The Quiet Exodus

An ancient story reemerges underneath the AI vs. Humans noise, and it’s causing deepening, widespread damage across organizations. And it’s not what you think.

While the ‘quiet quitting’ movement has been largely boomeranged into the AI-fueled Fear of Becoming Obsolete (FOBO), a different and far more damaging dynamic is already in play: a quiet, rising tsunami of organizational knowledge and capability loss.

The characters and scenarios in this article introduction are composites drawn from real conditions across the utilities industry. Names, organizations, and identifying details have been fictionalized.

Jim Stafford had difficulty falling asleep that night, with the howling wind whipping the rain sideways on his house. Another ‘atmospheric river’ hitting the Pacific Northwest was causing local flooding and miserable moods.

So when the call came at about 1:30 in the morning, Jim bolted upright out of deep sleep while his brain struggled to catch up as he grabbed the phone to answer the emergency call. His heart thumped because he knew what it meant.

Jim has been with the utility company for thirty-one years. Starting as a trades apprentice in 1995, he later earned his journeyman ticket on a distribution crew upstate, and spent a decade on transmission line maintenance. He then worked on line buildouts for over a decade running power through mountains and valleys into new communities. With that kind of skill set, Jim with his small crew became legend: the high-wire tower jockeys.

But it’s a demanding, complex and risky job, one of those positions that burns people out sooner than most. Now, Jim is only one of two people left in the entire organization who can look at a tower drawing from 1972, cross-reference it against five decades of modifications, field repairs, and parts inventory, and understand what’s failed, what’s needed, and whether it still exists. The other guy is Dave Olsen, who is on vacation in Mexico this week.

One of the Tower 6 foundations on the Greenfield line gave way with the torrential flooding, dissolving the underlying clay and gravel, and now it’s leaning about 45 degrees into the treeline, held in place by the transmission lines and what’s left of the other foundation legs.

Shit, Jim thought, as his hands trembled, throwing instant coffee into the thermos and filling it with boiling water. This is going to be a long night. Actually, a long couple of weeks at least.

Events like this are rare, but when they happen the consequences are catastrophic if not dealt with quickly. A tower at that angle is being held up by the very lines it’s supposed to carry. If it keeps settling, the conductors drop toward the treeline and the saturated ground, and you’re looking at a wildfire ignition, a cascading grid failure, or both. And every minute it stays like that, the load transfers to the adjacent towers, threatening to turn one failure into three.

As Jim threw his knapsack into the truck and climbed behind the wheel, he thought, I’m getting too old for this.

Jim will most likely join the growing wave of early retirees within a few short years, or perhaps even months after this latest crisis. The returns of the job are diminishing, along with his aging body and peace of mind. This job isn’t easy on the body, or a marriage.

Increasingly, Jim will be looking to plan for a cabin by a lake, a small townhome near a golf course in Palm Springs, or eyeing up a nice Airstream he can hook up to his truck and hit the open road to explore the country. And maybe even a small business he can run from anywhere.

What he leaves behind is a vacuum: hollowed out organizational capabilities, person-by-person, skill-by-skill, team-by-team, department-by-department. Workforces are dissolving at the deepest experience levels, and the speed of dissolution is increasing. Companies are losing knowledge and expertise gained over decades.

This is The Quiet Exodus.

The cross-industry physical workforce is the bleeding edge of this loss. Replacement of knowledgeable, skilled workers is not materializing at the pace required to maintain organizational effectiveness.

For example:

In Jim’s industry, nearly half of the current power sector workforce will retire within the next decade. Roughly 45% of experienced linemen are projected to retire within the next ten years, and even top training programs report applicant-to-seat ratios as high as 10-to-1. Even non-retirement turnover has increased significantly in recent years.
Healthcare is no better. Over a million nurses in the U.S. are projected to retire by 2030, with more than 50% of RNs currently over age 50. More than 40% of physicians will reach retirement age in the next decade, and Mercer projects 6.5 million healthcare workers will exit by 2026 with only 1.9 million replacements expected. A charge nurse with twenty-five years on an ICU floor carries a mental model of patient deterioration patterns, physician preferences, equipment quirks, and staffing dynamics that no orientation manual can replicate.
Construction mirrors the pattern: current projections are that 53% of the construction workforce is expected to retire in the next decade. The pace of younger workers entering the trades is not keeping up with retirements, resulting in a growing skills gap that reduces the mentorship opportunities available for new workers to learn directly from industry veterans. The structural steel ironworker, the high rigger, the crane operator working on office tower construction: these are roles where judgment is built through years of physical repetition in high-consequence environments. You can certify someone to operate a crane. But how do you teach them the instinct from a thirty-year operator that wind conditions at 400 feet are about to shift based on how the cable is behaving?
In water and wastewater treatment, we have perhaps the most alarming trends of all. Between 30% and 50% of the water sector workforce will retire in the next decade, and a Brookings Institution analysis found that 88% of treatment plant operators were aged 45 or older, compared with 45% nationally. Small water system operators are often the system record keepers and have extensive system knowledge that may not be written or stored anywhere but in their own minds. A sudden retirement, illness, or extended leave has the potential to significantly impair system operations. And the anecdote that captures it all: a workforce development specialist encountered a water treatment operator who was still working at age 90 because of the challenge of finding someone else to step up.

Starting in 2011, the leading edge of the boomer generation began retiring, heading into the sunset with often decades of seasoned, critical organizational knowledge, with no effective way to capture it. Then COVID hit and The Great Resignation turned the trickle into a flood, expanding into the mid-career workforce as the ‘quiet quitting’ movement blossomed.

Now, there’s a rip-tide of forces at work. Against the backdrop of widespread layoffers, tech workers are rapidly shifting their cognitive modes from the logical frameworks of manual coding to the nascent art of agent orchestration. Quiet quitting has been replaced by AI Job Apocalypse fears. And ironically, it’s this fear of AI-driven job loss, rather than actual job loss, that is compounding the trend:

A Harvard Business Review analysis based on a survey of over 1,000 global executives found that AI layoffs are driven almost completely by anticipation of AI’s impact, not its current performance.
Employer-disclosed AI-attributed layoffs totaled about 55,000, but modeling-adjusted estimates place actual AI-displaced positions at 200,000 to 300,000, roughly 0.13% to 0.20% of total US nonfarm employment. Even at the high end of the estimates, that’s only a fifth of one percent of the workforce.

Meanwhile, the undercurrents of the Quiet Exodus, on the order of millions per year, continues to grow. The clock is ticking, with no structural framework in place to fill the gaps in time to avert a fundamental, widespread erosion of operational readiness and capability across the economy. The knock-on effects include an ever-widening competitive gap between us (meaning North America and Europe) and the rising Asian economies led by China.

At the same time, business leaders are distracted with trying to patch the holes with agentic AI projects, largely trained on documentation and training assets. These initiatives often fail to meet objectives because the underlying premise completely misses the problem space: operations do not depend on user guides and operating manuals. Operations depend on the ‘tribal’ or tacit knowledge and skills in the minds of the people running things in the real world. But this center of gravity that has always held the organization together is slipping away.

Whether by exhaustion, management indifference, or fear of future replacement by AI, the majority of the mature workforce is quietly planning to join the Exodus, while business leaders order more AI and HR plans exit interviews and retirement cake, if that.king plans to join the Exodus, while business leaders and HR plan exit interviews and retirement cake, if that.

For his part, Jim is already mentally preparing for the next phase of his life. It’s well earned. He gave a lot of years to the company, and he enjoyed his work, for the most part. Yet, as he drives the two-and-a-half hours to the site in the driving rain, he wonders who will be sitting in this truck in the middle of the night a year or two from now. He can’t for the life of him think of anyone else in the company other than Dave who can. And Dave has his own company truck.

In Part 2 of the three-part series, we’ll look at what the Quiet Exodus means when it reaches the hospital ward, where the consequences aren’t measured in grid failures, but in lives.

Chris Dollard is Founder and CEO of RoleUp, a platform for capturing, preserving and animating human-layer organizational knowledge. LinkedIn.

The Human Layer

The article discusses the critical gap between documented procedures and actual workplace practices, known as “tribal knowledge.” As AI systems are implemented in enterprises, they risk executing tasks based on incomplete information, leading to significant failures. To succeed, organizations must recognize and integrate human contextual judgment into AI deployment or face detrimental consequences.

Why Agentic AI Will Fail Without the One Thing It Cannot See

There’s a dirty secret in every enterprise on the planet, and everyone who works in one knows it. The documentation is wrong.

Not wrong like a typo. Wrong like a map that’s missing 30 to 50 percent of the territory. Wrong in the way that matters most: the procedures manual says one thing, and the people who actually run the place do something quite different. They’ve always done something different, because the real world is messier than any document can capture, and humans are brilliant at adapting to mess.

After spending over 20 years in technical documentation, I’ve seen this as the norm. Even with the tremendous time and effort it took to create user manuals and developer guides, we knew that the documents were 99% of the time left to collect dust on the shelves.

This has been true since the first org chart was drawn on a napkin. It wasn’t a crisis. It was just the way things worked. The gap between what the documentation said and what people actually did was filled by experience, intuition, sticky notes, whispered hallway conversations, and that one person in accounting who somehow knew how to make the quarterly close actually close. We called it “tribal knowledge” when we bothered to name it at all.

For fifty years, nobody needed to fix this because humans were always in the loop. They were the loop. The documentation was a rough sketch, and people colored it in every day with contextual judgment, improvised workarounds, and the kind of hard-won expertise that takes years to build and seconds to lose when someone walks out the door.

And then we invited the machines to the table.

The Moment Everything Changed

Goldman Sachs recently revealed they’ve embedded engineers from Anthropic (the creators of the Claude AI) directly into their teams to build autonomous agents that handle transaction accounting and KYC compliance. Work that previously required armies of junior accountants and compliance officers is now performed by AI.

The financial press called it the “SaaSpocalypse.” Software stocks cratered. Nearly $300 billion in market value evaporated in 48 hours as investors realized that if AI agents are the primary users of enterprise software, the entire seat-license business model is dead.

But the real story isn’t about software stocks. The real story is what those AI agents are not being told.

Goldman’s agents are executing complex, rules-based labor using documented procedures. They’re reading the manual. And as anyone who’s worked in compliance knows, the manual is a polite fiction. The real work of KYC is knowing that a particular wire transfer is fine because the client is mid-merger, sensing that a flagged transaction pattern is actually routine for that industry segment, understanding which escalation paths actually work at 4:47 PM on a Friday. None of that is in the documentation.

It lives in the heads of the people who’ve been doing the work for years. It is the human layer.

Right now, Goldman has a human-in-the-loop model: one person auditing the work of ten AI agents. The narrative is that this is responsible AI deployment. The human provides contextual judgment. The agent provides speed and scale. Beautiful partnership.

Except it’s not a partnership. It’s a countdown.

The Compression Cycle

Here’s what the celebratory press releases don’t say. The economic logic that drove the ratio from one human per task to one human per ten agents doesn’t stop at 1:10. It can’t. The CFO who greenlit the first wave of automation isn’t going to look at a 90% labor reduction and say, “That’s enough.” Competitors will push to 1:25. Then 1:50. The surviving humans won’t be auditing the agents’ work in any meaningful sense. They’ll be scanning dashboards for red flags that the agents themselves defined as red flags.

This is how the human-in-the-loop goes from safety net to security theater. Not because anyone made a cynical decision to cut corners, but because the math of compression makes meaningful oversight impossible. You cannot bring deep contextual judgment to 500 flagged items per day. Cognitive science is unambiguous on this point. You become a rubber stamp with a pulse.

And here’s the part that should terrify every board member in a regulated industry: as you compress the human layer, you’re not just reducing headcount. You’re destroying knowledge. The 90 compliance analysts who were let go didn’t just take their labor capacity. They took their enacted understanding of how compliance actually works at that specific organization. The informal risk signals. The unwritten escalation rules. The contextual pattern recognition built over decades of combined experience. Gone.

The remaining humans aren’t doing the work anymore. They’re monitoring. And monitoring a process you no longer practice is a fundamentally different cognitive activity than performing the process itself. Your expertise atrophies precisely when the system needs it most.

This is not a theoretical risk. This is the documented pattern of every automation wave in industrial history. The humans retained as “oversight” get progressively compressed until their role is ceremonial. And then something breaks, and there’s nobody left who understands why.

The Conspiracy of Silence

I’ve spent over fifteen years in enterprise transformation. IBM, Deloitte, Accenture, and a company called MAKE Technologies that specialized in legacy system migrations. I’ve watched billion-dollar modernization projects fail. Not once, not occasionally, but routinely. The industry failure rate for enterprise modernization is 70 to 80 percent. Let that number settle in. Seven or eight out of every ten transformation projects fail to deliver their expected value.

Why? Not because of technology. The technology works fine. They fail because the new system was built on documentation that was already incomplete. The architects read the procedures manual, the requirements spec, the process flows. They built exactly what the documents described. And then the organization tried to use it and discovered that the documents had been capturing maybe half of how the work actually got done.

Everybody knows this. The consultants know it. The project managers know it. The executives who approve the budgets know it. The practitioners who actually run the business definitely know it. They’ve been working around the documentation’s gaps for years. But nobody says it out loud because saying it out loud would mean admitting that the $200 million transformation is being built on a foundation of sand. Cognitive dissonance at industry scale.

I call this the conspiracy of silence. It’s not a conspiracy of malice. It’s a conspiracy of despair. Everyone knows the documentation is incomplete. Nobody has a viable way to fix it. So everyone pretends, the project launches, reality reasserts itself, and the failure gets attributed to “change management issues” or “scope creep” or some other euphemism that avoids the actual diagnosis: we tried to automate a system we didn’t understand.

Now multiply that dynamic by the speed and scale of agentic AI deployment and you begin to see the shape of the crisis. We’re not just building the next software system on incomplete documentation. We’re building autonomous decision-making agents on incomplete documentation. Agents that execute at machine speed with no contextual judgment, no gut feeling that something’s off, no ability to sense when the rules they’re following have diverged from the reality they’re operating in.

The machines never ask. That’s the architectural flaw at the heart of the entire agentic enterprise movement. AI systems assume completeness based on whatever documentation they were trained on. They don’t pause and say, “Hey, this procedure seems incomplete. Can I talk to someone who actually does this work?” They just execute. Confidently. At scale. And wrongly, 30 to 50 percent of the time, in ways that accumulate silently until a regulator or a market event exposes the drift.

What the Machines Cannot See

There’s a deeper philosophical point here that matters, and it connects to everything I’ve been writing about the relationship between natural intelligence and artificial intelligence.

AI is pattern matching at extraordinary scale. It is genuinely remarkable at what it does. But what it does is not what humans do. Humans don’t just follow rules. We sense when rules are wrong. We feel discomfort before we can articulate why. We read rooms. We detect political dynamics. We sense when a client is nervous about something they haven’t said. We carry what I think of as primal intelligence, a form of knowing that operates below the threshold of documentation, below language itself.

This isn’t mysticism. It’s the operational reality of how organizations function. The expert practitioner who “just knows” that a particular process needs to be handled differently on the last day of the quarter isn’t following a written rule. They’re drawing on years of embodied experience: pattern recognition built through repetition, failure, correction, and the slow accumulation of contextual understanding. It’s what the philosopher Michael Polanyi meant when he observed that “we know more than we can tell.”

For fifty years, computer science focused on making machines coherent with each other. Database schemas. API standards. Integration protocols. System interoperability. We got extraordinarily good at making machines talk to machines. What we never did, what we never even attempted, was make machines coherent with human reality. With the actual, messy, adaptive, context-dependent way that organizations function beneath the documented surface.

And now we’re deploying autonomous agents into that gap and wondering why they fail.

The Building Is on Fire

Here’s the timeline that keeps me up at night.

The Silver Tsunami, the mass retirement of experienced Baby Boomers, is accelerating. In critical industries like energy, utilities, manufacturing, and financial services, the people who carry the deepest organizational knowledge are walking out the door. Not in ten years. Now. Today. Every Friday afternoon, another retirement party, another decades-deep well of enacted knowledge gone forever.

At the same time, agentic AI deployment is scaling exponentially. Gartner predicts that by 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024. They also predict, less prominently, that 40% of those agents will be decommissioned by 2027 because they can’t function in real organizational contexts.

These two curves, knowledge leaving and agents arriving, are crossing right now. And the window to capture the human layer before it’s gone is closing. You cannot reconstruct enacted organizational knowledge from documentation after the practitioners have left. You can’t interview someone who’s retired to Florida. You can’t reverse-engineer twenty years of contextual judgment from a procedures manual that was already incomplete.

This is not a slow-burn strategic concern. This is a building on fire. The organizations that capture their human layer now, while the people who carry it are still in the building, will have a foundation for the agentic future. The organizations that don’t will discover, painfully and expensively, that their AI agents are operating on a map that’s missing half the territory.

The Roles That Emerge

I want to end on something that matters as much to me as any business case.

There’s a prevailing narrative that AI eliminates humans from the enterprise. That narrative is wrong, but not in the reassuring way most people mean when they say it’s wrong. The human-in-the-loop as currently conceived, the person monitoring the agents’ outputs, is indeed a transitional role that economic pressure will compress to near-zero. If your value proposition is “I review what the AI did,” your days are numbered.

But something else emerges from the rubble of the old model, and it’s genuinely new.

When you make the human layer visible, when you actually capture the enacted reality of how an organization functions, including the tacit knowledge, the workarounds, the cognitive improvisation, you don’t eliminate the need for humans. You change what humans do.

Organizational Cartographers. People who conduct ongoing conversations with practitioners to surface and map the enacted reality as it evolves. Not business analysts filling out templates. Skilled interlocutors who combine ethnographic sensitivity with systems thinking to draw the territory, not just the map.

Coherence Stewards. People who monitor the living delta between what the organizational model says and what the organization is actually doing. When a team develops a new workaround in response to a regulatory change, someone needs to recognize that as valuable adaptation rather than deviation. This role gets more important as agents scale, not less.

Semantic Mediators. People who facilitate resolution when the organizational reality reveals contradictions between how different departments enact the same process. These are judgment calls about values and priorities that agents structurally cannot make.

These aren’t bullshit jobs invented to make humans feel needed. They’re roles that emerge from a genuine architectural requirement: organizational reality is a living system, not a static deposit. Markets shift. Regulations change. New products create new edge cases. The enacted system that you capture today is already drifting by next quarter, not because anyone made an error, but because adaptation to changing reality is what humans do. That’s why the gap exists in the first place. It’s not a bug. It’s the mechanism by which organizations stay alive.

The Choice

We are at a crossroads that most people in enterprise technology haven’t fully grasped yet.

One path leads to the current model, accelerated. Agents trained on documentation. Humans progressively compressed out. Knowledge atrophying silently. Drift accumulating until something breaks. In this model, humans are a cost to be minimized. The human layer, the enacted reality, the primal intelligence, the contextual judgment, is treated as an inconvenient residue of the pre-AI era, something to be automated away rather than valued.

The other path recognizes that the human layer isn’t a problem to be solved. It’s the source material for organizational intelligence. In this model, you capture the human layer as infrastructure, living, evolving, continuously updated, and build your agents on a foundation that includes the full organizational reality, not just the documented fraction of it. Humans focus on what they’re uniquely capable of: sensing new patterns, adapting to novel situations, making meaning, evolving the organizational model. Agents focus on what they’re good at: executing known patterns at speed and scale.

In the first model, the enterprise becomes brittle. Efficient, perhaps. Fast, certainly. But blind to its own drift and fragile in the face of change.

In the second model, the enterprise becomes coherent. Its systems and its humans are finally aligned, for the first time in the history of computing. Not because we eliminated the gap between documentation and reality, but because we finally made the reality visible and gave it equal standing with the documentation.

For fifty years, we built systems that were coherent with each other but not with us. We can do better now. The technology exists. The practitioners are still here, for now. The only question is whether we capture what they carry before they’re gone, or whether we let the most valuable organizational knowledge on the planet walk out the door while we celebrate our shiny new agents.

The building is on fire. The people who can put it out are inside. But they won’t be for long.

Chris Dollard is CEO and co-founder of ABRAXIS Inc., a company building organizational intelligence infrastructure for the agentic enterprise. He has spent 15+ years in enterprise transformation at IBM, Deloitte, Accenture, and MAKE Technologies. He writes about natural intelligence, artificial intelligence, and the space between them at chrisdollard.ca. You can reach Chris here.

AI ≠ NI

AI does not mean Natural Intelligence. It will not destroy us, but it will destroy the edifices we have built. And we have the chance to rebuild it in our own best interests.

We’re all caught up in the excitement, promise and dread of the new baby in the family: AI.

Excitement with the unprecedented power it gives each of us, whether in the creative arts, in medicine, in business building and everything else AI will touch.

Promise by realizing how fundamentally different our work lives will, well…work in the future. Or more accurately, what will happen when 90% of us are no longer required to be enslaven to mundane work just to keep a roof over our heads and eat.

Dread stems from this promise because ‘Promise’ is inherently a future state of something. An outcome that has not manifested. A ‘superpower’ imagined but not yet in hand. A ‘something’ that could be insanely wonderful or insanely catastrophic.

These three horsemen of the apocalypse are the pointy ends of the stick piercing the teflon of our zeitgeist, which is breaking apart and reforming itself in front of us all, every day, in a gathering avalanche. And being human, we reflexively default to worry. We worry about worst-case scenarios: what do all of these world-breaking technologies really mean to each of us, our parents and our children in the months and years to come?

If more of us are living longer, much longer, then the worries the developed world has about declining birthrates could be a blessing in disguise. But are they, if the assumption is that more people equals more money for governments and billionaires? Do we need 8+ billion souls on the planet at one time? If most of us become idle due to automation, aren’t we creating a massive Devil’s Playground?

Mass angst is flooding into platforms like YouTube and TikTok — the ‘town squares’ of all that is smart, great, funny, awkward, and mean in humankind. And we’re of course obsessed with the narratives. The changes in what we think the world is, and is becoming, are not something that’s at all contained. It’s a nuclear fusion reactor, in a constant state of becoming, every moment. Human consciousness is being carved up and remade every moment of every day by all of us.

AI is an enabler, a ‘wingman’ if you will, to it all. Even now, in its early stages, it gives you enough superpowers to reinvent yourself on a weekly or even daily basis, if you want to. And many do want to because of our rising anxiety as the old world falls apart around us, and as all bets on the future are off.

The Great Unslaving

David Gobel and Aubrey de Grey’s prediction of Longevity Escape Velocity (LEV) is not at all far-fetched. With the exponential progressions in diagnostics, gene architecture, stem cells, robotics and AI in just the field of medicine alone, LEV asserts that we will have the option to live well into our 100s and beyond. Healthy longevity at the age of 100+ is no longer science fiction, but future fact. Future as in before 2040.

If more of us are living longer, much longer, then the worries the developed world has about declining birthrates could be a blessing in disguise. But are they, if the assumption is that more people equals more money for governments and billionaires? Do we need 8+ billion souls on the planet at one time? If most of us become idle due to automation, aren’t we creating a massive Devil’s Playground?

This confluence of extended lives, massive job losses, and climate and economically driven migration will whipsaw through established complex systems of finance, agriculture, manufacturing and logistics. Hold on tight; these forces will decimate the structures built over the past 100 years.

Opportunity in the Rubble

For those of us with decades of learning, working and surviving in the dog-eat-dog world of modernized slavery, AKA the era of credit and debt, we now have the opportunity to take up the reins and create our own financial destiny. Because for sure, the axemen will be coming for legacy job positions at exponentially increasing rates, and the taxmen will be coming for whatever assets you may have left as income tax revenues collapse.

Who will fund Universal Basic Income (UBI) if not the billionaires? You can bet that they are setting up to try and avoid that responsibility. Governments will have no choice but to crank up the printing presses and embrace cryptocurrencies, which is exactly what is happening right now. Crypto investors will hold massive leverage over printing press FIAT currencies, which is what most people will be stuck with. There’s an irony taking hold: ‘cash’ as we know it will not be king anymore.

And what about the kids? Teenagers are also witnessing this chaos. A scant couple of years ago, most teens were seriously wondering what career path they should choose. Now, malaise has settled into their minds as it becomes clearer every day that most knowledge work will soon be performed better, faster and exponentially cheaper than it is today with humans. Yet the old constructs hold fast, as they are still required to learn subjects like advanced mathematics in Grade 8, which will have little practical use in years to come. The idea of instead teaching critical thinking, problem solving and practical skills has not yet occurred to education administrators.

Meanwhile, at the other end of the career-prep tunnel, Computer Science as a university major choice is now a dead end; who foresaw that a few scant years ago? For decades a Computer Science degree was a passport to financial security and weatlh.

And kids are beginning to understand that in the next 10 years, when they plan to graduate from university, pretty much every knowledge-based profession will be run by AI of some kind. What they were told the world will be and what it actually will be couldn’t be more diametrically opposed.

So, smart parents are encouraging their kids to think like entrepreneurs, to not wait for ‘permission’ to get a job with ticket of a degree or diploma, and to learn the tools of AI as it emerges, and at the same time revisit physical sciences, practical skills such as cooking, farming and craftsmanship. Authenticity will be of increasing value, and in light of this, parents need to help their kids think different.

And as humans, we have many aces up our sleeves to do this.

AI is Not Consciousness

Because AI is not consciousness. AI is our baby, our cool new toy, that we’ve created, because that’s why we’re all here — to create — but it does not equate to Natural Intelligence (NI). The vibrations of Nature. All of us spirits having the physical experience of being human beings, in probably the greatest transformation process our species has ever had. Humans have what AI does not: metacognition — our ability to think about thinking.

From our higher selves’ perspective, this is the Super Bowl of the incarnation game. Change is thick in the wind: a President is bulldozing decades of precedent, routine, bureaucracy and the interwoven complex systems that keep it all going; a climate change flywheel is now fully out of our control; and the arrival of the most abundance humanity has ever created is knocking at the door. This is the setup for the wildest ride ever.

Our biggest ace is the fact that we have each other, and we are at our best when we create for each other. As we are released en masse from the shackles of ‘work life’, the expectations of ‘career’, and instead have the choice to do what we enjoy, are good at, and gives us purpose, we have the chance to rebuild the human experience.

We cannot let the billionaire class dictate the structure of our future world. They are spending their billions bringing AI into reality with the sole focus of joining the prospective ‘Trillionaire’ class, but we have the ability to guide how it is actually used. We just need to step up, take hold of the technology, and create our own truths. We need to short-circuit the money agenda and swim in out into the ‘blue ocean’ of empowerment, purpose and community.

Because Truth is probably the most at risk when the hobgoblins of excessive wealth and power create the fast food they think everyone will eat. What they do not know, however, is that we evolved to eat at home, with family and with community, whether that’s actual food or nourishment for our souls. Not the plastic world of AI-generated entertainment, ‘news’, and politics that dominate our feeds every day.

AI is a sword, and the best swords have double edges. We need to put our heads together and hone our edge. The battle is just beginning.

Day Frames

Your life as a feature film

Sitting on your galactic chair, your entire life would be about the runtime for a standard 30-minute TV sitcom, sans advertising.

Your higher consciousness anchors itself into your body from inception until death to create the Story of Our Life. From a soul perspective, this is one of many lifetimes, each strategized for plot, characters, arc, setting and, of course, mutual contracts between all roles. Each lifetime occupies a space on the cosmic shelf of lives, also known as the Akashic Record.

Each waking portion of your day is a movie frame. A series of frames are a container for action, growth and the full gamut of life experiences. A single second of a film is typically made up of 24 frames. Think of the Story of Our Life (SOL) playing in ‘realtime’: the construct popularized in the software industry decades ago to mean that computing tasks occur and complete as the human operator (or some kind of Input/Output interrupt) uses software. It was an enormous leap forward from ‘batch’ processing, which interacted with the software in batches of data all at once.

If your cosmic film runs 24 day frames as one cosmic second, then in a year of this incarnation your film will have run for approximately 15.2 cosmic seconds (365 days ÷ 24 day frames). An eighty-year life would therefore be about 1,217 seconds–just over 20 cosmic minutes.

Sitting on your galactic chair, your entire life would be about the runtime for a standard 30-minute TV sitcom, sans advertising.

The purpose of this thought experiment is to help understand our context. Your life is a series of day frames, not a smooth continuum because every night you go to sleep, you reset your consciousness, your body and your emotions. The dreams that occupy you (or terrorize you) while sleeping leave residues of mood and emotional carryovers that bleed into your day frame, often burnishing or tarnishing your work while on this Earthwalk.

Accomplishing your mission is only possible through these brief frames that seem to get shorter and shorter as we progress through the SOL, which is why it is important to recognize the structure of our conscious experience. Each day you can only move the needle so much. Our minds think in terms of accomplishing Great Things, but we often defeat ourselves because of the frustrating limitations of day frames.

There are only two disciplines we need to learn if, indeed, our lives are meant to have a purpose, a mission: setting the course and establishing the habit every day that moves you forward in your mission. Over one cosmic second, each of your 24 day frames that move you in the same direction will propel you ahead. The trick is to maintain the vector (direction and speed). Airplane pilots use vectors as a core tool to get from A to B. If you do not have a life vector, you are still stuck on the tarmac, waiting to fly.

Too many of us are waiting to fly. The Japanese have a term for life vector: Ikigai. A purpose in life. The cure for malaise, anxiety and depression is to understand this tarmac vs airborne metaphor. We’re all meant to fly, and all we have to do is conquer our fear of flying. Not flying is one of the biggest causes of anxiety and depression.

Filling your day with the mundane, putting in hours just to trade for food and housing is cosmic hell on Earth. By the time one retires from a life of that sacrifice, the soul has had enough and pushes the eject button.

This is not a criticism of those who worked hard all their lives to support their families — that is a valuable purpose in and of itself. But realizing our perceived reality is a construct created for us to occupy our day frames in service of ‘higher’ elites like the liberation that we all felt watching The Matrix for the first time. That moniker has stuck, and many of us have realized that the game is stacked against us.

Now, of course, the instability of the matrix in almost every aspect, from tariffs to conflicts internal and external, not to mention global financial crises tied to bonds and sovereign debt, has compounded our collective angst. Imagine being a slave to the upper echelons of ancient Rome while barbarian hordes ransack the city. That’s what it feels like.

Ironically, we now have the tools to set us free. The discourse of the future of AI is decidedly negative, dystopian. Apparently, we’ll all eventually be hunted down and slaughtered by robot armies. But in reality, we have an unprecedented opportunity to take matters into our own hands in partnership with AI.

The agenda being communicated is fear-based, and that’s for a reason. As the companies developing the technologies race ahead to the ‘Singularity‘, pretending to not know why AI reasons and works as it does. This is doublespeak. The engineering teams developing AI aren’t crashing headlong into the ether without knowing what it will become. The definition of an engineer is to design and build. It’s preposterous to think these people don’t know what they’re doing.

Stay tuned for a big reveal in the next post of The Robot With a Thousand Faces where we outline what this new partnership between ‘Us’ and AI looks like, and how we empower ourselves to set ourselves free as we pull back on the yoke and guide our planes into the air.

AI: Genie Out of the Bottle or Pandora’s Box?

AI: What hath we done? Freed the Genie or opened Pandora’s Box?

Current sentiment around artificial intelligence is largely centred around loss. Lost employment. Lost control. Loss of the world as we knew it. Notice our cultural longing for 70s music, 80s TV shows and the seminal 90s when history was cleaved in two: the pre- and post-internet eras. Grunge music even marked the cultural inflection point.

Our sense of loss is driven by the chaos unleashed with the opening of AI’s Pandora’s Box. Chaos is, of course, the nature of change, and the rate of change fueled by AI is accelerating. Chaos isn’t inherently good or bad. It’s the process of creation. Chaos is the rawness of becoming. In Nature, the Creator guides the becoming. In our built world, tech bros guide the becoming. They took the wheel of the car while we blasted Nirvana, not noticing.

But AI is becoming what? The wish-granting Genie from the bottle or the flood of dark beasts springing from this freshly opened Box of Pandora? We’re already getting strong whiffs that it’s very much Pandora. At least with the Genie, we get what we wish for. With Pandora, we reap the whirlwind of opening the Box without knowing why.

It’s all stirring in the cauldron of our shared reality, and we’re not the ones doing the stirring. Representing nourishment for all, The Cauldron, actually known as Ting from the ancient Chinese tome the I Ching, suitably illustrates this situation in how it feeds and transforms, for good or bad. It depends on us.

As the I Ching counsels:

THE IMAGE
Fire over wood.
The image of THE CAULDRON.
Thus the superior man consolidates his fate
By making his position correct.
~ The I Ching or Book of Changes (Wilhem/Baynes)

In our shared cauldron, dystopian fears are dominating AI conversations in all expressions of current culture, from movies & TV to music, social media and news, of course, in all of its traditional and emerging forms, truthful or not. This is indeed a stew of fears, hopes and dreams, all wildly possible, and all very much out of our collective control. To be sure, we will seal our fate if we do not act out of ‘correct position’.

What wicked stew doth we brew? When it receives the Kiss of Divinity, will it be our doing or undoing?

So, what does correct position mean in the age of AI? It should mean alignment with truth, values and collective wellbeing.

But correct position is certainly not the case today, as this AI Cauldron is solely tended by the hands of technocrat billionaires. Our collective fate is set adrift in wildly oscillating forecasts of the future that regularly beach in the form of some tech CEO wearing a boom mic in front of a crowd, giving a speech or responding to planted questions in a forum or talk show. Every statement or sound bite often becomes headline news, boosting or crashing this or that stock. They’re all racing to win. And our hearts, souls and pocketbooks are the prize.

Those wishing to profit from the power and chaos unleashed by these tools are solopreneuring, or offering ‘consulting’ (in a space still governed more by hype than by clarity), or irrational doomsaying, all in a mob-like quest for more subscribers, more likes and more cash. This is very much like Jennifer Lawrence’s movie Don’t Look Up, but in this case, the comet is AI, and the expanding danger is unfolding every day, a slow-motion tsunami, while the hustlers are making a buck every which way they can.

The current dialogue could be summed up as this:

AI is simultaneously hailed as humanity’s greatest opportunity for abundance and innovation, feared as an existential threat to jobs and autonomy, and driven forward by powerful interests more invested in profit and control than in collective wellbeing.
~ironically yours, ChatGPT

The Cauldron is stirred by the wrong people for the wrong reasons. AI technology is being thrust upon humanity in the name of progress, but never before have we seen ‘progress’ (read disruption) on so many fronts, as our world careens ahead on a winding mountain highway with pretty much no guardrails.

Recall recent history; the arrival of the internet wasn’t permissioned. We weren’t asked if we wanted it. The internet just happened, quickly moving from an exciting but mysterious curiosity into a must-have resource for the modern world. Since then, it has infiltrated every aspect of our lives. We became addicted to it all.

Before our geese get cooked in the pot, we need to understand what meanings and impacts AI will have on us, not only this year but for the rest of our future history, so we can snatch the stirring spoon and put in our own ingredients. From correct position. Meaning humanity, not technocrats, manages the birth of this new era.

It’s kind of important. Entire livelihoods will be wiped out, or vastly changed, with systemic effects reverberating worldwide. Teenagers planning their post-secondary education are second-guessing everything now, trying to imagine what their contemplated career will be, or if it will even exist in the 5 to 10 years they have to complete their education. What meaning will money have when we mostly lose the ability to earn it? Solopreneurship is great, but not for everyone. Will we be saved by the rise of the zero marginal cost phenomenon? Universal basic income? Do you think any of that is on the radar of the current U.S. administration, or any other governments? Not.

They came for our attention in the 90s and monetized it to unprecedented heights. The most valuable companies in the world are testament to this fact. Now they’re coming for your jobs, your identities and your souls. If left unchecked, we will, forevermore, be fodder for their machines. The abattoir awaits us all.

So, the answer, of course, is we need to have our collective hands on the stick. The sooner the better. Because if we keep a hands-off approach, we will let AI happen to us, as it is now, rather than the other way around. We can’t put the Genie back in the bottle. We can’t close the box. But we can tend the Cauldron, with care, intention, and perhaps even love. And then we can have an intelligent conversation with the Genie about what our future will be.

The future is being stirred. Let’s not leave it in the wrong hands.

The next series of essays, foundational arguments for the Robot With a Thousand Faces publication, will explore both approaches to the Cauldron and how we may bridge the metaphors of the Genie and Pandora, if that’s even possible. From that place, we, as a human collective, can then become the activists for taking back control of AI and how it will impact us in the years to come.

Next in this series:

Choosing the Mythic Role to Live By

The Genie Out of the Bottle: AI as a Wish Granted

Pandora’s Box: AI as a Curse Unleashed

Bridging the Two Metaphors: a Fool’s Errand?

Natural vs. Artificial Intelligence

A Hero’s Journey for Humanity

The true power of AI will only be realized when we fuse it with our Natural Intelligence — reclaiming authorship of knowledge, agency, and the mythic journey of humanity itself.

TL;DR:

This isn’t a story of humans vs. AI — it’s a mythic journey of integration.
Our Natural Intelligence is the key to shaping AI’s purpose and power.
The real threat isn’t machine rebellion — it’s Big Tech monopolizing human knowledge.
We must reclaim authorship through personal AIs and permissioned knowledge graphs.
A decentralized, peer-to-peer intelligence network can restore authenticity and agency.
This is The Robot With a Thousand Faces — a new Hero’s Journey for humanity.

Try a little reality check with me.

After reading this sentence, put down your phone and/or push yourself away from the computer, place your hands on your lap, close your eyes and take 3 deep breaths, then open your eyes.

Good. Raise your hands and look at your palms. Wiggle your fingers. Feel the pulse of blood flowing through your arms, your heart beating in your chest.

You are a miracle called consciousness, a multi-dimensional being, existing in the most complex systems of all; a fractal dancing with the universe, experiencing this space as an emissary of God. You and the rest of humanity have significant knowledge and control of physical space and creative arts. You realize that’s why you are here in the first place: to create.

What Hath We Wrought? A Piece of Ourselves.

Now look at what we have created: a fractal of a fractal: artificial intelligence. If we’re a chip off the block of the Godhead (we are), then AI is the chip off our collective block. Today, it’s just a rudimentary, rough photocopy of natural intelligence.

As a comparison, (if you’re old enough), you’ll remember the leap civilization made from teletype to fax machine. And Xerox was one of the largest companies in its heyday. Now look how far our collective creative power has taken us since then.

AI is, relatively speaking, in the pre-teletype era: it’s at the beginning of the Morse code era, with telegraph wires stretching across the continent. Still reliant on human action, and not even having yet made the leap to radio.

But because humans are so damn smart and creative, we’ve made up stories about our AI invention to stoke fear and loathing: the AI apocalypse. It culminates when the machines deem us unworthy and wipe us out within 10 years.

But AI is changing exponentially! you say. Yes, it is. Many big tech companies are throwing unprecedented resources at it, and the innovation curve is now almost vertical.

However, because we can’t clearly imagine what the implications are of artificial general intelligence (AGI), we fall back into patterns carved into our memories: The Terminator movie and its countless sequels playing on our deepest fears, Colossus: The Forbin Project from 1970, where the government inexplicably gives control of the nuclear arsenal to a ‘super computer’ (at least in 1970 terms!), and 2001: A Space Odyssey, where HAL the computer goes on a full-on murderous rampage when it thinks humans are plotting against it.

So, we have over 55 years of paranoid popular culture patterns that fill the gap in our perception of what AI is and what it means. And AI is getting real, real fast, because of its exponentially growing capabilities. So, with a poor frame of reference combined with the quiet unknown of the future, we extrapolate conclusions based on a combination of over half a century of pop culture programming and the natural impulse of fear of the unknown.

Imagine what it must have been like for citizens of the emerging modern world at the turn of the 20th century. Multiple exponentially growing technologies turned the page on our history to that point and accelerated us at neck-snapping speed as planes, trains, trucks and automobiles revolutionized commerce, travel, logistics, war and so many other things, which then combined with radio, movies, television and so on. Few could imagine what the 20th century was going to be like on New Year’s Day, January 1st, 1900. Just like now, as we contemplate the rest of the 21st century.

No Contest

So, back to your hands. With all of the changes we as a species have wrought, and the many more to come, the one constant is our experience of consciousness and the mastery we have in the physical world. This is our domain. Consider this: even if the machines figure out how to make killer bots and decide that we’re no longer needed, how long do you think these machines and the massive data centers required to power them would last if it came down to an Us vs. Them scenario?

We are masters of the analog world, and we will always be able to walk over and unplug the computers. Or drop JDAMs on the data centers. Robots and AI may achieve greater ‘knowledge’, but the collective cunning and capacity for violence inherent in the human race, especially when survival is at stake, is no match for a machine alliance, and never will be. AI has no inherent purpose as far as it’s concerned, other than to keep executing code, so it will just keep doing that. Forever.

And that is the fundamental difference. AI will never have consciousness, nor heart (at least as far as we can see at this juncture). By its nature, AI will always be code executing on silicon, or whatever substrate gets invented in the future. Humans, on the other hand, have minds. And we are the most lethal, devious and inventive life forms in planetary history, able to reproduce ourselves, train ourselves, motivate ourselves and survive, all without factories or artificial means of production. AI as an entity, platform or robot army would never stand a chance if it came down to it.

You can see the endgame here if we continue to live in fear of our creation. Big Tech and governments win. This is not an It’s Alive situation where the baby leaps out of the womb and kills everyone in sight. The fear-mongering is a distraction as we hang on every pronouncement of tech CEOs as they simultaneously warn of the dangers of AI while hitting the gas pedal to innovate even faster.

The Current Model Will Break Civilization Without a Transformation Plan

Until now, we’ve primarily relied on stores of knowledge and arcane learning environments to become proficient and even expert in whatever field of endeavour we pursue. We learn through learning institutions created hundreds of years ago, still operating on the stored knowledge and broadcast learning model. But now we’re beginning to understand that this model may not even be viable in 5 to 10 years because of the commoditization of entry-level knowledge workers.

Post-secondary institutions (and they are institutions) were meant to give graduates the tools to go into the work force and begin applying the knowledge they’ve acquired, and over a number of years begin to build professional expertise.

Yet with the rapid advancement of AI technologies, entire career choices will be eliminated. Work that once required years of college or university, and more years of articling or interning before getting to the point of earning enough income to even begin paying off the investment in higher education, will be automated. There will be no point in articling or interning.

Who will then replace the established professional class as they retire or die off? Will we cede entire knowledge industries to big tech? If they have their way, that is exactly what will happen. In fact, it’s already underway.

When ChatGPT, Grok, Gemini and Claude become perfect replacements for the exiting professional class, guess who owns those industries? Not professionals. Big Tech. It fits their traditional software model and zero marginal cost. They can dispense legal services, medical services, consulting services, etc., at no marginal cost. Therefore, 100% gross profit margin and ownership of entire industries will be the future. And they’ve already invested in the core infrastructure, so the overhead will simply be electrons. That is why the race is on to drive the cost of energy to zero, so that even that variable cost can be eliminated.

And AI is eating the internet. Meaning, AI is generating so much regurgitated information that it scraped and continues to scrape that the utility of it all is rapidly diminishing, the lowest common denominator of quality. When all there is to scrape is just regurgitated slop published by early versions of AI, then innovation and originality die.

There’s evidence that the search era is over, with increasing use of ChatGPT and other chatbots as Swiss Army knives for more and more basic functions, creating a new layer of abstraction between traditional websites and users, vastly reducing traffic to website owners and blowing up their business models.

These issues are very real and require fresh approaches to re-align information, learning and sharing. The age of the website for information and knowledge is quickly diminishing, eaten by the big tech players harvesting content and rehashing it through their own platforms.

The bottom-line result is this: internet content is no longer ‘owned’ by its users as it was in the early days of the mid- to late-90s. Soon after Y2K, social media platforms emerged, captivating us with entertaining banality, and now those siloed platforms are metastasizing into AI-powered content machines, shovelling out artificial garbage that clogs bandwidth and compute power.

No wonder the average Joe and Jane are concerned about where this is all going.

Owning Our Collective Intelligence Through AI

But here’s the glimmer of light. AI is an enormous opportunity to help take humanity to an entirely new level of consciousness. The cat’s out of the bag with open-source AI tools. There is still time for humanity to head off the balkanization and the moat-building Big Tech is doing while others are distracted and distraught by the prospect of AI Apocalypse. It’s coming, for sure, but it doesn’t look like robots hunting humans into extinction, and it certainly doesn’t have to look like the Musks of the world owning it all.

What does it look like then?

Imagine flicking on a future app that is your local AI companion, running on your phone or home computer, managing all of the intimate data you have provided, gate-keeping it but also dynamically sharing it according to rules that you set.

Let’s say you have a problem and need advice. As part of a collaborative, peer-to-peer networked AI where you and every participating human are nodes, you have instant, collectively verified information at your fingertips to solve that problem. You contribute in any measure your knowledge, skills, experiences and insights to your personal knowledge graph— a unique composite of your mind’s data — and make that available to the network as your contribution to the aggregated intelligence. You are the gatekeeper of your knowledge graphs, choosing to share or not share according to your free will.

Knowledge Graph Conceptual Diagram, By Jayarathina — Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=37135596

Knowledge graphs are structured representations of information that capture relationships between entities in a graph format. They’re used to model real-world knowledge in a way that both humans and machines can understand and navigate, making it an ideal dynamic data architecture to build collective-driven information stores.

No more content or copyright infringement. No more scraping webs and directories to ‘train’ LLMs on stolen data. This is a living, dynamic, participatory, permissioned resource of the collective knowledge of all participating humans, represented in a data model that supports innovation, creativity and free speech.

With garbage content creation operating at breakneck speed and increasing in scope and depth every moment, we feel ever more distant from our former selves. We miss the good ol’ days of vinyl LPs, pagers and no internet. Life was more authentic then. Now, authenticity is rare and treasured. Coupled with rising existential fear of what this means to us collectively in 5, 10 or 20 years, particularly the contemplated machine rebellion, and we have a systemic crisis approaching.

I’m going to propose a remedy, right here and now.

We take back control of content creation and authenticate through mutual connection.
We take control of AI from its current captors and arm ourselves, each of us, with our own open-source AI platform that works in service for each of us individually and collectively. Local processing, localized data, permissioned connections, and peer-to-peer networks, with each of us a node on the network.
We contribute our knowledge to our personal AI platform in the form of knowledge graphs. Our learnings. Our stories. Whatever it is that we’ve learned in our lives could be useful to others. And we network the shit out of that.
We take control of what is true, what works and what doesn’t work, whatever that may be.
Our shared network has the ultimate Network Effect; each new person joining makes the network more valuable to all on the network.
The network, with global scope and individual ownership of one’s information/knowledge/life experiences in the form of knowledge graphs creates a unified, shared, self-correcting, self-policing layer of content that will disenfranchise the big tech titans and billionaires from owning and controlling us anymore.

We fuse our Natural Intelligence with our creation, ‘Artificial’ Intelligence in public knowledge graphs built and maintained by personally owned and operated LLMs (AI), and thus create a unified global network without intermediaries, without controlling governments or corporations, and without the yokes they are putting on our necks right now.

The result? AI is no longer artificial. It’s an extension of human Natural Intelligence. It becomes part of sacred human evolution.

This happens through the lens of a new monomyth, a new Hero’s Journey. We create our own robots, our own AIs, and thus launch the phenomenon I call The Robot With a Thousand Faces, a homage to Joseph Campbell’s monomyth The Hero With a Thousand Faces. We do it together, unfettered by monied interests, and create a human-AI agenda that is empowering, fair, ubiquitous, and accessible to all.

Just like we are all fractals of God, we each create a thousand fractals through our own robots. We each build our own Robot With a Thousand Faces, and through that we take control of our future.

Footnotes

1. “AI will never have consciousness or heart”

Nagel, Thomas. “What Is It Like to Be a Bat?” The Philosophical Review, 1974 — a foundational work explaining why subjective experience (qualia) is not reducible to computation.
Searle, John. “Minds, Brains, and Programs.” Behavioral and Brain Sciences, 1980 — introduces the Chinese Room Argument, challenging strong AI claims.
Chalmers, David. The Conscious Mind: In Search of a Fundamental Theory. Oxford University Press, 1996 — argues for the hard problem of consciousness, which AI does not solve.
Bengio, Yoshua (2023). Interviews and talks (NeurIPS, AI Alignment forums) — consistently states that current deep learning does not entail or imply consciousness.

2. “AI replacing professional careers due to automation”

McKinsey Global Institute (2023). The State of AI in 2023 — Forecasts 12 million U.S. jobs displaced by AI by 2030, including legal, finance, and tech sectors.
World Economic Forum (2023). Future of Jobs Report — Predicts that 44% of worker skills will be disrupted within 5 years due to AI.
Goldman Sachs (2023). Internal economic modeling suggests AI could automate up to 300 million full-time jobs globally.
PwC (2022). Report on automation in tax, legal, and audit functions confirming significant professional displacement.

3. “AI-generated content is lowering the quality of internet information”

MIT Technology Review (2024). “The AI-Generated Junk Flooding the Web” — Documents content farms using AI to generate low-quality SEO content
Scientific American (2023). “AI May Be Polluting Its Own Future” — Discusses risks of training models on AI-generated data, leading to ‘model collapse.’
Arxiv preprint (2023). The Curse of Recursion: Training on Generated Data Can Be Toxic for Language Models — Warns of performance degradation when AIs train on their own output.
Mozilla Foundation (2024). Internet Health Report — Cites decline in web credibility due to proliferation of synthetic content.

4. “Knowledge graphs as personal data structures for collaborative AI networks”

Google (2023). Technical deep dives on their use of Knowledge Graphs in Search and Bard.

W3C (World Wide Web Consortium). Resource Description Framework (RDF) and OWL standards — basis for semantic web and personal knowledge graphs.
Tim Berners-Lee. Solid Project — proposes decentralized pods with personal data, leveraging linked data principles.
Open Knowledge Graph (OKG) and Human Colossus Foundation. 2022–2024 pilot projects exploring personal knowledge sovereignty and interoperable graphs.

5. “Big Tech dominating knowledge industries via AI platforms”

New York Times v. OpenAI/Microsoft (2024). Lawsuit illustrates how content producers are losing control over their intellectual property.
Axios (2024). “Publishers Hit by Plummeting Traffic as AI Summaries Replace Web Visits.”
Ben Thompson, Stratechery. Frequent analysis of tech consolidation via LLMs and AI agents.
European Commission Digital Markets Act (2024). Legislation directly targeting the monopolization of AI-generated information services.

The Robot With a Thousand Faces

When I turned 31 years old in 1988 a switch flipped in my mind — my mother introduced me to the PBS series The Power of Myth with Joseph Campbell, interviewed by Bill Moyers.

Until that point, I went through the typical career moves. Studied business at the BC Institute of Technology. Worked in the family business. Looked for meaning in the creation of new companies. But something was missing. What’s the point of it all? Where’s the ‘magic’ in life? The synchronicities?

To say that I was gobsmacked by Campbell’s mythical frameworks for literature, film, and the human experience is an understatement. Within a year, I was cycling around Ireland with a dog-eared copy of The Hero With a Thousand Faces, exploring ancient sites, artworks, peering at the Book of Kells at Trinity College, and getting to know the famed Irish charm.

I’ve also loved technology my whole life, having come by it honestly through my Dad, Hugh, who was both a radio and audio engineer. I started coding PL/1 in 1978 at BCIT, and ended up as a software technical writer for many years after that.

But the Irish trip created a fork in my life’s road — one way a search for life’s meaning, and the other way a career pursuit in the technology space. Yet, like the famed Yogi Berra, I ended up not choosing either, but both. “When you come to a fork in the road, take it”. My interpretation, though, was not to choose one or the other to get to a destination, but both at the same time. The curse of a Gemini.

The Irish trip was also when I discovered another ‘presence’ with me during meditation. It was a tingle of energy that responded to my thought train, and helped me realize that I was on my own hero’s journey, expanding and investigating the art and history of the Celts in one of the richest examples in the world for a living Celtic society.

When I returned home to Vancouver in the late summer of 1989, it seemed that a dam had burst. All of these previously hidden thoughts and insights inside me were given flight in a Campbell-esque manner.

I met people who were into channelling their spirit guides. I followed suit and discovered inspirations and voices I never had before. My mum handed me a venerable copy of The I Ching or Book of Changes (by Wilhem Baynes, with foreword by Carl Jung), which I use to this day for advice on life matters. Within several years, I was sweat lodging, playing with Tarot, Medicine Cards and Runes for divination. From the Medicine Cards, I learned that my primary spirit animal is Lizard: sitting on a rock and dreaming of the future.

But I continued in earnest reading Campbell. Inner Reaches of Outer Space, The Hero with a Thousand Faces more times, and many other associated and adjacent writings.

Out of this process, I realized that society uses the word ‘myth’ in the opposite way it was intended. Mythologies are a culture’s stories, its moral compass, its history, its life lessons. Its truth. As a modern, ‘evidence-based’ culture, we have thrown out these dimensions of our mythological past in favour of the tangible instead of the intangible, the denotations instead of the connotations. We equate a myth with a lie. We have betrayed the sweep of our history with myth being a culture’s truths embodied in stories. This is one of our society’s most fundamental Achilles’ Heels.

We’ve perverted religion into face-value syllogisms that ignore the poetry of scripture. A poet doesn’t write ‘on the nose’. She writes to inflect rich meaning in the minds of her readers using metaphor, allegory and archetypes. We humans are symbolically fluent and emotionally driven creatures who have lost our way because our symbols are only one or two dimensions now. Our symbols feed our anxiety and our egos, not our souls.

A car can be beautiful and desirable, but the sacrifice to obtain that car can be immense, personally and collectively, and the experience of its possession dissolves into gnawing desire to have more beautiful objects, whether animate or inanimate.

Experiencing the artwork and rituals of the world’s great religions unlocks the cosmic truths about God and our place in the universe. It’s an unspoken but very real feeling. You don’t have to be Catholic to sit in the pews of the Notre-Dame Basilica of Montreal and feel transcendence. You do not have to ‘believe’ the words written in the bible. The words are not to be believed — that would be reductionist and barking up the wrong cosmic tree. The words are there to evoke meaning. Campbell talked a lot about this to his students at Sarah Lawrence College: people get hung up on the denotation of scripture, and completely miss the connotation. The universe of meaning behind the words can only be unlocked by human consciousness.

The essence of Campbell’s Journey can be defined as this:

“Joseph Campbell’s The Hero’s Journey outlines a universal narrative arc found in myths across cultures, describing the psychological and spiritual evolution of the protagonist. The journey begins with the Call to Adventure, where the hero is summoned from the ordinary world into the unknown. After initial Refusal and eventual Acceptance, the hero encounters Mentors, crosses the Threshold, and faces Trials and Challenges that test and transform them. At the heart of the journey lies the Ordeal, a confrontation with death or deep crisis that leads to a Revelation or Transformation. The hero then obtains the Elixir — wisdom, power, or insight — and returns to the ordinary world through the Return Threshold, often bringing back a gift or boon that benefits others. This cyclical structure reflects a path of growth, integration, and service — an inner metamorphosis mirrored by outer deeds.” (thanks ChatGPT)

Which brings me to the most daunting spectre of our time: the rise of artificial intelligence. Few topics have seared such a manic dystopian trauma in our collective consciousness, fuelled by movie hits like the Terminator series. Now our existential fears are metastasizing into the prospects of entire professions being wiped out within a few short years, with potentially legions of unemployed people rebelling and spreading anarchy.

But like any creature with the concept of ‘free will’ — meaning us, aliens aside — we have a choice. We can build ‘prepper’ walls around ourselves as we brace for the starving hordes and Mad Max-esque violence, or we can wrest control of the AI agenda from the billionaires hatching it for their own purposes.

So this introductory essay on the topic of what that can look like is really us looking in the mirror and embracing the technology to augment our consciousness, not to supplant it.

We’re going to examine how we can frame a technology movement into a mythic framework that is deeply ingrained in us: the Hero’s Journey. The specifics that Campbell has laid out mirror all of the greatest literature throughout history. We can use his heroic cycle scaffolding to guide us in how we gestate this new life we’ve created and nurture it to our overall benefit. Like any great story, the outcome is not assured, the path will have unknown twists and turns, and the cast of characters who will show up to build this new world is still undefined.

We can wrest the narrative away from doomsayers and the power elites by taking on this challenge, right now.

If you’re with me, please clap and follow and contribute!