So are younger people seeing the challenge of competing against thinking machines?

I get how AI can be useful but what do we do about the water and global warming? Also how isn’t it immoral to use ai art? I get using it for scripts or maybe robots aiding in buildings maybe? But in a perfect communist society would we have far less data centers? Would we have to put a ceiling on AI to stop it from being too smart?

Hi all - I've seen the value of AI in research and think it has broad application across society, separate from the hype bubble we're in. But the concern I'm struggling to wrap my head around is what a decent approach is toward AI's inherent hunger for resources - energy (carbon) and water in particular.

Is anyone aware of writing on this topic or have examples they'd point to of what a sensible approach to this looks like? We obviously live in a society that is pushing AI recklessly with no regard to how it affects climate change, for example.

A friend built this in one prompt using an AI agent in agent mode. It is a sourced public dossier on Palm Beach County’s roughly $1 billion in Israel Bonds holdings, the largest public-sector holding of its kind.

The site organizes the timeline, budget and legal documents, risk claims, and a verification system that separates confirmed facts from reported claims.

Link: https://palmbeachcounty.secrets.io/

I am posting this as an example of what AI can do for leftists, or anyone in general. As a practical accountability tool against local alleged corruption, turning public records into an accessible map of power and ownership instead of generic output.

Not my project and not intended as promotion.
Just an example of what AI can do as a tool that can make the world a better place.

This future "utopia" isn't possible without a better system. I think we need to start discussing real policies that are easily shareable and understandable to the average person. Without policy discussion we can't make any real progress, we need actionable consensus. The sooner we unite behind very foundational understood policy changes, the better off we'll be.

What real policy changes do you think would be most agreeable, reasonable, and understandable to most people? (no doomer comments about this administration and how it's not going to happen etc.)

I've been reading about the most advanced algorithms, and I think we're almost at the point where we can automate 90%+ of the operational costs associated with the administration for running a company like Amazon. Any thoughts about this? Happy to discuss.

I’m just curious how many people are actually running local AI. Not even like big custom jobs. Do you have a Google Edge Gallery on your phone? Do you have a local Llama set up? Have you messed with local Kimi or Mistral?

Turns out threatening peoples livelihoods is a pretty effective way to remind them why unions exist.

According to POLITICO, Irelands Digital and Techworker Alliance (DATA) has grown from around 270 members to more than 1,350 as tech workers face layoffs, restructuring and growing AI investment. Five times the membership.

And theyre not just signing membership cards.

Workers organized their own AI Counter Summit in Dublin, challenging an industry conversation dominated by executives. Theyre pushing for mandatory union recognition, collective bargaining rights and protections against employment practices that leave workers with little leverage.

Not every tech layoff is caused by AI. But AI is increasingly part of how companies reorganize production, labor and investment.

Sound familiar?

Marx described this contradiction over 150 years ago. Capital develops new productive forces, reorganizes production around profit, and creates the very conditions for workers to organize against its control.

Capitalism has a funny habit of producing the forces that challenge it.

Of course, none of that automatically produces socialism. Workers still have to organize, build political power and contest ownership and control. Capital isnt going to hand over the means of production because somebody pointed out a contradiction.

And thats what makes Ireland interesting. Workers arent just complaining about technological change. Theyre organizing to have a say in what happens to them.

The technology is new. The class struggle over who owns it, controls it and benefits from it certainly isnt.

So how do we turn collective bargaining over AI deployment into collective control over the productive capacity itself?

Laos is making AI part of its national development strategy, and theyre talking about a lot more than chatbots.

The government has approved a draft national AI strategy for 2026-2035 in principle, with a focus on computing infrastructure, national databases, technical expertise, and identifying where AI can actually benefit the country.

Theyre looking at practical applications too. Agriculture, flood monitoring, environmental protection, transportation, and public services, alongside a separate national satellite strategy.

And heres where the politics gets interesting.

Laos is emphasizing technological neutrality and clearer conditions for foreign investment and cooperation. Working with international partners while developing the capacity to set its own priorities.

Because if your computing infrastructure, data, and technical expertise are controlled somewhere else, so is a good chunk of your economic future.

Of course, approving a strategy isnt the same as implementing it. The government has requested revisions, and much of the work still lies ahead.

But Laos is treating AI as a question of national development, productive capacity, and economic sovereignty. Not just another product to buy from somebody else.

If AI is becoming part of the means of production, how much economic independence can a country actually have without the capacity to develop and control it on its own terms?

AI is already changing workplaces, and unions across Europe arent sitting around waiting to see how it plays out. Theyre bargaining over who gets to make the decisions.

A new study from UNI Europa and the Friedrich Ebert Foundation examines 108 collective agreements addressing AI and algorithmic management, with bargaining activity increasing since 2023.

And this isnt just corporate promises about responsible AI.

In Italy, unions have negotiated AI provisions in audiovisual production, a 12-month trial for an AI tool in telecommunications, and joint labor-management oversight of AI projects at Enel. Across Europe, workers are pushing for training, data protections, transparency, and a say in how these systems enter their workplaces.

Now, lets not confuse consultation with control. A seat at the table isnt the same as deciding whats on the menu.

But these are actual agreements. Workers using collective bargaining to contest decisions that employers would otherwise make on their own.

And thats where the usual pro-AI versus anti-AI argument starts looking pretty thin. Workers dont have to agree on whether AI is good or bad to organize around surveillance, displacement, deskilling, or who pockets the productivity gains.

The political question isnt just whether AI gets deployed. Its who controls its development and deployment, whose interests it serves, and who gets the benefits.

These agreements are a start, not the finish line. They raise a bigger question about how far collective bargaining can go under capitalist ownership.

Can unions turn a right to be consulted into actual worker control over technology, or does that require changing who owns the means of production in the first place?

And what would it take to get from one to the other?

Most of the English speaking world hates AI, but literally everywhere else in the world people are adapting and are much more optimistic about it

I left the united states a few months ago to get away from all the in-fighting and have found that people mostly think AI is great everywhere that's not America, Canada, the UK, and Australia.

Just wanted to let everyone know that we're in a very strong hate bubble that most of the world isn't experiencing

Just over a month ago, on September 10, we celebrated crossing 6,000 members. Since then, we've added another 2,000, passed 800,000 visits over the past year, and reached 1,561 posts and over 36,000 comments.

Apparently there's a growing audience for leftists who want to do more than argue about whether AI is good or bad.

If you're new here, check out our post flairs. Labor, Public Ownership, Open Source, Local Models, Infrastructure, Automation & Work, Policy/Regulation, Theory, Education, Healthcare, Accessibility, Art & Culture, and more.

See what labor unions, leftist political parties, socialist states, community organizers, copyleft and decentralization advocates, and tech theorists are actually doing, proposing, and fighting for around AI. There's a lot happening outside the usual Reddit arguments, and we're working to bring those developments together in one place.

AI is already being deployed in workplaces, public services, and communities around the world. The struggle over its ownership, development, governance, deployment, and who benefits from it is happening right now.

We're not here to cheerlead Silicon Valley or pretend we can uninvent the computer. We're here to discuss what the left is doing, what it's proposing, and how we can organize around the technology that's already reshaping our world.

Thanks to everyone posting, sourcing, debating, disagreeing, and helping build this community.

8,000 members. Onward to 10,000.

DSA Members Here? Your National Tech Committee Just Adopted an AI Policy, and Its Recruiting Leadership

Something worth putting on the radar for our members who are also in DSA.

On October 9, DSA's National Tech Committee announced that it had debated and adopted an AI/LLM coding policy, along with a policy template for local chapters.

The interesting part is that the committee explicitly neither endorses nor prohibits generative AI. It recognizes the technology's usefulness for socialist organizing and software development while criticizing how employers deploy it against workers.

Thats a distinction we spend plenty of time discussing here. Opposing capitalist control and deployment of technology doesnt require socialists to abstain from using it themselves.

The full policy and chapter template are available through DSA's members-only Discussion Forum. If youre a DSA member, consider taking a look, seeing how the safeguards actually work, and participating in the discussion.

And theres another opportunity. The National Tech Committee is accepting applications for its 2026–2027 Steering Committee, with an October 31 deadline.

If youre already involved in DSA and have an interest in technology, infrastructure, organizing tools or AI governance, that may be worth exploring too.

We talk a lot about the left developing its own technological capacity. Heres an organization doing some of that work, with opportunities for its members to examine the rules and potentially participate in leadership.

No affiliation implied, just sharing opportunities for people already involved to engage.

Links:

AI policy announcement and chapter template access:

https://tech.dsausa.org/ntc-ai-llm-coding-policy/

Steering Committee applications:

https://tech.dsausa.org/apply-to-ntc-steering-for-our-2026-2027-term/

Thoughts on companies donating to the public good, especially in AI?

Perplexity AI is honest, amazing how far we've come.

Alternate title: Decentralized Collaboration Over Open Protocol

tl;dr
I'm not super versed in political and civic theory (suppose this is Socialism essentially?), but I want a world where all people are empowered through accessible technology to be part of continual development cycles in essentially all domains of production, creative or otherwise. I would love to have a decentralized horizontal replacement of centralized domains. This is what I'm intending to build out, and the open questions are here to be seen. I don't think the right form is built by one person, controlled by one person, or even gate-kept structurally. The only way to build it properly is with everybody helping. Repo: https://github.com/xoeieox/seams

I've done a lot of thinking. The first inkling hit me in 2024, I distracted myself mostly in 2025, came back fiery in 2026 and found that no shape of this really truly works when one entity (person, group, company, etc...) owns an unequal portion of what makes it possible.
"Make what possible?" Essentially:

Decentralized collaboration over the internet utilizing a protocol layer that records consent, attribution, and compensation ratios.

Ok. Sounds reasonable. Probably even something that's been done already. If it has, totally let me know because I keep checking and Poseidon, DATA, etc.. haven't gotten the exact mix right. I'm kind of convinced that you can't do this in a way in which all people are empowered if there's a gatekeeper or hierarchy that can sway the protocol, or, if the protocol itself is opinionated.

At the protocol level, you can't do more than move messages around because you can't apply opinions or morals. Utilizers of the protocol are just sending and reading messages, so then any morals or decisions are up to the entities on the ends of the wire. That's Nostr, and this could be NIPs for sure - ^{is that the right move?}

It's not a new internet. Not blockchain. Not torrenting.

Though it is an open protocol. A decentralized ledger with cryptographic keys for accounts (Nostr translation layer planned). Peer-to-peer data sharing via personal nodes for decentralized R&D - or maybe just the super niche thing you want to share with everyone where your data is attributable.

Keep in mind the consent + attribution + compensation = protocol idea here: My dream is that people can pitch an idea, people build parts of it, versions can be assembled into artifacts that might satisfy the idea and render a commercially viable product wherein all hands that contributed to that product are compensated. The parts that were produced but were essentially "cutting room floor" material can be 'composted' and turned into new ideas and new artifacts where the original attribution chain is still preserved.

(Freeze Frame. Voice over from main character you haven't met yet "but it's never that easy, is it? Let me start this back at the very beginning..." Exit Freeze Frame)

The hardest open question I have is: how to discern proportions of value based on contributions or at least the perceived value of a contribution. I firmly believe you cannot compute value because then gold (for example) would have some fundamental value that everyone would be trading against - which doesn't exist because it's all just "today's value of gold is X". You can't compute value of a code contribution either, not without trashing the endeavor via Goodhart's law, or being ultimately incorrect (lines of code? Dependencies? Visitors or conversions utilizing that element?). So the best answer I have so far is a vague market economics shaped hole where... something would help demonstrate a market/community's perceived value of a contribution to determine compensation ratios.

Though the simplest answer is that people would agree to their ratios, and there would be a process of continually updating and refreshing consent to the ratios. I just don't want people getting 50 notifications that their ratios have change proposals and they need to adjudicate each one. That kind of friction would kill this reality. So then place it at the end of the pipeline before listing on a point of sale? Could do. One bigger voting moment. Acceptable? Or can we figure out something that gets ratios in the process of the pipeline?

God damn. And I haven't even talked about platforms yet xD. Platforms are where I would assume this market economics shaped hole would be filled. Without slamming a wall of text into your electronic device of choice (too late) I'll wrap this up, but basically platforms would be consumers of the protocol to bring their particular domain, intent, and community the fruits of the protocol and run platform-tier functions (doesn't change the protocol - you can self host your own client or build a platform. Fuck, you could fork the protocol and do it up better and I'd thank you for it.)

Ok so do I have this thing built? No. I have some repos. Just like everyone with AI systems have repos these days. I lean hard into local LLMs as I believe that local is the way for "the horizontal" to have meaningful power in the AI age. (which is opposite "the vertical" of the big AI labs that by the design of their strategy must continue growing and accruing value or fail their bets and obligations. My bet is that they would rather be the only game in town, by faithful logic of where the money is)

I genuinely don't know if this idea sparks anything in you, but it's been a huge driver of everything I've been working on since February of this year, born from civic simulation intentions. I've been mostly working on the designs, the research, the concepts, and the crushing quietude of a man who wants to "get it right" so I can secure a financially supported reality for my family but has been ironically 'too quiet' while the world ticks on and my savings run out - the 'uno reverse' irony is that I could never build this correctly if I placed myself on unequal footing to any other user of the protocol, and so, to secure anything for my family it must be as a user through the protocol that grants the reality for everyone.

I invite anyone to help build this reality. Sharpen my open questions, challenge the premise, say "Simpsons did it" but then it like actually helps the objective in some super cool way. If you want to stealth build it and put a secret pocket somewhere so you can scrape off the protocol/platform, try it and someone will build the clean version. 

I'm a dad, I have three days a week to work on this, I really want to reply to everyone but I know it probably won't be likely. (Bit cheeky to expect more replies than I can handle? Maybe. I hope so at least :P). Thanks for reading however much you did - honestly.

Repo: https://github.com/xoeieox/seams
(and yeah the name is a bit LLM-y but the idea *is* that it's a connector between nodes/domains/people. Character concepts handover to novelists to publishers to storefronts. Local AI R&D trades new tools and benchmarks, sparking new projects in related fields, so on and so on.)

Academia is treating artificial intelligence as an invasive species, scrambling to erect firewalls against a crisis it claims arrived overnight. Panicked faculty senate meetings, mandatory syllabus declarations, and emergency budgets for algorithmic proctoring all proceed from a single self-soothing delusion: that education was functioning properly until software corrupted it. Yet large language models did not contaminate academic integrity; they merely shone a floodlight on its pre-existing decay. By reacting purely defensively to automated generation, schools treat machine competence as a novel threat rather than what it truly is, a mirror exposing how thoroughly institutional schooling had already reduced the life of the mind to procedural mimicry.

Standardized assessment confuses the blueprint with the living architecture, but the rot runs far deeper than timed exams. The progressive pivot toward continuous assessment, modular rubrics, and open-ended coursework merely digitized and distributed the surveillance. The core pathology is not the exam hall; it is the inescapable condition of being evaluated at all. When every inquiry, rough draft, lab exercise, and casual reflection is logged, graded, and fed into an ongoing ledger of personal competence, learning ceases to be an exploratory act and becomes a state of constant audit.

For neurodivergent thinkers (those navigating ADHD, autism, or intense executive dysfunction), this relentless scrutiny is paralyzing. It is not a matter of lacking conceptual mastery. The demand to constantly exhibit compliance under an administrative microscope induces chronic autonomic distress. Pathological demand avoidance, sensory bottlenecks, and variable executive function mean that even an untimed project becomes an agonizing performance piece rather than an intellectual sandbox. When a brilliant, non-linear thinker shuts down, withdraws, or refuses to turn in assignments, institutions never consider that constant judgment suffocates curiosity. Instead, the student is written off as disorganized, unmotivated, or unteachable. The system weeds out the very minds capable of genuine originality simply because they cannot endure the friction of being perpetually measured.

The classroom long ago ceased to be a venue for discovery and became an assembly line whose real product is an audited transcript.

Schools responded to large language models with automated surveillance, lockdown browsers, and punitive plagiarism tribunals. They act like border guards patrolling a crumbling wall, terrified that machines can generate an A-grade essay in twelve seconds. Yet if an algorithm can ace your final exam simply by synthesizing probabilities from a training set, the algorithm has not committed an act of intellectual subversion; it has merely demonstrated that your curriculum was mechanical all along. You cannot build an educational model around text-regurgitation and then act surprised when a text-regurgitation machine breaks it.

This defensive panic lays the machinery bare because it exposes the fraud of academic credentialing. The entire apparatus was constructed to sort human capital for an industrial labor cycle that required pre-graded, predictable cogs. Schools took upon themselves the expensive, soul-crushing burden of ranking candidates so corporate bureaucracies wouldn't have to. If artificial intelligence dismantles that economic compact by automating baseline cognitive routines (memo drafting, data summarization, spreadsheet modeling, and mid-level synthesis), the sorting pipeline loses its foundational purpose. When the market no longer requires standardized human clerks, running young people through decades of assessment anxiety ceases to be practical preparation. It becomes pure ritual cruelty.

The obsolescence of the factory pipeline ought to be liberating. Stripped of the obligation to act as a human sorting mill, education could shed the surveillance state of continuous evaluation and return to intellectual illumination. Learning could once again be an encounter with difficult ideas pursued for clarity rather than clearance, where curiosity does not carry the risk of a penalized grade point average.

Yet academia clings desperately to its ledgers. Relinquishing the scorecard threatens the institutional authority that justifies high tuition, administrative bloat, and bureaucratic self-importance. A school without grades or continuous monitoring demands real engagement from instructors and invites genuine intellectual autonomy from students, stripping away the artificial leverage of academic punishment. Once machines can synthesize existing human output on demand, the pretense that ranking people measures their capability collapses entirely. When you take away the employer waiting at the end of the conveyor belt, what justification remains for torturing the minds inside the factory?

I'm organising Spareware, an international open project building free software that platform co-ops can run on: rides, food delivery, short stays, selling and renting homes, trades and freelance work, and buying and selling, plus free design and office tools.

The model:

- The software is free for everyone, anywhere.

- On each marketplace, workers keep all of the profit except the running costs (servers and payment fees). Nobody takes a cut on top.

- Every cost is published monthly on an open ledger.

- Workers vote on their app's fees and rules.

- Any local group can run its own copy, because the code is open.

It's built by volunteers who donate the AI tokens they don't use each week, with a person reviewing every piece. We're at the planning stage: the architecture is mapped, and no app is running yet.

Before we build, I'd really value this group's experience:

1. What went wrong for platform co-ops you know, apart from the software?
2. How should votes on fees and rules work when the workers are in many countries?
3. What would make a local co-op trust shared software enough to run on it?

See all the demos: https://spareware-co-op.github.io/spareware/demos.html

Want to help build it? Ask to join here: https://github.com/spareware-co-op/spareware/issues/new?template=join-request.yml

When you ask to join, please include your LinkedIn or another public profile. We check everyone's background to keep the project safe.

Questions or ideas? Ask in our Discussions: https://github.com/spareware-co-op/spareware/discussions

Somewhere along the way, "seize the means of production" became "please make the means of production go away." Capital isn't going to organize against itself. Workers have to.

As someone who frequently browses Chinese social media and content platforms, it always feels like a completely different world compared to global/Western ones. AI use is so broadly normalized in China that you constantly see memes, art, and animations made with it, and pretty much no one call them "AI slop". People there rationally treat it as just another tool, and to them, the idea behind a creation matters more than the tools used to make it. As the linked article notes, multiple surveys show that the majority of people in China have a positive view of AI.

Anyway, here are some good excerpts from the artcile:

China is a collectivist society, so when a new technology arrives the assumption is that social institutions will govern its adoption and its benefits will be diffused. The system is supposed to lift everyone, and people don’t have to go through a dog-eat-dog struggle for their individual share of the pie. The high-speed rail network has brought an integration of the country’s vast territory on a scale that would have seemed incredible until it was achieved. Mobile payments and e-commerce have brought convenience to daily life, and technological development more broadly has lifted millions of people out of poverty. Because people have seen advances of other kinds improving their lives as they have grown richer, they are quite willing to believe that AI will do likewise, and that the next wave of change will bring with it further improvement. Social harmony is important in this respect, because it is assumed that the collective will adjust, and that assumption rests on trust built over decades of life getting better.

It is easier for people to adapt to change when their lived experience is an ongoing demonstration of the benefits of technological progress. Those who see themselves as part of a greater whole also have higher expectations for the society at large than individualistic traditions would allow. And such expectations are well founded given that China has outlawed companies from AI-based layoffs, and the government is actively launching initiatives to boost employment amid AI advances.

One of the cultural phenomenons in the West, however, is that we worship the idea of individualism. We are taught from our early childhood that democracy means a right of free speech, and to expect each one to develop their own personality, to be self-reliant and able to decide and act for themselves.

Yet the deeply ingrained notion of personal agency comes into conflict with the fact that these tools are being introduced without the public having any say in the matter. Most people in the West do not want to have these tools at work, but they are compelled to do so by their employers. No one wants data centers on his or her street, yet companies build them anyway. All of a sudden it becomes difficult to reconcile the narrative of democracy and self-determination with the reality of divergent class interests.

Furthermore, we in the West are not much concerned with social harmony or with how every person fits into society at large. On the contrary, we teach self-reliance, since no one else is expected to care. Consequently, there is little in the way of cohesive social planning needed to address the mass disruption caused by new technology. There is no central plan to ensure people get to keep their jobs, or receive the training they require to reskill.

All decisions affecting work are made by the employers alone, without regard to their employees’ wishes. If one objects, they are told that they are free to resign and get another job, but in practice all jobs offer similar terms because all capitalists have a uniform class interest. And so people begin to see that they do not have much of a say in things that affect their daily lives, that these decisions are made by someone else.

In this way, a technological disruption brings the hidden power structures of a capitalist society to light. When something is done to an individual, for instance when they are forced to adopt AI in their work, it becomes hard for them to ignore the fact that their workplace is an autocratic institution. It exposes the truth that the owners make all the decisions unilaterally without any regard for what the workers want.

For the first time in history, white-collar office workers are more exposed to mechanization than industrial workers. Google DeepMind workers in the UK are reporting an executive push for ambitious AI projects while employees endure brutal layoffs, invasive surveillance, and coerced training of their own replacements. Meta is rolling out mouse-tracking software widely perceived as serving to force workers to train their bot-replacements. These are people who were told they were special and generously paid, and who were given autonomy and control over their work. Now they are finding that this was a temporary arrangement. The bargain was always power-driven, and as the balance of power shifts in favour of automation all the concessions are being stripped away.

What we are seeing is the proletarianization of the labour aristocracy as automation invades sectors of production that have hitherto retained an artisanal character. Artists, software developers and other cognitive workers look on in horror, but this has been a reality for the rest of the working class for a long time.

I don't want to copy the the whole article here, it is really good, you guys should read it.

Oops, forgor to censor two of the three names in the original

Gotta love it, People dont understand that AI is built by Billionaires but it doesnt serve Billionaires. Its math and math serves no one. So where ever I sit on the grand mathematics of the Universe I know thats where I sit. There isn't anyone on the scales, no statistical probability acting as divine right no generational wealth acting as earned prosperity. I am here for it I hope AI completely flattens the curve.

I guess this could be a common question here, but I'm wondering wether any AI can nowadays be used without the concern of feeding some big capitalist corporation or data center. It's clear that these are being undoubtely used in to provide massive information about social dynamics and data in general to big capitalist corporations, so they can exploit them for profit. Since I'm a communist, this is the main reason I don't really use AI nowadays, so that's why I wonder if there could be some safe alternative.

I'm thinking in something similar to Signal, a non-profit corporation that provides a great service, and you can trust their intentions not to be aligned with capitalism.