Tribune’s recent call to “destroy” artificial intelligence reveals a concerning trend. It reflects growing pessimism among parts of the modern left, which views technological progress not as a tool for human emancipation but as a threat to be feared, opposed, and ultimately eliminated. Although Matthew Cole’s article employs radical language, it ultimately channels valid concerns into a reactionary dead end. It highlights genuine social and environmental issues like the carbon emissions from data centres, the extraction of minerals in the Global South, the concentration of computation in American monopolies, and the British government’s tendency to give land and water to tech oligarchs. It blames not the capitalist elite responsible, but the productive forces themselves.[1]
This is not socialism; it is despair- a despair that Marx examined over 150 years ago. In Capital, Marx scrutinised the Luddite movement and emphasised a key point: workers should distinguish between machinery itself and how capital uses it. Machines are not inherently neutral or oppressive; they become tools of exploitation only if controlled by capital. Cole reverses this, viewing AI as inherently destructive, as if the technology alone causes social problems rather than the capitalist system governing its development and application. This mistake leads him to connect struggles from the Luddites to the Writers Guild of America, implying machine-breaking and modern trade unionism share the same strategy. They do not. The Luddites were defeated, but the machines remained. What improved workers’ conditions was not smashing the looms, but the rise of organised labour capable of negotiating over the wealth these machines created. To revive Luddism is to reject the very history that gave birth to the socialist movement.
Cole’s claim that AI differs from railways, electrification, or industrialisation because it offers no tangible benefit is simply inaccurate. Historically, major infrastructure projects under capitalism have involved bloodshed: railways were built through colonial conquest, with slave-grown cotton, and during famines in India. Electrification benefited monopolies and increased factory exploitation. Industrialisation destroyed artisanal trades and displaced communities. However, the socialist movement never called for dismantling railways or banning electricity; instead, it aimed to socialise these systems. The true enemy is capitalism, not the productive forces.
Cole’s dismissal of AI’s usefulness overlooks the facts. Even within capitalism, machine learning is already employed in protein structure prediction, medical diagnostics, weather forecasts, climate models, materials science, and drug development- significant applications that represent technological progress with substantial benefits for humanity. However, these are often used for profit, surveillance, or military purposes. In a socialist system, such technologies could reduce working hours, eliminate monotonous labour, and enable more rational production planning. The real contradiction isn’t the technology itself but private ownership of the means of production and the existence of competing nation-states.
Cole’s evidentiary claims fall apart under close examination. He references a small MIT preprint to argue that AI is “retarding our brains,” but this study, with only 54 participants, cannot support broad civilizational claims. He also blames AI for falling OECD PISA scores, even though the tests were conducted before ChatGPT was available. The OECD links the score decline to pandemic-related school closures, a consequence of the ruling class’s negligent response to COVID-19, which kept workers employed while children lost years of education. His claims about carbon emissions are inconsistent: he states that the “global data cloud” emits more carbon than aviation but cites figures far below aviation’s actual footprint. While data centres do contribute to environmental harm, addressing this issue requires careful analysis rather than rhetorical exaggeration.
When Cole discusses strategy, his political class character becomes evident. He endorses anarchist sabotage, such as arson attacks on Tesla facilities and tactics like data poisoning and misinformation traps. Historically, the Marxist movement opposes such reckless actions, as they replace mass struggle with individual acts, risk provoking state repression, and leave ownership structures unchallenged. These acts also demonstrate disdain for the working class. Cole then suggests a state-led approach to dismantle data infrastructure, but given that the Labour government is influenced by finance capital and U.S. tech giants, expecting it to dismantle its own infrastructure is unrealistic. His notion of “digital sovereignty” overlooks the global nature of technology resources, from Brazil and Colombia to Kazakhstan and Taiwan’s manufacturing. No single nation can “decompute” a worldwide system; only the international working class can seize control of these productive forces.
Workers involved in building data centres, mining cobalt, labelling training data, assembling GPUs, and dismantling e-waste are not foes of technology; they are its creators. The socialist vision is not about destroying, but about expropriating: bringing tech giants like OpenAI, Anthropic, Amazon, Microsoft, and Palantir under public ownership and democratic workers’ control. Only through this can decisions about energy, water, land, and automation serve social needs instead of private profits. Like previous technological leaps, the potential of AI must be freed from capitalist ownership, not destroyed.
Cole’s article highlights a common pattern among the academic middle class: blaming social problems on productive forces instead of capitalist relations. It offers workers nostalgia instead of actionable strategies, advocates sabotage over organisation, and induces moral panic rather than critical analysis. This approach is not socialism; it is a retreat. It adopts a politics that attributes alienation to the machine rather than to the capitalist owner. Moreover, it fears the future instead of trying to control it.
The reality is that artificial intelligence, much like previous major technological advances, embodies a contradictory force. In a capitalist system, it often amplifies exploitation, reduces jobs, and supports warfare. Conversely, in a socialist framework, it can shorten working hours, remove monotonous tasks, and enhance human freedom. The core contradiction does not lie in the technology itself but in the social relationships that regulate its use. To eliminate AI is also to eliminate the chance of using it as a tool for human emancipation.
The socialist movement has consistently believed that the productive forces developed under capitalism, such as railways, electricity, industrial machinery, and computing, should be seized rather than destroyed. The goal is to advance modernity, not retreat from it. The working class must take control of these technologies to build a society centred on human needs rather than private profit. Cole’s call to “destroy AI” is therefore not a radical departure from capitalism but a surrender to it. It adopts the capitalist view that technology is inherently oppressive and that workers are powerless against it. It provides no plan for workers, no strategy for expropriation, and no vision of a socialist future. It only spreads fear.
WSWS Articles on Artificial Intelligence (AI)
A curated list with summaries
1. “The class issues in artificial intelligence”
A foundational WSWS analysis arguing that AI is not an autonomous threat but a product of capitalist social relations. It emphasises that the danger lies in private ownership, militarisation, and exploitation — not in the technology itself.
2. “Artificial intelligence and the future of work”
Examines how corporations use automation and machine learning to intensify exploitation, cut jobs, and suppress wages. Argues that AI could shorten the working day under socialism but is weaponised under capitalism.
3. “The militarisation of AI: US imperialism’s new frontier”
Discusses Pentagon and NATO investment in autonomous weapons, battlefield analytics, and surveillance systems. Frames AI as a central component of the drive toward world war.
4. “Tech layoffs and the restructuring of the global workforce”
Analyses mass layoffs at Google, Amazon, Meta, and Microsoft, linking them to automation, shareholder pressure, and the broader crisis of capitalism.
5. “The environmental cost of data centres: capitalism’s irrationality”
Explores water usage, energy consumption, and land grabs associated with hyperscale data centres. Argues that these problems stem from anarchic capitalist competition, not from computing itself.
6. “AI, surveillance, and the police state”
Covers the use of machine learning in predictive policing, biometric surveillance, and border control. Shows how governments deploy AI to suppress dissent and monitor populations.
7. “The Writers Guild strike and the question of AI”
Analyses Hollywood’s labour struggle, arguing that the WGA’s concerns about AI reflect broader contradictions between creative labour and corporate control of technology.
8. “ChatGPT and the crisis of bourgeois ideology”
A theoretical piece exploring how large language models expose the intellectual bankruptcy of academia and the media, while also revealing the enormous potential of automated knowledge systems.
9. “The global semiconductor supply chain and the drive to war”
Examines TSMC, Nvidia, ASML, and US–China rivalry. Shows how AI hardware is inseparable from imperialist conflict.
10. “Artificial intelligence and education: A capitalist catastrophe”
Discusses the use of AI in schools, testing regimes, and ed‑tech platforms. Argues that the crisis in education stems from austerity and privatisation, not from AI tools.
11. “The myth of ‘ethical AI’: Capitalism cannot be regulated”
Critiques liberal calls for AI regulation, arguing that no ethical framework can restrain profit-driven corporations or imperialist states.
12. “Automation, productivity, and the socialist reorganisation of society”
A programmatic article explaining how AI and robotics could eliminate drudgery, shorten the working day, and enable planned production — but only under workers’ control.
Pip: A documentary about AI that asks billionaires whether the future is safe — freerein61 has thoughts, and they are not gentle.
Mara: This episode follows a single extended piece of film criticism: a Marxist reading of Daniel Roher's documentary The AI Doc, which landed on Netflix in September. The argument runs from liberal affect all the way to class power and who controls the means of computation.
Pip: Let's start with what the film actually does — and what it refuses to do.
The AI Doc: Feeling the Future Instead of Analysing It
Mara: The post opens with a clear indictment of what kind of documentary this is: not an investigation of AI's social forces, but a therapeutic narrative aimed at an anxious professional class. That's the frame everything else hangs on.
Pip: And the film's central device makes that concrete. Roher's impending fatherhood converts a collective social crisis into a private psychological journey. The post is direct about what that displacement costs the viewer.
Mara: The post puts it plainly: "The question is no longer: What does AI mean for society? But how should one feel about AI? The answer Roher offers — 'apocaloptimism' — is a hybrid of dread and hope, a mood rather than a theory, and a telling ideological manoeuvre."
Pip: A mood rather than a theory. That's a precise diagnosis — and it shapes everything else the film does.
Mara: The post traces that shaping through the interview roster. Roher turns to Sam Altman, Ilya Sutskever, Demis Hassabis, and the Amodeis — executives of corporations valued in the hundreds of billions. Critics and ethicists like Timnit Gebru and Yoshua Bengio appear too, but the film treats all of them as voices in a debate to be balanced rather than evidence to be weighed.
Pip: Asking the owners of the oil majors whether the climate is in good hands — the post actually uses that comparison, and it lands.
Mara: It does. And the structural consequence follows: by flattening the difference between corporate executives and their critics, the film obscures the power relations driving AI's development. Pluralism substitutes for analysis.
Mara: The post is equally pointed about who is missing entirely. Data annotators in Kenya and the Philippines, warehouse workers under algorithmic surveillance, engineers in hyper-competitive corporate environments — none appear. Workers show up only as abstract figures who might face disruption, never as agents capable of shaping the future.
Pip: Which is doing a lot of ideological work quietly.
Mara: The post grounds that in a Marxist framework drawn from Marx's Grundrisse and Braverman's Labour and Monopoly Capital — the argument that technology is never autonomous, that social relations of production shape it entirely. Under capitalism, AI's deployment follows from the imperatives of profit, surveillance, and military advantage, not from ethics or philosophical reflection.
Mara: The post names what the film cannot say: "The problem, in other words, is not the machine. It is who owns it and to what end." And it names what democratic control of that technology would actually require — directing it toward social need rather than private profit.
Pip: The film's emotional resolution, "apocaloptimism," gets the sharpest treatment: a class-specific coping mechanism that demands nothing of the viewer except emotional calibration and proposes no collective force capable of changing anything.
Mara: That's the post's closing argument — that the documentary is not simply inadequate but symptomatic, reflecting a political culture that has lost the capacity to think structurally and looks to the architects of technological upheaval for guidance on how to feel about it.
Pip: A film that turns a social crisis into a parenting anxiety, reviewed by someone who noticed the substitution.
Mara: The deeper question the post leaves open is whether any documentary working inside liberal conventions could ask who owns the means of computation — or whether the form itself forecloses it.
The AI Doc: Or How I Became an Apocalyptic Optimist presents itself as a reckoning with artificial intelligence at a moment when AI is transforming labour processes, reshaping global competition, and accelerating technology’s militarisation. Its theatrical release in March 2026, followed by its arrival on Netflix in September, secured a mass audience of workers, parents, and students urgently asking what AI means for their future. Daniel Roher’s documentary claims to answer that question. In reality, it avoids it. Rather than analysing the social forces driving AI’s development, the film offers a therapeutic narrative aimed at an anxious professional class.
The film’s central conceit, Roher’s impending fatherhood, immediately reframes a social crisis as a private psychological dilemma. Instead of examining how AI is reshaping the global economy, intensifying exploitation, or deepening geopolitical conflict, the documentary invites viewers to calibrate their feelings about the future through Roher’s personal journey. This displacement of analysis by affect marks contemporary liberal documentary filmmaking, which increasingly treats political questions as matters of personal anxiety rather than collective struggle. The result is a film that is slick, emotionally resonant, and ideologically hollow.
Roher assembles a collage of opinions from Silicon Valley executives, futurists, ethicists, and celebrities. The documentary’s promotional materials describe these voices as “eye-opening,” but the film’s reliance on tech oligarchs’ self-presentation is one of its least enlightening moves. Asking billionaires whether the future is safe is not an investigation; it is an abdication of analysis. The people driving AI development- those who stand to profit from its deployment- are treated as neutral experts rather than as actors with material interests. Their anxieties, hesitations, and self-justifications become the substance of the debate, while the structural forces shaping AI- capital accumulation, military competition, and the search for new avenues of profit- remain unexamined.
The film’s aesthetic choices reinforce this ideological sleight of hand. Roher’s signature style- rapid montage, intimate confessionals, and a swelling score- creates an atmosphere of emotional urgency. But emotion substitutes for explanation. The viewer is encouraged to feel overwhelmed, hopeful, frightened, or inspired, without ever being asked to understand the economic and political dynamics driving AI’s explosive growth. The film’s narrative arc mirrors the therapeutic culture of contemporary liberalism: anxiety is acknowledged, processed, and soothed, but never politicised.
The documentary’s failure is not simply one of omission. It actively reproduces the ideological framework through which the ruling class seeks to manage public concern about AI. By focusing on individual feelings rather than collective interests, it obscures the fact that corporations and states deploy AI to intensify exploitation, discipline labour, and expand military capabilities. The question millions of people are asking- what does AI mean for my job, my rights, my future- is displaced by Roher’s question: what does AI mean for my child’s emotional wellbeing?
The film’s title, with its self-conscious blend of apocalypse and optimism, encapsulates this ideological manoeuvre. The viewer is invited to oscillate between fear and hope, between dread and reassurance, without ever confronting the material conditions that produce those emotions. The documentary becomes a mood, not an argument.
In the end, The AI Doc is less a reckoning with artificial intelligence than a symptom of the cultural moment that produced it. It reflects a political culture that has lost the capacity to think structurally, that treats social crises as personal dramas, and that looks to the very architects of technological upheaval for guidance. It is a film for a class that feels anxious about the future but cannot imagine challenging the forces that shape it.
The Personalisation of a Social Question
Roher’s impending fatherhood becomes the catalyst for his inquiry. He wants to know what kind of world his child will inherit. This is a legitimate concern, shared by millions of workers who face an unprecedented technological transformation. But the film immediately converts this collective anxiety into an individual psychological journey. The question is no longer: What does AI mean for society? But how should one feel about AI? The answer Roher offers—“apocaloptimism”—is a hybrid of dread and hope, a mood rather than a theory, and a telling ideological manoeuvre.
The first ideological move displaces social analysis with emotional calibration. By framing AI as an emotional dilemma, the film avoids confronting the social relations within which the technology is being developed. It avoids asking who owns AI, who profits from it, and who it harms. Instead, it asks how one should respond emotionally to a rapidly changing world. The viewer is encouraged to oscillate between fear and hope, rather than to analyse the material forces shaping AI’s trajectory. This oscillation is not neutral; it is a political act that substitutes affect for critique.
“Apocaloptimism” functions as a class-specific coping mechanism. It acknowledges danger, permits unease, and then resolves to be hopeful—because hope is more comfortable than struggle. It is a psychological balm for a professional class that senses crisis but cannot imagine challenging the structures that produce it. The film’s emotional arc mirrors this class’s ideological habits: anxiety is recognised, processed, and soothed, but never politicised. The viewer is asked to manage their feelings, not to interrogate the system.
This ideological framing has concrete consequences. By centring Roher’s personal fears, the film erases the collective dimension of AI’s development. The international working class—the only social force capable of altering the course of technological change—does not appear in the film’s frame of reference. Workers are present only as abstract figures who might lose jobs or face disruption, never as agents capable of shaping the future. The documentary thus reproduces a familiar liberal narrative: history is made by individuals with feelings, not by classes with interests.
The film’s choice of interviewees compounds the absence of class analysis. Roher turns to Silicon Valley executives, futurists, and ethicists—figures whose perspectives are shaped by their proximity to capital, not by the experience of exploitation. Their anxieties and hopes become the film’s emotional palette. But these are not neutral observers. They represent corporations that stand to profit enormously from AI’s expansion. Their reassurances, hesitations, and moral reflections serve to naturalise a technological trajectory driven by competition, profit, and geopolitical rivalry.
By presenting these voices as part of a balanced debate, the film obscures the structural forces at work. It treats AI as a phenomenon understood through a collage of opinions rather than through an examination of capitalism’s need to intensify productivity, reduce labour costs, and expand surveillance. The documentary’s emotional framing thus becomes a method of depoliticisation. It transforms a social crisis into a personal drama, and a political question into a psychological riddle.
“Apocaloptimism” ultimately reveals the film’s ideological core. It is a mood designed for a class that feels threatened by technological change but cannot imagine collective resistance. It demands nothing of the viewer except emotional calibration. It proposes no alternative social order, no democratic control over technology, no worker mobilisation. It is a politics of feeling in place of a politics of struggle.
In this sense, Roher’s film is not simply inadequate; it is symptomatic. It reflects a culture in which structural analysis has been replaced by therapeutic narratives, and in which the future is imagined not as a terrain of conflict but as an emotional landscape to be navigated. The danger is acknowledged, the hope is affirmed, and the system remains untouched.
Asking the Oligarchs Whether the Future Is Safe
The film’s interview roster reveals its ideological horizon with remarkable clarity. Roher turns not to workers, educators, or those whose lives are already being reshaped by AI, but to the most powerful executives in Silicon Valley: Sam Altman and Ilya Sutskever of OpenAI, Demis Hassabis of Google DeepMind, and Dario and Daniela Amodei of Anthropic. These figures are not neutral experts. They are the executives of corporations valued in the hundreds of billions, backed by the largest concentrations of finance capital in history. Their companies are at the centre of a global technological arms race, competing for market dominance, military contracts, and geopolitical advantage. Asking them whether AI will be good for humanity is like asking the owners of the oil majors whether the climate is in good hands. Their answers are predictable: AI is dangerous, but manageable; transformative, but controllable; risky, but ultimately beneficial—provided, of course, that they are the ones managing it.
The documentary supplements these corporate voices with researchers and ethicists: Yoshua Bengio, Timnit Gebru, Eliezer Yudkowsky, Tristan Harris, Aza Raskin. Their perspectives range widely—from labour exploitation and data colonialism to existential catastrophe and runaway superintelligence. Yet the film treats them all as “voices” in a debate to be balanced, rather than evidence to be weighed. The result is a collage of opinions, not an explanation. The viewer is presented with a spectrum of viewpoints, but no framework for understanding why these viewpoints exist, how they relate to one another, or what material interests they express.
This is the hallmark of contemporary liberalism: present disagreement as pluralism, and pluralism as insight. A documentary that sets out to explain a phenomenon and ends by presenting a spread of opinions has explained nothing. It has merely curated a marketplace of ideas, treating every perspective as interchangeable and none as analysed in relation to the underlying social structure. The film’s method is to gather voices whose assessments do not neatly align and to present this dissonance as a virtue. But disagreement is not analysis. A cacophony of perspectives does not constitute understanding.
The ideological function of this approach is clear. By flattening the differences between corporate executives, academic researchers, and critics of the tech industry, the film obscures the power relations that shape AI’s development. The executives who stand to profit from AI’s expansion are placed on the same plane as those who warn of its dangers. The film treats their statements as contributions to a conversation rather than expressions of class interest. The viewer is encouraged to see the debate as a clash of ideas rather than as a struggle between competing social forces.
This pluralistic framing also allows the film to avoid taking a position on the central question: what drives AI development? The answer is not mysterious. Private corporations are developing AI under intense market competition and geopolitical rivalry. Its deployment is shaped by the imperatives of profit, surveillance, and military advantage. But the documentary’s collage structure prevents these forces from coming into view. Instead, the viewer is left with a series of personal reflections, anxieties, and speculations—none of which illuminate the material dynamics at work.
In the end, the film’s interview roster is not simply a list of participants; it maps its ideological limits. By privileging the voices of the tech elite and framing their perspectives as part of a balanced debate, the documentary reproduces the worldview of a class that sees technological change as a matter of ideas rather than interests. It offers pluralism in place of analysis, opinion in place of explanation, and emotional resonance in place of political clarity.
The Absent Subject: The Working Class
The film’s most striking absence is the working class. Roher’s documentary contains no examination of the labour conditions under which AI is developed, the global supply chains of data annotation, the militarisation of machine learning, the geopolitical rivalry between the United States and China, or the use of AI to cut labour costs and intensify exploitation. AI is not emerging in a vacuum. It is being developed within capitalist social relations, under conditions of inter‑imperialist competition, and in close collaboration with the military‑intelligence apparatus. Its first large‑scale applications are not in utopian problem‑solving but in automating managerial control, expanding surveillance, reducing labour costs, and enhancing targeting systems in warfare.
This omission is not accidental. It reflects the film’s ideological horizon. Roher’s narrative centres on personal anxiety, elite opinion, and emotional calibration, not on the material processes through which AI is reshaping global capitalism. The documentary’s defenders often point out that executives such as Altman, Hassabis, and the Amodeis have publicly called for slowing “frontier” development. But none of them will do so unilaterally, because doing so risks falling behind rivals. This is a candid admission that AI’s trajectory is dictated not by ethics or philosophical reflection, but by profit and national advantage. The film circles this truth and moves on.
The absence of the working class is particularly glaring given the scale of transformation already underway. AI systems are trained through vast, invisible labour forces—data annotators in the Global South working for subsistence wages, content moderators exposed to traumatic material, and engineers labouring under intense pressure in hyper‑competitive corporate environments. These workers do not appear in Roher’s film. Nor does the militarisation of machine learning appear: the integration of AI into drone warfare, battlefield logistics, intelligence analysis, and autonomous weapons development. The geopolitical rivalry between the US and China—one of the primary drivers of AI investment—is likewise absent. The documentary treats AI as a technological debate rather than as a terrain of global conflict.
Instead, the film focuses on two categories of risk. The first is speculative: runaway superintelligence, existential catastrophe, the familiar tropes of AI apocalypse. The second is reformable: bias, misinformation, harms to children, ethical design. Both categories are framed as solvable through regulation, industry self‑restraint, and “humane” design. These are the risks that Silicon Valley is comfortable discussing, because they do not threaten the underlying social order. They let executives present themselves as responsible stewards of a dangerous technology while avoiding confrontation with the economic imperatives driving AI’s expansion.
Absent from the film is the most immediate and certain danger: that a technology capable of vastly increasing human productivity will, under capitalism, be used to throw millions out of work and concentrate wealth even further in the hands of a tiny elite. This is not hypothetical. It is already happening. AI is being deployed to automate managerial oversight, intensify workplace surveillance, and restructure labour processes in ways that reduce staffing levels and weaken workers’ bargaining power. Productivity gains accrue to shareholders, not to the people whose jobs are being transformed or eliminated.
The problem, in other words, is not the machine. It is who owns it and to what end. Roher’s documentary cannot confront this question because it is structurally incapable of doing so. Its emotional framing, its reliance on elite voices, and its refusal to analyse the social relations of AI development all serve to depoliticise a profoundly political phenomenon. The result is a film that gestures toward danger, acknowledges anxiety, and then retreats into therapeutic reassurance—leaving the real dynamics of AI power untouched.
“Apocaloptimism” as Ideology
The term “apocaloptimism” deserves scrutiny because it crystallises the ideological core of Roher’s documentary. It is presented as a mature emotional stance—acknowledge danger, feel the requisite unease, and then resolve to be hopeful. But this posture is not politically neutral. It is a quintessentially upper‑middle‑class response to crisis, shaped by a social stratum that senses instability yet cannot imagine collective struggle or systemic transformation. “Apocaloptimism” demands nothing of the viewer except emotional calibration. It proposes no social force capable of altering the course of events, because the only force that could—the international working class—does not appear anywhere in the film’s frame of reference.
The documentary’s emotional arc thus substitutes for political analysis. Roher’s impending fatherhood becomes the structuring device through which the film interprets the future. His personal anxiety is treated as a universal experience, and the viewer is invited to identify with his oscillation between dread and hope. This emotional oscillation is the film’s method: it acknowledges crisis, gestures toward catastrophe, and then retreats into reassurance. The danger is real, but the response is affective rather than analytical. The viewer is asked to feel their way through the problem, not to understand it.
This emotional framing is not incidental. It reflects the ideological habits of a class that experiences precarity but lacks a political vocabulary for confronting it. The professional‑managerial class, whose members dominate the documentary’s imagined audience, is caught between capital’s power and the insecurity of technological change. They fear downward mobility, job displacement, and the erosion of their social status. Yet they cannot conceive of collective struggle, because their worldview is shaped by individualism, meritocracy, and the belief that social problems are best addressed through personal reflection or ethical consumption. “Apocaloptimism” is the emotional ideology of this class: a way of managing anxiety without confronting its structural causes.
The film’s reliance on elite voices reinforces this dynamic. By centring Silicon Valley executives, futurists, and ethicists, Roher constructs a narrative in which the future is shaped by individuals’ insights and decisions rather than by conflict between social classes. The international working class—the only force capable of democratically shaping technological development—remains invisible. Workers appear only as potential victims of automation or as abstract figures in discussions of “labour disruption.” The film never depicts them as agents with interests, capacities, or political power. This erasure is essential to the film’s emotional logic. If the working class were present, the viewer would confront the possibility of struggle rather than the necessity of hope.
“Apocaloptimism” also functions as a mechanism of depoliticisation. By framing AI as an emotional dilemma, the film avoids asking who owns the technology, who profits from it, and who it harms. It avoids examining the capitalist imperatives—competition, profit maximisation, and geopolitical rivalry—that drive AI’s development. Instead, it encourages viewers to adopt a mood that is neither fully pessimistic nor fully optimistic. This mood mirrors the ideological confusion of a class that senses crisis but cannot imagine alternatives.
Historiographical Context: Technology, Capital, and Class Power
Marx’s Grundrisse and Braverman’s Labour and Monopoly Capital provide the essential theoretical foundation that Roher’s documentary lacks. In the Marxist tradition, technology is never treated as an autonomous force or a morally ambiguous phenomenon floating above society. It is analysed as a moment within the social relations of production. Machines do not liberate or enslave on their own; they are instruments of class power. Their effects depend entirely on the social system into which they are introduced. Under capitalism, technological innovation is inseparable from the drive to reduce socially necessary labour time, extract surplus value, intensify managerial control, and compete globally between capitals. These dynamics shape not only the development of AI but its deployment, its risks, and its social meaning.
Roher’s documentary belongs to a long lineage of liberal technological discourse that treats technology as autonomous, neutral, or morally ambiguous. In this tradition, machines appear as independent actors, capable of reshaping society according to their own internal logic. The social relations of production—the ownership of technology, the imperatives of profit, the organisation of labour, the pressures of competition—are displaced by narratives of innovation, creativity, and ethical responsibility. The result is a historiographical distortion: technology is framed as a psychological dilemma rather than as a weapon in capital’s hands.
This distortion is central to the film’s ideological function. By presenting AI as a force that might be dangerous or beneficial depending on how individuals feel about it, Roher obscures the class character of technological development. The documentary’s emotional framing—its oscillation between dread and hope, its emphasis on personal anxiety, its therapeutic narrative arc—serves to depoliticise a profoundly political phenomenon. AI becomes a matter of mood rather than of power.
The Marxist tradition insists on the opposite. Under capitalism, technology is developed to increase productivity, reduce labour costs, and intensify control over workers. Market competition and geopolitical rivalry between states shape it. AI is no exception. Its most immediate applications are not in solving global problems or enhancing human flourishing but in automating managerial oversight, expanding surveillance, restructuring labour processes, and enhancing military capabilities. These uses are not accidental; they follow directly from the imperatives of capital accumulation and state power.
Roher’s documentary cannot confront these dynamics because it rests on liberal assumptions. It treats AI as a neutral tool whose dangers arise from misuse or insufficient regulation. It frames risk in terms of speculative catastrophe or reformable harm—runaway superintelligence, bias, misinformation, ethical design—while ignoring the most certain and immediate danger: that AI will be used to throw millions out of work and concentrate wealth even further in the hands of a tiny elite. This is not a hypothetical. It is already happening. AI systems are being deployed to intensify exploitation, weaken labour bargaining power, and expand managerial control. Productivity gains accrue to shareholders, not workers.
By refusing to analyse these dynamics, the documentary performs a historiographical sleight of hand. It replaces political economy with personal emotion, class struggle with psychological calibration, and structural analysis with a collage of elite opinions. In doing so, it reproduces the ideological worldview of a class that senses crisis but cannot imagine alternatives. The problem, in the end, is not the machine. It is who owns it, who controls it, and what end it is deployed to. Roher’s film cannot say this, because to do so would require abandoning “apocaloptimism” and confronting the reality of class power.
The Real Question: Who Owns the Means of Computation?
Roher and Kwan are undeniably talented filmmakers. The AI Doc is polished, emotionally resonant, and crafted with the narrative intimacy that has become a hallmark of contemporary liberal documentary style. A parent’s fear for a child’s future is real, and Roher’s framing taps into a widespread and legitimate anxiety. But the answer to that fear does not lie in the reassurances of billionaires or the moral exhortations of Silicon Valley’s in‑house critics. The film’s emotional power cannot compensate for its political evasions, and its aesthetic sophistication ultimately obscures the social forces shaping AI rather than illuminating them.
The documentary’s central conceit—Roher’s impending fatherhood—creates a narrative structure that is affectively compelling but politically disabling. It transforms a collective crisis into a private dilemma, a social question into a psychological journey. The viewer is invited to empathise with Roher’s oscillation between dread and hope, but not to interrogate the material conditions producing those emotions. This is the ideological function of the film’s emotional arc: it substitutes personal feeling for political analysis, and therapeutic reassurance for structural critique.
The absence of the working class is decisive. AI is the product of global labour: data annotators in Kenya and the Philippines, warehouse workers monitored by algorithmic systems, engineers labouring under intense corporate pressure, and millions whose jobs are being restructured or eliminated. Yet none of these people appears in the film. Their absence is not merely an oversight; it reflects the film’s class perspective. By centring elite voices—Altman, Hassabis, the Amodeis—the documentary reproduces the worldview of a class that sees technological change as a matter of ideas, ethics, and personal responsibility rather than as a terrain of class struggle.
The film’s defenders often praise its “balanced” roster of interviewees, from corporate executives to ethicists and critics. But this pluralism is itself ideological. It treats perspectives shaped by vast concentrations of capital as equivalent to those shaped by research, activism, or existential speculation. It presents disagreement as insight, and insight as explanation. The result is a collage of opinions that never confronts the underlying social relations driving AI’s development: the imperatives of profit, the pressures of inter‑imperialist rivalry, and the integration of machine learning into military and surveillance infrastructures.
Against this backdrop, the film’s emotional resolution—“apocaloptimism”—functions as a class‑specific coping mechanism. It acknowledges danger, permits unease, and then resolves to be hopeful. But hope, in this formulation, is not a political orientation; it is a psychological balm. It demands nothing of the viewer except emotional calibration. It proposes no collective force capable of altering the course of technological development, because the only force that could—the international working class—has been excluded from the narrative.
A Marxist analysis points elsewhere. From Marx’s Grundrisse to Braverman’s Labour and Monopoly Capital, the tradition has consistently shown that technology is not autonomous. Social relations of production shape it. Under capitalism, technological innovation is inseparable from the drive to reduce socially necessary labour time, extract surplus value, intensify managerial control, and outcompete rivals. AI is not an exception; it is a paradigmatic expression of these dynamics.
The answer to a parent’s fear for a child’s future does not lie in billionaires’ reassurances or Silicon Valley critics’ moral exhortations. It lies in placing this extraordinary technology—the product of the collective labour and knowledge of generations—under democratic, public control, and directing it toward social need rather than private profit. Only then can AI become a tool for human liberation rather than another instrument of capitalist domination.
Key Articles (Analytical, Marxist, and Critical Technology Studies)
On AI, Labour, and Capital
Shoshana Zuboff, “Big Other: Surveillance Capitalism and the Prospects of an Information Civilisation” (Journal of Information Technology, 2015) — foundational analysis of data extraction as a new frontier of capital.
Kate Crawford & Vladan Joler, “Anatomy of an AI System” (2018) — maps the global labour, resource extraction, and logistics behind Amazon’s Alexa; indispensable for showing AI as a material system.
Aaron Benanav, “Automation and the Future of Work” (New Left Review, 2019) — argues that automation is driven by stagnation and competition, not technological inevitability.
Sarah T. Roberts, “Commercial Content Moderation: Digital Labourers’ Dirty Work” (Media Studies, 2016) — exposes the hidden labour behind AI training and moderation.
Meredith Whittaker, “The Steep Cost of Capture: How the Tech Industry Co‑opts AI Ethics” (AI Now Institute, 2020) — crucial for understanding why corporate “ethics” discourse depoliticises AI.
On Silicon Valley Ideology
Evgeny Morozov, “The Taming of Tech Criticism” (The Baffler, 2014) — explains how liberal tech discourse neutralises structural critique.
Fred Turner, “Machine Politics: The Rise of the Political Entrepreneur” (Harvard Kennedy School Review, 2018) — situates Silicon Valley’s worldview within American managerial liberalism.
Jathan Sadowski, “When Data is Capital” (Big Data & Society, 2019) — argues that data extraction is a new form of capital accumulation.
On AI, Militarisation, and Geopolitics
Paul Scharre, “Killer Apps: The Real Dangers of AI in Warfare” (Foreign Affairs, 2023) — mainstream but useful for mapping military integration.
Lindsay Cohn, “AI and the New Military Revolution” (Parameters, 2022) — outlines how machine learning is transforming command and control.
Elsa Kania, “AI and China’s Military Strategy” (Center for a New American Security, 2019) — essential for understanding US–China rivalry.
On Marxism, Technology, and Social Relations
Harry Braverman, “The Degradation of Work in the Twentieth Century” (Monthly Review, 1974) — classic analysis of managerial control and deskilling.
David Harvey, “The Technological Fix” (A Brief History of Neoliberalism, 2005) — situates technological innovation within neoliberal restructuring.
Nick Dyer‑Witheford, “Cyber‑Proletariat: Global Labour in the Digital Vortex” (Monthly Review Press, 2015) — indispensable for a Marxist analysis of digital capitalism.
📖 Bibliography (Marxist, Critical Theory, Labour Studies, AI Critique)
Marxist Foundations
Karl Marx, Grundrisse (1857–58) — especially the “Fragment on Machines.”
Karl Marx, Capital, Vol. I (1867) — chapters on machinery, large‑scale industry, and relative surplus value.
Friedrich Engels, The Condition of the Working Class in England (1845).
Harry Braverman, Labour and Monopoly Capital (1974).
Ernest Mandel, Late Capitalism (1975) — on technological innovation and competition.
David Harvey, A Companion to Marx’s Capital (2010).
Technology, Capitalism, and Labour
Nick Dyer‑Witheford, Cyber‑Proletariat (2015).
Ursula Huws, Labour in the Global Digital Economy (2014).
Shoshana Zuboff, The Age of Surveillance Capitalism (2019).
Aaron Benanav, Automation and the Future of Work (2020).
Sarah T. Roberts, Behind the Screen: Content Moderation in the Shadows of Social Media (2019).
Kate Crawford, Atlas of AI (2021).
AI, Ethics, and Ideology
Meredith Whittaker, The AI Industry and Its Ethics Problem (AI Now, 2020).
Timnit Gebru et al., “Datasheets for Datasets” (2018).
Ruha Benjamin, Race After Technology (2019).
Safiya Noble, Algorithms of Oppression (2018).
Evgeny Morozov, To Save Everything, Click Here (2013).
Geopolitics, Militarisation, and Imperialism
Paul Scharre, Army of None: Autonomous Weapons and the Future of War (2018).
Elsa Kania, Battlefield Singularity: China’s Military AI Strategy (2017).
Michael Klare, The Race for What’s Left (2012) — resource extraction and global competition.
John Bellamy Foster, The New Imperialism of Global Capital (Monthly Review, various essays).
Documentary, Liberalism, and Political Affect
Thomas Frank, Listen, Liberal (2016) — on the professional‑managerial class.
Lauren Berlant, Cruel Optimism (2011) — essential for analysing affect as ideology.
Jacob Coxon’s resignation from Anthropic, a company that loudly champions ‘AI safety,’ has been portrayed in the media as a personal moral crisis a lone engineer stepping back from dangerous territory. But it is actually much more important: it reveals, from within the industry, that the entire AI sector is propelled not by scientific progress or human necessity, but by capitalist competition driving toward potentially disastrous results that its own creators worry about.
Coxon’s warning is clear: “the people building AI earnestly believe that it could kill us all by the end of the decade.” This isn’t just a speculative fear or a distant hypothetical. It’s the assessment of those with the deepest technical understanding of the systems being created. Still, Coxon admits, “coordination between competing capitalist firms racing for market dominance and state backing cannot be relied upon.” The industry presses on at full speed. This paradox—knowing the danger but feeling compelled to act— isn’t psychological. It’s structural. Capitalism’s logic asserts itself forcefully and without ambiguity.
Anthropic was established by a splinter group from OpenAI, aiming for safer AI development. However, after three years, Coxon notes the company finds itself in the same competitive race it tried to avoid. This is because, under capitalism, no company can afford to slow its progress without risking destruction by competitors. The issue with safety isn’t purely technical but related to the nature of economic relationships. Under the capitalist system, “responsible scaling’ often remains just a marketing phrase, not a practical reality.
Evan Hubinger, who still works at Anthropic, emphasizes the serious risk involved. He personally estimates there’s over a 10% chance that AI could eradicate all humans within ten years, despite the company’s lack of concrete plans to address superintelligence alignment and not being clearly on track to do so. Samuel Marks, another staff member, notes that concern levels increase with seniority. These are not marginal opinions; they come from engineers directly involved with the systems. Their warnings are based on technical realities, yet companies continue their current course.
This illustrates the “rational irrationality” of capitalism: every firm needs to grow faster or face collapse. The overall result—possibly human extinction—fails to concern the market. Marx recognized this contradiction 150 years ago: productive forces outpace the social relations meant to control them. AI is just the latest, most intense form of this dilemma.
The Resignation Genre as Political Symptom
The media often depicts each resignation as a unique human-interest story: such as the conscientious objector, the disillusioned researcher, or the engineer who quits to pursue poetry. However, collectively, these stories expose a more profound trend: a technical workforce awakening to its own sense of powerlessness within capitalist production.
Mrinank Sharma cautions that “the world faces danger… not only from AI or bioweapons, but from a web of interconnected crises happening right now,” then announces he will leave the industry to pursue poetry. Another OpenAI researcher resigns over adding advertising to a chatbot used for sharing “their medical fears, relationship issues, beliefs about God and the afterlife,” warning of “possible manipulation of users.” These actions are not mere acts of conscience, but signs of alienation. Engineers, once confident as innovators, now see themselves as workers under capital, forced to develop systems they fear and cannot control.
The apocalyptic warnings—such as “10 per cent chance of killing all humans” and “could kill us all by the end of the decade”—serve a specific ideological purpose. They depict catastrophe as unavoidable, suggesting AI is an autonomous force beyond human control. This sense of fatalism hides a key truth: AI is not a metaphysical entity but a social relation. People create it—engineers in Silicon Valley, data annotators in Kenya and the Philippines, miners in the Congo, and chip fabricators in Taiwan.
The question of whether AI becomes a tool of liberation or barbarism is not a technical question of “alignment.” It is a political question of ownership and control. Between the present order and any catastrophic outcome stands the international working class.
Coxon proposes a “temporary ban on improving model capabilities,” but admits it is unlikely because coordination between competing firms and states cannot be relied upon. This is the essential point. Regulation cannot restrain capital. The capitalist state is not a neutral arbiter; it is the ruling class’s executive committee. It exists to defend private property, not to restrain it. Every proposal for “responsible scaling,” “constitutional AI,” or “government oversight” collapses the moment profit demands acceleration. The market does not permit restraint. The only solution is expropriation.
The Socialist Program for AI
Coxon and his colleagues highlight a contradiction capitalism cannot solve. Addressing this issue calls for a revolutionary overhaul of how we own and control productive resources. The socialist plan is explicit: nationalise AI, cloud services, semiconductor companies, and platform monopolies, and turn them into public utilities managed democratically by workers. Ensure no worker loses their job to automation by using AI to shorten workweeks without reducing pay. Also, bring all AI development under international planning, directing research to serve human needs rather than profit.
End the secrecy kept by private corporations by making all models, datasets, and research pipelines accessible to the public. Finally, use AI as a tool for global economic planning—helping coordinate production, reduce waste, and enhance living standards worldwide. This is not a reformist agenda but a revolutionary one. It demands the working class to take control of productive forces and reorganize society based on socialist principles. The resignations at Anthropic and OpenAI are not moral crises but alerts from within capitalism’s core. Those closest to the technology fear it could destroy humanity—yet the system forces them to continue developing it.
This represents capitalism’s most fundamental contradiction: a social system that endangers humanity’s survival. Humanity faces a clear choice: the working class must take control of the technology and utilize it to establish a rational, planned, socialist society—or the ruling class will persist in its reckless pursuit of disaster. The future of AI is fundamentally a political issue, not a technical one. Its outcome will be determined not by engineers or executives, but through the conscious struggle of the international working class.
The details from 404 Media regarding Amazon’s LAS8 facility — where workers remove spines from books, scan them, and discard the remains — have caused widespread shock. The rumoured internal logo, depicting a tyrannosaurus devouring an open book, is more than just dark humour; it symbolises the relationship between capital and culture. The key point is not the gruesome imagery or the destruction of rare books but that this process is not unusual. It exemplifies capitalism’s fundamental principle: turning all human labor, creativity, and cultural heritage into raw materials for profit.
Capital views only inputs, not the rarity or scholarly value of a first edition, a rare monograph, or a fragile volume. It ignores the loss of centuries of intellectual effort because it measures only the rate of return. The destruction of books to develop AI isn’t a flaw in the technology; rather, it’s how the technology functions within capitalist social relations.
The irony of “uncontaminated” text
The AI industry’s demand for pre-digital books highlights a deeper contradiction. As noted, these books are valued because they are “uncontaminated’—free from the recursive errors and stylistic decline caused when AI models are trained on AI-generated texts. This situation exemplifies a system consuming itself. The companies flooding the internet with machine-produced content now have to destroy physical books to access untainted text, as their digital outputs have compromised the quality of the digital commons, effectively strip-mining humanity’s intellectual heritage.
This is more than just irony; it vividly illustrates a core contradiction highlighted by Marx: as productive forces evolve, they surpass the social relations that regulate them. While AI has the potential to broaden human knowledge, remove monotonous tasks, and make culture more accessible, within capitalism it largely accelerates the erosion of cultural heritage and deepens exploitation.
Who owns the accumulated knowledge of humanity?
Tom Hall emphasises that AI systems are built upon the collective labour, knowledge, and creative outputs of millions of workers. This is especially true for the books destroyed at LAS8, whose contents—including scientific discoveries, literary works, and historical scholarship—represent the intellectual labour of humans across generations. These works are social products, created collectively and meant for universal access. However, under capitalism, they are regarded as a “finite and depleting resource” to be privately exploited by companies like Amazon, Anthropic, and others. After their informational content is extracted, the physical copies are often discarded as waste.
This isn’t simply a copyright dispute; it’s about who owns humanity’s collective intellectual legacy. The solution isn’t to stop AI progress—such reactionary calls divert blame from capitalism and target the technology itself. As Trotsky emphasised, technology represents a fundamental victory for humanity. While machines may oppress workers, workers can ultimately achieve liberation only through machines. The real question isn’t whether AI should exist but rather under what social conditions, in whose interests, and who should control it.
A key insight from the 404 Media investigation is that it relied on anonymous Amazon workers who risked personal safety to testify. This highlights a recurring point the WSWS emphasises: beneath every element of “automation,” human labour exists—hidden from public view and controlled entirely by corporate interests. The workers at VGT3, who cut spines and feed scanners, are part of a global workforce that also labels training data, moderates toxic content, and performs routine tasks critical to AI development. Their work is vital yet often deliberately kept out of sight.
The revelation about Amazon did not come from regulators but was uncovered by a $29 AirTag and a proactive reporter, which itself highlights a problem. No laws require Amazon, Anthropic, Google, or OpenAI to reveal what data they scan, delete, or how they protect rare materials. The industry’s own explanation of its actions surfaces only when it is compelled to disclose information—and even then, often through vague corporate statements.
Amazon’s statement, which claims to “purchase books through commercial channels to help develop and improve the products and services our customers use,” is a carefully crafted avoidance. It omits any mention of AI, destruction, or why a company primarily selling books now runs a facility focused on their disassembly.
Removing rare books to train AI models does not indicate a regulatory failure. It cannot be addressed solely through disclosure requirements, cultural heritage protections, or ethical guidelines — although these measures might temporarily lessen the harm. Instead, it reflects the core conflict between the social nature of production and the private ownership of its outcomes.
Humanity’s accumulated knowledge is a social creation, and the technology that makes this knowledge universally accessible is also the result of extensive social labour. However, a few monopolies control both and treat them as private assets for profit. The answer is not to reject AI but to advocate for the expropriation of major tech companies and their conversion into public utilities managed democratically by workers. The knowledge in books—and the technology that enables access—rightfully belongs to all of humanity, not to corporations like Amazon.
Pip: A BBC documentary tears the veil off OnlyFans and somehow manages to indict everyone except the economic system running the whole operation. Impressive restraint.
Mara: freerein61 takes that contradiction apart in a piece that connects platform capitalism, the pseudo-left's defence of commodification, and what the collapse of sustainable cultural work actually looks like on the ground. Let's start with the BBC investigation itself and what it reveals — and conceals.
BBC Investigation, Platform Capitalism, and the Pseudo-Left's Alibi
Pip: The BBC went inside OnlyFans expecting to find bad actors. What the post argues is that they found the system working exactly as designed — and then flinched from saying so.
Mara: The piece sets the frame directly: "he is following a business model that is discussed openly in these forums." The agent who threatened a woman and her daughter, who sent masked men to strangle her in her own home, is not a rogue element. He is the informal enforcement arm of a platform taking a twenty percent cut and disclaiming responsibility for everything downstream.
Pip: Which is the rentier logic in its purest form. OnlyFans generated $684 million in pre-tax profits last year by extracting value from labour it does not employ, policing exploitation it does not acknowledge, and parasitising creators it does not protect.
Mara: And the BBC's response to all of this is to invoke the Online Safety Act and interview the UK's anti-slavery commissioner. The post argues that framing matters enormously here: calling it "modern slavery" portrays extreme exploitation as a rare crime rather than a structural feature. It "individualises exploitation, prosecutes the worst offenders, and leaves the economic structure that produces the desperation intact."
Pip: So the documentary functions less as exposure and more as pressure-release — enough outrage to satisfy viewers, not enough analysis to threaten the system producing the outrage.
Mara: The post makes the same argument about the pseudo-left. The "sex work is work" position, it contends, is not progressive but capitalist realist — it accepts that all human relations must become commodities and frames resistance as prudishness. The post puts it plainly: "No amount of regulation can make the commodification of the human body humane."
Pip: The comparison to justifying nineteenth-century child labour lands harder than it should.
Mara: There is also a sharp economic dimension. The piece points to Kate Nash losing money on every tour and turning to OnlyFans to cover costs — streaming paying $0.00173 per play, touring costs up forty percent since the pandemic, eighty percent of music revenue captured by one percent of artists. The post's argument is that sexual commodification is not a choice but a forced response to the collapse of culturally supported work.
Pip: The language of agency, the post notes, belongs to a class for whom OnlyFans might be a lucrative side hustle. "For Rebecca from South Wales, it was a trap."
Mara: The Marxist position the post advances is abolition of the conditions, not sanitisation of the market: expropriating tech monopolies, socialising digital platforms, treating cultural labour as a public good. Regulation, it argues, cannot humanise a market whose violence is not accidental but structural.
Pip: The violence, as the post puts it, is capitalism without its ideological mask — which is perhaps the one thing the BBC documentary accidentally got right by showing it.
Mara: The thread running through all of this is what happens when a system has no use for most of its people and no language for saying so honestly.
Pip: Next time, presumably, the BBC will commission a follow-up about Uber drivers and call it a labour story. We'll be here.
I have known Emma for over a month. She has contacted me four times and follows me after I post an article. Although she claims to live in Shoreditch each time, she seems to have multiple personalities. Her end goal appears to be to generate revenue from her OnlyFans page, which she advertises.
To draw in customers, she shares photos of herself in revealing clothing. She is attractive and has a notably large backside, if that’s your preference. The source of these images is uncertain, but they are likely generated with highly realistic synthetic faces, bodies, or bios created by language models to mimic real users. These accounts are primarily involved in coordinated influence campaigns, crypto scams, spam, and political boosting. Research shows that such accounts often operate in groups and tend to have fewer followers.
To understand how these accounts operate, particularly given the advanced AI technology involved, visual and behavioural cues are crucial. Emma’s fake accounts seldom post original or varied content. Other fake profiles often act as reply-guys, spam affiliate links, promote schemes like “get-rich-quick,’ cryptocurrency scams, or use generic language similar to ChatGPT. These profiles usually follow thousands of users but have very few followers.
Although Emma the bot dismisses her work as trivial and insists she’s real, the rise of AI-generated fake identities and synthetic bot networks poses more than just a technical challenge. It exposes a deeper problem rooted in capitalism’s social dynamics. This issue significantly affects humans as aware, social beings and could be harmful. To fully understand this, we must link it to capitalism’s long history of using technology to benefit the ruling class, as well as the wider social crisis capitalism has induced in human awareness and community.
I identified Emm’s game early, but for others less aware, a collapse of Shared Reality can threaten mental health. One of the most damaging effects of AI-created fake profiles is what can be called an epistemic crisis—a systematic breakdown in an individual’s capacity to tell reality from falsehood. This problem isn’t novel under capitalism; historically, the ruling class has sustained control via ideological mystification.
However, AI bots operating on an industrial scale mark a significant advancement. When someone cannot be sure if their online interlocutor is human or machine, if the consensus they see reflects genuine public opinion or a synthetic effort, and if the emotional connection they feel is with a real person or an algorithm the very basis of rational social discourse begins to break down..
This has profoundly corrosive effects on individuals. The natural human response to an environment saturated with deception and manipulation is a generalized suspicion, not merely of bots but of everyone. When you cannot reliably distinguish the genuine from the fake, you begin to distrust all online interactions. This cynicism is, in many ways, a rational adaptation to an irrational environment, but it carries an enormous psychological cost. It deepens social atomisation, makes solidarity harder to build, and breeds a pervasive sense of isolation and powerlessness. People retreat from engagement, or are drawn into filter bubbles where algorithmic amplification — often driven by bot networks — creates false communities built around manufactured outrage.
In this already fragmented social landscape, the emergence of AI-generated fake social environments often results in predictable harms. Young people, still forming their social identities and seeking validation through peer interactions, are particularly vulnerable. When online communities are dominated by artificial personas created to provoke engagement, outrage, or emotional reliance, authentic developmental progress is hindered. The fundamental human ability to form genuine relationships—based on mutual vulnerability, genuine uncertainty, and meaningful stakes—is jeopardised when these interactions occur mainly with machines rather than real individuals.
