The Brooklyn Rail

If America had a brain, we could say it’s losing cortical tissue. The neocortex—the part of our brain that helps us plan, learn, and think beyond the moment—balances long-term planning against short-term reflex. Yet the proposed 2026 budget cuts deeply into the very institutions that claim to serve that role in this country: the agencies that regulate industry, the systems that educate and care for people, and the protections that safeguard the environment.

As the economy slows down,¹ shot callers are finding that making America dumber is a good business opportunity. It’s more profitable to plunder the higher functions of the institutional brain and divest those public resources into hurting people. Deportations, detention centers, weapons, and software that spies on people are good business. Some of these contractors are building artificial brains that supposedly make up for America’s lost grey matter. Elon Musk led a team of twentysomething engineers—prefrontal lobes barely formed—to mutilate the federal brain via layoffs², ending in the loss of 80,000 workers.³ Gen AI companies like Musk’s xAI, OpenAI, and Anthropic, are now securing Department of Defense contracts worth hundreds of millions.⁴

The debraining of the federal government under the promise of artificial brains reflects a wider lobotomization happening throughout the whole economy. Managers everywhere are getting orders from higher-ups to figure out how to replace the human brain power in tech, marketing, and legal services with LLMs. Junior level jobs are eliminated with the excuse that their labor can be reproduced with a prompt in ChatGPT.⁵

As the higher brain functions of society fade, what remains gradually starts to look like an economic creature moving on instinct—a zombie, mostly brain-dead, reacting only to immediate stimuli and driven by an insatiable hunger. That hunger, a craving for productivity and profit that never actually materializes, pushes society to devour its own organs of intelligence for short-term gain. Not the “new industrial revolution”⁶ promised by AI leadership, but weak productivity, low-value workslop⁷, and a massive bubble of unprofitability.⁸

This tendency towards debraining was noted by Harry Braverman, a rare sociologist who, before entering academia, had extensive experience in both white- and blue-collar labor. Braverman argued⁹ that capitalist technological development is based on stripping thinking from most work and concentrating the “brain work”¹⁰ of design, planning, and calculation in the hands of a small number of highly paid professionals. Over the last two centuries, many technological breakthroughs have served precisely this function: machines made it possible for cheap, minimally trained labor to operate production processes, while expensive scientific knowledge was encased in only a few skulls.

Today the same hierarchical division of labor lies behind the thinking of the Silicon Valley CEOs who downplay the collective intelligence of “ordinary” people. Instead, they elevate a cult of individual genius, insisting, implicitly or explicitly, that the brainpower of a select “visionary” is the only thing that matters.¹¹ Those views aren’t merely ideological, they are expressions of a material process holding back the creative powers of our species.

 

Thin vs. Thick Intelligence

Consider how Alan Eustace, a former Google vice-president, once revealed just how narrow and backward Silicon Valley’s view of human intelligence can be. He claimed that “one top-notch engineer” is worth more than 300 average ones¹²—an assertion he no doubt believed applied to himself. But the idea that one “top-notch engineer” is literally worth 300 average ones isn’t just arrogant; it comes from a worldview that can’t imagine the potential scaling power that happens when hundreds of capable minds collaborate.

Even on Silicon Valley’s own terms—its habit of comparing the brain to a computer—the claim falls apart. In computing, one faster processor is almost never a match for hundreds running in parallel; that’s why real scientific and engineering problems rely on distributed systems. If one processor somehow outperformed 300 working together, you’d assume the code was badly written. No “elite” engineer has anything close to 300 times the working memory, processing speed, or depth of insight of a perfectly capable human being, let alone of 300 of them working together.

This hierarchical view of cognition happens to be deeply individualistic. It posits intelligence as something that exists in individual skulls, an idea that simply reflects the capitalist division of labor: once thinking is stripped from most work and centralized at the top, intelligence must be treated as a scarce asset held by few individuals rather than an attribute of the group. Consider standard measures of intelligence like IQ: the skills they measure have little to do with working together, but instead track abstract puzzles solved by individuals working alone at desks.

In contrast to measures of individual intelligence like IQ, decades of research on collective intelligence¹³ shows that the capacity of a group to problem solve is mostly driven by social awareness, the ability to pick up on emotional cues. Another important factor is inclusiveness, achieved through equal turn-taking. The average or maximum IQ in the group is not significant. Most socially significant problem solving is a group endeavor, so the typical equation of intelligence with individual mental operations reflects a warped world view motivated by the hierarchical division of labor.

Here we find evidence of a thicker conception of intelligence. In the case of reading another’s emotional state, social awareness draws on the body’s full apparatus: how eyes catch facial cues, how the nervous system mirrors another’s tension or ease.¹⁴

In fact, there are reasons to believe the full extent of our creative powers depends on the interwoven interplay of our evolved perceptomotor apparatus, not the mutilated version left by this capitalist division of labor, which frays the weave between abstraction and the richly textured sensations of touch and movement.

Consider how a hand that grasps a ball helps the mind make sense of its more abstract representations—for instance, intuiting a 2-D representation of the ball, such as a photograph or drawing. The remembered feel of its roundness, weight and the texture of its surface helps the brain conjure up its three dimensions.¹⁵ Anthropologists have shown that early abstractions grew out of tactile craftwork. Ideas about space and time, including the first geometric reasoning, developed alongside textiles, shaped by the structures and symmetries that weaving revealed.¹⁶

The capitalist division of labor severs these synergies between the abstract and embodied practice, leading to warped perceptions of reality. The urbanist Richard Sennett¹⁷ used the construction of the Peachtree Center in Georgia, a commercial complex, as an example. Its blueprints, overdetermined by CAD and drawn at a distance from the tactile reality of the site, produced a design that looks good on a screen but when executed in the real world faced significant issues that didn’t surface in the tidy virtual world. Outdoor café seating that seemed perfect in the simulation sits unused in the region’s harsh daytime heat. Hotel windows open onto parking lots because the architect, rotating a 3-D model on a monitor, never stood there to see what a guest would actually see.

A more catastrophic consequence of this division of labor are the Boeing airplane crashes. The on-the-ground knowledge of engineers, their conversations with other workers, their inspections, their misgivings, were filtered through business dashboards built around short-term profit metrics, resulting in cost cutting through sloppy quality control. The result was catastrophe: hundreds of people died.¹⁸

All of this is part of what the geographer Phillip Neel calls the “mutilation of productive subjectivity.”¹⁹ Instead of a form of knowledge where abstract conception interplays with embodied, situated practice, modern production tears these elements apart—flattening both. The embodied interaction with the world loses texture, reduced to routine motions on factory floors and the thin cues of screens and touchpads. Abstractions hollow out. A technician, programmer, or maintenance worker often has little sense of how tightening a bolt, adjusting a sensor, or writing a line of code connects to the whole. Designers and planners engage with what they shape mostly through diagrams and strings of symbols. thinned-down representations of messy, biophysical reality.

Now imagine how problems arising from the disconnect between conception and execution scale up from buildings and single companies to whole economies and governments. A small circle of people at the top—executives, politicians, strategists, policymakers—now makes decisions that ripple across whole institutions, working from a virtual world of slides, dashboards, and spreadsheets. The people who build, repair, drive, nurse, and maintain the infrastructures that keep everyone else fed, sheltered, and alive have little say or expertise in the systems that steer those institutions. This division of labor is at the heart of what the historian Adam Tooze calls a polycrisis, a maelstrom of simultaneous economic, political and environmental crises that feed off each other—“pandemics, wildfires, threats of world war.”²⁰ This mutilated division of labor concentrates decision-making into a few warped brains that lack the capacity of grappling and steering this increasingly more complex social reality, while keeping the needed brainpower of the majority from taking control.

 

Blind Automaton

As the tendency to cheapen labor increasingly concentrates conceptual brainwork, not only stripping deliberative judgement from “unskilled” manual labor but also increasingly debraining white-collar work, decision-making systems at even higher levels start behaving as blind automata escaping human control.

Corporate life transforms its own decision-making apparatus—the firm’s internal brain—toward something that feels like algorithmic repetition rather than human thought. What gets called a “decision” inside many firms is rarely a creative act at all, but a standardized response—analogous to the repetitive behavior of workers on factory floors.²¹ HR departments follow scripts for hiring and conflict resolution; managers lean on standardized frameworks like Scrum; payroll and compliance are largely automated. Insurance and finance rely on forms, formulas, and decision-trees. Even the bosses can’t avoid their own mechanization, with CEO choices considerably narrowed around chasing metrics in standardized financial statements, leaving little room for imagination. AI is just their increasing digitalization.

The corporate decision-making systems, much like old factory lines, churn out decisions with less and less human input. Mass layoffs and the disappearance of entry-level jobs are the consequence of the tendency to have fewer people handling more decisions. Human behavior stripped from creative brainwork, just going through the motions, starts to resemble a kind of machinery, operating beyond the organic intelligence of those that form it. The brain of the firm becomes a blind automaton, untethered from its human decision makers.

As people hand more and more of their judgment over to systems that grow too tangled and opaque for anyone to grasp, these networks of corporate algorithms—stretched across the planet and tuned to capital accumulation—appear as an alien power beyond human control: an autonomous zombie intelligence crystalized from the dead work of generations of once-living human minds. This strange, alien intelligence feeds on our living thoughts, draining away the parts of us that imagine and decide.²²

This idea of collective intelligence as a blind machine is defended by the likes of Marc Andreessen, a leading venture capitalist in Silicon Valley. In his techno-optimist manifesto,²³ when describing the collective behavior behind “progress,” he retreats to mechanical imagery like the “Techno-Capital machine,” with the “market” described both as a “sort of intelligence” but also as a machine, from which descriptions of living human minds are curiously absent. He also insists that AI will make society smarter.²⁴ Yet when he tries to explain what this augmented intelligence consists of, there’s little about thinking as an activity of the human organism. For him, “augmented intelligence” largely means replacing professions humans already perform well—therapists, coaches, tutors—with “AI assistants.”

 

A Brain Spread Across Skulls

Perhaps the reason why Andreessen and his Silicon Valley cohort struggle to imagine a breakthrough in genuinely living intelligence is that they can’t think beyond their wallets. To imagine a thicker intelligence we pay attention to group problem solving that doesn’t center on the thin abstraction of money but something more textured and layered.

The mega-collaborations in high energy physics might provide some hints. Although embedded in our economic system, financial balance sheets made of simple, textureless abstractions are not the central driving force of the enterprise. Instead, the center of attention and decision-making is something far richer: the extraordinary machines at CERN²⁵ used to probe the building blocks of the universe—a massive underground ring seventeen miles in circumference where atomic nuclei are accelerated close to the speed of light with powerful magnets cooled to near absolute zero, and detectors as big as multistory buildings that read the resulting particle showers. Operating these machines and understanding their signals is too big and complex an undertaking to fit inside the few skulls at the top who would then decompose them into tasks for fragmented specialists with no grasp of the whole. Instead of the traditional, fragmented division of labor, the scientists who operate the accelerators and detectors at CERN, while experts in highly specialized tasks like tuning beam optics, calibrating detectors, and reconstructing particle jets, also have deep knowledge of the mathematically sophisticated quantum physics that give the whole enterprise coherence.

Rather than tasks being broken into sets that maximize control and speed by managers, there is a natural division around the proximity of different physicists to “separated” objects such as calorimeters, muon chambers, and codes. Physicists are not only the caretakers and makers of these artifacts, but their lobbyists, accountants, and investors; the objects cannot be decided about or acted upon without “their physicists,” and the expertise developed is rich, combining the conceptual and the practical.

As scientists interact with the machines and each other, a collective sense of design and division of tasks becomes distributed through thousands of skulls. Group self-reflection coheres when the knowledge individuals accrue through machine use or calculation circulates through seminars, workshops, cafeterias, bars, the outdoor vineyards, informal gatherings among friends. Working groups emerge out of individuals who volunteer for tasks based on expertise, honor, curiosity, friendship, career potential, or through baser motivations like ego and power seeking.

Out of this fabric of speech, graphic plots, and machine interactions, the collective brain gains a degree of self-awareness, referring to itself with such names as “The Atlas Collaboration” or “The CMS Collaboration.” This collective consciousness is documented in the authorship of peer-reviewed papers where there are no privileged “first authors”²⁶; instead, the whole Collaboration becomes the published author, the sum of thousands of individual scientists, representing virtually all major languages, national scientific systems, and cultures.

 

Social Rebraining

The difference between the thick collective intelligence cultivated in CERN and the fragmented cognitive hierarchy that sustains Silicon Valley lies in the artifacts around which decisions are cast. CERN centers the rich machine-human environments bound together by quantum physics, whereas Silicon Valley centers money—the thin abstraction behind their power. Deep probing into nature demands transparency and collective pooling of creativity; money for the sake of money turns mass understanding into a cost. Silicon Valley’s black boxes that degrade nature, intelligence, and work are not accidental. They are artifacts designed to feed Mammon, the concentration of wealth, not the inherent properties of the artifacts themselves, whose usefulness, beauty, and sustainability are secondary—if they matter at all.

When Silicon Valley figures like Andreessen invoke opaque “market forces” as a sort of intelligence standing above living human thought, they echo an economic arrangement that works precisely by veiling the arbitrariness of power relations that favor them. They resist making the social systems people inhabit intelligible in a way that allows ordinary people to shape it.

New York mayor Zohran Mamdani’s controversial platform gives us a glimpse of what it means to treat a social system as a concrete, textured dwelling, with accessible nutritious food, housing, transportation, and childcare, rather than treating the city as an abstract grid of prices. His platform includes free childcare, expansion of free public transportation, city owned grocery stores in food deserts—policies that should be feasible in one of the wealthiest cities on earth when other cities with less resources implement similar programs. Yet real estate and business interests often argue that such things are unaffordable, and somehow oppose “the laws of the market,” the same laws that in a city of abundance puts the control of resources in their own hands.

Given the resistance his platform faces from powerful groups, Mamdani’s administration may not be able to implement this vision without an activated base. People beyond municipal officials will need to become more directly involved in the inner workings of the city, learning through practice how to treat it as a shared, embodied dwelling. They must become a collective brain where a sense of design and division of tasks is distributed across the millions of the city’s minds, rather than just concentrated in bureaucrats. Some have therefore called for popular assemblies to act as institutions of participatory democracy in the city.²⁷ Yet most working-class people are busy and skeptical of politics in general. Historically, the labor movement is one of the forces that has enabled workers to function as a conscious swarm intelligence, where people deliberate over their textured needs and desires and challenge the bosses’ balance sheets. It’s very likely that the labor movement, which is experiencing a moderate revival in the US, will be required to deepen popular power.

If the city’s movement for popular control grows, this collective brain would have to extend beyond the city itself, since the physical goods imported into the city to feed, transport, and care for its inhabitants are made by workers throughout regional, nationwide, and planetary supply chains. As this brain expands and incorporates people beyond the city who are prepared to take control of the infrastructure that shapes nature into their sustenance, its synapses would spread across regions, borders, and oceans. In doing so it would encounter other people forming their own collective brains, capable of linking and merging into a world-brain.

At this point, the planetary brain would then become aware of its own body—the pulsing circulatory system of artifacts and interpersonal relations that holds the species together. The social revolution would have become a cognitive revolution.