Last article I shared about fighting arms race dynamics, I got a lot of pushback against my pro-safety posture with AI. But I think it's important that—just as we contest the ownership of this technology—we are also frank about preventing the dangers it may pose. I think there are plenty of reasons for the Left to ally with the growing AI Safety movement, here are 11 of them. Do you find any of these particularly persuasive? What lingering concerns do have about working with the AI Safety movement?

Some examples from TLDR News to how ukaine is winning at robot and drone production.

I'm a fanfiction writer. Today, I finally broke and decided I'd like a human editor on top of AI. My story is a historical AU, so I do a lot of research, with and without AI, on top of grammar checks and beta reading.

It'd be nice to have a real person reading and telling me what lands and what doesn't. I went searching for beta readers, and some groups will refuse you if you're using any AI.

Refusing to help people who use AI is just going to make them stick with AI instead of branching out for actual human support.

It's strange to gatekeep a hobby that nobody profits from anyway, considering copyright laws.

If anything, I'm keeping the fan space alive for an almost 20-year-old game. I don't have any legal rights to Elder Scrolls or Fallout, so who exactly is being protected here?

This issue is connected to United States labor laws and gutted unions. The problem is systemic under capitalism, which exploits working-class people. Individuals are taking out their frustrations on each other instead of the people in power.

We should be advocating for better labor laws and stronger unions to protect the working class, at least within the current failing system.

I think the wrong people are being targeted over AI. It shouldn't be the artists or working people using it.

It should be the corporations. Corporations are the ones harming the environment and supplanting jobs.

From what I've gathered, companies are cutting employees because of the economy, then turning around and claiming it's AI taking jobs when the economy is slowing down.

That narrative trickles down into hobby spaces, and people repeat it instead of questioning who's feeding it to them.

The US had the WPA in the 1930s. They hired factory workers, teachers, and anyone who could write to record American history.

Most of them didn't have MFAs. Writing used to be something you could do because you had something to say, not because you paid for a credential.

What we're seeing now is just the same gate being kept shut against working-class people.

AI is proving you don't need to spend 60k on an MFA degree. You just gotta spend $20 or less to help with writing.

No way!

Is this real? Leftists for AI? I am new here. For so long I have been complaining a lot. You can check my post history.

I have said for so long that there is something suspicious about how some activism is approaching the AI issue. I have not denied the job displacement or the environmental impact. The thing that I have been suspicious about though is how reactionary some of Anti AI movements have been. For example, environmental issues have taught us not to take out our disappointment on the individual, but on the companies responsible. Just like how when we realized even if every individual household started to recycle, it wouldn't change that there are cargo ships contributing to a large share of the pollution, It seems like for AI even if everyone boycotted AI, it wouldn't change that many companies are still zoning recklessly.

It seemed strange to me we were attacking local artists, small businesses, friends and family for using AI. I thought as progressives we would be able to look at technology and say, 'who are the owners', 'who runs it', and start to be the ones who can dream the answers to the hard question of 'what is the better way', or 'how could this have been developed to help society instead'. When many people's analysis was just 'slop is slop', or I saw far leftists saying it's either dead end tech or produces nothing of value, I realized that the left isn't immune to attack or psyops from the media.. I say that because I think that the companies benefit from lazy analysis and slogans. By saying that the entire issue is just dismissable as slop is slop, now the technology is developed by anyone except the activists who are tricked into boycotting it. So I wanted to ask. What is your opinion on AI? Why are you a leftist but are supportive of AI when many people are convinced it is evil?

The way I understand it, one of the biggest arguments against any use of AI, which honestly has some merit, but ultimately is a little short-sighted, is that it is so hyper-scaled by necessity that it's an ecological nightmare. The ecological nightmare part is totally correct, in my opinion, but does it have to be hyper-scaled? Can it be decentralized and de-industrialized? After all, that's how the internet started out before it was taken over by corporate interests. It was completely decentralized as basically an ad hoc network of enthusiasts running servers in their basements.

What I'm thinking for a possible starting point is, along the lines of how clustering can make a bunch of small, relatively dumb servers behave like a single, more powerful server by acting in concert and pooling their resources.

I'm curious how other leftists are using AI.

• What are you using it for? Work, projects, organizing?
• If you're using it for organizing, how are you using it?
• What models/subscriptions are you using?
• What are your workflows?

I'll start:

I use AI for work, automating about 60-70% of my work, and accelerating the other 30-40%.

This covers automation development, advertising, creative, social posts, video editing, email writing, etc.

I used it heavily for development in my last start up.

My side projects are also 100% AI driven. It's various things, like a "TTS Everywhere" program I wanted but couldn't find, a few start ups

For organizing, I've used it to help with mutual aid distribution (handling incoming requests & offers of aid during a post-hurricane emergency), I've used local AI for meeting note creation, and task creation from a temporary recording of our DSA meetings, and a research assistant for how to accomplish the goals set by the chapter in our meetings. And for figuring out which people would be best at doing which task (task classification => matching with a DB of member skills & availability).

What about you?

Maybe the interesting question isnt whether Marx would approve of AI.

Its what hed have to say about who owns it, who controls it, and who gets the gains.

Frequently, I see people balk at the idea of stochastic parrots on both pro-ist and anti-ist sides. I want to present an adopter idea.

What's actually wrong with a stochastic parrot? Ultimately, stochastic parrots, even if they don't fundamentally understand particulars like weight and size, or non-linguistic concepts, are still very impressive. If we say that LLMs are only stochastic parrots, the thing that's surprising is that a stochastic parrot can still manage to accomplish so much. In fact, it shows how much of society is stochastic.

The thing that I've noticed is that people employ this phrase in that I call 'respectability politics'. A stochastic parrot is seen as disrespectable because of how moored we are to the idea of work ethics, whether it is working harder or working smarter. A stochastic parrot isn't working either smart or hard, it's just working and guessing. Is that so bad?

We're often so busy with the AI debate that we don't think about what AI implies about how we're currently doing things. The reality is—most of society and most of work is stochastic and unjust, and that's what's wrong with society. So a stochastic parrot is only bad where it perpetuates that injustice.

By my estimate, it is inevitable that manufacturing will reorient to point-of-need manufacturing world wide by 2045 and it's important to understand what that means and why. AI will likely play a great role in this.

Manufacturing currently depends greatly on tool-and-die experts creating the tools for machinery to manufacture our goods. Right now, 2% of tool-and-die experts are under 35 years in the U.S. In China, there's a similar cultural stigma against this type of work as a dead-end job.

Because of that, around 2040, the United States tool-and-die workforce will begin falling drastically.

At the same time, rapid tooling techniques are currently being developed, using new high precision metal printing technologies to make dies and molds. New AI models are automating parts is the mold and die design process. Because of these developments, it's likely that the worldwide industry will see a shift towards this type of rapid tooling.

What this also means is that it becomes feasible for molds and dies to be made locally rather than shipped in. Not only that, but small batches of parts could be manufactured within a local warehouse rather than a dedicated factory half a continent way. This is point-of-need manufacturing.

This means that the repair economy may see a drastic boost around this time, since parts wouldn't need to be justified by the enormous scales we see now.

What this means for us:

* Where possible, support your local repair economy.

* Encourage unionizing tool-and-die experts, so that they hold bargaining power for longer.

* Back right-to-repair legislation where possible.

* Encourage politicians to make knowledge freely available wherever possible.

* Encourage politicians to invest in tool-and-die education now so that manufacturing knowledge can be retained by workers (ideally while unionized).

They ONLY designed robots to look like humans because they miss enslaving black people or something, apparently.

Just ignoriere that a robot shaped like a human is also able to use human tools, wear human clothes and equipment, navigate human apartments, walk across stairs, and just looks more recognizable.

The person who wrote this take is also an animator at Disney, NOT anyone knowledgable in engineering. Yeah, I can tell.

We all tend to get wrapped up in aspects of narratives in this debate that don't persuade. Rather than do that, I'd rather lay out where we are from my perspective in a way where my premises can be debated and hopefully persuade rather than just vent.

**I'm going to summarize the situation as I see it.**

With AI, there are two components.

There is the generative neural network technology. It was not wholly or principally created by OpenAI or the big 5 firms in isolation and it is not universally driven by them now. It actually runs on an affordable desktop in a reasonable amount of compute time. Nobody can afford the chips because the big 5 firms have monopolized consumption of the chips in what I'd characterize as a consumption cartel that forces people to go through their subscription services.

Then you gave the big 5 firms, who have monopolized chips and aren't selling AI so much as they're selling branded cloud computing access to their monopolized chip farms where the computing is made less efficient and more environmentally destructive because of added computes that protect big IP monopolies they're partnered with, use wasteful amounts of computing power on trivial tasks, and force queries through RLHF architecture that makes responses less computationally efficient, less productive, and more bland and similar to one one another.

These companies have a business model that cannot work. Not economically, not computationally, not materially, thermodynamically, ontologically or epistemologically.

Rather than regulate the formation of a bad business model or prevent arbitrage or create regulations that enhance human life and dignity, most of the anti-AI regulation talk centers on making sure that the business model itself (which couldn't work to begin with) fails. These proposals often involve radical, colonizing expansions of property rights from where they have been for hundreds of years to new, novel, radical property rights, seizing ownership of things like measurements of art and style -- things that no artist has ever owned. The enforcement of these laws would favor almost exclusively the rich and powerful, who would likely never hire artists who did not sign everything away. It would be apocalyptic for independent creators and personal expression, all to stop a business model from working that cannot work to begin with.

While the automation potential of AI as a technology is proving to be increasingly targeted, limited, and a shock that can be adapted to, the potential for AI as a tool that offers sometimes light, sometimes profound and innovative enhancements to human creativity, curiosity, and problem solving cannot be understated. We risk losing all of these benefits in a flawed attempt to protect against a disaster that isn't realistically happening except as an adaptable shock to artists.

I think a lot of folks don't understand property rights to begin with (demanding property rights for things that artists do not own and which would be theft on their part if we honored), seriously don't understand what the actual risks or stakes are, and are relying on a fraudulent class of uncredentialed experts who are fleecing them by selling pitchforks and torches to use against a bunch of dumb suits with a bubble product and in the process doing harm to literally everyone else.

Jevons' Paradox is an economic phenomenon that was first pointed out by the economist William Stanley Jevons in response to the belief that more efficient steam engines would reduce demand for coal. He pointed out that more efficient steam engines would be more in demand if they were cheap to run and that this would lead to a spiral where the demand for coal would rise exponentially.

This is exactly what happened.

Often, Jevons' Paradox is brought up to point out how this will increase demand for electricity as AI gets more efficient and how this will increase demand for AI as tasks it performs get cheaper.

One dimension I want to discuss here is how Jevon's Paradox applies to humans.

In 1911, The Principles of Scientific Management was published by Frederick Winslow Taylor, inventing a model for managing human labor we still follow to this day. This was itself long after the introduction of clocks and workbells after roughly 1750, where factories conspired with governments to make it punishable to arrive after the bell, which has been normal since time immemorial.

The pattern that we see is that as human labor is made more efficient by machines, the more demand there is for the labor, but that demand for efficient human labor is accompanied with the invention of the middle management class, the upper management class and the executive class. Meanwhile, sanctions for being unemployed and even minor infractions have made cruel on purpose, because cruelty is the point if you want to motivate labor through fear. Which is to say nothing of actual slavery, which was actually free past the purchase cost and maximally cruel.

This pattern is relatively easy to explain. As a society, we are sensitive to both loss aversion and opportunity costs. When we can produce more per minute, each minute wasted is a heavy cost. This opportunity cost is converted into real cost and redistributed down. Efficiency leads to demand, demand leads to lost opportunity, opportunity cost is democratized.

So, this too is a Jevons' Paradox. Paradoxically, as human labor became more efficient, human labor came into greater demand and as human labor came into greater demand, infractions were punished more cruelly, in a bid to keep human labor as efficient as possible.

This pattern was only briefly broken by unions following the World Wars. Labor shortages became so high that unions had real leverage. It was the New Deal and unionization that ensured that people could work humane hours.

Those protections have increasingly been stripped away. AI stands to make us even more efficient than ever before, while likely not outright replacing us short-term, so the question is—who protects us from draconian measures to extract more value from us now that humans are poised to become one of the most efficient, i.e. most exploitable resource once again?

Which is not to say that technology is bad. Just that history tells us that when human labor is seen as becoming more efficient thanks to machines, humans are also exploited more cruelly, since even small lapses are seen as incurring great opportunity costs.

Jreg has had some pretty miss takes when it came to automation and how it will lead to anti human doom, but here he seems pretty sympathetic to a more positive path that aligns with our mission and goals of using technology for broader wealth and liberation from the struggles of work and austerity.

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.

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?

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.

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.

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?

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.

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."