AI has become as a deeply polarizing issue on the left, with many people having concerns regarding its reliance on unauthorized training data, displacement of workers, lack of creativity, and environmental costs. I’m going to argue that while these critiques warrant attention, they overlook the broader systemic context. As Marxists, our focus should not be on rejecting technological advancement but on challenging the capitalist framework that shapes its use. By reframing the debate, we can recognize AI’s potential as a tool for democratizing creativity and accelerating the contradictions inherent in capitalism.
Marxists have never opposed technological progress in principle. From the Industrial Revolution to the digital age, we have understood that technological shifts necessarily proletarianize labor by reshaping modes of production. AI is no exception. What distinguishes it is its capacity to automate aspects of cognitive and creative tasks such as writing, coding, and illustration that were once considered uniquely human. This disruption is neither unprecedented nor inherently negative. Automation under capitalism displaces workers, yes, but our critique must target the system that weaponizes progress against the workers as opposed to the tools themselves. Resisting AI on these grounds mistakes symptoms such as job loss for the root problem of capitalist exploitation.
Democratization Versus Corporate Capture
The ethical objection to AI training on copyrighted material holds superficial validity, but only within capitalism’s warped logic. Intellectual property laws exist to concentrate ownership and profit in the hands of corporations, not to protect individual artists. Disney’s ruthless copyright enforcement, for instance, sharply contrasts with its own history of mining public-domain stories. Meanwhile, OpenAI scraping data at scale, it exposes the hypocrisy of a system that privileges corporate IP hoarding over collective cultural wealth. Large corporations can ignore copyright without being held to account while regular people cannot. In practice, copyright helps capitalists far more than it help individual artists. Attacking AI for “theft” inadvertently legitimizes the very IP regimes that alienate artists from their work. Should a proletarian writer begrudge the use of their words to build a tool that, in better hands, could empower millions? The true conflict lies not in AI’s training methods but in who controls its outputs.
Open-source AI models, when decoupled from profit motives, democratize creativity in unprecedented ways. They enable a nurse to visualize a protest poster, a factory worker to draft a union newsletter, or a tenant to simulate rent-strike scenarios. This is no different from fanfiction writers reimagining Star Wars or street artists riffing on Warhol. It’s just collective culture remixing itself, as it always has. The threat arises when corporations monopolize these tools to replace paid labor with automated profit engines. But the paradox here is that boycotting AI in grassroots spaces does nothing to hinder corporate adoption. It only surrenders a potent tool to the enemy. Why deny ourselves the capacity to create, organize, and imagine more freely, while Amazon and Meta invest billions to weaponize that same capacity against us?
Opposing AI for its misuse under capitalism is both futile and counterproductive. Creativity critiques confuse corporate mass-production with the experimental joy of an individual sketching ideas via tools like Stable Diffusion. Our task is not to police personal use but to fight for collective ownership. We should demand public AI infrastructure to ensure that this technology is not hoarded by a handful of corporations. Surrendering it to capital ensures defeat while reclaiming it might just expand our arsenal for the fights ahead.
Creativity as Human Intent, Not Tool Output
The claim that AI “lacks creativity” misunderstands both technology and the nature of art itself. Creativity is not an inherent quality of tools — it is the product of human intention. A camera cannot compose a photograph; it is the photographer who chooses the angle, the light, the moment. Similarly, generative AI does not conjure ideas from the void. It is an instrument wielded by humans to translate their vision into reality. Debating whether AI is “creative” is as meaningless as debating whether a paintbrush dreams of landscapes. The tool is inert; the artist is alive.
AI has no more volition than a camera. When I photograph a bird in a park, the artistry does not lie in the shutter button I press or the aperture I adjust, but in the years I’ve spent honing my eye to recognize the interplay of light and shadow, anticipating the tilt of a wing, sensing the split-second harmony of motion and stillness. These are the skills that allow me to capture images such as this:
Hand my camera to a novice, and it is unlikely they would produce anything interesting with it. Generative AI operates the same way. Anyone can type “epic space battle” into a prompt, but without an understanding of color theory, narrative tension, or cultural symbolism, the result is generic noise. This is what we refer to as AI slop. The true labor resides in the human ability to curate and refine, to transform raw output into something resonant.
People who attack gen AI on the grounds of it being “soulless” are recycling a tired pattern of gatekeeping. In the 1950s, programmers derided high-level languages like FORTRAN as “cheating,” insisting real coders wrote in assembly. They conflated suffering with sanctity, as if the drudgery of manual memory allocation were the essence of creativity. Today’s artists, threatened by AI, make the same error. Mastery of Photoshop brushes or oil paints is not what defines art, it’s a technical skill developed for a particular medium. What really matters is the capacity to communicate ideas and emotions through a medium. Tools evolve, and human expression adapts in response. When photography first emerged, painters declared mechanical reproduction the death of art. Instead, it birthed new forms such as surrealism, abstraction, cinema that expanded what art could be.
The real distinction between a camera and generative AI is one of scope, not substance. A camera captures the world as it exists while AI visualizes worlds that could be. Yet both require a human to decide what matters. When I shot my bird photograph, the camera did not choose the park, the species, or the composition. Likewise, AI doesn’t decide whether a cyberpunk cityscape should feel dystopian or whimsical. That intent, the infusion of meaning, is irreplaceably human. Automation doesn’t erase creativity, all it does is redistribute labor. Just as calculators freed mathematicians from drudgery of arithmetic, AI lowers technical barriers for artists, shifting the focus to concept and critique.
The real anxiety over AI art is about the balance of power. When institutions equate skill with specific tools such as oil paint, Python, DSLR cameras, they privilege those with the time and resources to master them. Generative AI, for all its flaws, democratizes access. A factory worker can now illustrate their memoir and a teenager in Lagos can prototype a comic. Does this mean every output is “art”? No more than every Instagram snapshot is a Cartier-Bresson. But gatekeepers have always weaponized “authenticity” to exclude newcomers. The camera did not kill art. Assembly lines did not kill craftsmanship. And AI will not kill creativity. What it exposes is that much of what we associate with production of art is rooted in specific technical skills.
Finally, the “efficiency” objection to AI collapses under its own short-termism. Consider that just a couple of years ago, running a state-of-the-art model required data center full of GPUs burning through kilowatts of power. Today, DeepSeek model runs on a consumer grade desktop using mere 200 watts of power. This trajectory is predictable. Hardware optimizations, quantization, and open-source breakthroughs have slashed computational demands exponentially.
Critics cherry-pick peak resource use during AI’s infancy. Meanwhile, AI’s energy footprint per output unit plummets year-over-year. Training GPT-3 in 2020 consumed ~1,300 MWh; by 2023, similar models achieved comparable performance with 90% less power. This progress is the natural arc of technological maturation. There is every reason to expect that these trends will continue into the future.
Open Source or Oligarchy
To oppose AI as a technology is to miss the forest for the trees. The most important question is who will control these tools going forward. No amount of ethical hand-wringing will halt development of this technology. Corporations will chase AI for the same reason 19th-century factory owners relentlessly chased steam engines. Automation allows companies to cut costs, break labor leverage, and centralize power. Left to corporations, AI will become another privatized weapon to crush worker autonomy. However, if it is developed in the open then it has the potential to be a democratized tool to expand collective creativity.
We’ve seen this story before. The internet began with promises of decentralization, only to be co-opted by monopolies like Google and Meta, who transformed open protocols into walled gardens of surveillance. AI now stands at the same crossroads. If those with ethical concerns about AI abandon the technology, its development will inevitably be left solely to those without such scruples. The result will be proprietary models locked behind corporate APIs that are censored to appease shareholders, priced beyond public reach, and designed solely for profit. It’s a future where Disney holds exclusive rights to generate “fairytale” imagery, and Amazon patents “dynamic storytelling” tools for its Prime franchises. This is the necessary outcome when technology remains under corporate control. Under capitalism, innovation always serves monopoly power as opposed to the interests of the public.
On the other hand, open-source AI offers a different path forward. Stable Diffusion’s leak in 2022 proved this: within months, artists, researchers, and collectives weaponized it for everything from union propaganda to indigenous language preservation. The technology itself is neutral, but its application becomes a tool of class warfare. To fight should be for public AI infrastructure, transparent models, community-driven training data, and worker-controlled governance. It’s a fight for the means of cultural production. Not because we naively believe in “neutral tech,” but because we know the alternative is feudalistic control.
The backlash against AI art often fixates on nostalgia for pre-digital craftsmanship. But romanticizing the struggle of “the starving artist” only plays into capitalist myths. Under feudalism, scribes lamented the printing press; under industrialization, weavers smashed looms. Today’s artists face the same crossroads: adapt or be crushed. Adaptation doesn’t mean surrender, it means figuring out ways to organize effectively. One example of this model in action was when Hollywood writers used collective bargaining to demand AI guardrails in their 2023 contracts.
Artists hold leverage that they can wield if they organize strategically along material lines. What if illustrators unionized to mandate human oversight in AI-assisted comics? What if musicians demanded royalties each time their style trains a model? It’s the same solidarity that forced studios to credit VFX artists after decades of erasure.
Moralizing about AI’s “soullessness” is a dead end. Capitalists don’t care about souls, they care about surplus value. Every worker co-op training its own model, every indie game studio bypassing proprietary tools, every worker using open AI tools to have their voice heard chips away at corporate control. It’s materialist task of redistributing power. Marx didn’t weep for the cottage industries steam engines destroyed. He advocated for socialization of the means of production. The goal of stopping AI is not a realistic one, but we can ensure its dividends flow to the many, not the few.
The oligarchs aren’t debating AI ethics, they’re investing billions to own and control this technology. Our choice is to cower in nostalgia or fight to have a stake in our future. Every open-source model trained, every worker collective formed, every contract renegotiated is a step forward. AI won’t be stopped any more than the printing press and the internet before it. The machines aren’t the enemy. The owners are.
My critique of AI is rooted in Walter Benjamin’s The Work of Art in the Age of Mechanical Reproduction, something it’s fundamentally incapable of overcoming. A photograph can be reproduced, but the print is worth the paper it’s on unless you do the actual labour of adding a signature. Like you said to produce the original takes actual skill and capital and creative intent. Coding a nice-looking website is artistic even though they’re just tappity-tapping at a keyboard. I could not replicate a good website without knowing multiple programming languages and all the fields web design draws from.
Fundamentally that is not there with AI. It is all slop no matter how much tech demons try to inflate their salary by calling themselves prompt engineers instead of someone who does a lower level of data entry than I did working in tech support for an ISP. No amount of precision refinement of the plagiarism machine will overcome the fundamental valuelessness of it. The moment you upload that AI image you spent 40 hours engineering to the web, I’m going to feed it into another image generator with a prompt that tailors it to my tastes. I can say “make this in the style of Van Gogh” and produce something much better than your original image without any of the time you wasted trying to make a coherent picture, and my energy cost is much lower to produce the better version of the same product. I can’t do that with any actual commodity, only something like an NFT which also insists on its own value. Both NFTs and AI images are standard fictitious capital which can be replicated by their own means of production even easier than the “original” product. You right click>save the NFT and suddenly their $1m monkey jpeg is any other jpeg.
Of course capitalists don’t care about it and just see it as a chance to turbocharge the primary contradiction of capitalism, but the closest historical parallel for me isn’t an artistic commodity so much as it is ersatz bread. They’re doing creative shrinkflation and the core limitation of the technology devalues their product to the point that people stop wanting it. There are Disney Adults who will pathologically seek out any slop with a face they recognise from childhood, but the same thing driving capitalists toward AI to save on labour costs is also driving them toward increasing the costs of the shittier product. People only bought into NFTs when the speculative value turned it into gambling just as they currently support AI because it represents a tech bubble. When that bursts, the energy costs of making an AI image will outweigh any amount of value you could get in the short term at the cost of your long-term reputation. Businesses who ratfuck their marketing departments to use it will cause a brain drain that hurts their ability to advertise, artists who use it will be lumped in with slop, and only niche applications like worse VFX in a product with greater actual capital investment will make economic sense.
The neo-luddite position is the only one that makes sense to me because it’s building on two subsequent centuries of Marxist art/tech/cultural theory. We’re not seizing the mechanised looms because they don’t make actual cloth. Pushing a coherent humanistic idea of what art means, universalising its production and consumption with an economic focus on supporting artisans and artistic co-ops, is the way for people to see value in leftist art. The modernists understood this until that future was stolen from us and only building off what they started will create art that’s something other than a spectacle or commodity. AI “art” is purely within the ideological framework of fascist futurism with no place for us.
I disagree with the critique because tooling around AI is already getting fairly sophisticated. Consider workflows in a tool like ComfyUI, it goes far beyond just typing in a prompt. There is a learning curve to using a tool like that, and it’s a skill just like any other.
More fundamentally, as argue in the original post, this sort of argument conflates technical skill with art. It’s stating that something becomes art merely because there’s labor involved in producing it. To me, art is fundamentally a form of expression. It’s one individual having an idea in their mind that they want to convey to others. The medium that’s used to flesh out the idea is not relevant, it’s the value of the idea itself and how it resonates with others that matters.
It’s also worth noting that slop has always been here in form of ads, Marvel movies and so on. All AI does is reduce the labor cost of producing it. I’d argue that the barrier to making good looking images being lowered means that people will have to find new ways to make art expressive beyond mere technical skill. This is similar to the way graphics in video games stopped being the defining characteristic. Often, it’s indie games with simple graphics that end up being far more interesting than a big title.
Finally, the key point I’m making is that it’s clear that this technology will continue to be developed and used going forward. So, the real question is whether we want corporations to drive its development or whether it’s better if this technology is developed in the open and community driven. The neo-luddite position ensures that the former will be the case.
Here’s a music video done with AI assistance (including Comfy UI) that is pretty cool: https://youtu.be/envMzAxCRbw
but @happybadger@hexbear.net confidently tells me that’s not art because it was just too darn easy to produce 🤷
It could be the most sophisticated plagiarism machine possible, requiring the most amount of effort to make a coherent image of any of the models, but I challenge you to make the absolute best image on the absolute best model out there. Really pour your heart and soul into it for a sincere amount of time. Make a prompt 10,000 words long with every parameter precisely dialed in. It will take me 30 seconds and an acre of rainforest to make all of that for nothing in a way I can’t do if you snap a photograph out of your window. You sculpt a shitty cup and I can’t replicate it, you paint the most meaningless abstract expressionist piece and I can’t replicate it, you record a cover of Happy Birthday and I can’t replicate it. Not at the level you did without a technical background, not better than you did without significant capital investment or unique talent. If I can do that with AI images using a library computer or cheap smartphone, your investment in making the image is way more than its worth as an instantly genericised jpeg. I can’t feed your cup into a kiln and effortlessly make a better cup, but I’m four clicks away from making a better version of your AI image.
Even if we develop it as open source and community driven, that doesn’t make it gain value it doesn’t intrinsically have. It devalues human art by flooding the space with slop, like it did with Clarkesworld and Spotify. It would still be ideologically futurist and alienating to the artists whose skill comes from years of practice. There’s no communist future where plagiarism is meaningful art when communists now and in the 1930s already saw through it. Would you buy an AI image I make as a Marxist who knows a lot about art theory? Would you buy it for the same price as a napkin doodle I make? This one’s pretty good, reflects my communist values with two decades of studying art nouveau behind it, and I’ll sell it to you for the right price:
You’re just repeating the same tired argument I’ve already addressed above. As a Marxist, I do not see the value of art coming from how much it can be sold for. This is an intrinsically capitalist world view that you have to break out of.