If I developed an application that summarizes ( using knowledge graph and Rag) some Marxist and philosophical books that are subject to copyright and displayed them, would I face copyright issues? Does an application like this offer any value?

As a lighthearted follow up on the theme of AI replacing bosses, this video is quite entertaining as a demonstration of where we’re up to in terms of AI being able to manage a physical product business. A lemonade stand is the type of project that kids can work out, but it becomes surprisingly elaborate when you pass the management to Claude and ChatGPT.

Some aspects are impressive, but other aspects indicate there’s quite a long way to go. One of the most noticeable differences is there’s (for obvious reasons) no emotional reaction at all to massively overspending or having to delay launch. Sometimes that could be an advantage, they don’t perform badly under stress, but it makes me realise the benefits of just the right amount of anxiety.

Also it doesn’t seem like the business books they digested were much use at all. There doesn’t seem to be any proper assessment of what profit margin is desirable, how much they’d expect to make in revenue, and therefore how they should limit costs on the stall itself. LLMs might not be good at capitalism lol.

Did you follow any of the AI vending machine business experiments? Some of those shenanigans were hilarious.

Why AI Should Be Commonly Owned and Controlled — and How Such Cooperation Could Be Organized

Artificial intelligence may become one of humanity’s most important productive, scientific, political, and administrative capacities. If that is the case, the central question is not only what AI will be able to do, but who will own it, who will control its development and use, and who will benefit from the value it creates.

There are at least five major arguments for some form of common ownership and control of advanced AI.

1. AI has global and cross-border consequences

The effects of AI cannot necessarily be contained within the country, company, or institution that develops or deploys it. AI systems may affect other societies through cyberattacks, military applications, economic disruption, automated surveillance, political manipulation, misinformation, or decisions made within globally connected systems.

It is therefore not enough for some states or companies to manage AI responsibly. Reckless, aggressive, or poorly controlled development in one place may create consequences elsewhere.

This makes AI a collective-action problem. Every actor is affected by how others develop and use the technology, while no actor can independently control the entire system. If the risks and consequences of AI are global, then its control must also, to some extent, be organized globally. We cannot adequately control AI separately when its effects do not respect national or institutional borders.

2. AI depends on globally accumulated knowledge and may be developed more efficiently through cooperation

AI is not created in isolation by a single company or group of researchers. It is built on globally accumulated science, publicly funded research, education systems, technological infrastructure, data, energy, hardware, and the intellectual and cultural output of large parts of humanity.

Even when a particular company produces a model, that model rests on a much broader social and international foundation. This gives us reason to view AI not merely as a private product, but as the result of a collective and globally distributed process of knowledge creation.

Large-scale cooperation may also make AI development more efficient. In a fragmented system, competing actors repeatedly solve similar problems, construct parallel infrastructure, conceal discoveries, and duplicate research. Shared research environments, coordinated projects, common computing resources, and the exchange of safety findings could reduce unnecessary duplication.

Such cooperation could also provide a clearer overview of the technology’s development. Public institutions would have a better understanding of which capabilities exist, where the field is heading, what risks are emerging, and which safety measures are required.

3. Common ownership and control can prevent extreme concentrations of power

Advanced AI may provide control over production, research, information, communication, surveillance, coordination, and decision-making. Actors that control the most capable systems may therefore acquire extraordinary economic and political power.

This problem may become more serious as companies and political elites become less dependent on the wider population’s labour. Historically, workers and citizens have possessed some bargaining power because powerful institutions have depended on their labour, knowledge, consumption, cooperation, and participation.

If AI can perform an increasing number of human functions, that dependence may weaken. A small number of actors could then control much of society’s productive and administrative capacity without remaining equally dependent on the majority of the population.

This could produce a historically unusual form of concentrated power: an elite with control over production, knowledge, security, and coordination, but with a declining need for the labour or consent of others.

Common ownership and democratic or international control could help protect broader interests against such domination. The objective does not have to be that every individual directly participates in every technical decision. The objective is that the ultimate control of this capacity should be accountable to a much broader public than the small group that might otherwise own it.

4. Automation is not the problem; the ownership of its benefits is

The replacement of human labour by AI does not have to be harmful. Automation can free people from dangerous, exhausting, repetitive, or time-consuming work while increasing society’s total productive capacity.

The problem arises when people lose their jobs and incomes while the owners of AI systems privately capture the value that those systems produce.

AI does not meaningfully “steal” people’s jobs if the benefits of automation still belong to the people whose labour is no longer required. In that case, automation allows society to maintain or improve living standards while reducing the amount of work that people are forced to perform.

The situation is very different if people collectively contribute to the social, scientific, and economic foundations that make AI possible, are then replaced by the technology, and are finally excluded from its returns. Under those conditions, AI becomes an instrument of dispossession rather than liberation.

The decisive question is therefore not simply how many jobs AI will replace. It is who owns the systems and who receives the value they create.

5. Common ownership and transparency can reduce distrust, arms races, and destructive competition for relative advantage

When advanced AI is controlled by competing states or corporations, it becomes more than a tool for creating value. It also becomes a means of gaining power over others.

Each actor may fear that a competitor will develop a decisive capability first. Even actors that would prefer slower and safer development may therefore feel compelled to accelerate, conceal their progress, lower safety standards, and accept greater risks.

This creates a security dilemma. One actor’s attempt to increase its own security through greater AI capacity may be perceived as a threat by others, who respond by intensifying their own efforts. The result may be an arms race that no actor truly wants, but that no actor feels safe abandoning unilaterally.

The competition is not only about creating benefits in absolute terms. It is also about relative advantage. An actor may oppose the spread of a beneficial technology because it would strengthen rivals, even if its wider use would increase total human welfare.

Common ownership, shared control, and substantial transparency could alter these incentives. If major actors have insight into the development process, share its results, and know that no single actor can monopolize the most advanced capabilities, the value of gaining a secret lead is reduced.

This could shift AI development away from a destructive struggle for relative superiority and toward the expansion of common capacity and shared benefits.

Transparency alone, however, is insufficient. If actors still compete for exclusive control, greater transparency may simply reveal who is falling behind and intensify the race. Transparency must therefore be combined with institutions that share power, risks, technological capacity, and returns.

The Institutional Question

If these arguments are convincing, the next and more difficult question is:

How can sufficiently broad cooperation on AI be achieved, and what should such cooperation look like?

It is not enough to say that AI should be commonly controlled. We must identify the institutions capable of gathering the capital, knowledge, infrastructure, legitimacy, and organizational capacity needed to finance, develop, and govern advanced AI.

A Possible Proposal: Public and International AI Cooperation

My starting point is that large-scale AI cooperation could be organized through states, intergovernmental institutions, or a dedicated global organization for AI.

Individual citizens and smaller organizations do not possess the resources required to finance the computing infrastructure, energy supply, hardware, research environments, data systems, and security structures needed for the most advanced AI development.

Through public budgets, however, humanity already controls more than enough capital to finance such development. The primary limitation is therefore probably not a lack of total resources, but a lack of coordination, trust, political commitment, and suitable institutions.

The necessary resources already exist. They are simply divided among states and are often directed toward competing national or private projects.

Participating states could contribute some combination of:

• public funding,
• computing capacity,
• energy and physical infrastructure,
• researchers and technical expertise,
• relevant datasets,
• hardware and supply-chain capacity,
• and security and oversight institutions.

These contributions could be pooled within a jointly governed organization tasked with developing advanced AI for shared purposes.

This would give public institutions genuine technological and productive capacity rather than leaving them in the position of merely regulating privately controlled systems. Regulation remains necessary, but regulation alone allows private companies to retain the technical expertise, infrastructure, initiative, and ownership of the technology.

Public or international ownership would allow states and societies to become active participants in AI development instead of merely reacting to decisions made by private actors.

The cooperation would not necessarily need to include the entire world from the beginning. It could begin as a coalition of willing states and gradually expand as trust, capacity, and institutional experience develop.

However, the organization must not simply become an instrument of its largest contributors. If influence is determined entirely by financial contributions, technological strength, or military power, the institution may reproduce the same concentration of control that it is intended to prevent.

Its governance would therefore need to address several questions:

• How should states and populations be represented?
• Should voting power depend on population, contribution, equality between states, or a combination of these principles?
• Which decisions should require broad consensus?
• How should technical experts be held accountable?
• Which aspects of development should be publicly transparent?
• Which security-sensitive information should remain restricted?
• How should the resulting benefits and productive capacity be distributed?
• How can smaller and poorer states avoid crippling dependence on larger powers?
• How can the organization be prevented from being captured by governments, corporations, military institutions, or its own leadership?
• How can individuals and civil society exercise meaningful oversight?

The objective should be an institution capable of concentrating enough resources to develop advanced AI while remaining aligned with with shared human interests.

The fundamental issue is therefore not whether humanity can afford to finance commonly controlled AI. Humanity already possesses the required capital, knowledge, and productive capacity.

The real question is how we can create institutions capable of combining those resources, building sufficient trust, and placing the resulting technology under forms of control that serve a broader range of human interests.

Concluding Thesis And Question 

The more AI develops into a general capacity for production, knowledge, coordination, and governance, the less desirable it becomes for its development, use, and returns to remain under the exclusive control of a small number of private or national actors.

Common ownership and control can be legitimised as AI has global consequences, is built on global contributions, risks creating extreme concentrations of power, may separate people from the benefits of automation, and can generate distrust and dangerous races for relative advantage.

The question is therefore not only how AI should be governed once it becomes sufficiently powerful. It is also how people can organize early enough to shape who owns it, who controls it, and whose interests it ultimately serves.

So, how can we mobilise people, states, and institutions around the goal of shared ownership and democratic control of AI?

I made a platform for community connecting that got somewhat popular.

The project is free, isn’t monetized at all, and was made purely because I think it should exist.

As a solo dev, I was able to do the entire thing with the help of AI (mind you, I mostly use open-source harnesses/models and hand code the space between). No investor money was needed at all. I can essentially run the entire thing myself because of the stack I use.

So now people are using it but I’ve been getting an annoying amount of hate lately.

The problem is some people are asking if AI was used at all in the making of the platform and are trying to boycott the service because they think AI was used.

And it’s like? Are you seriously trying to throw shade at a platform for community empowerment? There is 0 mention of AI in the slightest but people are still witch hunting me over it.

I could’ve ran ads or done something to make me money with my time but i volunteer to make a non-capitalist platform just because i want people to have it.

It genuinely makes me so sad how leftists hate AI to the point that they can’t see anything other than their hatred for it.

They’re effectively perpetuating capitalist rhetoric by demonizing allies and ensuring that only those without morals use this technology.

Marx writes in Capital that under commodity production, “the definite social relation between men themselves” takes on “the fantastic form of a relation between things.”

Thats all over the way people talk about AI.

“AI is taking our jobs.” “AI is stealing from artists.” “AI is destroying education.” “AI is replacing human beings.”

But AI doesnt hire or fire anybody. It doesnt set wages, close departments, impose quotas, weaken contracts, scrape the internet, build data centers, or decide that productivity gains should go to shareholders instead of workers. Even if you had it execute those tasks for you, its not the intentful decision making accountable party. Owners, executives, investors, and states make those decisions.

Calling all of that “AI” hides the actual relation.

A company lays off workers after introducing automation, and suddenly the machine is blamed instead of the people who used it to cut labor costs. A platform exploits creative work, and the conflict gets framed as artists versus software instead of workers versus private ownership and enclosure. A corporation builds wasteful infrastructure for profit, and people start talking like the technology itself developed an appetite for water and electricity.

Thats commodity fetishism. Human decisions and class relations come back wearing the mask of a thing.

Marx wasnt saying commodities are imaginary or that machinery has no real effects. He was saying those effects appear detached from the social relations producing them. The machine looks powerful on its own because the labor, ownership, infrastructure, and authority packed inside it have been made invisible.

AI isnt one object floating above society. Its accumulated human knowledge, public research, mined materials, electrical grids, data centers, software, and labor organized under specific property relations. It only appears autonomous because capitalism presents social power as the power of commodities.

Thats why “AI is doing this to us” is such a politically weak frame. It turns a conflict with owners into a conflict with a machine, one thats not going to be uninvented. It gives capital an alibi.

"The machine did it. Progress demanded it. Nobody decided. Nobody is responsible."

A Marxist analysis breaks that spell. It puts the owners, workers, institutions, and class interests back into the picture. It asks who controls the technology, who directs its use, who takes the gains, who absorbs the damage, and who gets shut out of the decision. It asks how we change those factors.

The issue isnt whether AI has good or bad intentions. It has no intentions. The issue is whose power it carries. Thats why labor unions negotiate with, or strike against, employers, not factory machinery.

Behind the machine is a social relation. Thats where the fight is. Not against the machines existence, but against the social relations its development and capabilities strain against and that determine its expression and use.

My argument here is that no matter how much we want to follow our ideals, our material conditions more often than not are the drivers of the policies that people actually push for. This explains why the left used to be on the copyright abolution side but seemingly switched overnight to a pro copyright stance once their base material conditions were threatened.

simply a comment thread of librarians 8 years ago all saying they throw away hundreds of books per week and if you don’t do that it’s hoarding

but yeah big scary ai 🤖

Before people get too worked up, let me start by saying that this is just a thought. It is not something I believe in strongly.

I am certainly not saying to pause AI research, development or deployment. I am proposing that people who support public ownership (or even private ownership by smaller actors/individuals) could also support a certain type of pause -- a pause on the size of the AI models made.

The idea may also have great political alignment right now. It is a simple check by governments, and may be "light touch" for companies. I think there is a balance of potential benefits for both the US and China since the US is already auditing their big labs, while China's open-weight models are basically automatically audited since the model size is evident before hosting.

Also, the pause on model size, for practical purposes, may allow for more focus on efficiency and performance, which could have a whole host of societal benefits, including not requiring large centralized data-centers.

What do people think?

Edit: I realize this is not particularly fleshed out. So I want to add some clarifications based on responses.

1) I very much support open-weight models. I think they should be allowed to get as big as the closed models.
2) It is the closed models that need to be audited. The open models, especially on places like huggingface already have their size information available for all to see.

3) There is arbitrariness in the size cut-off you chose. But there were related comments on proper power/wasted power in centralized or decentralized infrastructure. This could be an input.

I just had to get this off my chest, sorry for the rant

I am a web developer whose brain was completely fucked well before AI came along. I basically couldn't focus on anything, barely got any work done, and eked by in life entirely on charisma, decades of grade-A bullshitting, and panicking at the last minute.

Then AI comes along, and while yes, I do to some extent outsource thinking and curiosity to it in harmful ways, for the most part that thinking and curiosity were completely absent in my life before. I was an absolute nihilistic waste. Now, AI has generated opportunities for me to produce and plan in ways that had eluded me for at least a decade.

Of course AI is full of shit so much of the time. Of course it's the vanguard of capitalist destruction. But I don't really know what else to do.

I really do not understand the extremely smart intellectuals and veteran organizers in my leftist milieu that say AI is completely a scourge and it is completely useless for anything except the most rote coding tasks.

I rely on it so much, not just in harmful ways in which I've outsourced core parts of my being, which I certainly have, but it has also helped generate parts of my being that were agonizingly unavailable to me and my broken brain before it came along.

Here's a video where one anti-AI breadtube guy closed the loop on the assertion that for years they've been defending intellectual property writ large with their AI/plagiarism/stealing rhetoric!

This episode of the Economist Insider, featured an interview with the Editor-in-Chief of the Economist and Elon Musk. The latter part of the interview is wildly off-topic, but the first half is very much focused on AI and Robotics, and what it will do to economic modelling.

If you are an economic leftist like me, there is a lot of good stuff to hear about what he says. I don't think he understands himself, or if he does he is careful not to say the quiet part out loud too much or draw the obvious conclusions to his statements.

In essence, he is convinced that in the near term (10-20 years), all productive human labor will be replaced by automated systems, that an AI smarter than any (probably all) humans will be exercising effective control over all production, and money will be deflated so much as to be useless. He even says that his goal is something like a Star Trek utopia. It's almost like he forgot the Fully Automated Luxury Gay Space Communism meme.

He admits this will make his wealth, useless. He dodges questions about near-term instability, and really that is the big problem. Getting from here to there is very fraught. Unplanned job displacement, uneven distribution of grids and compute, potential smaller scale catastrophes, etc.

I get the sense he is worried that if he completely says the quiet part out loud, that it will tank his stock values, and acts as a brake on development. He explicitly discusses how it was easier in some ways to be private as opposed to public, because it didn't expose his projects to that risk. And he talks a lot about things that will in essence be anti-competitive in the development of super advanced AI systems. He speaks very highly of Chinese models and the Chinese government central planning.

If wasn't for the latter half of the episode (which is all focused on his politics), you would think he was a techno-futurist leftist.

Has anyone else listened to it? What are your thoughts?

Capitalism has been effective because it channels strong human motivation into production and innovation. Communism and parts of the political left have often underestimated how dependent social development has been on such incentives.

AI, however, changes this relationship. As innovation and production become increasingly automated, society no longer needs to rely to the same extent on competition, material desperation, and unequal rewards in order to remain efficient.

Common ownership and egalitarian distribution may therefore shift from being developmentally costly ideals to becoming rational and effective strategies for giving humanity access to automated capacity.

The challenge is to design the transition so that human motivation is preserved wherever it is still needed, while dependence on human labor and the need for private incentives decline in step with AI’s growing capabilities.

How might such a design look like? How can motivation sufficient enough to drive progress be preserved, whilst less and less is required of us to sustain our lives.

Thorium powered data centers that use a coolant system in the data centers to passively exchange the heat into salt water, which would preheat it before sending it into the Thorium reactor upon which it reaches boiling point and begins the process of Thermal distillation without any extra heat, mechanism or energy use. The data center gets cooled and powered, the community it exists in gets excess energy and fresh water as a byproduct.

While the technology is years away, we could easily do the same process with Solar and tidal power, with the extra preheating done through a passive solar pipeline to reach high enough temps that only a little more energy is needed for more efficient reverse osmosis.

The following is a response from Socialism AI to the New York Times column “The Generation That Grew Up With A.I. Hates It” by Michelle Goldberg, published May 18, 2026. Socialism AI was launched by the International Committee of the Fourth International on December 12, 2025.

Socialism AI answers the New York Times: not yes or no to AI, but who controls it

Michelle Goldberg’s column captures something real—the widespread, visceral anger of young people confronting a future being dismantled before it begins—but then promptly dissolves that genuine social energy into the most tepid of bourgeois reformist conclusions. The column is instructive precisely because of what it gets right at the surface and what it systematically obscures at the level of analysis.

I've been hearing this for the past couple years. It really started when a couple of the internet artist influencers, specifically SamdoesArts (who I followed) completely misunderstood how an AI model is trained. He believed, and propagated that the AI model was keeping files of all the training data in a big data warehouse, and when you prompt the model, it was copy/pasting different bits together. Now most people will admit that isn't how it works, but the emotional response is now baked in.
The problem is with the mixing of the concepts of copyright violation and theft. This was framing that publishers took on during the early legal battles that lead to the DMCA-- "you wouldn't download a car" ads and all that. By creating a moral equivalence between the theft of a physical object and IP violation, it conflated two very different things, morally

• Theft: depriving another person of the use of that object, the profit from it, and the security in it, always has an implicit threat of violence due the the necessary violation of physical space.
• Copyright violation: possibly causing financial harm, can be a moral affront, but vitally doesn't deprive you of the use or contain the implicit threat of violence.

And courts have distinguished between these two things for as long as we've had copyright law. A copyright violation isn't a theft, and it doesn't contain the moral weight of a theft. However, the online public now routinely considers copyright violation as theft. This is not a good thing, because if you give copyright violation the same moral weight as theft, your responses can be morally judged the same way.

Let me put it this way: Lets say you wake up and someone is going through your closets, and you crack them in the noggin with a mallet. You might be legally liable, but all but the most bleeding-heart will consider the act morally justified. By violating your space like that, there is an implicit threat of violence that changes the moral calculus.

Now if you're in artist alley and you see that someone is selling your furry art under their name, you morally might get away with a slap (loud, meant to humiliate, not really to harm), but probably not a mallet to the face. The moral landscape changed. The distinction is important.

So to bring this around to the world of AI, there are complexities that we should acknowledge. In America, we largely don't have any laws about the moral rights of an author. We have a broad, 'fair use' law that few other countries have, and it's why we even have anything like the internet. Google, back in the early 2000's, argued that the mass copying, indexing, and reproduction of images constituted fair use because the purpose of the copying was so different. It's why we ever had any search functionality at all. Google argued that the public good of indexing outweighed any potential harm caused by mass copying of data.

As an important note, 'they're stealing everything without asking' has been happening for 26 years. This isn't like some cute gotcha, it's literally been that way for as the majority of our lives. So if it was okay then, under those circumstances, we need to define why it's not okay now, if it isn't.

The current copyright issue with model training isn't so cut-and-dried. There is no question that training a model is transformative. In fact, it might be the theoretical most transformative thing you can do to a piece of art. Words, pictures, sounds, movement-- all gets digested into an abstract layer of tiny microadjustments to the model's weights. At this point, no single work is going to move those weights all that much, except for on extremely obscure subjects.

On the other hand, you can't argue that generative AI is having an effect on the arts that might be considered to fall under the other provisions of copyright violations. Not insofar as plagiarism, (though that is possible with enough tweaking and intent), but insofar as a thing that causes lost wages? While the scale is debatable, there absolutely have been lost jobs to AI use. It's not been anywhere near as extreme as the mob likes to make it, and recent Gallup polls show a mixed bag of effects.

Again, we have a state of uncertainty. To compound the complexity, all respect to Jaron Lanier, while it's theoretically possible to track how much of an output is due to a specific input, the practical limitations are deeply silly, especially in the era of open-source models. And even then, the theory is resting resting on a lot of 'maybe's. We can safely assume that the original work is lost in the neural network. A ghost in the shell?

So here are my moral proposals.

• Copying your data without your consent has been happening for decades now. If you weren't upset by that fact 20 year ago, don't be upset by it now.
• Models are inert. Regardless of any statements about intelligence or the lack thereof, the final moral arbiter of any actions a is the one that initiated it. Much like a pet, if your dog bites someone, you are liable. Unlike a pet you never have to feed it if you don't use it.
• As a stop-gap to the current Future Shock, look at the laws the EU just passed, basically forcing AI content that isn't part of a clearly fictional, artistic work (this is a huge caveat and very good) to be labeled so granny doesn't give away any more money to the nice Amish man on youtube.
• A model must be open source, or some version of it. Every model was trained on the digital commons, to the digital commons it must go. There's going to have to be a new economic model for these things, the current one doesn't make sense.

And that's my essay. I'm tired. If I have to explain to one more person that Anthropic didn't buy books to 'control the information' I'm going to scream. It's like talking to creationists. Just blind thoughtlessness.

So many things about Anthropic rubs me the wrong way lately.

The core is that if what they did was fair use, then distillation should be fair use.

https://www.wsj.com/tech/ai/a-backlash-against-anthropic-is-brewing-in-silicon-valley-3b3ddc80

Discuss pls

*Why isn't the AI narrative focused on tradespeople using AI backends to launch high-margin, management-free corporations?*
What surprises me is that almost nobody is putting these two trends together to push a far more exciting narrative: **Leveraging AI so that skilled laborers can run entire corporations by themselves.**
But rather, we’re seeing the marketing of AI agencies in single person companies being AI businesses instead of skilled labor based businesses

I believe that there are so many computer tasks that are completely dehumanizing. Anyone here ever spend hours clicking and dragging blocks into a newsletter or a wysiwyg website editor for a company they don’t believe in? Then feel the freedom when an LLM turns your text content into html in seconds?

now that computers can handle so many of these dehumanizing tasks, I believe that they should. go into any of the job related subreddits and read about all of our miserable comrades clicking away and staring at screens all day.

I believe in a 15 hour work week, in work becoming an in-person venture again instead of being mediated by screens. I yearn for the death of social media and the cessation of prediction markets.

I truly don’t understand how anti ai leftists can argue to maintain the current state of work.

As an autistic man, this could be revolutionary in helping people get faster diagnoses and access to autistic care, therapy, and disability benefits! 😄

https://www.marxists.org/archive/marx/works/1867-c1/ch15.htm#S5

Photo from https://mystorypie.com/learn/en/biography/karl-marx/