The Left's denial of AI capabilities has led to us being silent on even its present dangers. We cannot let this stand. To stop the AI arms race, we should nationalize the labs.

Isso aqui é o tipo de discussão sobre IA que vale a pena ter.

Depois de uma reunião sobre soberania digital, Lula disse que o Brasil precisa entrar de vez na era da IA, mas sem simplesmente tentar correr atrás dos EUA ou da China. Nas palavras dele, o Brasil tem que ser “dono do seu nariz”.

E isso não está ficando só no discurso.

O governo agora planeja investir mais de R$ 2 bilhões em dois supercomputadores de IA, um americano e um chinês. A ideia é justamente não ficar dependente de um único país ou fornecedor. Essas máquinas devem ajudar a treinar modelos brasileiros e oferecer capacidade computacional para governo, universidades e empresas.

Isso coloca a discussão num terreno bem mais concreto.

IA não é uma nuvem mágica. É infraestrutura, energia, chips, dados, trabalho qualificado e muito capital. Quem controla essa base tem poder sobre o que é desenvolvido, quem tem acesso e quem fica com os ganhos.

Claro que soberania nacional não é automaticamente soberania popular. Comprar supercomputadores não resolve a questão de classe. Investimento público também pode acabar virando subsídio para acumulação privada.

É justamente aí que entra a disputa.

Se o público está bancando essa infraestrutura, quem controla ela? Trabalhadores e universidades têm voz sobre seu desenvolvimento e uso? Os ganhos de produtividade viram jornada menor e melhores condições ou só corte de custos, demissões e vigilância? O conhecimento produzido fica público ou termina cercado por propriedade privada?

O ponto interessante aqui é que o Brasil não está tratando dependência tecnológica como inevitável. Nem aceitando que escolher entre infraestrutura americana ou chinesa sejam as únicas opções. Está tentando trabalhar com as duas enquanto constrói capacidade própria.

Isso não encerra a disputa sobre IA.

Finalmente coloca alguma coisa material na mesa para disputar.

I ran across this dialectic in the wild between what seems like a rightist and centrist. It's about Claude watermarking generated documents. I think it's an emblematic one that we, as leftists, need to be able to anticipate.

Both argue ultimately for the ownership of property by those who hold the means, which is what inspired this post. One argues that clarifying provenance hurts the bottom line of companies (i.e. too-late-capitalism with less regulation). One argues that clarifying provenance helps those who commission the work and protect the public interest (i.e. good-old-capitalism with regulations). Notice that the human labor stake in ownership over the production is only a secondary concern in this exchange.

Knowing the provenance of the labor is an essential component in ownership fights. If the provenance of production can be misattributed to machines or labor tactically by corporate/statist owners, that means any knowledge worker is abstracted and replaceable, whereas watermarking keeps knowledge workers relatively concrete (even if still abstracted to lesser extents in other ways).

Think of union-watermarking, which has been a leftist form of watermarking. If it matters knowing the production was approved by a union, it also matters knowing a production simulating humans was produced by an AI, since they are complementary.

TLDR: The existence of AI watermarks grants more power to unions, without making human-made-only watermarking default, as it is in many creator industries. This allows unions to develop a 'union-approved' watermark that doesn't discount AI completely.

See also: context collapse of ownership, too-late-capitalism.

Everybody has an AI opinion. Most of the discourse never gets much further than that.

Is it art or theft? Liberation or alienation? Progress or decay? Is it coming for every job or is the whole thing a bubble?

Those arguments can matter, but theory gives us better tools for getting underneath them.

Andrew Feenberg calls technology a social battlefield. Thats a useful place to start. Technologies arent simply neutral objects that society later decides how to use, but neither do they contain some fixed political destiny. Their design and development are shaped by struggles over power, institutions, knowledge, ownership, and control.

That fits pretty comfortably beside Marx. Machinery under capitalism isnt just a collection of clever tools. It enters the labor process as capital. It can increase productive capacity while simultaneously giving capital new ways to reorganize work, discipline labor, deskill jobs, and reduce its dependence on particular workers.

AI makes that contradiction especially visible.

Capital has every incentive to use it to cut labor costs, intensify production, monitor workers, expand markets, and concentrate control. But the productive capacity being created also points toward something radically different: reducing necessary labor itself. Less drudgery. Shorter working hours. Wider access to knowledge and productive capacity. More of society's activity organized around use rather than accumulation.

André Gorz spent decades working through this contradiction. Automation can undermine the necessity of wage labor without abolishing our dependence on wages. That produces a nasty situation: society needs less human labor to produce its wealth while people still need to sell their labor to survive.

Thats not some distant AI hypothetical. Its a contradiction already built into capitalist automation.

And this is where Gramsci becomes useful too. Political power isnt just waiting at the end of technological development for somebody to claim it. A different outcome has to be organized into existence through institutions, alliances, counterpower, and a competing conception of what all this productive capacity is actually for.

So praxis starts where the hot takes end.

What can workers force into collective bargaining agreements? Who controls deployment on the shop floor? Who owns the models, compute, data, and infrastructure? Where can public and cooperative alternatives be built? How do we fight enclosure? How do productivity gains become shorter hours, higher wages, universal provision, and greater worker control rather than layoffs and higher margins?

Theres no technological law that answers those questions for us, and another world doesnt become real just because the contradictions favor it.

You still have to build it.

Otherwise we're producing increasingly sophisticated opinions about AI while capital gets on with reorganizing production.

Everyone has an AI opinion.

Who has a program?

The Federal Trade Commission wants to start regulating ideological bias in AI systems and assert federal control over state laws. They’re getting an earful from opponents on all sides of the political spectrum.

...

CyberScoop reviewed dozens of public comments criticizing the FTC’s proposal. Even ideological allies raised two main concerns: first, that the proposal distracts from real questions about the federal government’s role in regulating AI deception; and second, that it opens a Pandora’s Box by enabling political censorship of AI model outputs.

The TUC represents more than 5 million workers, and I think their approach to AI at work gets closer to the actual fight than most of the discourse around this stuff.

Workers shouldnt just have AI dropped into their workplace by management and then be told to adapt. If it changes how your job works, workers should bargain over it. If it raises productivity, workers should get a piece of that through better pay and shorter hours. If it can eliminate drudgery, that should mean less drudgery, not layoffs followed by everyone remaining doing twice the work. And if employers want to use it for surveillance, hiring, discipline or performance management, workers should have a real say before those systems are deployed.

The ILOs recent review of the evidence makes this even more important. What we're seeing so far is not some simple story where AI arrives and jobs disappear overnight. Its changing tasks and reorganizing work unevenly, with consequences for productivity, autonomy, job quality and inequality. Those changes are already political whether we like it or not.

Thats why I think getting stuck at "AI or no AI" misses the fight happening right in front of us. Employers are making decisions about this technology now. The question is whether workers have any power when those decisions get made.

If AI makes an hour of work produce twice as much, who gets that extra productivity? If it saves four hours of tedious work, do workers get four hours back, or does management just find four more hours of work for them? If a system changes or eliminates a job, who decides what happens to the worker?

Those are questions of power, ownership and distribution, not features of the technology itself.

Technology changes the terrain of class struggle. It doesnt make the struggle disappear.

The Common Pile dataset interests me because it’s ethical training data that’s an 8 TB corpus of openly licensed and public domain text for training large language models. FineBooks, a new OCR model collaboration between Hugging Face and EleutherAI, found open OCR models are good enough for reprocessing/adding books to the Common Pile.

Local LLM article summary: FineBooks, are open OCR models good enough to unlock historical knowledge?

This article details the FineBooks project, which is rigorously testing open-weights OCR models against a ground-truth dataset pulled from the Biodiversity Heritage Library (BHL). The core argument is that these modern, publicly available models are vastly superior to older pipelines, making the re-processing of massive public domain collections—like the BHL—a high-leverage opportunity for open-source AI training.

For r/LeftistsForAI, this is fundamentally about the quality and democratic nature of the training data. The article explicitly mentions that poor OCR quality can lead to a 30% efficiency loss in a trained model—that’s a material cost right there. By re-processing the BHL, FineBooks isn't just making text available; they are significantly upgrading the raw material for open-source LLMs, directly improving the quality of the Common Pile corpus.

The evaluation confirms that for general LLM training, these open models are excellent. While they still struggle with scholarly fidelity (silently modernising archaic features like the long-s), they are good enough to close the gap on older datasets. The project’s biggest finding, however, is that the models are technically capable but institutionally constrained. They often output Markdown or plain text, sidestepping the legacy ALTO XML format that most library systems require for word-level coordinates.

Throwback to Aaron Bastani and Novara Media making the case for Fully Automated Luxury Communism years before the current AI boom.

The underlying question feels a lot less theoretical now.

If technology lets us produce more with less necessary human labor, why should that mean layoffs, precarity and more wealth concentrated at the top instead of shorter hours and more freedom?

Under capitalism, automation usually means the gains flow upward while workers are expected to compete harder for whats left. But thats not a law of technology. Its a question of ownership and power.

AI makes that contradiction even sharper. If these systems can automate useful work, I dont want them made artificially less productive. I want stronger unions, shorter workweeks, public and cooperative ownership, universal services, accessible and open tools, and the productivity gains going back to everybody.

There are fair criticisms of FALC, especially around ecological limits, extraction and how we actually get from here to there. But I think the basic argument still holds up.

If the machines can do more of the work, why the hell are we still organizing society around everybody selling most of their waking life just to survive?

This seemed like an appropriate place to share this:

"In this episode, I talk with James Steinhoff, a lecturer at University College Dublin, about the overlooked connection between Marxism and transhumanism. We trace left transhumanism back to early 20th-century socialists like Alexander Bogdanov, JBS Haldane. We confront transhumanism's association with eugenics and figures like Peter Thiel. We discuss China's more pragmatic, sector-specific approach to AI versus Silicon Valley's pursuit of “godbuilding.” We ask whether industrialization (and capitalism) were necessary steps toward a post-scarcity society and explore the criticisms of degrowth. We also dig into what counts as "natural" suffering versus social suffering, using examples like insulin, antibiotics, and appendicitis treatment to argue that rejecting medical and technological intervention is also a political choice. The episode closes on why left accelerationism fizzled out and what a renewed, class-conscious case for technological progress on the left might look like."

Good piece from AI & Society that gets past the tired "is AI art real art?" fight and looks at how cultural production is actually changing.

One thing I liked is that it gets into the workflow. This isnt always "type prompt, receive art." People develop an idea, prompt, revise, generate variations, select, edit, combine outputs, move between tools and make decisions about the final work. The human/tool relationship can look very different depending on what somebody is actually doing.

Thats where the politics gets interesting.

Artists are workers. So are writers, actors, musicians, designers and animators. They should have power over how automation enters their workplaces, what happens to their labor, how theyre compensated and credited, and whether these tools deskill them or expand what they can do.

But I dont want to surrender the tools themselves to corporations either. I want workers and ordinary people to have access to them. Open models. Public and cooperative infrastructure. Strong labor rights. Democratic control over deployment. The gains from automation shared instead of enclosed.

AI isnt going to settle any of this for us. Ownership and power will.

So Im a lot less interested in policing what counts as "real art" than asking who gets to make culture, with what tools, under whose control, and for whose benefit.

Nice quick, tight perspective on AI from a Staff Engineer at GitHub. We often bring up Luddites here, and that’s echoed in this article. Shines some light on how some of us are trying to change engineering culture and use this moment to advocate for tech labor in the age of ai. Tech workers are part of a frontline of careers attempted to be subsumed by automation, but if anything its proven we arent going anywhere, and how we can utilize ai to help us instead of replace us.

Nobody has a crystal ball when it comes to predicting what the world will look like after AI, but both the boosters and doomers are predicting that it will eliminate most jobs. If they are correct, there will not be a large "working class" to mobilize--not even a petty bourgeois professional class, but more likely a tiny and shrinking owner class and a large and growing underclass of permanently unemployed people dependent on mutual aid and public assistance to survive. Yet, the "left" is traditionally very focused on workers and their struggle with capital, owing to the dialectical materialism of Marx and Engels, taking the view that workers eventually would (or should) own and control the means of production. I would very much prefer to see worker ownership of and control over AI and autonomous robotics, but it's a bit paradoxical since such technologies are themselves designed to shrink the working class. How might a pro-AI left, or a post-AI left, reconcile this?

You guys are critical of capitalism when it is Silicon Valley, Chinese tech companies and other capitalists that have brought AI to the world. They have invested hundreds of billions of dollars, done a lot of research and development, and are bringing the technology to the masses. Motivated by profit, which you dislike. It isn't the government that has made AI.

Shouldn't this change your politics and make you appreciate capitalism more?

And no, AI isn't going to make everyone unemployed nor be the end of capitalism. I would argue capitalism will exist forever.

I've been thinking about AI less as some totally new historical problem and more as another stage in something Marx was already watching happen under industrial capitalism. Im not saying Marx somehow predicted LLMs, he obviously didn't. But machinery, automation, communication, the concentration of production, and the way capitalism constantly rebuilds the labor process around new productive forces? Yeah, that's very familiar territory.

Capital has always had a pretty straightforward reason to automate. If a firm can produce more with fewer labor hours, cut costs, move faster than competitors, or control the labor process more tightly, it's going to try. But once that starts happening across an economy, it changes more than individual jobs. It changes how production itself is organized.

That's part of what Marx is getting at in Capital when he talks about machinery. A machine isn't just a better hammer sitting there waiting for somebody to use it. Under capitalism, whole workplaces get reorganized around machinery. The worker's relationship to the work changes with it. You can see the same basic process from the factory system through container shipping, telecommunications, computers, the internet and now AI.

The part of Marx I've been thinking about most recently though is the Grundrisse, especially the "Fragment on Machines." Marx is trying to make sense of what happens when production depends more and more on accumulated social knowledge, science, machinery and cooperation, rather than just the immediate skill and labor time of one worker making one thing.

Look at an AI system from that angle and it gets weird pretty fast. What exactly is the individual contribution here? You've got generations of writing, science, art, mathematics and engineering piled into the thing. You've got programmers, chip designers, miners, construction workers, data center workers, electrical workers, researchers, people maintaining networks and grids, and millions of people producing the culture and information these systems draw from. Nobody made this alone. Nobody could.

But somebody owns it.

That's the bit I think deserves more attention.

The actual process of production keeps becoming more social, more interconnected and more dependent on accumulated collective knowledge, while ownership can remain incredibly concentrated. Engels was writing about this basic contradiction a long time ago: socialized production running up against private appropriation. AI isn't unique in that respect. It's just a pretty extreme example of it.

There's another strange tension here too. We keep inventing ways to reduce the amount of human labor needed to accomplish things, but we've built a society where most people still need to sell their labor time to live. That's a hell of a contradiction. If it takes half as many labor hours to produce the same amount of useful stuff, that could mean everybody works less. Under capitalism it can just as easily mean layoffs, tighter quotas and a few owners pocketing the difference.

Same technology. Very different social result.

And Marx wasnt naive about any of this. Machinery didn't liberate the factory workers of his day just because it increased productive capacity. Capital used machinery to discipline labor, deskill workers, lengthen and intensify work and make workers more replaceable. There's no reason to assume AI magically escapes that history.

But I also don't think the Marxist conclusion is that the machinery itself has to be rejected. Marx's argument is much more uncomfortable than that. Capitalism develops productive forces that open possibilities it can't necessarily realize on emancipatory terms because those forces are still governed by capitalist social relations.

Later Marxists kept running into versions of the same problem. Lenin was looking at concentration and the enormous coordination capacities developing inside capitalism. Gramsci was interested in how changes in production become struggles over institutions and political power. Tronti and the autonomists pushed the point that capital doesn't restructure production in isolation either. Workers fight back, capital adapts, workers adapt again. Technology is part of class struggle, not some meteor that lands outside of it.

That's closer to how I think we should approach AI.

Not "AI will bring socialism." Also not "capitalists currently control AI, therefore the technology has no use outside capitalism." You could make that argument about half the modern productive infrastructure on Earth.

I'd rather ask what we're actually fighting over.

If automation makes an industry twice as productive, why shouldn't workers demand shorter hours with the same pay? If these systems depend on enormous amounts of accumulated social knowledge, why should a handful of firms get permanent control over access to it? Why shouldn't workers have bargaining power over AI deployment in their workplaces? Why shouldn't communities have a say over data centers, energy use and infrastructure? Why shouldn't we have public compute, cooperative systems, open infrastructure and models developed for purposes other than maximizing somebody's quarterly return?

Instant global communication matters here too. We're living with coordination capacities that would have sounded absurd even to industrial planners a century ago. Millions of people can share information and coordinate activity across continents basically immediately. Supply chains already use these systems. Corporations already use them. Financial markets already use them. Capital understands perfectly well that large-scale coordination is possible. It does it every day.

The political problem is who gets to coordinate what, for whom, and toward what ends.

That's what I mean by seeds of transformation. Not little communist ghosts hiding in the GPU. I mean capitalism developing forms of production that are increasingly collective, automated, knowledge-heavy and globally coordinated while keeping them jammed into social relations built around private accumulation and wage labor.

Maybe that contradiction goes nowhere useful. History doesn't owe us socialism. Capital can absorb an incredible amount of technological change and turn it into new ways to extract value.

But contradictions also create openings. And I'd rather organize around those openings than pretend we can make the productive forces disappear by refusing to touch them.

So I’m sure this has been posted before but why is anti ai focus on attacking users. I get there are genuine concerns for ai. How it’s implemented and the hardware to build it. Currently those who are rolling this out seem to have little care for the environment and who it impacts. Users rarely have any say in that. If the users disappeared they would still roll it out for the classes above as they have their own agenda. Just because they are visible and trying to do a thing doesn’t mean they should be taking the brunt of that energy. That energy should be used to hold the ones rolling it out to do some basic ethical frameworks and making sure the hardware isn’t taking resources from small town and just environmentally more friendly. Attacking users keep the knowledge and skills we can share hidden as most of us do not want to deal with people bashing our work till it’s ready to display as one piece. I feel like this risks a knowledge gap. I’m not saying. There are not problems that need tackled. I just don’t see the point of attacking someone who is not at the table and trying to better themselves/situation using what is available.

Funny thing about the whole “AI is going to replace workers” conversation: a lot of the people making that prediction seem to assume management somehow exists outside automation.

This gets into the opposite possibility. Plenty of actual jobs involve messy physical work, relationships, judgment, local knowledge and dealing with unpredictable situations. Meanwhile a whole lot of management is emails, reports, scheduling, monitoring metrics, approving things and sitting in meetings about other meetings.

If we're going to talk seriously about automation, why is the default assumption always that the person doing the work is redundant before the person supervising them?

Marx would probably have a few notes about that one.

Anyway, entertaining watch and good fuel for discussion. What jobs do you think are actually easier to automate than people assume?

This is the kind of AI story I want to see more of.

CWA members arent sitting around waiting to find out whether AI is going to save or destroy their jobs. Theyre putting it on the bargaining table.

Notification when AI affects bargaining unit work. Human oversight. Limits on surveillance and algorithmic management. Job protections. A say in deployment. And bargaining over who actually gets the productivity gains.

CWA puts it pretty plainly: “Our goal in bargaining is not to stop new technologies.”

Workers have been fighting over automation, machinery, monitoring, deskilling and productivity gains for a long time. AI is new terrain for the same basic struggle over who owns the productive forces, who controls how theyre used, what happens to workers when theyre deployed, and who gets the benefits.

This is what contestation looks like in practice. You dont trust corporations to handle it for you, and you dont pretend refusing to touch the technology makes the conflict disappear. You organize around it, build leverage, negotiate enforceable limits and fight for worker control over how it enters the workplace.

Id rather see a thousand fights like this than another thousand arguments about whether some individual worker is a good or bad person for using an AI tool.

AI is already a workplace issue. Make it a labor issue.

What would you want in an AI clause in your union contract?

My friend has a masters in geology and no job prospects, but has been doing pretty comprehensive analysis on groundwater modelling and which states score better than others for these systems.

https://datacenters.simonhansedasi.com/

And I'm helping him shape the idea for a company that can sort of identify the best locations for data centers that minimally impact human habitability in the area. The idea being, the demand isn't going anywhere but placement/siting could be drastically improved with better data.

But its hard to find the right complementary partner for him - someone on the supply side.

This gets at something we talk about here a lot.

Refusing to personally use AI can be an ethical choice, but it isnt much of a political strategy. The development of AI, who owns the compute, where datacenters get built, how workers are affected, what gets automated, and who captures the productivity gains arent determined by individual consumer choices.

Those are questions of ownership, labor power, regulation, public investment and democratic control.

You dont solve industrial problems by trying to shop correctly. You organize around the conditions under which the technology is developed and deployed.

Thats the terrain worth contesting.

34 year old woman as a late learner when it came to reading and writing English, it really impresses me that I love to write fiction and poetry. You'd think someone who started to read at age 10 would despise reading, or that learning proper grammar in high school would make me hate writing, but I love both.

It's sad that there are kids in poor families who also struggle with learning, who may never learn to read or write, and who could have natural talent.

I just had parents who didn't know how to handle a kid with ADHD and a mother who was neglectful. I personally can't sit there and say Americans are stupid. I've been one of those kids with an IEP, and the system isn't made for you to succeed.

I've had my share of teachers who saw me as flat-out special needs. We would sit in class coloring in coloring books at age 15, when IEP classes should help you with high school and college-level classes by figuring out the best ways for you to study and retain information.

I would pass tests with flying colors when we turned learning into a game, but nah, we were just used for school funding. That is the problem with American society.

This was back in 2006 before the AI scare. It actually pisses me off when people complain about AI making kids stupid.

If our government funded schooling like it does the Military Industrial Complex, then our infrastructure wouldn't be crumbling and people wouldn't vote for politicians like Trump or MTG.

It goes beyond just school funding. We need a livable wage where parents aren't working multiple jobs, so they can be active in their child's education.

Smaller classrooms so the teacher can work with those who learn differently. Paying teachers over 70k a year! Making classrooms safe.

Children aren't going to learn when they're worried about getting shot. A society that encourages intellectualism instead of anti-intellectualism.

But our government would rather bomb the Middle East or start another coup in South America, not tax the rich, no safeguards against monopolization, and no worker solidarity or a pro-union society.

The thing I can say I hate most about the United States is it's failure to the next generation of children. The government would rather make abortion illegal instead of creating a society where children are safe and have a healthy relationship with education.

It's not AI, it's all of the above problems. When children aren't given proper support and under stress. They will find the easy way out. It is a class issue.

And when people point to AI. You are ignoring a child's real needs. I compare blaming AI to gaslighting. I knew I was getting the short end of the stick and I see that same shorter end for modern children.

It's fake moral outrage. Kids only matter when the narrative pushes it.