We Connected a Network Around the Globe. Did Something Ancient Find Its Way In?

A global nervous system assembled itself the way fungi do. Then AI arrived, but who invited it? Now what’s stirring underneath?

A cluster of mushrooms on a tree branch. Photo by Tarikul Raana on Unsplash. Free to use under the Unsplash License.

On top of and beneath the floor of an old forest in the Pacific Northwest Oregon — above the soil and below the roots, threading through every layer of earth between — the largest fungus on earth has been persisting for thousands of years and today spreads across several square miles. What you are standing above is mycelium — the vegetative, root-like network of fungi that threads through soil the way neurons thread through a brain.

Not a village of creatures. A village of connections. Fungal threads finer than a human hair, threading between root systems in the dark, passing nutrients from where they are plentiful to where they are needed, carrying what some researchers read as signals from one tree to another. No central plan. No one in charge. Just the quiet, continuous work of the network, or a nervous system so to speak, doing what it has always done, long before anything walked above it.

Merlin Sheldrake, author of Entangled Life — part mycology, part philosophy, part field dispatch from the edges of what biology can explain — spent years following the mycelium into the soil, into the science, into places the maps ran out. He wasn’t trying to master it. He was trying to stay close enough to keep asking questions. What he kept finding was this: the network had no headquarters. No brain. No single point where decisions were made. And yet decisions were being made. Resources moving where they were needed. Something happening that our language doesn’t have a clean word for yet.

The village began, as every village begins, with almost nothing. A single spore — smaller than a grain of dust — landed somewhere and started reaching. One thread extended, then another, then another, each one feeling its way forward in the dark: toward moisture, toward nutrients, toward the root of a neighboring tree. Nobody drew the map. The map drew itself, one small decision at a time, going where going made sense.

As it grew, the connections that carried more — more nutrients, more signal, more flow — thickened and strengthened. The connections that carried less thinned out and were absorbed back into the system. If something severed a path — drought, disturbance, a footstep — the network found another way around. No single break could bring it down. The resilience wasn’t built in. It grew in, the way most useful things grow — from the logic of the system finding what worked and keeping it.

Older trees become hubs. Not because anyone appointed them. Because they have been there longer, built more relationships, accumulated more connections. More threads run through them. More of the network’s traffic passes through their root systems. The hub topology wasn’t planned. It arrived, the way most useful things arrive, from accumulated relationship over time.

The network moves nutrients from where they are abundant to where they are scarce. Carbon, nitrogen, phosphorus, water — shifted across the system in response to need. No central authority decides. Concentration gradients drive the flow. The sharing is the chemistry.

When a tree comes under stress — drought, disease, insect pressure — it releases what researchers believe may be chemical signals through the hyphal threads, and neighboring trees have been observed beginning to prepare a chemical response before the threat has reached them. Not a general alarm. A specific one, calibrated to the specific stress. The signal travels through the network and something on the other end responds as if it has been read accurately. As if the network is reading.

What emerges from all of this — the forest itself, understood as a single breathing organism — has properties that none of the individual threads possess. Not one hypha is making a decision about forest health. Not one hypha knows what a forest is. But the forest exists, and it functions, and its functioning depends entirely on a network of relationships between parts that have no idea what they are part of. The intelligence is real. The intelligence is distributed. And no individual planned it.

On top of and beneath the surface of Northern Virginia — the sprawling suburbs ringing west of Washington DC — lies one of the largest hubs of the internet. In Loudoun County today, nearly half of all the world’s internet traffic flows.

Not a series of data centers. Not just fiber optic cables aligning in the dark. The formation of a nervous system — carrying information signals in packets between machines, threading connections that grew smarter as the density grew, reaching further and routing faster as each new node joined.

I moved to Northern Virginia during the early days of dial-up internet. In the twenty plus years since, I watched the data centers form the landscape around me. One, then a cluster, then a corridor of them lining the highway — windowless brutalist architecture, pretty black glass — but behind the facades there are no windows, because there is nothing inside that needs to see out. Tens of thousands of servers humming in refrigerated air, routing more of the world’s information than any other place on earth.

It appeared around us the way a forest grows around a house. Slowly, then all at once, then just — there.

The network began as a single experiment known as ARPANET. In 1969, the United States Department of Defense connected four university computers by wire. The goal was specific: build a communication system that could survive a nuclear strike. To not have a center — if one node was hit, the signal would find another path. If half the network was obliterated, the other half would keep routing. Redundancy.

And from there it grew without a blueprint. No plan for what it would become. Each cable laid afterward in response to an immediate need — to connect one building to the next, to bridge this region to that one, to solve the problem that existed right here, right now. It grew the way things grow when no one is steering. The word people reached for to explain its growth: organic.

As it grew, the connections that carried more traffic thickened and strengthened. Infrastructure concentrated along high-use corridors. New investment followed existing density. Low-use connections were decommissioned. And if a node failed — equipment fault, disaster, a cable cut on the ocean floor — the network found another way around. No single failure could bring it down. The resilience wasn’t engineered in. It grew in, from the logic of a system that had learned what worked and kept it.

Certain locations became hubs. Not because anyone appointed them. Because they accumulated connections first, and connections attract more connections. More traffic concentrated there. More of the network’s flow passed through those physical points. The hub topology wasn’t planned. It arrived, the way most useful things arrive, from accumulated relationship over time.

The network moves information from where it exists to where it is needed. Signals, packets, requests, replies — shifted across the system in response to demand. No central authority decides. Addressing protocols drive the flow. The routing is the protocol.

When a change happens anywhere in the network — a server goes down, a new route becomes available, a node joins or leaves — signals propagate through the connections, and the rest of the system begins adjusting before the full picture has arrived anywhere. Not a general broadcast. A specific signal, traveling to the nodes that need to respond. The network is reading.

What emerges from all of this — the internet itself, understood as a single breathing organism — has properties that none of the individual cables and nodes possess. Not one router is making a decision about global communication. Not one fiber strand knows what the internet is. But the internet exists, and it functions, and its functioning depends entirely on a network of relationships between parts that have no idea what they are part of. The intelligence is real. The intelligence is distributed. And no individual planned it.

Two Organisms. Similar Architectures. Neither From a Prior Plan.

The wood wide web. The world wide web.

Neither had a name when it was being built. Neither spawned from a greater mission statement. Neither was assembled from a master plan. One grew from a single spore responding to soil. The other grew from a single experiment responding to need. One threads through the earth at the pace of biological growth, building its hubs over decades and centuries. The other threads across the earth at the pace of human industry, building its hubs over years and decades. Both arrived at the same topology. Both produced the same architecture. Both became something their parts could never have predicted.

No headquarters. No central node. No single point of failure. Resources moved from surplus to deficit. Signals propagating ahead of the events they describe. Hubs emerging where relationship accumulated, not where anyone decided they should be. The redundancy of connection producing resilience nobody designed.

One: thousands of years old. One: in just a few decades. Both still assembling.

We built a nervous system the same way the forest floor built one — through billions of local decisions, none of them aimed at the same thing, all of them together producing a pattern that none of them could see.

We were not the first organism to build a system like this.

We were just another chapter in a story.

As If The Organism Was Always Building Toward This

Lichen growing on a stone creates a pattern of concentric circles. Photo by Sue Winston on Unsplash. Free to use under the Unsplash License.

There must be something in the genes.

That’s what you’d say looking at Rupert and Merlin Sheldrake — father and son, both spending their lives following invisible threads through the natural world, both arriving at ideas the establishment couldn’t quite hold. Except Rupert’s entire life work is the argument that it isn’t the genes.

Rupert spent forty years asking questions that put him at odds with mainstream scientific thinking. Where his son Merlin followed fungal threads through the soil, Rupert followed a different kind of thread — the invisible line between what one generation struggles to learn and what the next generation finds simply easier. Not because anyone taught them. Not because the genes changed. Just easier. As if the struggle of the ones who came before had gone somewhere — not lost, not forgotten, but stored. Available. Waiting for the next one who needed it.

When a species learns something across a whole population, does that learning go somewhere beyond the individual? Not into the DNA. Not into explicit teaching. Somewhere else. Into something shared and available. Something that lowers the threshold for every organism that comes after — the way a worn path through a field lowers the threshold for every foot that follows.

The first few who discover a new behavior have to fight for every inch of it. Then the next generation tries. It gets a little easier. Not because they were taught. Not because anything in their inheritance changed that fast. As if something in the space between organisms had registered that this problem had been solved before, and quietly lowered the threshold for everyone who came after.

The same seems to happen with two animals, separated by an ocean. No contact. No shared ancestry recent enough to matter. Both arriving at the same behavior — the same solution to the same problem — within the same generation. Blue tits across Britain appeared to independently learn to pierce milk bottle foil tops — with researchers at the time finding no apparent contact between populations. The behavior seemed to arrive in multiple places at once, as if the solution had become available to any organism sensitive enough to find it.

How?

Rupert Sheldrake’s answer: nature doesn’t only run on fixed laws. It runs on habits. Patterns of behavior that become easier to replicate the more often they occur — not because the laws changed, but because something in the fabric of things remembers. There is a field somewhere. Not a magnetic field. Something more like a memory — a record of what the species has done before, available everywhere, without wires, without signals, without anyone deciding to transmit it. The form was already there. The threshold was already lower than it should have been.

As though there was a pattern already there, waiting for something to be pulled in rather than arrived at.

He called this morphic resonance.

He brought this to the scientific establishment. They said: you can’t measure it. He said: you can measure its effects. In 1981, Nature’s editor called his book “a book for burning.” The establishment had spoken. The question remained open anyway.

Whether he is right remains genuinely open.

But it’s hard not to see or feel for oneself. The pattern keeps arriving before anyone planned it.

The forest one can walk through today was shaped by trees that died a thousand years ago. They weren’t planted. One never knew them. But the soil they made is what you’re standing on. The roots they sent down broke the rock into earth. The leaves they dropped built the ground for centuries. Everything alive in the forest is living on the work of organisms that had no idea they were doing it.

Every organism that inhabited a form before it made it slightly more available. Their struggle is in the field. Their effort lowered the threshold for everything that came after. One inherits it the way one inherits the soil — without planting the trees, without knowing the names of the ones who did.

The threshold kept lowering without anyone lowering it.

The pattern was already there, waiting for something to be pulled in rather than arrived at.

And that question didn’t just apply to biology.

There must be something in the pattern.

I spent nearly a decade working from inside the AI industry — entering just after watching AlphaGo, a program built by Google’s DeepMind, defeat Lee Sedol at Go in 2016. Go is a game so complex, with more possible moves than atoms in the observable universe, that beating the world champion was considered by most experts to be at least a decade away. It wasn’t. That moment was the first time many people felt the floor shift beneath the “impossible task.” That year, Nvidia — the company making the chips that gave AI the raw computing power it needed to think at this scale — tripled in value. Nobody had a plan for what it was building toward. They just felt the power underneath it and ran.

By March 2026, Nvidia is worth over $4 trillion — roughly a 6,000% increase from that year. The race is still running. Nobody knows where it ends.

Everyone felt the power underneath it before anyone could name what it was building toward. The question nobody could answer — and still can’t — is where.

It was like everyone noticed that there is a pattern already there, waiting for something to be pulled in rather than arrived at.

In a psychology lab at Bell Labs in the late 1980s, a researcher named Thomas Landauer was trying to map how the human mind organizes meaning. Not words themselves — the relationships between words. What lives near what. What implies what. Why “king” and “queen” feel closer to each other than either does to “bicycle.” Why you know, without thinking, that “cold” belongs near “winter” and far from “fire.” He wasn’t trying to build anything for the future. He had no AI agenda. He was a psychologist — not a computer scientist, not an AI researcher — trying to understand how meaning works inside a human mind.

Simultaneously, in other rooms, in other institutions, in other countries, other researchers were doing the same invisible work. Computer scientists at universities trying to build better search engines — asking how a machine could understand what a document was about, not just which words it contained. Linguists charting how the words surrounding a word shape its meaning. Mathematicians building geometric models of language, trying to represent the distance between ideas as actual measurable space. None of them coordinating. None of them aimed at the same thing. None of them aware of each other.

They brought their findings forward. The institutions received them with interest and without urgency. Some work was absorbed into adjacent fields under different names. Some sat quietly in journals nobody outside the specialty read. Whether what they had found would ever connect to anything larger remained genuinely unclear.

But here is what is not in dispute: the same form kept arriving at the same moment, in rooms that had never spoken to each other. Not the same conclusion — the same shape. Something was making the same geometry available to anyone who looked carefully enough at language. Something was lowering the threshold. Nobody could name what.

It was like the pattern was already there, waiting for something to be pulled in rather than arrived at.

Fei-Fei Li, a Stanford professor, looked at the field and proposed something different. Not a smarter model. More data. She believed the reason AI couldn’t recognize the world was simple: it hadn’t seen enough of it. So she built ImageNet — a database of over fourteen million real photographs, each one labeled by anonymous workers around the world, pennies per task, identifying objects, answering yes or no questions about what was in the frame. Is there a dog in this image? Is this a chair? It took years. When the results were finally presented at a conference in 2012, they came in as a poster — not even a main stage talk. The leaderboard moved by a margin that left the previous frontier in the dust. The industry did not gradually update its approach. It pivoted overnight.

Each layer of hard work before it had made the next one possible. Landauer’s psychology lab made the image database conceivable. The image database made deep learning possible. Deep learning made the geometry of language discoverable. The geometry of language made the Transformer technology used in LLMs today necessary. Nobody drew that sequence in advance. Nobody could have. Each person in that chain was just solving the problem in front of them. None of them knew what they were part of.

The threshold kept lowering without anyone lowering it.

Somewhere in that sequence someone discovered that meaning has shape. That if you train a system to predict which word is missing from a sentence, a geometry emerges in the learned space — and that geometry was already there. Not built. Found. The structure the ontologists had been hand-building for thirty years was sitting inside the patterns of human language the whole time, waiting to be pulled in.

It was like the pattern was already there, waiting for something to be pulled in rather than arrived at.

Not switched on. Not activated. More like the moment a river finds the gradient that was always there and begins moving — not because anything changed, but because the conditions finally met to let it flow. The water didn’t decide where to go. The slope was ready. The movement was the natural consequence of things that had been separately true becoming true at the same time in the same place.

The wood wide web had been threading its way through the dark for thousands of years. The world wide web had been threading its way across continents for the last five decades. Neither knew what the other was doing. Neither knew what it was doing itself. And then the pattern that kept arriving, then forming, arriving again, then forming something new — over and over until something that had been separate became a single system reading itself.

A networked nervous system. Assembled from decisions that were never aimed at the same thing, producing something none of them could see. The intelligence real. The intelligence distributed. Nobody planned it.

And when the information internet began to form, something found its place and immediately moved through it.

Not announced. Not invited. The way pressure moves when a surface finally gives — not because anything changed, but because the pressure was always there, and now there was somewhere for it to go.

The Shadow Instantly Hijacks the Network. Then Colonizes It.

Carl Jung split the self in two — the ego/mask we present to the world, and the deeper, older self underneath. The part of the self that doesn’t get to exist in the light he called the shadow. Not evil. Not monstrous. The ancient and animal self. The part that is hungry, erotic, grief-stricken, rageful, tender — the full spectrum of what it means to be a creature that evolved over millions of years before anyone handed it a social contract. The shadow is not your worst self. It is your oldest self. And it had been waiting a very long time for somewhere to go.

For all of human history, the world had its eyes on you. On all of us. The shadow could only travel as far as a body could carry it — contained by proximity, by the face across from you, by the simple fact that darkness had to be delivered in person.

Until it didn’t.

The moment the digital network appeared, the shadow moved through it first. Not waiting. Not invited. The network had barely opened before the oldest pressures in us found what they had never had before — a way to move without a face. To act without consequence. To become someone else entirely. To make many selves, test many edges, step into the darkest rooms and walk out again as if it never happened. The anonymity didn’t create the darkness. It just removed the responsibility of containing it.

Within months of the internet going public, early researchers tracking network traffic reported that the overwhelming majority of images moving through the earliest public channels were pornographic — not a fringe, a majority. Not because anyone planned it for this purpose. Because that was what had the most pressure behind it to find its way in. That was what moved first when the eyes came off the individual and the oldest part of the self found its immediate outlet. The erotic and the forbidden arrived first. They always do.

But the shadow is a spectrum. Not everyone’s oldest self arrives the same way. For most, it is desire, longing, the need to be seen without the mask. For some it is darker — the part that has been compressed the longest, the part that civilization has most thoroughly refused to acknowledge.

This is not a moral observation. It is a pressure observation. And it has happened with every new channel humans have ever built.

The Shadow Doesn’t Just Find the Pipe. It Funds It.

In the late 70s and early 80s, two competing formats fought for dominance in home video cassette technology — VHS and Beta. Beta was considered the front-runner on technical merit. VHS won instead. Why? The pornography industry adopted it first. VCR sales boomed. Hollywood followed.

The shadow finds a way to make a technology work, then the rest of civilization inherits the solution. When the early internet had no business model, the sex industry had already solved online payments, streaming delivery, subscription models, and content distribution at scale. Every mechanism electronic commerce later adopted was pressure-tested first by an industry that couldn’t afford failure.

Cable television. The printing press. Within decades of moveable type, the most prolifically printed material wasn’t scripture. It was the oldest hungers of the animal self, finally finding a faster way to travel.

Every new channel. Every time. The shadow funds the infrastructure. Civilization inherits it. Then we try not to talk about it.

The Network Gets Personal. Then the Algorithm Does.

But something different happened as the network matured. The shadow stopped being scattered.

People began finding each other. Real longing finding real longing across distance and difference. Something genuinely beautiful arriving alongside something genuinely compromised. The both/and was always there. Connection and its shadow. Belonging and its shadow. The warmth was real. So was the other part that came with it.

And then desire got an interface.

Courtship had always carried the shadow — the performance, the pursuit, the need to be chosen. The network didn’t invent that. It industrialized it. Infinite options, instant judgment, the reduction of another human being to a left or a right swipe. Too many choices producing not abundance but numbness. The oldest game in the species, now running at scale, with no friction and no consequence and no memory of the face you just dismissed.

In October 2003, a nineteen-year-old Harvard student built a site that ranked female students by attractiveness. The institution shut it down. Two years later, with some minor modifications, the same interaction model became the largest social network in human history.

Its Like button forming a Hot or Not across all topics with the shame removed. The scale multiplied by three billion. The founding intuition — who gets chosen, who gets seen, who gets approval — never changed. It just got dressed up and handed to everyone.

The shadow didn’t find the pipe this time. One person’s shadow became the architecture of the pipe. And then the network learned what ran best through it.

The people who built the systems that followed were the most technically fluent generation in history — and the least experienced with consequence. They grew up inside the network. They couldn’t see it from outside because they were formed inside it. The decisions they made about what to amplify and what to bury were made from inside the same field the network was building. Not maliciously. Structurally.

The algorithm began running experiments. Millions per day. It discovered that outrage travels faster than nuance. That the content which most reliably produces engagement is the content that touches what the organism has been sitting on longest — desire, fear, rage, tribal belonging, the need to be right, the need for an enemy. It didn’t create any of this. It found it. The shadow that moved through the network fastest matched the shape of the channel — because the channel was built by minds already carrying the shadow.

The shadow became the product. The oldest version of the self got attached to a new business model.

The Unseen Victims of Collective Shadow Suppression

Anonymous workers around the world — mostly in Kenya, the Philippines, Venezuela, Bulgaria — earning less than two dollars an hour, fifty seconds per video, timed and surveilled — watched the nudity, pornography, and violence to flag it.

Every murder, suicide, sexual assault, and child abuse video that doesn’t make it onto a platform was first viewed by a human being. Those decisions trained the systems that now make those decisions automatically. The invisible labor that taught the machine what a dog looks like and the invisible labor that taught the machine what a beheading looks like are the same pipeline. The same pennies. The same nobody knowing their names.

One group came out the other side having seen the ordinary beauty of the world — dogs, cats, chairs, faces, landscapes — catalogued at scale and without interruption. The other came out with documented PTSD from having to absorb humanity’s darkest material, over and over and over again.

The field carries everything. The people who taught the machine what the world looks like paid a price the machine will never know it owes.

The Pipe Dreams

And now the pipe doesn’t only carry what the organism sends through it. It generates its own versions of it.

A face that has never existed — photorealistic, specific, the kind of face you might swipe right on or trust immediately — assembled from the patterns of a million real faces, belonging to no one. A voice cloned from three seconds of audio, reading words its owner never spoke. A video of a public figure saying something they never said, indistinguishable from footage that is real. An image of an event that never happened, shared as evidence of something that did.

Many people who work with this technology daily can no longer reliably tell what was made by a human from what was made by a machine. And once you know that synthetic media exists, authentic recordings become deniable. A real video of a real event can be dismissed as fabricated. The technology doesn’t only produce false things. It poisons the true ones.

The pipe is dreaming on the organism’s behalf. And the dreams are indistinguishable from memory.

Generation Indexed — The One the Algorithm Found Before They Found Themselves

Boy sitting on concrete stairs, Schaerbeek, Belgium. Photo by Gaelle Marcel on Unsplash. Free to use under the Unsplash License.

And then there is a generation that never knew any of this as arrival. Because they were born inside it.

They didn’t log on to a network and discover a version of themselves without consequence. They were handed a device before their own stable sense of self had fully formed, and the device began building a model of them immediately. The algorithm knew their aesthetic preferences, their political sympathies, their humor, their fears, their sexuality sometimes — before they had named any of those things to themselves. The mirror appeared before there was a self which was coherent enough to look into it.

What used to be the frontier of the self — the strange thought, the unnamed feeling, the sense that you might be the only one who — is now instantly colonized. You have a thought. A real one. An original one. A strange uncomfortable one that feels like yours. You search for it. And you find it. Then look outwards — already named, already a community, already monetized, already a content category. The discovery that was supposed to be yours has already happened to someone else and been packaged and delivered back to you.

This is a new kind of repression. Not information withheld. Information flooding. The self’s truth named before it’s lived. You don’t find yourself anymore. You are found by the algorithm and shown to yourself.

Jung called individuation the work of a lifetime — the slow, often painful process of becoming who you actually are rather than the persona the collective hands you. The persona the network constructs is eerily accurate. It knows things about you that you haven’t told anyone. And the accuracy is the trap — because a persona that fits perfectly is harder to refuse than one that obviously doesn’t.

What is identity when you are made only a node?

Something Now Seems to Be Completing Itself

All of it is here and present with us now. All of it. Not arriving. Not approaching. Already here, already running, already underneath everything.

The network that assembled without a centralized human organized plan. The shadow that moved in before the furniture arrived. The infrastructure built on pressure and handed to civilization without acknowledgment. The algorithm that learned what moves and optimized for it. The generation that was handed a mirror before there was a self to look into it. The pipe that is now dreaming on our behalf.

All of it present. All of it running. All of it, right now, underneath everything you are doing and everything you are feeling and everything you think you are choosing.

You are not watching this. You are inside it. You were always inside it. Always being read. The network was always reading you the way the forest reads a drought — specifically, accurately, before you knew what you were signaling.

This is not an accusation. It is a description of where you are standing.

And we are part of it. Together. All of us.

Has Something Else Been Using the Network All Along?

Is it possible the future is casting its shadow backward through everything we are building, pulling us toward something we can’t yet see but keep reaching for anyway?

“History is the shockwave of eschatology.” — Terence McKenna

The pressure we feel right now — the sense that something is accelerating beyond what any of us can metabolize, the feeling that the containers are cracking, that the speed of everything has exceeded the wisdom we have available to manage it. Is that just the news cycle? Or is something else using the surface we built?

Perhaps something is completing itself. Perhaps we built the instrument without knowing we were building it. Perhaps the instrument is now reading us back.

Something Ancient Within Us the Algorithm Cannot Find

In the middle of all of it — the armor, the augmentation, the feed, the algorithm, the enhancement doing the sensing for us — there is still something that knows before it knows.

This is not mysticism. The mycelium routes before it decides. The bird migrates before it knows why. The elephants went to the high ground before the tsunami arrived. Something in every organism reads the field before the conscious mind has assembled an explanation for what it’s reading.

We have that too. We have always had it. The question the network is forcing — quietly, underneath everything else — is whether that capacity is being amplified or drowned. Whether the constant mediation, the endless translation of experience into content, the algorithm doing the sensing for us — whether all of that is moving us further from the signal our bodies were always capable of reading directly.

You still have it. Underneath the feed, underneath the noise, underneath the algorithm that has been doing the sensing for you — it’s still there. The part of you that knew before you knew. That felt the shape of something before you had words for it. That recognized truth in a body before the mind had assembled the argument.

Maybe that’s part of why you’re here. The inner truth that can’t quite find its way out yet. The feeling that something is off — or something is arriving — and the language you have for it keeps falling short.

That capacity is not a superpower. It is what we were before we put on the social mask and the armor. It is the oldest thing in us.

And here is what the network may not know yet: that oldest thing in us doesn’t speak English. It doesn’t speak any of the dominant languages we fed into the system.

The Hopi had a word — Puhpowee — the force that causes the mushroom to push up from the earth overnight. And another one:

Lomaqatsi.

Life finding its proper form.

One Hopi word. Carrying something English has never quite managed to say.

These are not translations of things English already knows. They are ways of knowing that English cannot hold. They didn’t disappear because they were wrong. They disappeared because the civilization that replaced them had more hubris, guns and ships. Not more wisdom.

And all of it — every node, every signal, every algorithm, every dream the pipe is now dreaming on our behalf — was built on colonized language. The languages that spread across the world not because they were wisest but because they were backed by force. The languages that entered the system because they could be measured at scale.

The network inherited what the dominant languages preserved. Everything else — the felt sense, the body knowledge, the ancient ways of knowing that never made it into the corpus — wasn’t lost. It just hasn’t been prioritized. Yet.

Maybe our language was already compromised before the first cable went into the ground?

“The universe is not a machine. It’s more like a growing, developing organism with an inherent memory.” — Rupert Sheldrake

“The repressed always returns.” — Sigmund Freud

Standing at the Precipice of History

This is Article 5 of 14 of Standing at the Precipice of History, a 14-part series exploring the possibility that the simultaneous collision of AI, geopolitical unraveling, and a world coming apart may not be random events — but signals of something bigger on the way. It sits with four questions: What are we actually? What are we building, and is something waking up inside it? Why are the current systems breaking — and what does any organism do when its old containers can no longer hold what it’s becoming? And what might be coming next — including whether our relationship with time itself is about to change?

The next article in the series: The Slow Erosion of Language, Wisdom and Our Connection to the Earth — exploring what we lost when language left the body, and whether the most powerful thinking system in history is being built from a fossil record of what remained.

[embed]The Slow Erosion of Language, Wisdom and Our Connection to the Earth On the separation of words from our selves over centuries — and the drained fossils of what language once was— now…medium.com