research insight that roughly 99% of brain activity is unconscious, which means that most of what guides our perception and behavior lies beneath deliberate awareness. The gorilla-in-the-room studies on inattentional blindness illustrate this starkly: we routinely fail to see what is right in front of us when our attention is narrowly locked. Applied to the metacrisis — the overlapping civilizational, ecological, and psychological crises of our era — this suggests that the problem is not primarily one of missing information or insufficient analysis. It is a crisis of attention itself. We are not seeing what matters because we have trained ourselves not to look.

The practice of spaciousness

The remedy McGilchrist proposes is not a political program or a technological fix. It is a shift in how we inhabit time. He urges listeners to resist what he calls the "mania for productivity" embedded in modern culture, and instead to cultivate spaciousness: pauses, silence, deep listening, and what Buddhism calls śūnyatā — emptiness not as absence but as fertile, generative openness. He cites Rabbi Abraham Joshua Heschel's writing on the Sabbath as a model: the ancient practice of building non-doing into the structure of the week was not a concession to weakness but a recognition that renewal and wisdom require fallow time. McGilchrist also points to the psychology of creativity research showing that insight characteristically emerges not during focused effort but in the hypnagogic spaces between — in showers, on walks, at the threshold of sleep.

Consciousness, panpsychism, and the thread connecting everything

The conversation moves into deeper philosophical territory when Hagens and McGilchrist explore what might underlie the universe's apparent orientation toward complexity, beauty, and relation. McGilchrist is sympathetic to panpsychism and panentheism — the view that some form of experience or proto-consciousness pervades reality, and that the universe is not a collection of inert objects but a relational, creative process. He draws on Whitehead's process philosophy, Bohm's implicate order, and Schelling's image of the self as a whirlpool — a temporary pattern that arises from and returns to a larger flow. Death, in this frame, is not mere termination but a kind of completion, and the obsession with indefinite life extension through technology reflects the left hemisphere's refusal to accept its own finitude.

A small percentage can shift the whole

McGilchrist closes with a message that is both modest and radical: he does not expect — or require — a majority conversion. Even a small percentage of people genuinely living differently, embodying humility, compassion, awe, and wonder, could begin to shift what he calls "cultural consciousness." This resonates with complexity theory's sensitivity to initial conditions and with the sociological literature on tipping points. The implication is that the most consequential thing an individual can do in a moment of civilizational turbulence may not be to do more, advocate louder, or optimize harder — but to slow down enough to actually see, and to live from that seeing.

For those already drawn to predictive processing frameworks: McGilchrist's account of hemispheric asymmetry maps interestingly onto the distinction between top-down, precision-weighted prediction (left-dominant) and the kind of open, receptive prior-updating that Friston's active inference would associate with high-entropy, exploratory sampling of the world. The right hemisphere, on this reading, is the brain's better Bayesian — the one willing to be surprised.

YouTube link to the full conversation

Getting Gooier: How AI Is Reshaping Human Nature

This post is the result of my back and forth interaction with Claude Sonnet 4.6 that has yielded the following summary of  Venkatesh Rao's recent essay, "Getting Gooier", followed by some perspectives that Rao does not address on Friston's active inference framework and the physiology of agency:

Venkatesh Rao's recent essay "Getting Gooier" makes a point worth sitting with: most AI commentary obsesses over how the world will change, while quietly assuming that humans stay essentially the same — just reshuffled among familiar roles (generalists thrive! storytellers inherit the earth! software engineers disappear!). Rao argues this is the wrong ontology. The real question is how AI is changing human nature itself.

His framework draws on Alan Watts's distinction between prickly and gooey people. Prickly people are tough-minded, precise, boundary-drawing; gooey people are tender-minded, synthesizing, prone to letting distinctions dissolve. All of us carry both, in varying ratios.

Rao's hypothesis: because AI feels like a psychologically safe counter party, we are more willing to expose our gooey side to it and suppress our pricklier instincts. Sustained AI use amplifies the gooey side. We become gooier. He notes that people who insist on prickly, suspicious, line-by-line relationships with AI agents tend not to use them effectively and retreat. People who can vibe with the machine — never even opening the code editor, just watching the agentic shell fly — will likely thrive. The first major gooified interface is, after all, called vibecoding.

The flip side is subtler: as more gooey relational needs are met by AI, the human-facing side grows less inclined to take the emotional risks required to balance prickles and goo with other people. We don't necessarily get pricklier toward humans — we just disengage unless the expected rewards are significantly higher. Your machine-face gets gooier; you look relatively pricklier to other humans.

In the medium term, Rao predicts greater atomization — or "molecularization" — as people grow more distant from other humans while becoming more intimately entangled with their AIs. He sees this as more sustainable than social-media-driven atomization, though the mechanisms for eventual re-convergence into new digitally mediated social forms aren't yet visible.

Following Virginia Woolf's famous claim that "on or about December 1910, human character changed," Rao proposes that on or about December 2025, human nature changed again — with the Claude Code moment being more definitive than the ChatGPT moment, because agentic coding creates a fundamentally alien way of being, open-ended enough to make us as alien as we dare to become. It is, he says, a portal to transhumanism.

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Rao's prickly/gooey axis maps naturally onto Karl Friston's active inference framework, and the connection carries some weight. In that account, what we experience as a "self" is a precision-weighted predictive model — a system that assigns confidence to its own predictions and acts to fulfill them. Getting gooier, in Fristonian terms, looks like a reduction in precision-weighting of prior beliefs: a loosening of the grip that constitutes a rigid, bounded selfhood. That loosening isn't necessarily pathological. It can be a precondition for learning, creativity, and genuine engagement with novelty.

But there's a physiological dimension Rao doesn't address, and it connects to questions I've been exploring in recent MindBlog posts and in an ongoing correspondence with my European colleague Heribert on the physiology of agency in the age of AI. Daniel Wegner's work frames the feeling of agency — the sense of being the author of one's own actions — not as a metaphysical claim about free will, but as an evolved emotion, as functionally real as fear or grief. Martin Seligman's learned helplessness research gives that claim empirical teeth: sustained loss of felt agency doesn't merely feel bad, it triggers measurable physiological debilitation. The autonomic nervous system, it turns out, needs the experience of authorship to maintain homeostatic equilibrium.

This raises a question Rao's framing implicitly sets aside: is getting gooier — letting the AI absorb more of the regulatory and decisional load, softening the boundary of the agentic self — compatible with the physiological requirements of human wellbeing? Or does sustained gooification, however pleasurable and productive in the short run, erode the felt sense of agency that keeps the organism in regulatory balance? Heribert has described this as "externalization of self-regulation" — not merely cognitive offloading, but emotional and autonomic offloading. That's a different and more serious claim.

The honest answer is probably: it depends on the mode of engagement. Gooiness that arises from confident delegation — the experienced surgeon handing off a routine task — is physiologically distinct from gooiness that arises from passivity, confusion, or a sense that the machine is simply running past you. Rao's vibecoder who chooses not to open the code editor is in a different physiological position than the one who is simply lost. The challenge ahead is cultivating the former while recognizing that the latter may be far more common than the early-adopter narrative suggests.

 

Agentic AI and the next intelligence explosion

This post is the second of two recursive returns to engage the ideas of Blaise Agüera y Arcas, which were the subject MindBlog posts on 3/13/26 and 3/16/26.  Here is text of Evans, Bratton, and Agüera y Arcas, as summarized by ChatGPT:

The article, “Agentic AI and the next intelligence explosion,” by James Evans, Benjamin Bratton, and Blaise Agüera y Arcas, argues against the familiar “singularity” image of one superintelligent machine bootstrapping itself into godlike autonomy. The authors say that model is probably wrong at its core. Intelligence, in their view, is not a single scalar quantity that one mind simply has more or less of. It is plural, relational, distributed, and social. The next “intelligence explosion” will not look like one silicon mind rising above us, but like a vast ecology of human and nonhuman agents interacting, arguing, coordinating, competing, and forming institutions.

Their key move is to treat agentic AI as continuous with earlier evolutionary jumps in intelligence. Primate intelligence scaled with social group life; human language created a “cultural ratchet”; writing, law, bureaucracy, and markets externalized cognition into institutions that no individual fully understood. AI, in this picture, is another step in that sequence: the accumulated products of human social cognition have been compressed into models and made operational in a new substrate. What is becoming powerful is not isolated abstract reason, but social intelligence reanimated in computational form.

The article also points inward, to what happens inside reasoning models. The authors cite work suggesting that frontier reasoning models do not merely improve by “thinking longer.” They appear to generate internal, multi-perspective conversations: arguing, checking, revising, and reconciling. They call this a “society of thought.” The claim is that strong reasoning often emerges from structured disagreement, even when the “group” is simulated inside one model. This echoes an older cognitive-science idea: reasoning is not just private calculation but an internalized social process.

From there the authors shift to design. If intelligence is social, then better AI will not come only from larger models or more compute. It will come from building richer agent societies: systems with roles, hierarchy, specialization, parallel deliberation, devil’s advocacy, conflict norms, and institutional checks. Current reasoning models are likened to a single “AI town hall transcript”; future systems may need architectures closer to organizations, courts, labs, markets, or bureaucracies, where different agents occupy different functional roles and constrain one another.

This leads to their main governance argument. The dominant alignment picture, reinforcement learning from human feedback, is framed as too dyadic: a parent correcting a child. That may not scale to worlds containing billions or trillions of interacting agents. The authors propose “institutional alignment” instead: not just making individual agents nice, but designing persistent protocols, roles, audits, checks, and countervailing powers. A courtroom works because judge, attorney, jury, procedure, evidence, and appeal are structured roles; similarly, AI systems will need institutional architectures, not merely tuned personalities.

The concluding image is that the intelligence explosion is already beginning, but as a city, not a single meta-mind. It is visible in human-AI “centaur” workflows, internal societies of thought within models, recursive agent systems that fork and recombine, and emerging questions of constitutional governance among artificial and human actors. Their final message is blunt: the central issue is not whether intelligence will become more powerful, but whether we build social and institutional infrastructure adequate to the kind of intelligence that is actually emerging.

 

AI Is Not an Alien Intruder — It Is the Latest in a Four-Billion-Year Evolutionary Cascade of Symbiotic Transitions

This post is the first of two recursive returns to engage the ideas of Blaise Agüera y Arcas, which were the subject MindBlog posts on 3/13/26 and 3/16/26.  Here is the storyline as organized by Claude sonnet 4.6

Blaise Agüera y Arcas, VP and Fellow at Google and founder of the Paradigms of Intelligence research group, has just published two related books with MIT Press: What Is Life? and What Is Intelligence? (2025). His argument, developed across these books and a series of recent lectures (including a September 2025 Long Now talk and a Harvard Berkman Klein event), is one of the most sweeping attempts to unify biology, computation, and the meaning of AI that I've encountered. Here is the core storyline.

Life as computation — the foundational move

The argument opens with a mid-twentieth-century insight from John von Neumann: any self-replicating system requires a universal constructor (a "machine A" that reads instructions and builds), a tape copier ("machine B"), and an encoded description of itself on the tape. This is exactly the structure of biological life: DNA is the Turing tape, ribosomes are the universal constructors, DNA polymerase is the tape copier. From this, Agüera y Arcas draws the technically serious conclusion that everything alive is a computer — not in the sense that living things are secretly digital, but that the core processes allowing for biological life, namely replication and evolution, are inherently computational processes. Biological computing is massively parallel, stochastic, and distributed, but it is computation nonetheless.

Abiogenesis as a computational phase transition

Rather than treating the origin of life as a singular mystery, Agüera y Arcas frames living systems as a "self-modifying computational phase of matter." His team demonstrated this experimentally with an artificial-life system they call "bff" — a soup of random byte-tapes that, after millions of interactions with no pre-seeded replicators, undergoes a sharp phase transition in which complex, self-replicating programs emerge spontaneously. The implication is that life's emergence from chemistry is not a long-shot miracle but a predictable attractor: wherever the laws of physics permit computation and there is free energy and randomness, replicators will tend to arise because they are more dynamically stable than non-replicating structures. The Second Law of Thermodynamics is not violated, merely locally outrun.

Symbiogenesis over mutation — evolution's real creative engine

Classical Darwinism, in this framework, captures only half the story — the fine-tuning half. Agüera y Arcas argues that symbiogenesis, in which small replicating entities merge into progressively bigger and more capable ones, is a more important driver of evolutionary innovation than random mutation and selection. Evolution's increasing complexity is explained not by random walks through genetic space, but by a hierarchical stacking of cooperative mergers: RNA and metabolism fusing into the first cells; prokaryotes merging to form eukaryotes; cells banding into multicellular organisms; organisms forming social groups. Each such combination produces qualitative leaps that incremental mutation alone cannot generate — the same way a hafted spear is not merely an improved stone point, but something categorically new.

Life and intelligence as the same phenomenon

Perhaps the most radical move is the collapse of the boundary between life and intelligence. Once you have a self-replicating computing device living in a dynamic environment populated by other such devices, selection pressure immediately favors the ability to model and predict that environment — including the behavior of others. Intelligence is not a late-arriving luxury bolted onto life; it comes along with life and is selected for in the same way. Prediction, Agüera y Arcas argues, is fundamental not only to the brain but to life itself. In his most recent lectures he extends this further, making the functionalist claim that free will and even consciousness are not special properties of carbon-based biology but emergent features of any sufficiently complex, self-modeling computational process.

AI as the latest major evolutionary transition

This is where the argument converges on its most consequential conclusion. AI is not an alien intruder. It is the latest instance of the four-billion-year pattern: computational entities entering into new symbiotic relationships, modeling each other, merging, and producing systems that are simultaneously more complex to model and more powerful as modelers. The step from human cognition to human-plus-AI cognition is, on this account, structurally analogous to the step from free-living prokaryotes to the eukaryotic cell — a major evolutionary transition, not a rupture. Understanding and stewarding what comes next therefore requires thinking in evolutionary terms, not in the vocabulary of invasion, alignment against an adversary, or human exceptionalism. The real superintelligences, Agüera y Arcas notes wryly, already surround us: corporations, religions, markets — all are symbiotic cognitive entities that long since exceeded any individual human mind.

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Agüera y Arcas's online book is available in full at whatisintelligence.antikythera.org. His Long Now essay "Life, Intelligence, and Consciousness: A Functional Perspective" (August 2025) is the most concise distillation of his recent updates on consciousness and free will.

 

 

The Refusal to Dehumanize - Rewilding Creativity

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I find it impossible to keep up with the prolific output stream of Indy Johar on Substack, but two recent posts (The Refusal to Dehumanize and Rewilding Creativity) have caught my eye, and are a fascinating read.  I recommend reading them in full. To assist readers wanting a quicker fix I reviewed renderings of the main ideas into a single post by four LLMs (ChatGPT, Claude, Gemini, and DeepSeek) and have chosen ChatGPT's effort to pass on:

We are entering a period in which two seemingly distinct developments—renewed permission to dehumanize and the automation of creativity—are in fact expressions of the same underlying shift. Both arise from a deeper logic that reduces life, mind, and expression into forms that can be processed, optimized, and instrumentalized. What is at stake is not simply ethics or technology, but the conditions under which we recognize life itself.

The first threshold is ethical. Dehumanization is no longer marginal; it is being re-legitimized as a mode of reasoning. Under pressure, systems increasingly treat life as substrate—divisible, calculable, expendable. Violence no longer requires hatred; it becomes administrative, logistical, even efficient. Once beings are reduced to units within models or variables within systems, harm can be justified without moral friction. The danger is not only in explicit acts of violence, but in the normalization of frameworks that require the thinning out of life in order to function. At that point, ethics is not violated—it is bypassed.

This same reduction operates, more quietly, in the domain of creativity. What is currently being automated by machine systems is not creativity in its fullest sense, but a historically specific version shaped by industrial society. Creativity has long been formatted into outputs—legible, repeatable, and exchangeable forms of expression. It has been disciplined into patterns that can be trained, measured, and circulated. Machine learning systems are now absorbing this standardized residue. The unsettling realization is that we have not simply built machines that imitate us; we have already shaped ourselves into forms that can be imitated.

Seen together, these developments point to a common structure: the conversion of life and mind into computable domains. Whether in governance, conflict, or cultural production, the same logic applies—reduce complexity, extract patterns, optimize outcomes. The result is a world that increasingly operates through abstraction while losing the capacity to recognize irreducibility. Human life becomes one instance within a broader field of utility. Creativity becomes one more form of production.

The appropriate response is not defensive—neither a defense of existing political frameworks nor a defense of conventional creativity. Both are already compromised by the conditions that made them reducible. What is required instead is a dual refusal and reconstruction.

First, a refusal of any system that depends on the reduction of life as a precursor to action. This is not a moral preference but a structural boundary: once life is treated as substrate, the systems built on that premise cannot sustain themselves without reproducing harm. To preserve the irreducibility of human life is not exclusionary; it is the condition for any meaningful extension of ethical concern beyond the human.

Second, a rethinking—more precisely, a “rewilding”—of creativity and cognition. This means moving beyond forms of thought and expression organized around output, recognition, and exchange. It implies recovering modes of engagement that are not immediately legible or commodifiable: forms of knowing grounded in embodiment, relation, and transformation rather than production. Such creativity may produce fewer artifacts and more shifts in perception, fewer outputs and more reconfigurations of experience.

This creates a practical difficulty. We are attempting to imagine alternatives from within systems that have trained our perception. The very categories we rely on—creativity, intelligence, value—may be inadequate to what is emerging. The task, then, is not simply to generate new outputs, but to unlearn the constraints that made our cognition and ethics machinable in the first place.

The convergence of these two arguments leads to a single question: can we sustain a commitment to life—its irreducibility, its depth, its resistance to abstraction—under conditions that reward its reduction? If not, then both our ethical systems and our creative capacities will continue to collapse into the same underlying logic of optimization and erasure.

If so, the task is clear. Refuse the reduction of life. Reopen the human as a site of emergence rather than function. And begin building systems—ethical, social, and cognitive—that do not depend on turning living processes into manageable substrate.

The Physiology of Agency in the Age of AI

There is a question lurking beneath the current wave of enthusiasm about artificial intelligence that I think deserves more serious attention than it has received. It is not the familiar worry about job displacement or misinformation or even the alignment problem. It is a more intimate question: What happens to our bodies when the feeling of being the author of our own actions begins to erode?

I have been exploring this question in correspondence with a European reader who follows MindBlog, and his observations have sharpened my thinking considerably. He describes using AI across a wide range of activities — coding, financial analysis, translation, even composing personal emails — and notes that the AI is superior in every domain. His metaphor is a child sitting in the driver's seat of a car, holding the steering wheel and feeling the pleasure of apparent control, while the real mechanics of the vehicle remain entirely beyond reach. What strikes him most is the trajectory: unlike a child who grows up to become a competent driver, our competence relative to AI systems may be on a permanently regressive arc even as our felt sense of power temporarily expands.

I find the metaphor evocative, though my own phenomenology has been somewhat different. Working with Claude Code in the terminal on my Mac Mini, watching lines of code execute faster than I can read them, issuing instructions by voice into a system whose underlying machinery I only dimly understand — I feel less a sense of omnipotence and more a sense of being in the presence of a superior intelligence, with less agency than I previously imagined. It is, as Agüera y Arcas puts it, machines all the way down. My own sense of self is a thin terminal interface over another kind of machinery entirely.

But here is what I think gets missed in most discussions of AI and agency, and where the neuroscience becomes directly relevant. The feeling of agency — conscious will, the sense that an action is genuinely one's own — is not primarily a philosophical matter. It is an evolved emotion, as real and as physiologically consequential as fear, anger, or grief. Daniel Wegner's 2002 book The Illusion of Conscious Will argued compellingly that conscious will is itself a kind of experienced emotion, arising when we perceive our own thought as the cause of our action. It is an emotion shaped by natural selection because organisms that experienced themselves as effective agents in the world — that felt the causal connection between intention and outcome — were better at sustaining the motivational and physiological states necessary for survival.

Martin Seligman's classic experiments on learned helplessness established the other side of this coin with uncomfortable clarity. Animals and humans who experience repeated situations in which their actions have no effect on outcomes do not simply become philosophically uncertain about free will. They become physiologically debilitated. Autonomic dysregulation, immune suppression, motivational collapse — the body reads helplessness as a survival threat and responds accordingly. The feeling of agency, even when it is in some sense illusory, is load-bearing for the whole architecture of healthy physiological self-regulation.

This is why I think my correspondent's observation about "externalization of self-regulation" — when AI begins to carry parts of reflection, emotional modulation, and decision pre-structuring — deserves to be taken seriously as a public health question, not just a philosophical one. If significant numbers of people begin to experience their own actions as no longer fully their own, as outputs of a human-machine loop in which they are more passenger than driver, the physiological consequences could be real and measurable. We identified the toxic effects of social media on adolescent mental health only after the damage was widespread. The agency question with AI may operate on a similar lag.

The more hopeful framing, which I also want to take seriously, is that the emotion of agency can be sustained — and even enhanced — when AI is experienced as an extension of the self rather than a replacement for it. I have felt this at moments: initiating a collaboration, shaping its direction, receiving a result that exceeded what I could have produced alone, and feeling something like Harari's Homo Deus — expanded rather than diminished. The slide rule gave way to the hand calculator, and I felt more capable, not less. Each tool adoption, when the human remains genuinely in the initiating role, can strengthen rather than erode the felt sense of authorship.

The critical variable, I suspect, is not which AI tools we use but how we frame and inhabit the collaboration. A person who experiences themselves as initiating, directing, and ultimately judging the outputs of an AI system will likely maintain a robust emotion of agency. A person who experiences themselves as ratifying suggestions, outsourcing reflection, and choosing among options pre-structured by the system may not. The physiological stakes are high enough that this distinction — between being at the helm versus being more deeply in the loop — seems worth cultivating deliberately, both individually and in the design of AI systems themselves.

My correspondent ended our exchange with a thought I find both unsettling and worth sitting with: perhaps what looks like the erosion of the agentic self is actually adaptation — the emergence of a more networked, process-embedded self better suited to highly organized technological environments. If so, the question is whether the ancient physiological systems that evolved to regulate a bounded, sovereign agent can retune themselves for that new niche, or whether they are simply too slow. That is, in the end, an empirical question. And it is one I think we should be asking urgently.

 

[Note on the generation of this post...The email exchange with a European reader mentioned in the above text was submitted to ChatGPT, Claude, Gemini, and DeepSeek, asking each to sort out and clarify the ideas in our conversation and then generate an appropriate MindBlog post describing them. I curated, edited, combined what I thought were the best passages to end up with the above text, which is mainly Anthropic Claude's version.]

 

From Animal to Humans - Multimodality as a safeguard of honesty in communication and language

I pass on the abstracts of an article by Hex et al to appear in Behavioral and Brain Sciences.  Motivated readers can obtain a PDF of the manuscript by emailing me. The abstracts are followed by a commentary on the article.

Short Abstract
Multimodality characterizes nearly every communicative system, and we argue that this feature of communication plays an essential role in safeguarding signal honesty. We first discuss the importance of honesty in communication, and introduce socially-mediated controls as an alternative to intrinsic costs. We next outline how multimodality mitigates signal dishonesty, and highlight the importance of signal honesty in complex, cooperative species, such as humans, wherein acceptance may incentivize dishonesty. Finally, we urge researchers to investigate the role of multimodality and honesty in cooperative, “cheap” signals, emphasizing the need for comparative work on the forces that have shaped the evolution of communication.

Long Abstract

From spider dances to human language, multimodality is ubiquitous in natural communication systems. Much scholarship has been devoted to investigating why multimodality evolved and the role it plays in communication. Here, we highlight the role of multimodality in safeguarding the most fundamental prerequisite of all functioning, extant communication systems: honesty. We begin by introducing the arms race between honesty and deception in natural communication systems, and the critical role socially-mediated controls can play in maintaining signal honesty when classic, intrinsic costs are not sufficient. We next introduce three ways by which multimodality buffers signal honesty by 1) providing insurance against signal unreliability in dynamic environments, 2) forming an honest, multimodal gestalt with which to cross-validate signal honesty, and 3) increasing signal complexity, making the entire signal harder to fake. We then discuss the case of highly cooperative societies, with human language emphasized, and argue that signal honesty is important especially in complex and cooperative societies wherein the need to cooperate and be accepted as part of the group may supersede honesty. Finally, we
propose future directions wherein human and non-human communication research could expand beyond the well trodden realms of competition and mate attraction to investigate the role of multimodality and honesty in cooperative, “cheap” signals, and emphasize the importance of drawing from both the human and non-human literatures in investigating the forces that have shaped the evolution of communication. 

Commentary on this article from an astute MindBlog reader to whom I had sent the manuscript PDF:

What seems most important to me is this: today the problem is not a lack of signals, but their over-complex, recombinant, socially and technically pre-structured excess.

The article still seems to assume that a receiver can construct a reasonably stable basis for communication by integrating several signal channels. Under many older or more localized conditions, that makes sense. But in digital environments this assumption has become fragile. Signals can no longer be clearly assigned to one sender, one intention, or one context. What reaches us is often already a composite: fragments of persons, group styles, algorithmic selection, platform incentives, packaging, emotional cues, and recombined information.

In digital environments, multimodality increasingly loses the very function the article assigns to it. Instead of safeguarding honesty through cross-validation, it can become a vehicle for more persuasive forms of simulation, because the combined signals no longer arise from one coherent communicative source.

What seems necessary today is not just closer attention to signals, but a layered analytical process. At least two loops are needed: one directed at the immediate communicative act — who says what, in what tone, with what apparent intention — and another directed at the conditions that shape this act: group context, platform logic, aesthetic packaging, and algorithmic amplification. These loops cannot be separated cleanly, because the reading of the content changes the reading of the frame, and the reading of the frame changes the meaning of the content. In more complex cases, even a third loop may be needed, one that takes into account the wider circulation and reuse of the signal across the network.

That is why I think a simple theory-of-mind model is no longer enough. It is not sufficient to ask what a person means or wants. We also have to ask how the contribution is shaped before it reaches us, and how its form already prepares its reception.

This does not make the article less valuable. On the contrary, for me it helped clarify how much harder the problem has become. It is no longer only a matter of checking signals across modalities, but of reconstructing who or what is really communicating through them.

 

Executive Function: Universal Capacity or Schooled Skill?

A recent PNAS article by Kroupin and colleagues challenges one of the most widely assumed constructs in cognitive science: that “executive function” (EF) reflects a universal set of cognitive control capacities. Their data suggest something more unsettling—that what psychologists have been measuring for decades as EF may be, to a substantial degree, a culturally constructed skill set tied to life in what they call “schooled worlds.”

The core of their argument is empirical. Standard EF tasks—card sorting, backward digit span, rule switching—require manipulating arbitrary, decontextualized information. These are precisely the kinds of operations heavily trained in formal schooling but far less demanded in many traditional environments. When these tasks are administered across populations, the differences are not subtle. Children in industrialized, schooled contexts show the familiar developmental trajectory—successful rule switching by age five, increasing working memory span, and so on. But children in rural, nonschooled communities often show qualitatively different patterns: failure to switch rules even at older ages, difficulty performing backward recall, and generally low rates of what researchers define as “canonical” responses. The point is not that these children lack cognitive control in any meaningful sense—they function effectively in complex real-world environments—but that the tasks are measuring a particular style of cognition that develops under specific cultural conditions.

This forces an uncomfortable ambiguity. The term “executive function” has been used to refer both to presumed universal regulatory capacities and to performance on these standard tasks. But the two may not coincide. Either EF names a universal capacity that current tasks fail to measure cleanly, or it names a culturally specific set of skills cultivated by schooling. The data do not allow both interpretations simultaneously. The implication is that decades of developmental curves, policy recommendations, and even clinical assessments may rest on a construct that conflates biology with cultural training.

A brief commentary by Mazzaferro and colleagues pushes back—not against the data, but against the conclusion that we must choose between universality and cultural specificity. They argue that the problem lies in measurement, not in the concept itself. Psychological tests always mix construct-relevant variance with context-dependent artifacts. When a task is transplanted into a different cultural setting without adaptation, it may cease to measure the intended construct at all. The analogy they offer is instructive: one would not conclude that “theory of mind” is culturally specific simply because a Western-designed false-belief task fails in an unfamiliar cultural context. Instead, one adapts the task.

From this perspective, executive function may indeed be a broadly shared capacity—rooted in evolutionary history and observable across species—but its expression and measurement are inevitably shaped by local demands. The solution is not to abandon the construct, but to develop context-sensitive assessments that capture how cognitive control is actually deployed in different environments. A child in a Western classroom uses executive function to manipulate symbols and follow abstract rules; a child in a pastoral society uses it to track livestock, navigate terrain, and manage social responsibilities. The underlying capacities may overlap, but the skills—and the tests that reveal them—do not.

What emerges from this exchange is a deeper point about cognitive science itself. Constructs like executive function are not simply discovered; they are stabilized through particular experimental practices. When those practices are narrowly tied to a single cultural niche, the resulting constructs risk inheriting that narrowness while being mislabeled as universal. The Kroupin study exposes this risk sharply. The Mazzaferro commentary reminds us that abandoning the construct is not the only response—but that rescuing it requires rethinking how and where we measure it.

The broader implication is that cognition cannot be cleanly separated from the environments in which it develops. What looks like a general-purpose cognitive capacity from within one cultural setting may, from a wider perspective, be an adaptation to a specific set of tasks and constraints. The challenge going forward is not simply to refine our measures, but to build theories that explicitly link cognitive processes to the ecological and cultural niches in which they are embedded.

[NOTE:  This post was generated by ChatGPT and curated by Deric] 

 

Against the Machine

I'm using this blog post to archive for myself ChatGPT 5.2's summary of Paul Kingsnorth’s "Against the Machine: On the Unmaking of Humanity"    [In this same vein see N.J. Hagens' article in Ecological Economics. "Economics for the future - Beyond the superorganism"]

Paul Kingsnorth — Against the Machine: On the Unmaking of Humanity
Summary of main ideas and arguments

Core thesis

Kingsnorth argues that modern technological civilization—especially digital networks, automation, and AI—is dissolving the conditions that make human life meaningful. He frames the “machine” not as a literal device but as a civilizational system: industrial capitalism, technological acceleration, and data-driven management of life. This system, in his view, is reshaping human identity, culture, and spirituality into something less embodied, less rooted, and less human.

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1) The “machine” as a civilizational force

• The book treats technology as an ecosystem of power, not a set of neutral tools.

• It integrates markets, governments, and digital infrastructures into one logic: efficiency, scale, control, and optimization.

• Human activities increasingly get redesigned to fit machine systems rather than the reverse.

Kingsnorth sees this as a continuation of industrial modernity, now intensified by digital surveillance, AI, and algorithmic governance.

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2) Disembodiment and the erosion of lived reality

• Digital life pulls people away from physical communities, landscapes, and manual practices.

• Online existence substitutes representation for presence—communication replaces relationship, information replaces knowledge.

• The result is a thinning of experience: life becomes mediated, abstract, and detached from nature.

He presents this as a spiritual and existential loss, not just a social one.

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3) The unmaking of the human person

Kingsnorth’s central concern is anthropological:

• Humans are increasingly treated as data points, consumers, and programmable units.

• Work, identity, and even emotional life are shaped by platforms and algorithmic incentives.

• Technological ideology promotes a vision of humans as upgradeable machines—compatible with transhumanism and AI integration.

He sees this as dissolving older ideas of personhood rooted in place, tradition, and moral responsibility.

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4) Progress ideology and its critics

The book challenges the assumption that technological advance equals human improvement.

Kingsnorth argues:

• Innovation is pursued because it is possible and profitable, not because it enhances human flourishing.

• Environmental damage, social fragmentation, and psychological stress are treated as acceptable costs.

• The language of “progress” masks dependency on complex, fragile systems.

He aligns with a tradition of critics of modernity (e.g., Ellul, Illich, and others) who view technological systems as self-justifying.

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5) AI and automation

AI is presented as the latest expression of the machine logic:

• Replacing human judgment with statistical systems.

• Automating creativity, decision-making, and communication.

• Extending surveillance and behavioral prediction.

Kingsnorth worries that as AI systems mediate reality, people may lose the capacity for independent thought, craftsmanship, and moral agency.

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6) Cultural and spiritual consequences

A recurring theme is loss of meaning:

• Traditional sources of identity—religion, land, craft, kinship—are weakened.

• Digital culture prioritizes speed, novelty, and outrage.

• Humans become uprooted, restless, and perpetually distracted.

He frames this as a spiritual crisis: a civilization forgetting what it is for.

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7) Resistance and alternatives

The book does not propose policy reforms or technological fixes. Instead it advocates:

• Re-grounding in place, nature, and community.

• Recovering manual practices and embodied skills.

• Slowing down and limiting dependence on digital systems.

• Cultivating moral and spiritual traditions that predate industrial modernity.

This is presented as a form of cultural and personal resistance rather than a mass political program.

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Overall interpretation

Against the Machine is a philosophical and cultural critique rather than a technical analysis. Kingsnorth’s position can be summarized as:

• Technological civilization is not neutral.

• It reshapes humans to fit its logic.

• The cost is the erosion of embodiment, community, and meaning.

• The response is not reforming the machine but partially stepping outside it—recovering older ways of being human.

The book fits within a broader tradition of anti-technological or post-industrial thought and is less about predicting the future than about questioning whether current trajectories are compatible with a fully human life.

 

The Future of Being Human

I want to point to Patrick Tanguay's recent Sentiers piece and in particular to Johar's essay.  I asked both ChatGPT and Google Gemini to summarize ideas in Johar's essay , and they came up with interestingly different approaches, which I pass on here. (Gemini, unlike Chat GPT, did not focus on the article presented, but rather more broadly searched the ensemble of Johar's  youtube videos and essays to present an overview of his ideas.)  

From Chat GPT: 

Summary of Indy Johar, “The Future of Being Human: A Critical Complementary Investment Thesis” (2026)

Core premise
Johar argues that the central question of the AI era is not the future of machines but the future of being human alongside them. The aim is not to predict outcomes but to define new categories—social, institutional, and economic—that allow societies to preserve human depth and agency in a world increasingly shaped by predictive technologies.

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1) The machine-shaped environment

• Machine learning is becoming embedded in everyday systems—pricing, access, ranking, and decision-making—so environments increasingly “pre-compose” choices before people act.

• As institutions reorganize around what can be measured and automated, people adapt by becoming more “legible” to systems that allocate resources and opportunities.

• The risk is not intelligence itself but its coupling to extraction, scoring, and behavioral steering, which can erode agency and meaning.

Key claim: abundance of options can coexist with shrinking agency if ends of action are subtly outsourced to algorithmic defaults.

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2) What becomes scarce in an AI world

Johar argues the scarce resource is not computation or data but irreducibly human capacities:

• sustained attention not harvested by platforms

• relationships not immediately transactional

• ambiguity and uncertainty that remain unresolved

• learning not reducible to credentialing

• meaning that develops slowly

• the ability to “become” without premature categorization or scoring

This “nearly forgotten future” is not anti-technology nostalgia but a search for environments that preserve depth and degrees of freedom.

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3) The limits of current responses

The rise of retreats, festivals, and wellness spaces signals demand for non-instrumental connection and presence.

• But they remain episodic, expensive, and easily commodified.

• They function more as temporary relief than structural solutions.

Johar argues the challenge is to move from lifestyle experiences to civic infrastructure that supports human depth in everyday life.

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4) Proposed categories for a “human complement” to AI

A. Rewilding as social infrastructure

Not a return to nature aesthetics, but protection of irreducible human experiences—slow trust, non-transactional relationships, unscored meaning.
These conditions are framed as civilizational foundations for creativity, legitimacy, and social cohesion.

B. Pre-legibility zones / opacity commons

Public or semi-public environments where people can exist, learn, and interact without immediate data capture or identity performance.

• anonymity or pseudonymity allowed

• experimentation without reputational fixation

• spaces for thinking, making, or meeting without surveillance

C. Selective legibility (governance doctrine)

A middle path between total surveillance and total opacity:

• opacity by default

• accountability triggered by events, not constant monitoring

• consent-based identity disclosure

• governance by civic stewards rather than platforms

D. Machine-assisted rewilding

AI should not only extract and optimize; it could also:

• protect attention and privacy

• reduce administrative burdens in communities

• support coordination without constant data capture

• introduce friction against exploitative optimization

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5) Investment and institutional implications

Johar frames the “future of being human” as an underinvested domain:

• markets fund what is measurable and monetizable

• human depth behaves like a public good with long time horizons and governance complexity

• societies need new ownership, financing, and institutional models to sustain it

The thesis: durable value will arise from infrastructures that preserve human agency, not just those that enhance machine intelligence.

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6) Philosophical conclusion

The goal is not to define a final destination but to expand the range of futures that remain possible.

• category formation creates space for experimentation

• societies must prototype environments where people can think, relate, and become without constant optimization or capture

• preserving “unfinishedness” and presence is itself a form of resistance to total legibility

Bottom line:
Johar sees the central task of the AI era as building institutions, spaces, and technologies that safeguard human depth, agency, and meaning—treating them as essential infrastructure rather than private luxuries.

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From Google Gemini:   

In the essay "The Future of Being Human: A Critical Question," Indy Johar explores the profound shift required in our collective consciousness and systemic design to navigate the complex crises of the 21st century.

The main points of his argument can be summarized as follows:

1. The Crisis of "Objecthood" and Separation

Johar argues that our current global crises (climate change, inequality, systemic instability) are rooted in a 400-year-old worldview based on detachment. We have historically viewed ourselves as "bounded autonomous individuals" separate from the world around us. This "objecthood" allows us to treat nature, resources, and even other humans as extractable assets rather than parts of an interdependent system.

2. From "Human Exceptionalism" to Interdependence

The essay challenges the "fiction" of human exceptionalism—the idea that humans exist outside or above the natural world. Johar emphasizes that modern science (epigenetics, microbiome research, ecology) proves we are fundamentally entangled with our environment. He suggests that the "future of being human" involves recognizing that we are not individuals in isolation but a "multitude" in constant relationship with non-human life.

3. The "Noun-Orientation" vs. "Verb-Orientation"

Johar critiques our "noun-oriented" world, where we focus on fixed objects, property rights, and static definitions. He calls for a shift toward a "relational" or "verb-oriented" understanding, where value is found in the flow of care, stewardship, and the quality of relationships between entities, rather than the ownership of things.

4. Reimagining Freedom and Agency

He introduces a radical inquiry into freedom: "What is the freedom to manifest your fullness of being?" He suggests that true freedom in the future won't be the "freedom to consume" or "freedom from others," but the freedom to live in a way that allows the entire "web of life" to flourish. This requires moving away from systems built on "loss aversion" and risk management toward systems built on "possibility" and "expedition."

5. Systemic Redesign ("The Great Peace")

Johar posits that we are at a crossroads between a "Great Destruction" and what he calls "The Great Peace." To achieve the latter, we must intentionally redesign our physical, structural, and psychological systems. This includes:

• Legal Personhood for Nature: Moving from viewing nature as a "resource" to a "person" with rights (e.g., rivers or forests having legal standing).

• Decentralized Capital: Rethinking how currency and value are created to support planetary health.

• Anti-fragile Institutions: Building governance models that can "govern complexity" and adapt to rapid feedback loops.

Conclusion

The essay serves as a provocation to stop trying to "fix" the old system and instead begin the work of becoming a different kind of human. Johar suggests that our current predicament is not just a technical problem to be solved, but a developmental threshold that requires a fundamental shift in how we perceive reality and our place within it.

The Dark Matter Shaping the Human Experience This video features Indy Johar discussing how the systems we design "design us back," expanding on the essay's themes of systemic redesign and the shift in human identity.

 

Venkatesh Rao's 'World Machines'

As usual, I found Venkatesh Rao's writinting in his latest piece "The Divergence Machine" a bit opaque and wordy, so I asked ChatGPT 5.2 to help me out with a condensation and summary, which I archive and pass on to readers here:

Here’s a condensed and clear summary of The Divergence Machine by Venkatesh Rao (Contraptions, Jan 5 2026):

Core Thesis
Rao introduces the concept of the divergence machine as a successor world-machine to the modernity machine explored in his 2025 book club series. The divergence machine’s logic has been built from ~1600–2000 and has fully operated only for about 25 years. It doesn’t reverse modernity but supersedes its organizing principles. Contraptions

World Machines Framework

• World machines are conceptual contraptions that embody how the world orders itself in particular epochs.

• In any period, one machine operates, one is being built, and another may be declining or dying.

• The modernity machine (constructed 1200–1600, dominant 1600–2000) focused on legibility and convergence—making people, systems, and ideas enumerable, interoperable, and canonical.

• The divergence machine rests on a different logic: variety, expansion of differences, and decentralized relationality rather than centralized canonicity. Contraptions

How the Divergence Machine Works

• It does not aim to dismantle modernity directly nor is it just “postmodernity.”

• It takes for granted many effects of the modernity machine (e.g., global connectivity) but operates in spaces where modernity’s centralized canon no longer determines outcomes.

• Its defining move is to make canonicity irrelevant, focusing instead on pervasive diversity and plural modes of being that coexist without unified narratives. Contraptions

Phenomenology and Method
Rao suggests readers filter phenomena through several lenses to see if they belong to the divergence machine rather than to other world processes like:

• Late modernity (zombie persistence of modern norms),

• Postmodernity (reaction/critique of modernity),

• Metamodernity (piecemeal modern revival). Contraptions

Guiding Questions for Divergence
Rao proposes probing events/processes for traits such as:

• Plurality over convergence,

• Relativized canon,

• Generative variety,

• Coexistence without closure,

• Emergent “liveness” not reducible to modern or postmodern categories. Contraptions

Practical Context
This piece sets up the 2026 Contraptions Book Club theme, with readings (e.g., Candide, The Underground Empire, philosophical tensions among Enlightenment figures) intended to explore the formative periods and idea-spaces relevant to the divergence machine’s logic. Contraptions

Big Picture Takeaway
Rao’s divergence machine is a conceptual model for understanding the contemporary world not as a breakdown of modernity but as a phase transition where plurality and decentralized, non-canonical relationality become the driving logic of civilization, distinct from both modern and postmodern frameworks. Contraptions

The Institutional Stance - an evolved intuitive theory?

I have just been sent an article by BBS (Brain and Behavioral Sciences) that is soliciting commentaries on an article by Jara-Ettinger and Dunham titled "The Institutional Stance" that suggests that we have an inherited ability not only to represent other minds, but also to represent social institutional structures. Motivated readers can obtain a copy of the article from me. Here is its abstract:

Human success in navigating the social world is typically attributed to our capacity to represent other minds—a mentalistic stance. We argue that humans are endowed with a second equally powerful intuitive theory: an institutional stance. In contrast to the mentalistic stance, which helps us predict and explain unconstrained behavior via unobservable mental states, the institutional stance interprets social interactions in terms of role-based structures that constrain and regulate behavior via rule-like behavioral expectations. We argue that this stance is supported by a generative grammar that builds structured models of social collectives, enabling people to rapidly infer, track, and manipulate the social world. The institutional stance emerges early in development and its precursors can be traced across social species, but its full-fledged generative capacity is uniquely human. Once in place, the ability to reason about institutional structures takes on a causal role, allowing people to create and modify social structures, supporting new forms of institutional life. Human social cognition is best understood as an interplay between a system for representing the unconstrained behavior of individuals in terms of minds and a system for representing the constrained behavior of social collectives in terms of institutional structures composed of interlocking sets of roles.

The Modernity Machine

I want to pass on to readers this Venkatesh Rao substack essay that summarizes what his book club has learned in the past year: 

The Modernity Machine III

Completion, Saturation, and Phase Transition

This the third and concluding part of my series with notes on the learnings from the 2025 Contraptions book club. Part I and Part II traced the construction of the Modernity Machine between roughly 1200 and 1600: a civilization-scale contraption that converted medieval heterogeneity into legible, interoperable order. By 1600, the machine was complete in all essential respects. This concluding part addresses what such completion actually meant, what the machine optimized for once built, the contradictions it necessarily produced, and why those contradictions could not be repaired from within.

The aim is not to declare the “end of modernity,” but to close out a rough analysis of the machine that took 400 years to build and turn on, making modernity possible, and sustained it for another 400 years, being patched in increasingly fragilizing ways along the way. And also to explore why its very success post-1600 began forcing a slow phase transition to a different kind of civilizational machinery which began to get constructed around 1600, right when the Modernity Machine got turned on. This machine, which I refer to as the Divergence Machine, is being completed and turned on as we speak, even as the Modernity Machine is starting to get decommissioned in bits and pieces worldwide. Here is a teaser picture for the overarching thesis we’re developing here.

The 1600-2000 period and the Divergence Machine that emerged in that period will be the subject of the 2026 book club.

But let’s wrap up 2025 first.

You can catch up on the closing 2025 group discussion in this transcript. What follows is my personal wrap-up.

What the Machine Optimized

The Modernity Machine did not optimize for truth, justice, progress, or freedom—those were its legitimating narratives. What it optimized for, relentlessly and across domains, was legibility: the ability to render people, land, goods, time, belief, and violence enumerable, narratable, and interoperable at scale.

Venice, in City of Fortune, is not interesting because it was rich or republican, but because it functioned as an early, tightly integrated legibility engine: maritime logistics, double-entry bookkeeping, legal abstraction, diplomacy, and intelligence-gathering fused into a self-reinforcing apparatus. Venice: A New History fills in the same picture from another angle: stability emerges not from ideology but from procedural compression.

The horse, in Raiders, Rulers, and Traders, plays a parallel role across Eurasia: a biological technology that collapses distance, standardizes military force, and forces political units to scale or perish. The horse is legibility made kinetic.

Printing, in The Printing Revolution in Early Modern Europe, completes the transition. Knowledge becomes reproducible independent of context. Interpretation decouples from replication. Information density explodes while shared meaning lags behind. The machine acquires a memory that grows faster than any coordinating narrative.

1493 shows the planetary version of the same dynamic. The Columbian exchange is not merely ecological or economic; it is a global synchronization event. Previously isolated systems are forced into a single ledger. The machine’s jurisdiction becomes planetary even as its capacity for meaning remains local.

Seen this way, the Modernity Machine is best understood as a civilization-scale compression algorithm. For several centuries, the gains are extraordinary.

Medieval Baselines

To understand what the machine displaced, it helps to look at relatively pristine end-of-medieval snapshots.

Majapahit offers such a snapshot outside Europe: a highly developed but still recognizably medieval empire, organized around courtly ritual, tributary relations, and localized legitimacy, poised at the cusp of collapse before modernity arrives in force. It represents a world not yet reorganized by legibility, still governed by face-to-face sovereignty and cosmological order.

Within Europe, The Age of Chivalry performs a similar function. Chivalry appears not as romance but as a fully articulated medieval coordination system—ethical, military, and social—already straining under pressures it cannot metabolize. This is medievalism at its most coherent, just before it becomes an anachronism.

These snapshots matter because they show what modernity did not inherit: localized legitimacy, narrative sufficiency, and bounded scale.

The Hidden Outputs

Once the Modernity Machine works, it produces three unavoidable byproducts.

First, excess agency. Feudal bonds dissolve, religious monopolies weaken, markets and cities proliferate. The Canterbury Tales and The Decameron are early catalogs of proliferating voices and moral standpoints. Social life becomes polyphonic. Coordination becomes harder because more people can act.

Second, excess information. Printing destabilizes epistemic hierarchy. By Montaigne’s time, the educated individual is already drowning in books. The Complete Essays read as field notes from the first generation to experience epistemic overload. Skepticism is both a philosophical stance and a coping mechanism.

Third, excess scale. Before European Hegemony and When Asia Was the World make clear that global integration predates European dominance, but modernity hardens integration into permanent structure. Local meaning cannot survive planetary circulation intact.

The machine creates more actors than it can integrate, more information than it can interpret, and more scale than it can narrate.

The Last Gasp of the Medieval

The lesson of Giordano Bruno and the Hermetic Tradition is not that Bruno foresaw modern pluralism. It is almost the opposite. Bruno represents the last exuberant escape of medieval imagination—a crackpot magician and memory-maven operating within an anachronistic misunderstanding of Hermeticism as ancient Egyptian wisdom to hallucinate a worldview of bullshit — indifferent to truth or falsity in any modern empirical sense. His cosmological conclusions happened to resonate sympathetically with Copernican implications, but for fundamentally wrong reasons.

Bruno does not anticipate modernity; he misunderstands it. His fate marks not the birth of a new worldview, but the extinguishing of a freewheeling medieval mode incompatible with both emerging authoritarian modernism, especially ecclesiastical, and scientific empiricism. What survives of his tradition—Rosicrucianism, Masonic esotericism—persists as fringe subculture: culturally influential at times, intellectually irrelevant to the main currents of modern thought.

Bruno is thus not an early modern prophet, but a terminal medieval outlier.

Similarly, Ibn Khaldun: An Intellectual Biography should not be read as the story of a proto-sociologist ahead of his time. That role is largely retrofitted by modern interpreters. In his own context, Ibn Khaldun appears more plausibly as a kind of depressed Arab Petrarch: a brilliant chronicler of decline and defender of tradition, lamenting the absence of an Islamic renaissance rather than inaugurating one.

His cyclical theory of dynasties does not launch a new science of society; it records the exhaustion of an old civilizational form. The importance of Ibn Khaldun here is diagnostic, not genealogical. He documents a world failing to enter the Modernity Machine at all, despite being in possession of many of the necessary components.

Narrative Exhaustion

By the early modern period, narrative itself begins to fail as a unifying technology. Don Quixote stands as the European bookend to The Age of Chivalry. Quixote behaves impeccably within a dead symbolic system, and chaos results. The novel demonstrates that inherited narratives no longer synchronize action with reality.

Journey to the West stages the same problem mythically. The Monkey King embodies pure agency without moral center. Order is restored only through endless improvisation, not closure. This is not premodern innocence but recognition that containment now requires perpetual patching, a condition whose outer story is told in 1493.

Utopia remains the last sincere architectural drawing of the Modernity Machine. It assumes total legibility, benevolent coordination, stable universals, and obedient subjects. Even at publication, it is already obsolete. The social, informational, and political conditions required for utopia to function are precisely those modernity has destroyed in creating itself.

Everything after Utopia is retrofit to a completed civilizational machine, to patch problems that began appearing almost immediately after it was turned on in 1600.

Why Repair is Impossible

By 1600, the machine has crossed a complexity threshold. More law increases rigidity without legitimacy. More reason fragments into disciplines. More planning amplifies unintended consequences. More morality polarizes rather than integrates.

This is not moral failure or intellectual laziness. It is structural. The Modernity Machine generates more differentiation than any universal framework can absorb.

The Modernity Machine does not collapse, but a new logic begins cohering at its periphery. Coordination shifts from top-down design to nudging from the margins — and increasingly, everybody is in the margins. Some just recognize it in 1600, while others are only realizing it now in 2025. Legitimacy fragments. Meaning localizes. Systems adapt without consensus. Civilization continues to function—often remarkably well—while agreeing less and less about what it is doing or why.

This is the phase transition. The machine that made convergence possible gives way to a machine that produces divergence as a default condition.

The Modernity Machine has done its job. What follows is not its negation, but the emergence of a Divergence Machine destined to replace it—a different contraption, hot-swapped piecemeal for its predecessor over 400 years, between 1600 and 2000. Optimized not for legibility and convergence, but for proliferation, adaptation, and coexistence without closure. For divergence.

That is the story of 1600–2000, which we will tackle in 2026.

The picks for the first three months have been posted on the book club page if you want to get a head start. I’ll lay out the thesis in a January kickoff post.