The viral “welfare mom” clips did not fool Fox because they looked real. They fooled Fox because they felt familiar. The network framed them as proof of decay, lectured from them, and let the old stereotype do its work — until a toddler’s arm dissolved into pixels and a frozen backdrop betrayed the illusion. The software failed; the instinct did not. Nothing new was revealed about AI. Something old was revealed about us.

No model invented that narrative. It learned it. The prejudice did not arise from code; it entered through the culture that nourished the code. Reagan taught America this story long before neural nets existed. AI merely made it available at scale. A stereotype rehearsed for decades can now be summoned with a prompt instead of a press conference.

We talk about AI “hallucinating,” as if the danger were invention. But the deeper threat is repetition. The model does not pull prejudice out of thin air — it learns it from us, absorbs it into structure, and returns it as confidence. It does not know truth; it knows frequency. It does not reason; it reflects. And what it reflects most faithfully are the beliefs we encoded into culture long before we encoded anything into compute.

There was a time when narrative authority declared itself plainly: anchors at desks, headlines above the fold, a small circle of editors deciding which truths entered public life and which died in silence. Consent was manufactured through scarcity. Even when the story was warped, you knew who told it.

We once thought the internet shattered that. When the broadcast towers cracked, we celebrated. We believed that when anyone could speak, truth would rise — that when the old gatekeepers lost control, the public would govern its own attention. We misunderstood the terrain. The gate did not disappear; it became the feed. Authority dissolved into interface. We did not democratize media; we privatized distribution. The public square became a recommendation system optimized not for understanding, but for engagement.

The platforms that replaced the newsrooms did not abolish mediation — they deepened it. They learned to guide belief not through argument but through architecture. They let everything be said, then decided what would be seen. You do not need to police speech when you can engineer visibility. You do not need censorship when you can bury truth beneath convenience and reward conviction over comprehension. In this world, propaganda does not demand obedience; it rewards instinct.

And when power fears losing control of that instinct, it responds as it always has. TikTok did not trigger panic because of teenagers dancing. It triggered panic because it threatened America’s jurisdiction over narrative infrastructure. The Cold War never vanished — it migrated to the attention stack. Nations once fought for shipping lanes; now they fight for cultural bandwidth. Platforms feel like public utilities right up until they challenge state power. Then we remember who gets to define reality.

Yet occasionally reality punctures the interface. New York feels like one of those punctures. Zohran Mamdani’s mayoral campaign does not behave like content. It behaves like politics — not the performance of it, but the doing of it. Housing, transit, labor, taxation, the material obligations of a city to its people. No algorithm engineers commitment; people do. “So much of what feels hard right now,” Mamdani said, “is the sense that we are merely subjects.” He meant government. He meant platforms. And then the part the system cannot digest: this moment is not fixed. It will not change by going viral, but by choosing to act. “We took swings,” he told his volunteers, “because swinging means refusing the limits you were handed.”

That is not messaging. It is a public remembering it can move.

A politics that refuses to be formatted as content is dangerous to those who benefit from spectatorship. It reminds people that scrolling is not participation and cynicism is not sophistication. It suggests that struggle is not a relic but a method — and that power fears not outrage, but organization. In such a context, hope is not sentiment; it is subversion.

AI accelerates this contest. It does not invent new myths, but embalms the old ones in code and scales them. Bias was not smuggled into the model; we handed it over. We once spoke of “debiasing” like debugging. But the system was never neutral. It faithfully reproduces the structures we never dismantled. The risk is not synthetic content — it is synthetic inevitability. A future that looks exactly like the past, except faster and harder to dispute.

Which is why media literacy is no longer etiquette; it is civic armor. History is not nostalgia; it is ballast. The point is not to detect every fake, but to remember that fakes flourish where narratives already live. The lie that spreads most easily is the one we are most ready to believe.

The glitch in those welfare-mom videos was not the missing limb. It was how quickly belief arrived. The pixels gave out before the prejudice did. Technology did not invent the impulse; it helped it breathe. The fox was not fooled. It chased the tale it already knew by heart.

What breaks that training is not a better algorithm but a reawakened public — citizens who remember they can build rather than react, who recognize that the future is not predicted by models but constructed by movements, and who refuse to let convenience masquerade as reality. This moment carries that possibility. Not guaranteed. Not gifted. But available.

The story will change when we stop mistaking repetition for truth, inevitability for order, and participation for scrolling. The fox can learn new instincts — but only if we stop feeding it the old tale.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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Energy Without Duration

We have learned to control energy from the atom, but not the energy of our own passions.
— Freeman Dyson

We mastered the atom’s chain reaction but not our own — the reaction that sustains a civilization. We can still unleash energy, but no longer sustain it.

When Plant Vogtle Unit 4 finally entered commercial operation in April 2024, it was hailed as proof that America could still complete something large. The Vogtle expansion—Units 3 and 4, the first new U.S. reactors in more than three decades—took about fifteen years and cost over $35 billion, more than double its original budget and nearly a decade past schedule.

During the same period, China brought more than forty new reactors online and began construction on two dozen more—many based on the AP1000 design originally licensed from Westinghouse. That same design’s troubled U.S. projects at Vogtle and V.C. Summer Nuclear Generating Station helped drive Westinghouse Electric Company into bankruptcy in 2017, after billions in overruns and missed deadlines.

Westinghouse’s fall was not merely corporate but civilizational: the failure of a system that forgot how to build — a political economy that fractured coordination between state and market until neither could sustain the long rhythms of industry.

The turbines turned, but the rhythm that once made such projects routine was gone — not through loss of knowledge, but through the erosion of time itself, as a society mistook capital for continuity.

A reactor measures more than power; it measures a nation’s capacity for coordination. Mid-century America once did this instinctively. The Tennessee Valley Authority, NASA, and the Atomic Energy Commission fused public mandate with private execution, preserving institutional memory across generations. That circuitry has since been dismantled. The nation that poured the Hoover Dam in five years now struggles to replace a bridge in ten.

The problem is not technical decay but organizational entropy. Building is a chain of knowledge — and America broke the link.

The Entropy of Capital

A reactor that takes a decade to build and forty years to repay is invisible to markets tuned to quarterly returns. The neoliberal era’s deregulation of utilities and energy markets absorbed market logic into governance itself, outsourcing coordination to capital and calling it efficiency.

When Plant Vogtle’s costs spiraled, investors fled even though its output was guaranteed for decades. Markets priced uncertainty, not necessity. Venture-capital portfolios fund prototypes, not permanence. Silicon Valley can design ten apps in a year but cannot finance a grid, a foundry, or a port.

Even if markets could think in decades, they shouldn’t be trusted to. To privatize continuity is to privatize direction — to let the future be set by whoever can raise the most money this quarter. The result is not planning but auction.

Knowledge now erodes faster than technology evolves. Every project begins in amnesia. The cost is not only money but memory — the loss of institutions able to think beyond an election cycle.

While China coordinates its energy transition, the United States dismantles its own. Under successive administrations, federal oil-and-gas leasing expanded while renewable approvals lagged. The so-called “energy emergency” accelerated fossil-fuel production even as China built the future.

Energy, like memory, decays when it is not renewed.

Becoming Death

The United States still understands long-term coordination in one place: the Pentagon. Each year, the military defends redundant tank and bomber production on the grounds that if the factories close, the capability disappears. Congress sustains production lines not for efficiency but for endurance, because closing them would erase the muscle memory of industry itself.

In a landscape where public works rot and energy grids falter, defense manufacturing alone operates on decadal horizons. Its contracts stretch across administrations; its supply chains map the entire continent. A single weapons program can employ hundreds of subcontractors, each one a microcosm of continuity—furnaces that must never cool, apprenticeships that must never lapse. The machinery endures so that the act of endurance itself does not die.

Programs like the Abrams tank or the B-52 bomber survive through upgrades, not necessity, their obsolescence deferred in perpetuity to keep foundries and forges alive. The defense base functions as a parallel economy, one of the last arenas where the state still plans, synchronizes, and remembers across generations. It maintains inventories of rare metals, subsidizes precision machining, and trains the technicians who would otherwise vanish from the national genome of skill.

Here, the habits of mid-century industry still exist—but only in service of annihilation. The Pentagon behaves as a command economy disguised as a market: a planner that never admits to planning. It justifies continuity not as strategy but as security. Where civilian projects stall in budget cycles, the arsenal proceeds by inertia, its appropriations defended as existential necessity.

In a sense, the Pentagon is America’s last five-year planner. Its orbit of think tanks, contractors, and logistics firms sustains a shadow version of the coordination once used to build dams, reactors, and highways. The techniques of creation have been transferred intact to the technologies of destruction.

The irony is total. The state preserves its capacity to destroy in order not to lose it, while its capacity to build withers for want of the same design. The industrial arts that once raised a continent now survive only to maintain the instruments of its undoing. What the arsenal remembers, the republic forgets.

Sustained Criticality

China’s Fourteenth Five-Year Plan calls for seventy gigawatts of nuclear capacity by 2025 and another hundred and fifty reactors by 2035. These are not aspirations but instructions—translated into budgets, contracts, and manufacturing schedules. What mid-century America once achieved through the Tennessee Valley Authority, China now repeats with bureaucratic precision: a society that has mastered the long half-life of coordination.

In physics, a reactor reaches sustained criticality when each reaction generates the conditions for the next. Politically, one nation has achieved something similar. What was once imagined as perpetual revolution has settled into perpetual coordination—a continuous reaction converted into budgets, timetables, and concrete.

By 2024, clean-energy industries—spanning nuclear, solar, wind, storage, and electrified transport—accounted for just over ten percent of China’s GDP, generating roughly US $1.9 trillion in output. According to data compiled by the Centre for Research on Energy and Clean Air and Carbon Brief, this “new energy economy” has grown into one of the country’s most dynamic sectors, driving investment and exports alike.

Nuclear power anchors the grid’s baseload stability. Since 2010 China has completed nearly forty reactors, with more than thirty still under construction and a dozen advanced designs—such as the Hualong One and CAP1400—progressing from prototype to deployment. Each program sustains the next; each reactor seeds the following one. Growth and governance now move in tandem, joined by a shared industrial logic that treats technological continuity as national strategy.

From the outside it seems rigid; inside, the rhythm is alive. Budgets, permits, and research grants are synchronized like circuits in a single machine; supply chains for concrete, turbines, and fuel rods are sequenced years ahead. What appears static from afar is, within, a pulse—the steady burn of a system that never cools.

The American model prizes theoretical efficiency over endurance. It assumes competition can replace coordination. It cannot. A system that treats learning as waste will eventually forget how to learn—and then how to build.

China has turned time itself into a resource, compounding it through repetition. The West still treats time as a cost to be minimized; China treats it as capital to be invested.

The Unmade Sun

Fusion was supposed to prove that humanity could still imagine beyond the market. For decades it stood as the last collective dream of science—too slow for venture capital, too uncertain for privatization. It promised abundance without extraction, energy without decay. Then public funding ebbed, and fusion became an industry of startups: a constellation of private experiments orbiting a vanished center.

The dream did not vanish; it fragmented. What had once been a single national horizon divided into proprietary frontiers. Dozens of companies now chase confinement with different machines, magnets, and investors. Each holds a fragment of the reactor that might have been whole. Progress continues, but without memory—every breakthrough repeats an old one forgotten in a merger, a rebrand, or a fiscal quarter.

China’s program remains an exception. Anchored by the EAST tokamak and the coming CFETR reactor, its approach is cumulative: universities, enterprises, and grid operators working within one continuous plan. Competition exists, but it is disciplined—contained within the state’s architecture of coordination. Firms innovate, but toward shared milestones; rivalry is permitted as an engine of refinement, not fragmentation. EAST has already held plasma for over a thousand seconds; CFETR aims for grid connection in the 2030s. Each project sustains the next, like reactions within the same vessel.

The pattern extends beyond fusion. In semiconductors, the same philosophy applies: coordination without stagnation, competition without chaos. Faced with Western export controls, China treats chip fabrication not as crisis but as infrastructure—a discipline of time. State funds underwrite lithography; research institutes train process engineers; national labs link design with production.

Both fusion and semiconductors demand what markets cannot supply: patience. They reward continuity, not brilliance. Both nations chase the same frontiers of physics; only one is structured to persist long enough to reach them.

The sun we sought to build still flickers, scattered among laboratories and venture decks. The energy exists, but not the vessel to hold it. The future glows, but never forms—a light without a core, an unmade sun.

What fails in the vacuum of fusion repeats in the fabric of civilization: when energy loses its vessel, time begins to leak. The decay starts not in physics but in memory, as the crafts that once held continuity cool into silence.

The Decay of Continuity

Every civilization is a reactor: its stability depends on whether the chain of renewal can sustain itself. Industrial knowledge has a half-life. Without repetition, it cools, and the reaction slows. The welders who once shaped reactor vessels have retired; the factories that forged them have been dismantled. Each generation starts again, relearning what the last already knew. The result is not ignorance but interruption.

Suppliers once certified to forge nuclear-grade steel have fallen from dozens to a handful. Apprenticeships that trained thousands now survive mostly as memories—programs without practice, records without renewal. Institutions endure in form but not in sequence; they persist without pulse.

A society does not lose its capacity to build in an instant. It unlearns gradually, as the intervals between projects grow too long for experience to pass from one to the next. Skills atrophy, procedures become paper, and coordination collapses into isolated acts too brief to accumulate.

Continuity is an infrastructure unto itself—the unseen medium through which knowledge circulates, like coolant through a reactor. When that flow stops, the system overheats: memory burns away, and institutions drift toward entropy. The wealth remains, but duration is lost.

To rebuild that rhythm is not only a technical challenge but a democratic one. Continuity is the civic reactor core—a vessel built to contain the energy of collective work, to channel it rather than dissipate it. It requires institutions strong enough to hold pressure, and stable enough to outlast a single generation.

Markets allocate capital; democracies must learn to allocate time. Without that capacity, even abundance decays into heat, and liberty itself becomes momentary—a freedom that forgets how to endure.

The Continuity of Freedom

China’s ascent is not destiny, and America’s decline is not terminal. The difference lies in continuity, not genius. One system compounds experience; the other dissipates it.

Reclaiming the long view does not mean imitation. It means restoring the idea that collective planning is a civic skill — a democratic form of persistence. Continuity itself must again be treated as a public utility: the means by which a free society remembers how to build.

This is what a true abundance movement should mean. Not the libertarian fantasy of infinite markets but the civic practice of infinite renewal — a society that invests in capacity the way it once invested in capital. An entrepreneurial state would not crowd out private initiative; it would make it cumulative. It would take risks at scales individuals cannot and build patience into policy.

Abundance is not the proliferation of products but the continuity of capacity.

The United States still has the materials, the engineers, the capital. What it lacks is duration — the will to finish what it starts, to think in decades instead of quarters.

The half-life of opportunity shortens when memory fails; it lengthens when a nation regains the courage to plan, to build, and to endure its own ambitions. That is not ideology. It is survival.

You cannot escape the responsibility of tomorrow by evading it today.
— Abraham Lincoln

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CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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“They knew. They knew the taxpayers would bail them out. They weren’t being stupid; they just didn’t care.”
— The Big Short (2015)

There is a scene in The Big Short that still feels like prophecy. As the housing market collapses, a banker turns to the camera and admits that the whole thing was built on faith — faith that the numbers meant something, faith that the system couldn’t fail because it never had. It was a con of belief, not math.

That same fever — first mortgages, then modems — now burns beneath the rhetoric of artificial intelligence. The same hunger that once promised homes for all — and later, connection for all — now promises intelligence for all. Every era sells its miracle: the mortgage, the modem, the model. And each time, we are told that this one will redeem the last. Strip away the language and reality begins to melt — speculation takes the shape of salvation, hype hardens into strategy. Once, Wall Street packaged our homes; now, Silicon Valley packages our intelligence. Both sell the same illusion — that if we just believe hard enough, the system consuming us will somehow set us free.

There is a strange miracle in what we call the market. Every dollar, every share, every speculative bet represents something vast and human: our collective labor, our choices, our potential. The money that moves through Wall Street and venture funds is not abstract; it is the summation of our past labor and the collateralization of our future. It is our time, our creativity, our hopes — rendered tradable, then molded by those with the wealth to decide their worth.

When capital chases “intelligence,” it practices a new kind of alchemy: transmuting human thought into speculative gold. Each model is trained on our collective past — our voices, our labor, our words — and returns as something that claims to surpass us. The miracle, we’re told, is that machines can think. The truth is simpler and stranger: they only think because we already did.

We hear from Democrats and Republicans alike that the problem is greed — a moral failing, they say, rather than a structural design. But what system have we built other than one that glorifies it? The billions pouring into AI are not “new money”; they are the residue of our collective labor, recycled into a machine that promises efficiency while eroding the meaning of work itself. Something of value will emerge from this frenzy — just as the dot-com bubble left behind the infrastructure of the modern web — but we should be honest about what these manias are. They are moral decisions disguised as market logic: our shared labor repackaged as profit, our common future traded for someone’s gain.

And yet, without this latest speculative boom, our economy might already be in recession. The market’s vitality depends on its next story, its next frontier — and so we inflate another balloon. In 2024 alone, private U.S. investment in artificial intelligence reached roughly $109 billion, according to Stanford’s AI Index Report 2025, and major firms are now committing hundreds of billions more to AI infrastructure and data centers in 2025. For comparison, researchers estimate that ending homelessness nationwide would cost on the order of $9–30 billion a year; clearing the public-transit repair backlog would require about $140 billion; and cancelling student debt for millions of Americans could cost anywhere from $300 billion (for a $10,000 per-borrower plan) to over $870 billion. These are not impossible sums; they are simply directed elsewhere. The problem is not that we invest in technology — it’s that we do so to avoid investing in one another. We could rebuild public transit, deliver universal healthcare, cancel student debt, end homelessness — all projects of collective possibility — but instead we feed the circus. We reward those who promise salvation through algorithms while punishing those who simply demand dignity through policy. And if AI spend is today’s growth engine, it is also today’s concentration risk — a stimulus routed through a handful of firms, data centers, and supply chains.

The defenders of this frenzy will tell us to look forward — to think of the productivity gains that will surely justify today’s excess. It is, they insist, short-sighted to critique the future before it arrives. But history is not a ledger that balances itself. Productivity gains are not moral gains; they are distributed, like everything else, according to power. The Industrial Revolution doubled output but also deepened inequality. The internet democratized information yet concentrated ownership. Efficiency rose; bargaining power fell.

None of this means progress is futile. Real advances will come from AI — in medicine, in research, in the dull work of bureaucracy. But we should not mistake output for outcome. The measure of progress is not how quickly we can produce, but how fully we can live. Productivity is only liberation when it frees time for care, creativity, and collective flourishing. Otherwise, it is just acceleration — movement without direction, growth without meaning.

Beneath the tent, the showman smiles and tells us we’re having fun — that the chaos is part of the magic. But behind the applause, a quieter feeling lingers: this isn’t wonder; it’s surrender.

I am no Luddite. I believe deeply in using technology to make our lives better — to shorten the distance between people, to relieve us from drudgery, to open time for meaning and care. But that’s not what this is. What Silicon Valley calls “progress” is often a reshuffling of burdens — a promise of liberation whose costs are borne by everyone but the liberated. AI is not inherently the enemy. The enemy is our inability, or unwillingness, to direct its fruits toward the collective good. It is not the code that corrupts, but the context that consumes it.

Assemblyman Zohran Mamdani captured this tension perfectly when he told a crowd in New York:

“We have been told that change is not yet quite possible, that it’s not yet our turn… My friends, we are not afforded the luxury of waiting, because too often to wait is to trust those who delivered us to this point.”

What Mamdani calls for is more than political imagination — it is a politics of refusal, of faith made action, of people reclaiming the power to decide what the future is for. The ruling class has merely changed its costume. The bankers became venture capitalists; the venture capitalists became visionaries. The same men who built temples to debt now build temples to data, learning that belief is more valuable than truth. Yesterday they sold us the dream of universal ownership; today, the dream of universal intelligence. Each collapse births a new faith; each failure is repackaged as the next frontier. They call it innovation. We call it déjà vu.

But faith is not imagination — it is surrender disguised as hope. The question before us is not whether AI will “change everything,” but whether we will allow the same forces that profited from the last collapse to define what change means. Capital always finds its next frontier: land, labor, data, currency, cognition. What it cannot reproduce is will — the collective will to direct progress toward the public good rather than private gain.

For all the talk of transcendence, today’s machines are not thinking in any meaningful sense — they are pattern engines, fluent mimics trained to predict what sounds right, not what is true. They interpolate within the past but cannot imagine beyond it. What we call “intelligence” is mostly scale: more data, more parameters, more power drawn from the grid. The result is not cognition but compression — a mirror polished by our own reflections. Yet on this fragile scaffold of imitation, an entire economy of faith has been built, trading comprehension for confidence, and verification for valuation.

And what have these miracles yielded? A torrent of synthetic content and algorithmic noise — tools built less to enlighten than to extract, refining the art of persuasion into a quieter advertising, a subtler surveillance, mining not only what we see but what we think.

Once, technology was sold with the promise of leisure — shorter days, lighter work, freedom from drudgery. No one says that anymore. The language of emancipation has vanished, replaced by the rhetoric of disruption, regulation, and fear. We are told that artificial intelligence might end civilization or save it, depending on who controls the narrative. The result is the same: a politics of panic that consolidates power in the hands of those already trusted to manage risk.

The dot-com boom promised liberation through connection; the financial bubble promised security through ownership; the AI boom promises transcendence through intelligence. Each framed its miracle as inevitable. Each was built on the same moral deficit — the refusal to imagine a world where progress is measured not by valuation, but by how well it meets our common needs.

“Not everything that is faced can be changed, but nothing can be changed until it is faced.” — James Baldwin

The task, then, is not to resist technology but to reclaim possibility — to treat innovation not as spectacle but as stewardship. The resources exist; every crisis proves that when the will is found, the funds appear. The question is not how we will pay for it, but who it will serve.

In the end, every bubble bursts, every circus folds. What remains is the work — the unfinished labor of turning faith into will, and will into the common good.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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“The spectacle is not a collection of images, but a social relation among people, mediated by images.”
— Guy Debord

Something I’ve struggled with as an engineer is how real problems get eclipsed by the glitz of image and narrative. Marketing has a place; I don’t discount it. However, too often it overrides reality. The story that wins is the one that closes the deal, convinces the client, drives the sale, and lifts profit or the valuation multiple, not the one that best serves customers, society, or the problem itself. People often start in good faith: what begins as an honest attempt to translate the work for outsiders becomes theater. To make it sell, the truth gets bent or broken, and accountability shifts from delivering results to delivering optics and returns. Then KPIs become the job, and the metric replaces the mission.

This shows up outside tech as well. In nonprofits, funders favor whatever’s “hot”—the rebrand, the gala campaign, the ribbon-cutting for a new wing, a celebrity partnership or awareness blitz, the app or “AI pilot”—while maintenance of the systems that already serve people goes unfunded. This is the nonprofit starvation cycle: unrealistic expectations starve core operations, capacity erodes, results slip, and the underinvestment deepens. Value that could compound through upkeep never gets the chance.

Inside organizations, teams end up relating through slide decks, objectives and key results, and brand guidelines; the image layer starts setting the rules. A tool that’s good enough is sidelined for something more photogenic—more maintenance, more cognitive load, weaker integration—because the latter reads better in a pitch. We joke about “solving” fragmentation by adding yet another standard, and the joke lands because we’ve all seen it.

Image beats reality until it hits the pavement. ShotSpotter is marketed as high accuracy, near instant gunfire detection sold by the square mile, with glossy dashboards and a promise to fill gaps in 911 calls. Chicago’s inspector general reported that fewer than 1 in 10 alerts produced evidence of a gun crime. By late 2024 the city moved to end the contract. Officers were chasing alerts that rarely became cases, which pulled time from victim services and from real hotspots.

UnitedHealth’s naviHealth was marketed as algorithm-guided “right care, right setting,” promising faster discharges and less waste. Reporting and litigation allege it helped drive improper post-acute denials. A federal judge let a class action proceed in 2025, and policy work has documented broader denial patterns. Whatever is ultimately decided in court, the episode shows how models and metrics can outrun oversight.

Hyperloop was pitched as near-supersonic, privately funded transport that would leapfrog rail. What cities got were letters of intent, renderings, and a test track—not an operational route. The company shut down in 2023 without ever winning a contract to build one. In Los Angeles, a separate fast-tracked Boring Company “test tunnel” was dropped after a lawsuit. Net result: public attention, staff time, and scarce dollars chased photogenic promises while needed upkeep and proven transit waited.

Even research and measurement aren’t immune. “Surrogation” is what happens when a proxy for a goal becomes the goal, and teams optimize the number instead of the purpose. Think daily-active users instead of task completion, click-through instead of informed reach, test-coverage percent instead of the number of defects escaping to users. As Harvard Business Review notes, badly governed metrics can replace the strategy they were meant to represent.

Another pathology is when the story outruns verification. The MIT economics preprint Artificial Intelligence, Scientific Discovery, and Product Innovation drew wide attention in late 2024, in the churn of the AI hype cycle. On May 16, 2025 MIT’s Committee on Discipline said it had “no confidence in the provenance, reliability or validity of the data,” and on May 20 arXiv withdrew the paper. This is the hype loop in miniature: the image of a breakthrough outruns the truth, attention converts to citations, press, invitations, and funding. It pulls individuals, institutions, and audiences into feeding the hype, while the wider public shoulders the consequences and the few capture the gains.

What we reward is what we repeat. Regulation decides what actually pays. Regulators have started to notice the image over reality gap, particularly around AI. In late 2024 the U.S. Federal Trade Commission launched “Operation AI Comply,” a sweep against deceptive AI claims, and continued actions into 2025, including an order restricting “robot lawyer” marketing. Enforcement isn’t culture change, but it does reset the minimum for tying claims to truth.

Left alone, spectacle becomes a hype-extraction loop. For some actors it slides into outright grift, because attention mints capital faster than outcomes arrive.

So what can we do about it, practically, not performatively?

The hinge is governance. If money clears on optics, optics will govern; tie money to outcomes, and reality will instead. Change those structures, and you change the work. Inside the room, run the work democratically and transparently so the mission can’t be swapped out for the storyline. Give the people doing the work a real say in prioritization. Budget for stewardship—data hygiene, monitoring, retraining, incident response. Write explicit exit ramps for pilots that don’t deliver. Measure success by how the system behaves in production—reliability, safety, and user outcomes—rather than the beauty of the quarterly slide. When Prime Video’s engineering team showed that collapsing a chatty distributed service into a simpler architecture cut costs by about 90% without hurting outcomes, the lesson wasn’t “microservices bad.” It was “let the problem, rather than the fashion, choose the architecture.”

Outside the room, align incentives to reinforce these habits: fund maintenance by default; let grants reward negative results that prevent waste; require auditability and a real appeal path in high-risk settings. Without counterweights, attention and quick-win incentives crowd out facts: labs selected for flash over rigor yield more false positives, press-release overstatement is mirrored in news coverage, and on social platforms false stories travel farther and faster than the truth.

This is also where democratic ownership ties inside to outside. Worker cooperatives and broader employee ownership put voice and accountability where the work is; across many studies, these models are linked to higher productivity, better pay, more job stability, and firm survival. Steward-ownership moves on a different axis: it locks mission in law, separates voting control from profit rights, can cap returns, and constrains sale so purpose isn’t arbitraged. There are working hybrids:

• Mētis Construction in Seattle operates as a worker cooperative held in an employee/worker-ownership trust designed for the long term—day-to-day power stays with workers while the mission is legally anchored.

• Equal Exchange, a worker co-op, brought in outside capital through non-voting investor shares while keeping one-worker/one-vote and limits on voting rights—classic guardrails against demutualization.

• Organically Grown Company shifted to a perpetual purpose trust with a multi-stakeholder governance board to preserve independence and align profits with purpose.

• Firebrand Artisan Breads adopted an employee community ownership trust with worker and community representation to lock mission and broaden voice.

None of this requires demonizing individuals. The system selects for spectacle because spectacle clears the next gate: a sale, a grant, a quarter. Our task is to rebalance the system so that truth clears the gate instead. Fund stewardship as a first-class deliverable. Publish preregistered outcome targets and retire pilots that miss. Keep metrics auditable and tied to user outcomes. Design ownership and governance so the mission cannot be arbitraged for optics. Enforce claims so marketing cannot sprint ahead of reality without consequence. Do that, and the plain voice we hear in meetings, the one that says fix the workflow before adding another feature, stops sounding naïve and starts sounding like the plan.

The point isn’t to reject marketing, AI, or any particular tool. It’s to bring truth back to the center, align means with ends, and protect teams from the kind of debt that begins as a headline and becomes an operational burden. When image no longer runs the work, engineering stops being performance and returns to craft. The spectacle loosens its grip, and the simple voice—let us do the right thing—finally has room to be heard.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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There’s a kind of digital abuse you don’t notice until you’re inside it.

My first encounter was with an automated call system: the voice polite, the script thorough, the options neat—yet each choice narrowed me into categories that didn’t fit. “Zero” for an operator did nothing. It was like shouting into a void—present, speaking, and somehow still not there. It doesn’t arrive with force, but with persistence—intrusions that teach you, over time, your consent is optional. In the moment, it feels like nothing; only later do you register the aftertaste: a slip in your defenses, an intrusion disguised as normal.

That call system taught me the template: options as ceremony, routing as law, delay as enforcement. Escalation is taxed until it dies; the system only recognizes problems it has budgeted for. Anything outside that map is redirected until it disappears. On paper, you had a choice; in practice, your boundary was treated as a cost to be engineered away.

Online, I began to see the same template everywhere. In the mid-2000s, autoplay videos re-enabled themselves after you shut them off. Email “preferences” flipped back on after updates. Privacy settings, once buried in menus, would reset after a redesign. At first, you could tell yourself it was a bug or a fluke. But the pattern repeated until it was unmistakable: not an accident, but the model.

Over time, it left a mark: a slow loss of self and control, the sense that your place in the system was always provisional—a bruise that fades just long enough for you to forget, then returns in a different interface with the same pressure.

We’ve already lived through three acts of the same play.

Act I: Ad blocking. Installing a blocker once felt like a clean win: pages loaded faster, pop-ups vanished, the sense of being watched eased. But publishers built anti-adblock walls, ads slipped in as “native” content, and trackers moved into invisible channels. When blockers still worked too well, Chrome’s Manifest V3 weakened them further. Refusal didn’t stop extraction; it taught the system how to extract differently.

Act II: Do Not Track. Around 2010, browsers offered a polite request: “Please don’t follow me.” Compliance was voluntary, and the big players ignored it. Tracking migrated from cookies to device fingerprinting and stitched identities. Even Apple’s “App Tracking Transparency” didn’t stop the underlying economy—Meta used dark patterns to push “agree” and redefined tracking as measurement so data kept flowing. Again, “no” was just a routing instruction.

Act III: Don’t train on my data. In the 2020s, the promise is to keep your voice and style out of the model’s mouth. The moves are the same, only scaled: scraping from mirrors and caches, leaking paywalls, repackaging datasets. Watermarks are stripped or ignored. Even when a setting is honored, there’s no universal enforcement, and unlearning is rare and costly. The “no” still isn’t an endpoint—just another signal for how to keep going.

In every act, the rituals repeat: click “No,” flip the toggles, watch the ground shift. A feature refuses to work unless you concede. A “Not now” button replaces “No.” Menus reorder, old paths disappear. You aren’t adopting features; you’re being conscripted into a roadmap.

AI raises the stakes because the bruise is no longer about being handled—it’s about being replaced.

Extraction now stops at nothing less than imitation: your cadence, your style, your gestures—turned into parameters. Where ad tech made you visible to buyers, model training can make you optional to them. A version of you exists without you, summoned on demand, confident and hollow. Each output—an email in your tone, a portrait in your style—is ventriloquism dressed as assistance, flattering until it takes your place.

One scrape spawns a thousand derivatives. Training is opaque, provenance blurs, unlearning is partial at best. You can delete a post, but your voice remains in the weights. Companies claim they didn’t train on your file—because they trained on a mirror, a cache, or a synthetic clone. “Style transfer” becomes the euphemism for appropriation.

And the economics flip: where visibility once raised your value, imitation erodes it. Credit is optional, payment exceptional, and permission something added after the fact. The operating principle hasn’t changed: consent is an obstacle, respect is discretionary, and the constitution is written for profit. We don’t just live in private platforms; we live under private governments, where the law is the business model and the citizen is the product.

In the offline world, erosion of rights moves slowly—measured in years of policy shifts, regulatory rollbacks, or corporate mergers. You might notice when a neighborhood library closes, when public transit raises fares, when a park is fenced off. On the internet, the same erosion happens at the speed of an update. One morning a feature is free; by evening it’s throttled, paywalled, or gone. The cost is the same: a public space quietly privatized, a common good turned into a gated one. The difference is pace. Online, rights don’t decay—they vanish.

In private governments, the master key is four words: terms subject to change. It’s the clause that voids every safeguard the moment it becomes inconvenient, the magic spell that turns “no” into “not anymore,” “private” into “shared for your benefit,” and “included” into “now behind a paywall.” It makes every right revocable, every promise conditional, every win temporary. A real digital democracy would lock that door—decisions are made with the public, not for them; not by silent updates to the code or the fine print.

Beyond Toggles: Building Digital Democracy

Respect can’t be a setting you have to keep turning back on. It has to be built into the constitution of the platform—limits no CEO, update, or profit motive can cross.

Law can draw those limits: make “public” mean licensed, not free to harvest; make opt-in the default; make extraction without consent more expensive than restraint. It can demand a supply chain for data—provenance, licensing, and the ability to revoke permission that travels wherever your data does.

But law alone will always trail the frontier. That’s why we need democratic ownership of the means of computation: the data, the models, the infrastructure. On a collectively owned platform, refusal isn’t a courtesy to be engineered around—it’s a survival rule. Consent becomes a contract we write together, enforced by charters we elect and budgets we control.

Digital democracy isn’t a metaphor. It’s clouds that serve schools, libraries, and newsrooms without auctioning their attention. It’s charters that ban surveillance resale and facial recognition, and make those bans enforceable in code. It’s unlearning budgets for when harm is found, and genuine exit rights—export, deletion, kill switches—that don’t depend on who owns the server this quarter.

We’ve lived long enough under the corporate state of the internet to know its defaults will never favor refusal. The bruise won’t fade until the constitution changes—until the people who live here also write the rules. Respect is architecture; ownership pours the concrete. Without both, “Don’t train on me” stays a plea. With both, it becomes a boundary the system cannot cross.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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The United States has never lacked for technological imagination. From the creation of the internet to the mapping of the human genome, public investment has been the force behind many of the breakthroughs that now define our economy. As economist Mariana Mazzucato has shown, the state has often acted not just as a fixer of market failures, but as the first mover—funding risky, long-horizon innovations that private capital wouldn’t touch.

But time and again, the financial rewards from those public investments have flowed in only one direction: toward private capital.

The internet itself was developed with billions in public research through DARPA and the National Science Foundation, yet today we pay monopolistic telecoms and rent-seeking platforms to access the digital infrastructure we already paid to build. The Human Genome Project cost U.S. taxpayers over $3 billion, but its breakthroughs were quickly privatized by biotech firms that locked up key tools behind paywalls and patents. Google’s original search algorithm was funded by a National Science Foundation grant. Tesla’s critical early years were underwritten by a $465 million Department of Energy loan. The U.S. government invested at least $31.9 billion— decades of foundational research, clinical development, manufacturing, and direct purchases—to make mRNA COVID-19 vaccines possible. Moderna alone received nearly $2.5 billion in direct public support, while building on NIH-co-invented mRNA science. Yet the company later quadrupled its vaccine price and declined to share patents, profits, or licensing rights with the public institutions that made its success possible—despite the potential of this technology to save millions more lives in future pandemics and beyond.

Venture capital (VC) and private equity (PE) have perfected a flywheel: a self-reinforcing machine that turns money into ownership, ownership into political power, and power into more money. Public institutions, by contrast, rarely keep a seat at the table once the innovation is proven. They fund the early risk, but when it comes time to scale, the work is sold, licensed, or spun out into private hands. The public takes the risk. The private sector takes the reward.

No company has embodied this strategy more fully than Amazon. It engineered it into the core circuitry of its empire. Amazon reinvested nearly all of its early profits into warehousing, logistics, infrastructure, and data capacity. This allowed it to offer low prices and fast delivery, out-competing rivals not just on convenience, but on sheer infrastructural scale. It then extended that model into cloud computing, building Amazon Web Services (AWS)—now the dominant cloud platform—on top of internal infrastructure, and turning that control into pricing leverage over the very startups and competitors it hosted.

Amazon’s flywheel wasn’t just financial. It was infrastructural and extractive. By controlling logistics, data centers, retail interfaces, and labor conditions, Amazon created a system where each layer reinforced the next—and where competitors found themselves trapped within an ecosystem they couldn’t escape. The more Amazon grew, the more power it accumulated over markets, labor, and even public policy.

And Amazon wasn’t alone. This model helped elevate a new class of billionaire–executives—Jeff Bezos, Elon Musk, Mark Zuckerberg, Peter Thiel—whose fortunes were built atop publicly seeded technologies but who now wield private sovereign power. They shape global labor markets, influence national elections, control satellite networks, manage internet infrastructure, and direct AI research at planetary scale. They answer to no electorate, no regulatory framework, and no democratic process.

Ironically, these titans of the “free market” operate more like central planners than capitalists. Amazon, Meta, and Google are not marketplaces—they are private command economies. They set prices, direct logistics, coordinate production, and manage labor at a scale that rivals state apparatuses. Their vast infrastructure is governed not by competitive dynamics, but by internal software systems, algorithmic control, and top-down directives. They have achieved what 20th-century governments only dreamed of: seamless, real-time coordination of information, goods, and labor across billions of users and millions of suppliers. But unlike public institutions, their planning capacity is used not to meet collective needs, but to extract value—enriching shareholders and concentrating control.

This is the power of the flywheel: each success makes the next one easier. But right now, it’s spinning in the wrong direction—concentrating wealth, eroding democracy, and enclosing the very technologies that were created with public resources.

If we want AI, cloud computing, broadband, and the rest of our digital foundation to serve the many rather than the few, we need to build our own flywheel—actually, we need two: one public, one cooperative. These funding engines, rooted in the principles of democratic ownership and reinvestment, can ensure that the next generation of infrastructure is not just publicly funded—but publicly owned, governed, and scaled.

The Public Funding Flywheel

To build a democratic digital economy, we must reclaim a simple truth: the state is not just a funder of innovation but a builder of it. As Mariana Mazzucato has shown, the public sector has long shouldered the highest-risk, longest-horizon bets in modern economic history—from aerospace to clean energy to biotechnology. What’s been missing is not ingenuity, but a way to retain the value those investments create.

Rather than handing off the most strategic breakthroughs to the private sector, the public can act as a long-term investor and partial owner—financing the scale-up of critical technologies and recycling the returns into future rounds of innovation. This is the heart of the public funding flywheel: a self-sustaining engine where public capital builds infrastructure, infrastructure generates revenue, and that revenue finances the next generation of public investment.

This concept is vividly illustrated in the television series For All Mankind, where NASA evolves into a self-funding agency. In an alternate history, the U.S. government allows NASA to retain and reinvest profits from its operations and license its technology. The revenue cycle not only finances further space missions but transforms NASA into a powerful, mission-driven institution capable of competing with privatized space ventures. While fictional, it offers a compelling blueprint: public ownership paired with reinvested returns can generate enduring capacity.

In the real world, one partial analog is the success of Norway’s Government Pension Fund Global. Financed by oil revenues, the fund was designed not just to hold capital, but to grow it over time in service of public welfare. Though its investments are primarily financial, the model demonstrates how publicly generated wealth can be institutionally recycled for long-term benefit—and how public entities can act as savvy stewards of capital.

Instead of relying on one-off appropriations, this flywheel can be fueled by enduring funding streams: a slice of spectrum auction proceeds, equity retention clauses in federal tech procurement contracts, redirected pension fund allocations, technology bonds, or windfall taxes on monopoly profits. These resources would flow into independent public investment authorities, guided by clear public-interest mandates, insulated from short-term political pressures, and governed with transparency and accountability.

The targets of investment are clear: general-purpose infrastructure that underpins the digital economy. National-scale AI compute clusters. Public broadband fiber. Semiconductor fabs with public equity stakes. Open-source cloud platforms. These are the railroads, power grids, and water systems of the 21st century. Building and owning them publicly ensures not just efficiency, but democratic control.

As these assets generate service fees, licensing revenue, and equity returns, those funds flow back into the public tech fund, which reinvests in new infrastructure. Over time, this compounds—mirroring the growth dynamics of private venture capital, but with the gains accruing to the public as a whole.

Crucially, this model does not require heroics each budget cycle. Once seeded, the flywheel can operate with institutional momentum, delivering long-term capacity with short-term accountability. As Carlota Perez has argued, every technological revolution needs a "Golden Age" of broad deployment. But such an age doesn’t arrive by accident. It must be built—and financed—on purpose.

To succeed, governance matters. Public investment must be shielded from capture, mismanagement, and short-termism. That means professionally managed funds with citizen oversight, open audits, anti-corruption safeguards, and democratic transparency.

Done right, the public funding flywheel can anchor a new era of mission-driven innovation. It can ensure that the rewards of public ingenuity flow not to monopolies, but to the people who made them possible. And it can give us the financial architecture to match our technological ambitions—not just once, but again and again.

The Cooperative Funding Flywheel

Running parallel to the public model, the cooperative funding flywheel offers a democratic, decentralized path to building and owning technology. While the state aggregates capital through taxation and public investment, cooperatives empower members—workers, users, and communities—to pool their own resources, govern collectively, and reinvest in enterprises that meet shared needs. This approach rejects the logic of speculative exits and external shareholders. Instead, it roots capital in participation, long-term benefit, and values-aligned stewardship.

Cooperative capital can come from many sources: worker-owners pooling savings, communities seeking digital sovereignty, anchor institutions such as universities and hospitals seeking stable, ethical service providers. These sources reflect the ethos of platform cooperativism, as advanced by thinkers like Trebor Scholz and Nathan Schneider: applying cooperative ownership and governance to digital infrastructure, data-driven services, and the platforms that increasingly mediate daily life.

This model is already visible across the technology landscape. Cooperatives operate movement-rooted digital infrastructure: for example, May First Movement Technology—a nonprofit, democratically governed cooperative—provides shared hosting, email, file-sharing (Nextcloud), and web services on infrastructure collectively owned by its activist members. Similarly, Webarchitects offers managed hosting under cooperative governance. Other examples include community broadband networks like RS Fiber and People’s Choice, federated platforms like Mastodon, ride-hailing cooperatives such as the The Drivers Cooperative, and emerging models for worker-owned AI/data-labeling collectives. These initiatives often emerge where traditional platforms exploit labor, neglect communities, or prioritize surveillance and profit over community, trust, and service.

The flywheel dynamic emerges through reinvestment and replication. Members invest to start or grow a cooperative; the enterprise generates revenue through platform fees, subscriptions, or infrastructure access; surplus is split between dividends to members and reinvestment into the enterprise or broader ecosystem. Over time, mature co-ops begin to seed new ones—offering mentorship, technical assistance, shared infrastructure, or cooperative capital. Organizations like Start.coop, Seed Commons, and The Working World already embody this cycle, operating cooperative loan funds and accelerators that mirror the support functions of venture capital—without the extraction.

To scale, the cooperative ecosystem needs more than idealism. It requires access to patient, non-extractive capital; open-source tools and federated identity systems that reduce duplication; legal frameworks that recognize and support cooperative governance; and cultural visibility that presents cooperation not as niche, but as a serious and strategic path for founders and funders alike. If the public flywheel builds fiscal capacity, the cooperative flywheel builds civic capacity—the ability of people to organize, govern, and sustain the digital systems they depend on.

The Moment of Choice

We are standing at a pivotal threshold. Artificial intelligence, cloud infrastructure, spatial computing, bioengineering, and other emerging technologies are still in their formative stages—technically, commercially, and politically. Standards are not yet fully set. Markets are not yet fully captured. Governance regimes are still fluid. This is the window in which foundational decisions are made, not just about how these technologies work, but who they work for.

But the clock is ticking.

Once private capital locks up the infrastructure—through exclusive data access, proprietary algorithms, intellectual property fences, and hyperscale compute monopolies—the combination of network effects, capital intensity, and vertical integration will make it nearly impossible to dislodge them. We've already seen how this plays out with social media, cloud computing, app stores, and broadband: early public support or open access gradually collapses into corporate chokepoints, extractive pricing, and winner-take-all market structures.

AI is already trending this way. The training of frontier models is dominated by just a few firms. The GPUs are cornered. The model weights are closed. The APIs are rented. Even open-source initiatives risk becoming dependent on infrastructure layers controlled by Big Tech. If we don’t intervene now—with public investment and cooperative ownership—the rules will be written for us, by others, in terms that cannot be easily unwound.

This is a narrow but decisive window: a moment to seed the public and cooperative flywheels before the gates close.

And the choice we face is not a caricature between state-run bureaucracy and corporate monopoly. It is something more fundamental: do we want the foundational tools of the 21st century—AI, broadband, cloud, chips, and digital services—to be owned and governed by the few, or by the many?

• Do we want infrastructure that reinforces monopoly and surveillance—or infrastructure that empowers creativity, community, and care?

• Do we want a digital economy optimized for quarterly earnings and speculative exits—or one grounded in resilience, equity, and democratic participation?

The two-flywheel strategy gives us a path forward. Public capital can build and sustain the core layers of our digital future—ensuring accessibility, openness, and durability. Cooperative capital can animate those layers with services and applications that are responsive to the people who use and depend on them. Together, these flywheels compound not just capital, but capacity: the ability to shape our technological destiny from the ground up.

The VC and PE ecosystems have already demonstrated what happens when you design institutions for compounding returns. The problem is not the flywheel—it’s the direction it spins. We need to reclaim that logic, retool it for public and democratic purposes, and build a parallel innovation economy—one that doesn't treat extraction as success and exclusion as innovation.

This moment won’t last. The power dynamics of the next fifty years are being shaped right now. We can choose to be passive observers—outsourcing our future to monopolies—or we can build the institutions, infrastructure, and ownership structures that ensure a digital economy by and for the people.

The flywheels are ready. The choice is ours.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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I recently watched a thought-provoking video essay, The New Aesthetics of Fascism by Ben, a content creator from Germany. Many believe they’d recognize fascism if it returned — expecting uniforms, parades, and brute force. However, today’s threat is much subtler, even as the underlying principles remain the same. Technology, AI, and the design philosophies shaping our digital lives are converging to create a softer, more insidious form of authoritarianism— one masked by seamless convenience, corporate branding, algorithmic decision-making, and the polished veneer of bureaucracy. This “friendly fascism” doesn’t announce itself. It blends in through frictionless interfaces and familiar language, making it easy to overlook because we are still searching for the old warning signs. The danger is how effortlessly it becomes part of everyday life, reshaping our reality without any fanfare.

Ben presents a visually compelling and wide-ranging narrative, weaving together history, art, meme culture, the manosphere, and current events to show how aesthetics, technology, and politics can intertwine in unexpected ways. Whether or not you agree with every conclusion, it is a fascinating watch for anyone interested in the deeper forces shaping our digital age. I highly recommend watching it in full for its visual storytelling, excellent score, and the broader context, which cannot be fully captured in writing. Below are some reflections on the themes that resonated with me.

Serving Looks, Serving Power

Today’s tech aesthetic is built on clean minimalism, sleek branding, and a constant promise of progress. On the surface, it feels modern and open, reflecting the spirit of efficiency and ease. But this visual language carries echoes of the early 20th-century futurists — artists who celebrated speed, machinery, and industrial power, often in the service of authoritarian politics. Their glorification of force and hierarchy was overt; today’s Silicon Valley offers a softer, friendlier face. We see smooth surfaces and calming interfaces designed to invite trust and lower resistance.

Yet beneath this polished appearance, similar patterns of control and hierarchy still operate. Technology shapes behavior and reinforces existing structures of power, guiding users down managed paths. The veneer of convenience conceals algorithms and interfaces optimized for institutional interests, shaping what we see, how we interact, and even what we believe.

Older forces of militarism and authoritarianism don’t simply vanish when new ideologies or styles arrive; they adapt and persist. Just as remnants of feudal authority lived on within capitalism, today’s tech world still draws on motifs of force and control from earlier authoritarian systems. Companies like Palantir and Anduril blend advanced technology with national security, positioning themselves as leaders in algorithmic warfare. Their branding leans heavily on themes of strength, vigilance, and existential threat; recycling classic tropes of heroism and dominance in a digital form. In areas like autonomous weapons and defense-focused AI, the fusion of futurist style and militarism is unmistakable, revealing how old logics of power reappear under the guise of innovation.

The desire for control, however, extends far beyond defense contractors. Mainstream consumer tech pursues a subtler form of managed order, most famously in Apple’s “walled garden.” Here, comfort and predictability are achieved by hiding complexity and enforcing uniformity. The message is: "You will like it here," but the cost is a narrowing of autonomy and alternatives. Security and seamlessness are traded for confinement within boundaries defined by the corporation, discouraging dissent or deviation from the prescribed experience.

Nowhere is this orchestration of behavior and discourse more visible than on social media, especially in the evolution of Facebook and Twitter. Both platforms have shifted from open public forums to tightly engineered environments where algorithms dictate what users see, how conversations unfold, and even which ideas are permitted to circulate. Over the last decade, Facebook’s algorithm has consistently amplified sensational, divisive, and often far-right content, particularly on issues like trans rights, creating echo chambers and facilitating the spread of misinformation and hate. Investigations have shown that white supremacist and extremist groups continued to thrive on Facebook for years, often evading moderation or benefiting from weak enforcement. More recently, Meta’s decision to phase out professional fact-checkers in favor of crowd-sourced moderation has raised concerns about increased exposure to radical content, especially among older users.

Twitter has followed a similar arc, especially since Elon Musk’s takeover. Moderation was scaled back, previously banned far-right and extremist accounts were reinstated, and algorithmic biases toward right-wing content became more pronounced. Research has documented a sustained spike in hate speech, including racist, anti-LGBTQ+, and anti-Muslim slurs, and algorithmic amplification of right-wing voices and news sources. Recent policy and design changes—including paid “visibility,” trending topics, and opaque content moderation—have increased the reach of ideas and personalities once considered fringe or unacceptable in polite society. Through repeated exposure, what was once shocking has become normalized, eroding public resistance and shifting the boundaries of mainstream debate.

There is a deeper cost to this comfort and control. When unpredictability and dissent are designed out of digital environments, users are separated from the possibility of real agency and debate. Conflict and ambiguity are reframed as technical glitches, flaws to be optimized away. Tech companies, presenting themselves as neutral engineers of usability, recast complex social and political questions as problems for algorithms and moderation queues, rather than matters for democratic contestation. The result is a worldview that privileges order, efficiency, and predictability at the expense of dissent, pluralism, and authentic engagement.

This aestheticization of technology is never neutral. What appears to be the triumph of user experience is, in practice, the centralization of power and the narrowing of acceptable behavior. Human unpredictability—essential to democracy and creativity—becomes something to be managed and controlled. In this way, the tech aesthetic expresses not just a commitment to making life easier, but a deeper commitment to control—one that reaches far beyond the surface of our screens and into the structure of everyday life.

Memes & Machines

Layered on top of AI’s cultural flattening is the weaponization of irony and meme culture. Today’s so-called “friendly fascism” does not march in lockstep or shout through megaphones. Instead, it slips in through jokes, edgy memes, and shared online references. What starts as playful or provocative humor can, over time, become a powerful vehicle for spreading exclusionary and even authoritarian ideas.

Meme culture makes controversial or extreme positions feel unserious. Everything is "just a joke" or "just trolling." When critics push back, meme creators and communities quickly hide behind irony. If you take something seriously, you are accused of lacking a sense of humor or being "cringe." This dynamic does more than deflect real critique—it actively discourages honest engagement about genuinely harmful ideologies.

The effects go even deeper. The repetition of ironic or outrageous memes gradually shifts what feels normal. What was once shocking becomes a running joke, then background noise, and eventually just another part of the discourse. As time passes, the line between irony and sincerity gets blurry. People are left asking: is this for real, or just another bit? That ambiguity is deliberate. It gives cover for radicalization and plausible deniability for those spreading harmful messages.

Meme culture also builds strong in-groups, bonding people through humor, shared references, and even collective mockery of outsiders. This sense of belonging can make individuals more susceptible to adopting the group’s views, while outsiders—those who protest or point out harm—are labeled as humorless, overly sensitive, or even enemies. In this way, meme communities enforce boundaries, incrementally radicalize members, and create an environment where even the most fringe beliefs can feel mainstream.

The result: irony, memes, and “shitposting” are not just digital noise—they’re tools for softening extremism, desensitizing the public, and helping dangerous ideologies move from the margins to the mainstream, often without anyone noticing until it’s too late.

A Profitable Distraction

Today's endless culture wars are not simply organic societal disagreements. They are strategically profitable phenomena, meticulously engineered and amplified through digital media. Social platforms, with their engagement-driven algorithms, thrive on outrage and controversy. The constant churn of cultural conflict, often over symbolic, identity-driven, or sensational issues, keeps users locked into perpetual cycles of emotional reaction. This produces valuable clicks, shares, and comments. For tech companies, each new controversy means more user activity and more advertising revenue.

The consequences, however, reach far beyond commercial gain. By constantly steering public discourse toward emotionally charged but ultimately inconsequential debates, culture wars act as a smokescreen. This draws attention away from the structural realities that create deep social tension, such as widening economic inequality, systemic exploitation, the erosion of labor rights, diminished social mobility, and creeping authoritarianism. The more the public is locked in battles over symbols, identity, or "hot button" topics, the less energy remains for building coalitions to challenge power or pursue meaningful reform. In this environment, urgent conversations about healthcare, housing, climate, or democracy are drowned out by the latest manufactured outrage.

Manufactured polarization also erodes social cohesion. It fractures communities and pits people against one another along lines of identity, culture, and values, rather than shared economic or civic interests. Algorithmic sorting of content and friends on social media encourages us to see the world through an "us versus them" lens, deepening mistrust and making it harder to find common ground. As communities fragment, collective action and solidarity; essential for democratic progress, become much more difficult to achieve.

Ironically, as culture wars deepen these divisions, they also make people more receptive to authoritarian messaging. Populist and demagogic leaders step into the breach, offering narratives that promise a return to stability, order, and traditional values. These simplistic stories, usually anchored in nostalgia or fantasies about a better past, offer emotional comfort in chaotic times. But while they promise safety, they often lay the groundwork for rolling back rights, increasing surveillance, and concentrating power, which are classic hallmarks of authoritarian drift.

We should not underestimate how effective this dynamic remains. In recent years, politicians and media figures have turned culture wars over “wokeness,” school curricula, immigration, policing, and public health into tools for division and distraction; not genuine debate. These manufactured controversies are deliberately amplified to avoid addressing systemic failures in economics, social mobility, or power structures. While the topics may vary, the aim is the same: keep the public agitated, divided, and disengaged. Even if the issues themselves are constructed or exaggerated, the consequences are very real: weakened democracy, policy inertia, and increased susceptibility to authoritarian narratives.

Crowdsourcing Resistance

It’s easy to miss the spread of “friendly fascism” in our lives. Its power isn’t loud or obvious; it is woven into the interfaces we trust, the algorithms that guide us, and the smooth promises of progress. This soft authoritarianism has already shaped the choices we make, the culture we consume, and the way our democracy functions. If we don’t push back by questioning, challenging, and organizing, its hold will only tighten.

If this got you thinking, go watch The New Aesthetics of Fascism. The questions it raises and the images it shows are too important to ignore.

If you’ve come across “friendly fascism” in your daily life—whether online, at work, or elsewhere—consider sharing what you’ve noticed or what concerns you. Your stories, warning signs, or ideas for resistance are welcome below. The more we name and map these patterns together, the better chance we have of understanding and responding to them.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

Share

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Early in my career, software engineering seemed to promise financial freedom, creativity, and meaningful social impact. Tech companies promoted themselves as hubs of innovation, offering attractive salaries, appealing perks, and genuine purpose. Their messaging highlighted investments in employees and social contributions, sparking widespread enthusiasm and drawing many into technology careers with sincere curiosity and optimism.

Successful tech workers eagerly encouraged others, suggesting prosperity was achievable by simply learning to code—no formal degree required. Initially heartfelt, this advice became oversimplified and dismissive. The meme swiftly spread online, reducing human ambition to a narrow route: coding. It implied genuine success and societal worth existed only in tech, trivializing fields like teaching, care-giving, arts, and trades, and ignoring structural barriers such as limited educational access, inequality, and discrimination.

Casual encouragement—late-night study sessions and shared resources—soon morphed into aggressive marketing by bootcamps and influencers. Ads promised rapid career transitions, overshadowing the steady, disciplined effort required. Many borrowed heavily, convinced that instant transformation was within reach. But there are no shortcuts—meaningful careers require time, effort, and resilience.

For every celebrated success story, I saw many talented, dedicated individuals quietly struggle. After completing intensive training programs, they entered an overcrowded job market, competing with countless other bootcamp graduates and STEM degree holders for limited roles. While some found supportive environments, many were met with unrealistic expectations and little mentorship. Employers, focused on speed and productivity, offered minimal guidance, expecting immediate results. These challenges, compounded by rapid technological change and job market volatility, left many feeling unprepared and unstable. Rather than recognizing the systemic nature of these obstacles, individuals often blamed themselves, internalizing their struggles as personal failures.

Over time, the oversimplification of software engineering eroded both confidence in the field and its perceived value. Once defined by disciplined problem-solving, critical thinking, ethical reflection, and sustainable innovation, the profession became narrowly framed by slogans like “Move fast and break things,” “Disrupt or be disrupted,” and “Just learn to code.” Training programs and employers increasingly emphasized short-term productivity and easily marketable skills, reducing engineers to interchangeable technicians. Broader concerns—ethical design, social impact, and long-term sustainability—were dismissed as obstacles to rapid monetization. This shift not only diluted the profession’s identity but also constrained technology’s ability to address real societal challenges.

This troubling trend echoed my own experiences entering college during a widely publicized STEM shortage. Politicians, industry leaders, and educators portrayed STEM careers as secure and patriotic, vital to innovation and economic competitiveness. Yet many graduated into the turmoil of the 2008 financial crisis, facing prolonged unemployment, limited opportunities, and heavy student debt. Instead of respected contributors, we felt expendable, easily discarded in pursuit of short-term profits. Industry narratives shifted, casting skilled workers advocating fair treatment or equitable compensation as burdensome or entitled. Now, warnings that technical roles might be replaced by AI further erode confidence, making even highly skilled professionals feel replaceable and undervalued.

Economic policies reinforce this betrayal. In crises, corporate risks are socialized—trillions mobilized to rescue banks in 2008 or billions of forgiven PPP loans during the pandemic—while individual debts, especially student loans, remain personal responsibilities. Young people encouraged to invest in their futures are later told relief is undeserved or fiscally reckless. The message is clear: when corporations falter, the state intervenes; when individuals struggle, they bear the consequences alone.

Recent economic policy debates, exemplified by the passage of the One Big Beautiful Bill Act (OBBBA) and ideas like Ezra Klein’s Abundance, echo a familiar logic: privatizing profits while offloading risks onto individuals. OBBBA funnels resources upward, cutting social supports even as it promotes self-reliance narratives reminiscent of "just learn to code." Similarly, Klein’s emphasis on deregulation as a path to prosperity overlooks how unchecked market power reinforces inequality, conflating genuine democratic protections with bureaucratic inefficiencies. Both examples illustrate how policy choices often deepen economic insecurity rather than addressing structural barriers, reinforcing narrow views of success that prioritize private gain over collective well-being.

This disposability isn’t unique to tech—it reflects a systemic, short-term, profit-driven pattern. Workers retrained for manufacturing jobs in the 1980s experienced similar betrayals when factories closed and jobs moved abroad. Decades later, STEM graduates promised stable careers encountered insecurity during the 2008 crisis, revealing exploitative cycles that repeatedly redirect talent away from public benefit toward speculative gains.

Today, we see this troubling pattern intensifying in the tech industry. Highly trained engineers with the skills to address urgent public needs—like healthcare, climate resilience, housing, and education—are routinely steered toward projects driven by speculation, surveillance, or engagement metrics. Platforms prioritize ad revenue and compulsive use over public benefit. Cryptocurrency consumes vast energy with little social return. Artificial intelligence, while promising, also demands enormous computing power and is frequently deployed in ways that deepen economic insecurity and systemic bias. These aren’t just missed opportunities—they are choices that undermine sustainability, equity, and collective well-being. Motivated by venture capital and stock-based rewards, tech companies increasingly prioritize short-term profit over ethical innovation, worsening the very problems they claim to solve.

There’s profound sadness in narrowly defining ambition. Human talent and creativity now serve simplistic transactional goals measured by clicks or quarterly returns. The "Just learn to code" meme isn’t the cause but a symptom of deeper cultural and economic values prioritizing short-term productivity over ethical innovation, stewardship, and meaningful contribution. This mindset obscures the deeper questions we ought to be asking: How can our economy prioritize shared well-being, equity, and human flourishing, rather than focusing solely on private gain?

True progress must embrace equitable education, universal healthcare, sustainable housing, environmental stewardship, and meaningful work. Economic success should uplift everyone, enabling lives of dignity and resilience rather than merely increasing GDP or quarterly earnings.

Today's AI hype feels all too familiar—lofty promises paving the way for gains at the top and disruption below. Advocates enthusiastically promote AI tools like ChatGPT and GitHub Copilot as transformative breakthroughs promising increased productivity, creativity, and economic opportunity. But beneath this optimistic narrative lies a more complicated truth. Without deliberate safeguards and thoughtful policy interventions, AI could easily deepen existing inequalities rather than address them. Historically, technological innovations have disproportionately enriched executives, investors, and corporations, while ordinary workers have faced job displacement, constant reskilling pressures, and financial insecurity. The rise and quiet decline of initiatives like IBM’s Watson Health exemplify this pattern, leaving employees facing job losses and uncertainty while corporate leaders largely avoided consequences.

Yet, there is hope. We don't need a crystal ball to predict the future—we already possess significant leverage to actively shape it. Corporations and industry lobbyists clearly recognize this, investing considerable resources to influence policies that safeguard their interests. However, organized workers and communities hold similar power. Through collective bargaining, strong unions, worker cooperatives, mutual-aid networks, and democratic participation, we can effectively counterbalance corporate influence, ensuring innovation and economic growth serve broad societal interests rather than narrow private gains. Policies designed to buffer ordinary people from systemic shocks—universal healthcare, guaranteed retraining, fair labor standards, and robust social safety nets—can protect communities from economic uncertainty and technological disruption. Rather than passively accepting a future dictated by corporate interests, we can consciously build structures that foster shared prosperity, human dignity, and genuine economic democracy.

There's a better, more hopeful path forward—one rooted deeply in solidarity, democratic control, and collective empowerment. Instead of workplaces defined by rigid hierarchies, inequality, and insecurity, we can intentionally build organizational structures centered around fairness, cooperation, and mutual support. Worker cooperatives like Loomio in New Zealand and Outlandish in the UK demonstrate that democratically managed tech companies can flourish, equitably sharing profits and decision-making. Recent unionizing efforts at companies like Alphabet further illustrate how collective action can rebalance workplace power, ensuring economic benefits are broadly distributed. Community-driven initiatives and mutual-aid networks offer critical support during economic downturns or technological disruptions, fostering resilience and collective well-being. Publicly funded lifelong education programs, exemplified by Germany’s vocational system and Denmark’s tuition-free universities, highlight how societies can proactively support continuous skill development without imposing heavy financial burdens. These practical examples demonstrate clearly that equitable workplaces and genuine economic democracy aren't distant ideals—they're achievable, functioning models already thriving today.

Perhaps it's finally time for the tech industry—and society as a whole—to move beyond the outdated myth of the solitary genius, the heroic innovator transforming the world in isolation. This individualistic narrative glorifies singular achievements but obscures the collaborative reality of meaningful innovation, which emerges from diverse teams solving complex problems together. Genuine abundance should not be measured by accumulated wealth or the number of billionaires created, but by widespread human flourishing—accessible opportunities, equitable education, robust social safety nets, and meaningful, fulfilling work.

Nearly eighty years ago, President Franklin D. Roosevelt envisioned an "Economic Bill of Rights", recognizing that true individual freedom depends upon fundamental guarantees: meaningful employment, adequate healthcare, quality education, secure housing, and economic security for everyone. Roosevelt understood that genuine abundance isn’t defined by endless economic growth or profits for a privileged few, but by ensuring these basic rights universally.

We possess extraordinary talent, boundless creativity, and remarkable imagination—qualities uniquely capable of addressing humanity's most pressing challenges and profoundly transforming lives. Yet far too often, these precious resources are wasted on superficial slogans, fleeting profits, and narrow ambitions benefiting only a privileged few. Such misuse of human potential doesn't merely represent missed opportunities; it actively diminishes our collective future. It is imperative that we consciously build an economy—and particularly a tech industry—dedicated to meaningful, transformative, collective prosperity. True success should never be measured by towering private fortunes or short-term market gains, but by tangible improvements in people's lives, the strength of our communities, and the equity of our society.

As Amartya Sen reminds us:

“The success of a society is to be evaluated primarily by the freedoms that members of the society enjoy.”

Our progress must be judged by our effectiveness in overcoming systemic inequities, expanding opportunity, and creating environments in which everyone can thrive with dignity, respect, and security. By intentionally directing our talent and creativity toward these deeper, purposeful goals, we can achieve genuine progress—manifested vividly in enriched lives, empowered communities, and a truly abundant, equitable society.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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When I first discovered technology, it felt like pure passion. It wasn't just coding—it was a vibrant landscape filled with creativity and possibility. Early chat rooms and forums became global classrooms buzzing with curiosity. Friends shared discoveries, strangers became collaborators, and mentors patiently guided newcomers. Technology promised a transformative new world, as powerful and inspiring as music or medicine.

Early tech connected us in ways we'd never experienced before. Silicon Valley promised a borderless global community and limitless innovation. Initially, this promise felt real: we openly shared our lives—posting videos, sharing photos, blogging about personal journeys, connecting deeply across borders. It was exhilarating, a shared human adventure. Yet we soon recognized Silicon Valley’s familiar playbook: offer services cheaply or freely, build trust until we're dependent, then quietly tighten control—raising costs, degrading quality, or limiting choices—often simultaneously. We've seen this repeatedly: Uber undermining taxis, streaming platforms appropriating artists' work, dating apps monetizing loneliness, social networks exploiting personal relationships. This bait-and-switch quietly reshapes our lives.

Today, that early vibrant community feels distant, replaced by something colder and more transactional. Automation—once celebrated as our proudest achievement—now quietly takes over tasks that once defined our creativity and craftsmanship. Technology itself is not inherently harmful; thoughtfully applied, it can enrich human potential, free us from tedious labor, and foster creativity. The real issue lies in who controls this technology, and to what end. Careless or profit-driven automation isolates workers, weakens mentorship, and erodes community. Newcomers struggle to find opportunities, labeled too inexperienced; seasoned workers chase deadlines, sacrificing insight for speed. Under this narrow, exploitative use of technology, creative work becomes like fast food—quickly produced, cheaply valued, easily discarded.

We've witnessed commodification repeatedly throughout history. Looms replaced artisan weavers with machines; Ford’s assembly lines reduced skilled machinists to interchangeable parts; McDonald’s transformed cooking into standardized button-pushing. Each technological shift promised liberation, but instead delivered mass-produced sameness, emphasizing efficiency over creativity and skill. Today, creative and intellectual labor faces the same fate—low-code platforms, SaaS tools, and generative AI quietly automate away engineering and artistic tasks, often using workers’ own contributions to train their replacements.

Yet many engineers didn’t recognize this pattern at first. Immersed in myths of meritocracy and exceptionalism, we believed we were immune—indispensable and secure. Reality, however, is beginning to catch up. While the full impact of automation and generative AI has not yet transformed the entire industry, the trajectory is clear, even if the timeline remains uncertain. A privileged few might continue thriving for now, but history consistently warns that their numbers shrink over time. Manufacturing, journalism, entertainment—each offers a cautionary tale. Automation doesn't need to fulfill CEOs' grand promises to cause real harm; even the mere threat of automation disciplines workers, justifying layoffs, offshoring, and relentless demands that we do “more with less.” Executives rarely speak of empowering workers; their true goal remains—higher profits, lower wages, endless commodification.

Today’s stakes extend far beyond paychecks. Platforms harvest our thoughts, relationships, and culture, selling them back to us as rented “services.” Hollywood screenwriters have gone on strike, pushing back as major studios increasingly rely on AI-generated scripts, often trained on the writers’ past work. Visual artists watch helplessly as AI rapidly replicates their distinctive styles, forcing creators to lease back their own creativity. Amazon sellers painfully discover that thriving the marketplace ultimately means paying escalating fees—akin to rent—for innovations originally their own.

Yet commodification doesn't stop at tangible products—it penetrates deeply into our minds. Our attention, emotions, thoughts, and beliefs have become commodities, extracted, packaged, and sold back to us. Algorithms don't merely deliver personalized content; they shape our perceptions, nudging us toward predictable reactions, cultivating dependency. This psychological enclosure fragments identities into profiles optimized for targeted ads. Capitalism now seeks our consciousness itself.

This commodification reshapes how society views and treats individuals. Employers increasingly see workers as interchangeable parts, valued solely for immediate productivity rather than unique talents or potential. This perspective reduces workplace relationships to transactional exchanges, weakens genuine collaboration, and prioritizes compliance over critical thinking. Employees sense their disposability, valued only as long as economically convenient. The constant threat of replacement fosters anxiety, isolation, and precarity, draining joy and meaning from life. Individuality—the unique self capitalism claims to cherish—becomes disposable. Empathy fades, replaced by arbitrary measures of efficiency. Solidarity, purpose, and authentic human connection steadily erode. Yet workplace democracy—where workers collectively participate in decisions—offers a powerful counterbalance, restoring meaningful engagement, ownership, and dignity by recognizing each individual's intrinsic worth.

This erosion of autonomy increasingly blurs the boundaries between work and personal life. Work profoundly shapes relationships, finances, health—even physical and emotional safety. Corporate control seeps into personal lives, subtly influencing choices, freedoms, and dignity. Entering work often means leaving democracy behind, stepping into hierarchies where basic rights become negotiable. This loss of autonomy reshapes society at large, steadily weakening democratic structures and norms.

Tech giants further intensify this erosion, becoming modern-day feudal lords enclosing shared digital commons—attention, creativity, relationships—and charging access fees. They impose hidden tolls on our thoughts, silently profiting from digital labor we unknowingly provide—an exploitative dynamic that scholars call technofeudalism. Cities adopt predictive policing and facial recognition, automating injustices disproportionately targeting marginalized communities. Civic spaces are distorted by social platforms optimized for outrage and misinformation, shaping elections through micro-targeting and polarization, eroding informed consent beneath the illusion of engagement. Powerful corporations lobby lawmakers weakening privacy protections under the guise of convenience. Ownership and autonomy become illusions, replaced by commodified dependency— bleakly summed up: “You will own nothing and love it.”

Filmmaker Adam Curtis reminds us meaningful change is always frightening and destabilizing. Genuine transformations aren't comfortable—they require us to surrender familiar comforts, sacrificing security for something greater. Liberals, engineers, and middle-class professionals accustomed to stability often prefer incremental improvements that protect existing privileges, resisting necessary structural changes. Yet millions, feeling abandoned and stripped of autonomy, increasingly turn to reactionary promises precisely because they have nothing left to lose. Curtis’s insight is a warning: without a genuinely hopeful, transformative vision, we risk surrendering our future to these reactionary forces.

How do we reclaim our hopeful future? We must draft a bold social contract rooted in democratic socialism, prioritizing the de-commodification of our digital, physical, and cultural commons. Reject passive consumerism; actively participate locally through mutual aid networks, democratize workplaces inspired by Spain’s Mondragon cooperatives, build radical community platforms akin to Wikipedia, and form cooperatives empowering workers and creators directly. Choose openness over enclosure, transparent governance over opaque algorithms, and meaningful mentorship over relentless productivity. Demand technology enriching human life instead of extracting from it. Through collective action and solidarity, we reclaim creativity, autonomy, and dignity.

This fight belongs to all of us—engineers who dream of meaningful tools, artists whose voices deserve respect, workers demanding dignity. Real change means embracing uncertainty, surrendering something safe for a vision greater than ourselves, risking comfort to achieve something profound.

We’ve faced uncertainty before, knowing that change involves risk—but we moved forward, armed with creativity, courage, and trust in one another. The first hesitant line of code, the blank page, the empty canvas: each was a step driven by the belief that our collective imagination could lift humanity toward something genuinely transformative.

That belief still thrives. Now is our moment to reclaim it—to unite across differences, amplify our voices, and build a world that reflects our shared dreams. Reconnect. Dream boldly. Build anew. Together, let's reclaim our joy, renew our communities, and create a future worth believing in—where technology truly empowers humanity, compassion guides progress, and each of us can fully thrive.

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

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At Democracy At Work, we critically analyze capitalism as a systemic problem and advocate for democratizing workplaces as part of a systemic solution. Our mission is to build a stronger, fuller democracy. Today, we’re excited to introduce CommonBytes, a new column dedicated to a crucial question: What should technology’s role be in a world beyond capitalism?

Why This Matters Now

Today’s technology is dominated by corporate interests—driven by profit, surveillance, and control. Social media platforms exploit our attention, AI reinforces biases, and automation often displaces workers rather than liberating them. Under capitalism, so-called technological "progress" rarely serves collective well-being; instead, it deepens inequality, erodes privacy, and commodifies human relationships.

But what if technology were designed differently? What if it were a communal resource, shaped by democratic participation, cooperative ownership, and sustainable innovation?

CommonBytes

This column explores a central question: What should technology’s role be in a world beyond capitalism? Today’s technological landscape is largely shaped by profit, commodification, and control—often undermining community, creativity, and personal autonomy. CommonBytes critiques these trends while imagining alternative futures where technology serves collective flourishing. Here, we envision technology as a communal asset—one that prioritizes democratic participation, cooperative ownership, and sustainable innovation. Our goal? To foster human dignity, authentic connections, and equitable systems that empower communities to build a more fulfilling future.

Share

Subscribe now