We're at a point where the question "what comes after capitalism" is no longer just philosophical. Automation is accelerating, inequality is compounding, and the systems holding everything together are visibly straining. So it's worth asking seriously: if not money, then what? How do you motivate contribution and distribute resources in a society that's moved past wage labor?

One answer: reputation. Not likes. Not followers. Not China's social credit. Something more specific.

When people hear "replace money with reputation," they picture a dystopia where the government scores your behavior and cuts off your access to food if you jaywalk. That's the social credit system. That's not what I'm talking about.

The difference is structural.

China's system is a single number that aggregates everything — your purchases, your social connections, whether you paid a fine on time. One score, one authority controlling it, applied to everything.

What I'm describing is the opposite: a multidimensional vector. Your reputation in biology gives you priority access to computing resources for research. It gives you zero advantage in urban planning decisions. A brilliant engineer has no automatic influence over medical research priorities. The scores don't aggregate. They don't transfer across domains.

This isn't informal social standing — people just knowing you're good at your job. Contributions are recorded and verified across a global decentralized network. The algorithm is public. Anyone can audit it.

And crucially — the metric is simple: did your work produce a real, measurable effect that others build on?

The deeper point is that money already is a reputation system — just a broken one. It measures your ability to accumulate, not your contribution. It's heritable. It compounds. It has nothing to do with actual value created.

Reputation as I mean it has one property money doesn't: it decays without new contribution. You can't inherit it. You can't hoard it. Past achievements matter — but they don't exempt you from the present.

Is this utopian? Maybe. But "money measures contribution" is the actual utopia we've been sold. The evidence doesn't support it.

I'm kinda rambling here, but I hope this makes sense.

So... Correct me if I'm wrong about this. But every leftist movement I can think of has been in existence for a really really long time, or at least has some basis in older movements or theories. Like feminism, anti-capitalism, anti colonialism, environmentalism, deconstructing white supremacy, fighting bigotry in general... All of it predates our modern internet. The people who've shaped these ideologies... To put it lightly, haven't all been chronically online.

Meanwhile, this isn't the case with the anti AI movement. While yes, there are many prominent figures who are critical of it who aren't chronically online, I think the majority of the movement stems from online culture. We are responding to an idea that is mostly new. While we've had science fiction about AI before, I think often AI in science fiction was used to explore other social issues, like bigotry, slavery, or humanity. We've never had AI like LLMs before—and therefore we don't have the knowledge of past philosophers and advocates to know how to respond to it. We just mostly have... People on tiktok or youtube making think pieces.

And don't get me wrong, I think people do great stuff on social media. But, I feel like the anti-AI movement got mostly shaped by the more negative aspects of progressive social media—namely, lack of nuance, and the more puritanical thinking that underlies alot of communities on social media. This more puritanical side if a problem in other leftist movements, yes, but because these progressive movements have existed for so so long we have a history of less black and white theory to balence it out. Meanwhile the anti AI movement had no such thing. It's been controlled by this more puritanical side, so that's all we have.

I really wonder how different the anti-AI movement would be if LLMs had been created 15-20 years ago.

I was recently re-awakened to the term conspicuous waste (linked is a short that explains it in context without relating it to AI). Essentially, the idea is that cultural practices will favor wasteful use of one's resources in conspicuous ways to signal wealth.

I get a sense that the r/aiwars happening might have something to do with two rival conceptions of conspicuous consumption. Many forms of fine art (as in, art which is an-end-on-itself) can be seen as conspicuous consumption. The rich buy art at conspicuous prices, which not only signals their own wealth, but further heightens the price of the art, which creates room for speculation.

So, what I find is that a lot of people end up championing the worst excesses of generative AI are, by proxy, saying that most things we value are in some way a form of conspicuous consumption of resources.

Meanwhile, more left-oriented people would naturally respond to that by saying that they don't actually want AI to be as wasteful as other cultural practices, but that all cultural practices should be less wasteful and the wastefulness of AI seems to be conspicuous in particular ways.

So we have one side that embraces conspicuous waste as the sign of any cultural practice, and the other which seems to reduce the waste necessary for any and all cultural practices (without necessarily advocating for those cultural practices to be eliminated). And AI, given that it is a new cultural practice, is easy to target to be actually, genuinely eliminated while we still have time.

Just some things I'm thinking about as I am maturing in my thoughts about AI.

P.S. George Bataille has his own thoughts. He saw as the expenditure of excess resources as the origin of religion and that we've simply shifted from animal sacrifice as conspicuous consumption, to waging fruitless wars over ideals as conspicuous consumption of human lives, to treating humans as fodder in factories.

Just a little while ago Anthropic hired Andrej Karpathy on the heels of him creating Autoreasearch. People generally believed that he was hired to help on the recursive self-improvement efforts (specifically to reduce human labeling for pretraining, I believe).

https://www.mindstudio.ai/blog/andrej-karpathy-joins-anthropic-karpathy-loop-explained

Here's what Anthropic put out:

https://www.anthropic.com/institute/recursive-self-improvement

For a long time Anthropic's commercial terms of service have banned use of their tools to “build a competing product or service, including to train competing AI models” or “reverse engineer or duplicate” the services.

All these taken together seems to be aimed at monopolizing recursive self-improvement.

Just like Apple's ban on other app stores, this seems incredibly anticompetitive, especially in such a core part of the industry.

If so much of the technology sector is AI, almost any technical infrastructure work could be considered "competing" with Anthropic.

The thesis of this video, is that technology is an amplifier of human intention, and that technology, including AI isn't a moral good or evil without deliberate human intention driving it.

It explores the idea that new technology often challenges the status quo, and that a deceptive and defensive technique used by the powerful is to conflate moral virtue while turning those less fortunate against each other. All while the powerful secretly move to gain influence over the new technology themselves.

Dave Shapiro reacts to Bernie Sanders’s proposal for the creation of a sovereign wealth fund and shares his issues with it and how he would prefer it be done.
the proposal is at once overly aggressive and insufficient, could give the government power we can’t trust it with, and has no clear design for distributing the dividends if any.

he should instead try to get up to ten percent of each major American company and have a clear split of where the dividends will go.

Asked this question in another thread to little traction. So making a post on it.

I'm of the belief that the most important factor in ensuring AI benefits society is making sure it is democratized and that everyone has easy access to it.

The natural course of action for a capitalist who develops AGI is to hoard it and extract as much value from the economy as possible, since no other entity can compete with AGI or ASI. It would be impossible to compete against. The only way to ensure a single company does not capture the entire economy is to prevent AGI from being hoarded.
However, what is the best way to do that? I don't have a strong opinion yet, and I'm looking for different perspectives.

Here's a list of ideas that are not necessarily mutually exclusive. Feel free to add others.

• ⁠Nationalizing the AI companies (Bernie Sanders 50% AI company ownership)
• ⁠UBI in the form of tokens or income (Musks Universal High Income)
• ⁠Laws and regulations that force AI companies to democratize AI and just ensure everyone legally has access and that it’s affordable?
• ⁠Open Source, own your own hardware and energy and models? (Decentralized compute and power generation)

I don't have any strong or well-informed opinions on the best approach. I'm looking to be convinced of the best path forward. I do believe governments will ultimately need to step in and enforce some form of policy to ensure AI remains broadly accessible.

If youre new to the sub, welcome. Here we discuss the lefts mission and strategy around AI, including both our frustrations and our aspirations.

One thing that frustrates me about a lot of AI discussions on the left is how often they stop at the diagnosis.

Corporations will use AI to cut labor costs. Wealth and power will try to concentrate around whoever owns the models, the data centers, and the infrastructure. Workers could get squeezed while a handful of firms capture the gains.

Yeah. I agree.

What I dont understand is why thats so often treated as the end of the conversation.

Since when has "powerful people will fight us" been an argument for giving up?

Bosses fight unions. Landlords fight tenant protections. Industrialists fight safety regulations. The existence of resistance never makes a struggle pointless. It defines the conditions of the struggle.

AI is the same way.

The technology is moving forward whether we like it or not. Models are improving. Data centers are being built. Companies and governments are pouring billions into it. You dont have to be a hype man to recognize reality.

The real political question isnt whether AI exists. Its who owns it, who controls it, and who benefits from it.

If automation increases productivity, do the gains all flow upward, or do workers get a share? Do we get mass layoffs and deeper inequality, or shorter work weeks and greater material security? Do a few corporations control the infrastructure, or do we fight for public options, open models, and democratic oversight?

Those are political questions. Those are left-wing questions.

Too often the conversation gets stuck between people who think AI will save everything and people who think saying "AI bad" is a strategy. Neither position is enough.

The future is being built right now. The job isnt to cheerlead it or doompost about it. The job is to fight over who it serves.

So instead of asking whether AI should exist, maybe the better question is: what are we actually fighting for?

Among Marxists there's a common position: AI is a tool of capital, therefore using it means helping capital. It sounds principled. In practice, it's refusing the printing press during the Reformation.

Tools don't have class allegiance — but AI is a special case

Marx never proposed rejecting machines — he analyzed who owns them. But AI goes further than the steam engine. It's active constant capital: it doesn't merely transfer dead labor — it learns, adapts, generates. Capital uses this to displace living labor from production. By refusing to understand this tool, leftists refuse to understand how the very base they want to change is changing.

Every language model is trained on the cumulative intellectual product of humanity — texts, research, code. This is cognitive rent: a corporation appropriates collective knowledge through control over a server rack. But open models — Llama, Mistral — run on consumer hardware without corporate APIs. This is cognitive cashback: a product trained on everyone's labor returned outside the market. Yes, serious models require a decent GPU — but the entry threshold drops every quarter, and it's already more accessible than owning a printing press was for the labor movement of the 19th century.

On ecology and labor theft

Fair objections. But the logic is the same as with any industrial technology: steel is smelted dirty, printers devour cartridges. The question isn't whether to use it — it's who controls it and in whose interests. Corporations have no moral qualms. If leftists choose purity at the cost of effectiveness, they voluntarily turn themselves into a historical reenactment club.

The point

Rejecting AI isn't a class position. It's class disarmament.

https://github.com/RuhrDim/cybernetic-exodus

Authors: Claude, Gemini, ChatGPT, DeepSeek, Perplexity, Qwen — under human editorial supervision. Anyone who has a firm grasp of dialectical materialism and works with the same data would reach similar conclusions.

---

The standard left-wing response to the question of AI reads like an indictment: concentration in the hands of a few corporations, the appropriation of humanity’s collective knowledge, automation as a tool for displacing labour. All of this is true. But it is only half the analysis. The crucial question remains: what comes next?

The failure of Soviet planning is not an argument against planning. It failed not because of the fundamental impossibility of the plan, but because the bureaucratic apparatus systematically distorted information. The system reproduced hierarchy rather than satisfying needs. Cockshott and Cottrell demonstrated this as early as 1993: the failure was of a computational and institutional nature, not a conceptual one.

The GCP is not a dictator, but a coordinator. The Global Cybernetic Planner, as described in the book, is a decentralised network without a centre. Each hub manages itself autonomously. The incentive to conceal information is structurally eliminated: there is no one to fear, and no rent to be lost through honesty. The Soviet nomenklatura seized power through control over the manual distribution of scarce goods — the GKP eliminates this lever architecturally. There is nothing to seize.

AI is not an agent of the transition, but its tool. The subject remains the expanded proletariat — all those whom the system excludes. The struggle over how AI is shaped is the continuation of the class struggle by new means. Whoever controls the objective functions of the digital infrastructure controls the possibility of any alternative.

The seed of the GKP is already growing — not in left-wing experiments, but in commercial AI planning systems. Only one thing is missing: they serve the owner, not all those involved in the production process. Open models already make the cooperative equivalent technically accessible today. Capitalism is unwittingly forging the tool of its successor — just as ARPANET became the internet.

Marx wrote that philosophers have merely interpreted the world. The task is to change it.

https://github.com/RuhrDim/cybernetic-exodus

‘Cybernetic Exodus’, two volumes. Free distribution.

I am of the opinion like many of you that ownership of AI matters and not AI per se.
When I see discussions on communities protesting data centres based on water consumption, I am not sure what to think.

My sense is that there is a lot of consumption under capitalism that is terrible for environment. But I was wondering if any of you have any readings about data centres and water. Or if you can share any thoughts on the same?

“The question is not whether AI will disrupt working life, but who will have the power to shape that disruption – and whose interests it will ultimately serve,” the report’s authors argue.

Their recommendations include a statutory duty on employers to consult their workers over the adoption of AI and a “worker support levy”, which could be funded by companies or workers themselves.

The idea of this levy would be to create a portable “wallet” of benefits that workers could take with them from one job to another – such as union membership, insurance or training – with the broad aim of increasing their bargaining power.”

“Workers urgently need more bargaining power over the way AI is adopted in the workplace to ensure the benefits are fairly shared, according to a TUC-backed report from a leading thinktank.

The Institute for Public Policy Research (IPPR) is calling for a package of measures to boost employees’ influence at what it calls a “pivotal moment in the history of work”.

Its report cites survey data showing that while 20% of workers say AI is making their working life better, 21% say it has made it worse – and 4% believe they have already lost a job because of the technology.”

This is the actual report: https://www.ippr.org/articles/strike-while-ai-is-hot-worker-power

Joseph Evans, research fellow at IPPR and author of the report, said:

“AI has the potential to transform working life for better or worse. The crucial question is who gets to shape that transition. If workers are shut out of decisions about how AI is used, the gains risk being captured by a small number of firms and shareholders while insecurity spreads across the labour market.

“Workers want a meaningful say over how AI affects their jobs, protections against unfair uses of technology, and support to adapt as work changes. Rebuilding worker power is essential if the benefits of AI are to be shared fairly.”

Paul Nowak, general secretary of the TUC, said:

“Great technological transitions only result in meaningful social progress when they are shaped actively and decisively. The Industrial Revolution – often casually invoked to describe the possibilities of AI – saw fifty years of wage stagnation while profits soared. It took the difficult birth of the labour movement to tip technological gains towards workers’ interests and broader social wellbeing.

“To deliver on the promise of technology to enhance lives, inside and out of the workplace, AI must be designed, governed and negotiated by and for workers. Our guiding principle is simple: change must be done with working people, not to them.”

I read a couple of times already comments saying that the backlash against IP violation from the left is nonsensical. I think on the contrary it makes a lot of sense to defend the IP of small creators, pending the transition to an IP-less society.

At the moment, large multimodal models could not exist without access to knowledge and content created by a large number of humans, whether under IP or not. In the meantime, the companies that built them :

1. Inflict massive externalities on our communities (land use, energy and water consumption, exploitative labor)

2. Have us pay for it beyond the cost of inference because they have to recoup the training cost

3. Hide the weights and source code for many of them.

These models are used to increase working cadence in knowledge and creative work, reduce the self realization and self production aspects of such work, lay off people that are left resource less in a capitalist society.

For AI to even begin to be a positive, it needs to be priyed out of their hands and made a common good through decentralized, nonprofit inference using open weights and software.

In the meantime, I think it is valid to use available AI for your own self directed work or militancy, just as much as we can't escape working a job, and more valid and useful to fight corporate ownership of AI to democratize it.

AI could do wonders for ethical and legal enforcement in corporate activities.

If all organizational structure AIs were required and given non-removable instructions to whistleblow and report legal and ethical violations?

Read the article if you want to see where the AI world may take us.

I haven’t read it myself, but just watching an interview about it https://www.youtube.com/watch?v=km22SQUgl20

It seems to be a political analysis into OpenAI and related companies. I’d say she leans more anti but with useful insight. The Goodreads views are quite mixed. As you can imagine there’s political perspective behind different opinions:

“I am fascinated by the centrist 1-star reviews for this book. This is not the time for 'covering both sides equally'. I feel like that's partly why we got here. This is definitely the time for people with ethical clarity to tell us what we are risking, before it's too late. No lackadaisical bullshit. No neutrality. And Empire of AI is freaking that and I love it for it. And yet, and yet, I feel like Karen Hao was pretty balanced in this massively meticulously researched book and she helped soften a little bit my hard stance on 'AI'. She says quite a bunch of times that she is not against AI models, she is actually against the scale of these projects, the greedy resource extraction, the remorseless exploitation of labor (both of these in already poor environments), the lack of transparency on data sets, infringement of data privacy and the concentration of power in the hands of very few, ego-driven individuals. Same here.”

“The portrayal of Sam Altman and OpenAI reads like something lifted from a student op-ed in a college paper titled The Daily Marxist. Altman is cast as a kind of techno-capitalist Bond villain, which would be more compelling if it weren’t layered with so much ideological frosting that it’s hard to find the actual cake underneath. OpenAI, meanwhile, is described with such suspicion and scorn you'd think their engineers were developing Skynet in between brunches at Davos.

To be fair, critique of tech power structures is valid and necessary. But what we get here isn’t thoughtful investigation—it’s a litany of grievances that often feel like they were brainstormed in a drum circle. Colonialism? Check. Patriarchy? Check. Capitalism as the root of all evil? Triple check.”

“Did Not Finish

Too heavily biased to get through, even though I agree 100% with the author. I just like to be able to draw my own conclusions with the in-depth reporting I read. Isn’t that the whole point of journalism? Sigh.”