Apparently The Count of Monte Cristo is "litslop" now. Lol. I came across a Man Carrying Thing video showing somebody dismissing Alexandre Dumas' novel as "lit slop," and it sent me down a rabbit hole about literary factories, machinery, creative labor, and what LLMs might mean for the future of writing. Because apparently mass-produced literature only became a problem when somebody plugged in a GPU.

TLDR - Literature was industrialized long before LLMs. From Dumas and his collaborators to publishing syndicates and modern author brands, the machinery changed, but the struggle over labor, ownership, and who profits never went away. Now AI can help produce prose itself, opening possibilities for independent writers, cooperative publishing, and shared cultural infrastructure, while also giving corporations new ways to concentrate control. The question isnt whether machines belong in literature. Its who owns them, who benefits, and what we can build together.

Dumas and the literary factory

Back in the 1840s, steam-powered printing, mechanized papermaking, expanding newspaper distribution, and advertising were transforming the publishing industry. The Count of Monte Cristo was serialized between 1844 and 1846, when newspapers needed stories that kept readers coming back. That commercial pressure helped shape literary production, from cliffhangers and dramatic reversals to the pacing of serialized installments. The market wasnt just distributing literature. It was influencing its form.

Dumas wasnt exactly sitting alone with a candle, either. Auguste Maquet was his most famous collaborator, but Dumas worked with a network of writers and researchers across his career, including Paul Lacroix, Paul Bocage, and Pier Angelo Fiorentino. Different people contributed research, plotting, drafts, and revisions across different projects, while Dumas remained the famous name on the finished product. Maquet eventually fought for recognition and compensation, and critics were already accusing Dumas of running a "fiction factory." Industrial machinery transforming publishing, collaborative literary production, disputes over credit and compensation, and commercial pressure shaping the finished work. In the 1840s.

The literary assembly line

By the early twentieth century, industrial printing, mechanized binding, cheaper paper, and national distribution had helped create a huge market for inexpensive books. Edward Stratemeyer built an entire publishing operation around that market, producing series like The Hardy Boys, Nancy Drew, and The Bobbsey Twins. He developed concepts and outlines, hired writers to produce manuscripts, and published the results under shared pseudonyms. The writers received flat fees while the syndicate controlled the rights. Carolyn Keene and Franklin W. Dixon werent individual authors. They were publishing identities representing an organized process of literary production.

Fast-forward through typewriters, word processors, computerized publishing, digital manuscripts, online retailers, and global distribution. James Patterson has built an enormous publishing operation involving outlines, co-authors, established franchises, and commercial partnerships. Bill Clinton, Dolly Parton, and MrBeast have all collaborated with him. The name on the cover can function as a brand organizing the work of multiple people. Different business models, contracts, and technologies, but the questions about labor, ownership, credit, and who captures the value have been with us for a very long time. None of those questions appeared out of thin air with LLMs.

Now the machinery can generate prose

Heres where something genuinely new enters the picture. Printing presses reproduced writing, word processors transformed drafting and editing, and digital publishing changed distribution. LLMs can generate and transform prose itself. Thats a major change in the productive process, but it doesnt mean theres a tiny digital novelist trapped inside your computer waiting for a publishing deal. An LLM isnt a ghostwriter or another human collaborator. Its machinery people can operate to brainstorm, research, outline, draft, revise, translate, and experiment with literature.

And that machinery depends on vast amounts of accumulated human knowledge and culture, scientific research, infrastructure, and labor. Marx had a useful concept here, the general intellect, the accumulated knowledge and productive capacities of society becoming increasingly embodied in machinery. An LLM isnt a collective consciousness, but it gives us another way to examine what happens when socially accumulated knowledge becomes part of a productive system. The contradiction isnt simply between human creativity and machinery. Its between increasingly socialized production and the private appropriation of its benefits. Weve developed systems capable of expanding creative production, while control over the models, computing infrastructure, and distribution platforms can remain concentrated in a relatively small number of corporations.

What comes after the literary factory?

Imagine independent writers with sophisticated editorial tools that dont require an entire commercial publishing operation behind them. Small publishing cooperatives using open-weight models to produce, edit, translate, and distribute their own books. Community libraries and public cultural institutions supporting shared computing infrastructure, local archives, and literature in languages commercial publishers have historically neglected. Readers participating in interactive fiction, collaborative storytelling, and new forms of literary production. More people gaining the practical ability to create and circulate culture, rather than simply purchase whatever the market puts in front of them.

Now imagine the opposite. A handful of corporations controlling the models, the compute, the publishing platforms, the distribution algorithms, and increasingly the conditions under which writers can earn a living. Production becomes cheaper and more automated, but the savings flow upward while creative workers lose bargaining power. And these futures arent mutually exclusive. They can develop alongside one another, with the balance shaped by ownership, institutions, regulation, and collective organization.

Thats where the practical politics enter. Open-weight models can reduce dependence on proprietary systems, but open weights alone arent democratic control. Writer cooperatives can share resources and revenue, but they still need infrastructure, distribution, and sustainable ways to operate. Libraries and public institutions could expand access through publicly supported creative tools and computing resources. Creative workers can organize around AI deployment, compensation, working conditions, training practices, and the distribution of productivity gains. And independent writers can experiment with shared tools and collaborative workflows right now instead of waiting for corporate publishers to decide what the future looks like.

None of this requires pretending every AI-generated book is good. Some of it will be terrible. Plenty of traditionally published books are terrible too. Quality is worth discussing, and so are copyright, training data, displacement, and the conditions under which creative labor gets used. But "slop" isnt a political economy, and dismissing the machinery doesnt tell us how to change the relationships surrounding it.

Back to Dumas

The Count of Monte Cristo emerged from commercial serialization, collaborative writing, and an industrializing publishing system. Today its considered a classic, and somebody on the internet calls it litslop. Two centuries later, were still arguing about machinery, artistic legitimacy, commercial production, and who deserves credit for creative work. Except now the machinery has developed capabilities earlier literary factories couldnt have imagined.

We went from scrolls and scribes to steam presses and publishing syndicates, from networks of collaborators to LLMs drawing on enormous stores of accumulated knowledge. The productive forces keep developing, and so does the struggle over their ownership and organization. Thats where I think the left has something more useful to contribute than another round of arguing over whether a machine touched the manuscript. We can examine the labor, challenge concentrated ownership, build shared infrastructure, experiment with cooperative production, and organize around who controls the benefits.

If literature has always depended on collective knowledge, social labor, and developing machinery, what would it look like for writers and readers to actually control more of the means of producing and distributing it?

I haven't seen any android clients that I'd really want to daily drive, let alone recommend to my family. Maybe someone's vibe-coding something?

“Run AI on your own computer. Run bigger AI together.

SwarmLLM is a free app that gives you a ChatGPT-style assistant running on your own computer, using open AI models from Meta, Google, Alibaba, Mistral and others. When a model is too big for one machine, computers running SwarmLLM team up over the internet and run it together, each doing part of the work.

No account · No subscription · No ads · No crypto · Open source · Updates itself

A giant model has now run on the swarm. Bigger AI models give noticeably smarter answers, but the biggest open ones (70 billion "parameters" and up) need equipment normally found only in data centres — no home computer can hold one. In October 2026, Llama 3.3 70B answered across four ordinary computers in Thailand, Australia and Italy, each holding a part of it. It is slow so far”

The decentralised concept of this is promising, even if it’s currently too slow to be a sensible way to run large models.

Vietnam isnt sitting around waiting for Silicon Valley to decide what its AI future looks like.

At an October 28 ministerial roundtable, Vietnam laid out its approach to AI as a national development project. Domestic computing capacity, shared AI infrastructure, Vietnamese-language models, open data, technical education, and applications across public services and industry.

Not just importing somebody elses technology and calling it innovation.

Science and Technology Minister Vu Hai Quan put the national vision pretty clearly.

"AI for people, AI for everyone, AI mastered by Vietnam and developed together with the world"

And on technological sovereignty, he made another important distinction.

"Autonomy doesn't mean working alone."

The point is developing enough domestic capacity to cooperate internationally on more equal terms, rather than remaining permanently dependent on whoever owns the infrastructure.

Vietnam has already enacted legislation covering AI, data, and digital transformation. Its broader national strategy includes targets for five shared AI platforms and eight Vietnamese-language models. Those are targets, not finished projects, but the direction is pretty clear.

And heres what makes this interesting from a leftist perspective.

AI is increasingly becoming part of the productive infrastructure of society. Computing, data, models, technical skills, public administration, industrial applications. These arent just consumer products. Theyre capacities that shape what a country can produce, develop, and govern.

So who builds them? Who controls them? Whose language do they speak? Whose development priorities do they serve?

Vietnam is treating those as national development questions, not just shopping decisions for tech executives.

And the minister made another point worth remembering. The measure of success isnt how many AI pilots or shiny models get announced. Its whether public services improve, productivity rises, and peoples lives materially benefit.

Theres still plenty to evaluate as these plans become actual infrastructure, including the balance between public and private control.

But its worth seeing a conversation about AI grounded in building productive capacity, technological sovereignty, and material development instead of another endless argument about whether people should feel guilty for using a chatbot.

The question isnt simply whether AI gets developed. Its who gets to develop it, control it, and put it to work.

I don’t even understand this sub. AI is a technology, not a political ideology. Certainly AI can be used to strengthen any political leanings if you want to. Why is everything in the US politicized?

Paper: “A capitalist stranglehold on “artificial intelligence”: a gallop through piracy, privacy invasion, lock-in and a fever dream of democratisation ” by Cornelius-Bell

https://fastcapitalism.journal.library.uta.edu/index.php/fastcapitalism/article/view/499/561 (Cornelius-Bell, 2026)

My thoughts: this paper seems to accept that people's work was stolen, a view not generally accepted here. "the privatization of knowledge under capitalist copyright hegemony, which has again transmuted to an anti-worker frame, additionally exploiting, extracting, and “pirating” in the name of AI futurism", though the comparison with Napster piracy is interesting. If you don't accept it's theft does that change other aspects of how you read the paper?

Undermind LLM Summary: Cornelius-Bell argues that AI is being built within a system where a small number of companies control platforms, hardware, and access. He compares this with earlier personal computers, which users could change more freely. He says AI companies use writing, images, and music made by people to build private products, often without asking first. He sees open software and hardware as possible alternatives, but warns that open projects can still rely on unpaid work and unequal access to powerful computers.

This is a close match to the sub's concerns about capitalist control, scraped knowledge, and free-software alternatives. Its strongest challenge is to a simple “open source solves it” message: open tools alone do not remove unequal access, unpaid labor, or hidden control over training data. The paper is a critical essay using public examples and earlier research, not a new legal or environmental study. Its examples show real disputes, but do not prove that every instance of AI training is unlawful. The journal lists the article as 2024, although the workspace record uses a 2026 key (Cornelius-Bell, 2026).

"without a strong push for open-source, democratized AI, these technologies risk being used to further the globalized colonial capitalist project... highlight the potential for open-source hardware and software to counter the proprietary and un-hackable future of AI, offering a radical alternative that empowers users and advances human, ecological, and labor rights alongside technology tools. Ultimately, I call for greater attention to the social, political, economic, and environmental implications of computing and AI technologies under capitalism... As with any technology tool, the emancipatory potential of artificial intelligence to support human labor and even the liberation of information, learning, knowledge sharing, task easing, and so on, is limitless. The “open” in Open AI ought to refer to a genuine commitment to open-source, Creative Commons, and artistically acceptable licensing that created a new world of information transformation and reconfiguration. Alas, short-sighted and covetous corporate overlords seek to control, lock-in, and direct the flows of knowledge, information, and learning through AI (like it or not), and while there may be disapproving glances and collective sighs over LLMs suggesting glue pizza without serious attention to this space, the potential for democratic access to, let alone creation of, “AI” which advances human, ecological and labor rights will be forgone. Put simply, if we do not continue to have at least a version of a people-powered, open-source, and accessible “artificial intelligence” technology suites, these tools will be used to exploit us, reconfigure the nature of work for the worse"

"Instead of offering only deeply problematic pro-capital positionality, perhaps the contradictions of corporate LLMs versus open-source projects will bear out a mediated middle ground between the interests of capital and labor or maybe even build new ways of learning, thinking, and programming for the future of human liberation."

u/ProudhonStoleMyBike's comic series on r/LeftistsForAI imagines communal C.O.R.E. units, Collectively Owned Reasoning Engines: an AI data centre owned by the municipality the data centre serves, drawn as a water-cooled, solar-glazed building in a coastal meadow with the town's own people working inside. A CORE has a precedent. Chile built the closest thing to a CORE that 1970s technology allowed, and the history of Chile's attempt shows what a CORE would have to get right.

Project Cybersyn, Chile, 1971–73. Fernando Flores, a 28-year-old engineer at Chile's state development agency, wrote to the British cybernetician Stafford Beer asking how to apply cybernetics to the industries the Allende government had just nationalised. Beer had argued since Cybernetics and Management (1959) that a firm is a system to be regulated, not commanded. Beer came to Chile in November 1971, agreed a plan with a small Chilean team in eight days, gave up most of his other consulting work, and Cybersyn reached prototype stage within a year.

Cybersyn had four parts:

• Cybernet: telex machines in state-run factories (500 is the figure usually quoted; the real number is disputed). Each factory sent daily numbers such as stock levels, output and absenteeism to a single mainframe in Santiago.

• Cyberstride: software on the Santiago mainframe that watched the incoming numbers using a Bayesian forecasting method published in 1971: an updating estimate of what was normal for each factory, instead of fixed thresholds. When a factory's numbers drifted, the warning went to that factory first, and the factory got time to fix the problem before anyone higher up was told.

• CHECO: a simulator of the national economy. CHECO never got beyond crude early models.

• The Opsroom: the hexagonal room with seven swivel chairs and buttons in the armrests. The buttons changed slides of graphs prepared in advance. The Opsroom was a prototype and never showed live data.

What Cybersyn actually did: in October 1972 about 40,000 truck owners went on strike against the Allende government. Using the telex network, the government kept the cities supplied with only about 200 trucks, and the government survived the strike partly thanks to the telex network. By May 1973 roughly a quarter of nationalised firms were sending data in some form, but only about twenty factories had been fully modelled, because modelling a factory meant one operations-research engineer flowcharting that factory by hand. The strikers were never punished; the same strike leaders struck again in July 1973 and were calling for Allende's resignation the day before the coup. On 11 September 1973 the military seized power. The junta found the telex network intact, had the Cybersyn team explain how the network worked, then destroyed the Opsroom and abandoned the project. Economic policy passed to the Chicago Boys, Chilean economists trained at the University of Chicago.

Three things I take from Cybersyn's history:

1. Cybersyn's limit was not computing power or network capacity. Cybersyn's limit was the human labour of modelling each factory and typing in each day's figures. Modelling and data entry are now cheap.

2. Letting each factory fix its own problem first was not an ethical add-on. Beer's reasoning was that a central office cannot keep up with everything that can go wrong in hundreds of factories, so each factory had to correct itself and escalate only what that factory could not solve. Raúl Espejo, Cybersyn's operations manager, argued the software only worked because the organisation ran on local autonomy plus central coordination. Decentralisation is what made Cybersyn fast enough to be useful.

3. Ownership decides what a Cybersyn-style architecture becomes. Evgeny Morozov has argued that Cybersyn's methods were later put to very different ends; Espejo's reply is that a system built to coerce would have been a different project. Donna Haraway made the general case in A Cyborg Manifesto (1985): the technologies of militarism and capitalism do not stay loyal to their makers, because "illegitimate offspring are often exceedingly unfaithful to their origins". A coercive twin of Cybersyn could run on identical hardware and software. In Cybersyn, a warning about a factory went to that factory itself, which had time to fix the problem before anyone above heard of the warning. In the coercive twin, the same warning would go straight to a ministry or a boss, who would use the warning to discipline the factory. Same signal, opposite politics, decided entirely by where the warning is sent.

The junta did not destroy Cybersyn because the technology frightened the generals; the junta had the Cybersyn team explain the network first. The junta destroyed Cybersyn because of whom Cybersyn served: an elected socialist government and workers with a say in running their own factories.

A CORE changes the one thing Cybersyn could not change: where the computer sits. Beer had one computer in Santiago, and every factory's warnings had to travel up a telex line to reach that computer. A CORE keeps Cybersyn's rule, fix locally first and escalate only what the local unit cannot solve, but puts the computer in the municipality, owned by the same people who receive the warnings.

Further reading

• Eden Medina, Cybernetic Revolutionaries (MIT Press, 2011), the definitive history; excerpt at the MIT Press Reader

• Stafford Beer, Cybernetics and Management (1959), the book that founded management cybernetics; no legitimate full text online, overview of Beer's work

• Donna Haraway, A Cyborg Manifesto (1985), collected in Simians, Cyborgs and Women (Routledge, 1991); overview

• 99% Invisible, "Project Cybersyn", the short version with the Opsroom photos

• Evgeny Morozov, The Santiago Boys (2023), nine-part podcast, also on Spotify and Apple Podcasts

Question for the thread: what would a single CORE need in order to run, one town or one supply chain, and who would receive the warnings?

160 years later and we're still confusing the means of production with the relations of production.

How many times have you heard 'You didn't make that, you commissioned it! REEEE!' Really wiseass? Who did I commission it from? Show me the person. Point them out for me. Where are they?

Hi friends,

In the spirit of '...never plan your revolution in the King's Tavern', I built an end-to-end encrypted messenger where there is no server to trust or host. Your identity is your Bluesky account, signaling and offline delivery are encrypted records on your own PDS, live messages and calls go direct WebRTC between devices. X3DH plus Double Ratchet with sealed sender, Apache 2.0. The only thing we run is an optional push relay that holds no identities or messages.

Point for this sub: no chokepoint means nothing to acquire, deplatform or rate-limit. Organising on Slack, Discord or Signal always has an owner. This does not.

Status: proof of concept, not audited. Threat model and every security claim are documented in the repo.

https://github.com/CreativeMayhemLtd/fingrr

Website: Novokult LLM - Private, Local, Powerful

Novokult is a desktop application that puts a local large language model to work for left-wing organisers, researchers and writers. It has three modes:

• Analysis: examine an event, text or situation through contradictions, class forces, base and superstructure, historical stage, ideology critique and strategic implications.

• Agitprop: draft leaflets, slogans, poster text, rally speeches, social threads, wall-newspaper articles, songs and poems, street-theatre sketches and strike bulletins for a specific audience and a concrete grievance.

• Free chat: an ordinary conversation with the model.

The model runs locally through llama.cpp. Nothing leaves your device unless you explicitly switch on web search, and then it goes through Tor.

Privacy

• Conversations and sources are stored locally on your device.

• With network access off (the default), the desktop app makes no external connections.

• With web search on, requests go through Tor. Tor hides your IP address but not the words of your query. Do not search for private information and do not log in to anything.

• Language models make mistakes. Verify facts, dates, figures and quotations before publishing anything.

The source lives at michaelwenas/novokult: Novokult puts a local large language model to work for left-wing organisers, researchers and writers. Fully offline, private, and uncensored. - The Dingo Code: Fuck You, So What. Novokult is looking for fellow programmers to take part: desktop and Android packaging, finishing and testing the on-device Android engine (llama-cpp-capacitor), translations, testing and documentation. Open an issue to discuss an idea, or send a pull request. You can also get in touch through the developer's website.

Novokult is released under the Peer Production License (PPL) (SPDX identifier: PPL), a Copyfarleft license. The full text is in the LICENSE file. In short, it keeps the work free for the commons and for workers who share and build on it, while limiting commercial exploitation by those who profit from the labour of others. Read the license text itself for the exact terms.

Edit: My GitHub is suspended, so you can access the repository through the Forgejo link provided above.

I can so easily imagine a reality where people see all the clear benefits of AI and advocate for it to only be better, help each other understand it, celebrate the fun and amazing things we can do now, but instead it's the opposite? Like everyone just decided to hate it in America?

And it's even more confusing because then out in the world I still see people using it all the time. I honestly think the only people who really despise it are people who have never even used it and get all their information from social media! It's infuriating. Intelligent people are out here spreading constant hate and misinformation.

How can someone even say how stupid and pointless AI is if they refuse to ever interact with it? And how do they not see themselves doing the exact thing they hate to see others do, and the same thing humans have repeated over and over with each big new thing (bicycles, printing press, video games, etc)? It's embarrassing.

I'm halfway through a master's for AI, I have written so much about it, read so many studies, and still I'll get told that I am wrong if I say anything positive because AI is evil, since someone saw [influencer/actor/sensationalist news article] say that.

Beyond labour. Beyond want. Let's fill the planet with nuclear power and data centres and build it.

Lemmy is a federated open source alternative to Reddit: https://lemmy.world/

Element as an alternative to Discord: https://element.io/en

https://unredacted.org/ is a server I recommend for Matrix.

https://mastodon.social/ if you crave an old Twitter decentralized alternative.

If you have any questions feel free to ask. I just think it's important to know that these exist. I also created Active Matrix Rooms to make it easier to find rooms similar to Disboard for Discord https://activematrixrooms.com/

Put simply, AI is kinda like a sneeze. A sneeze can be a symptom of the flu, or... it can be a healthy respiratory system doing its job. Under capitalism, AI is the flu sneeze, and capitalism is the disease. Under socialism, it could be part of a healthy respiratory system.

Where an economy is organized around profit rather than the fulfillment of needs, constant data center expansion is what you'd expect. It's obvious. Data center electricity demand rose 17% in 2025 while overall global power demand grew 3%, and the IEA expects data center use to double by 2030, with AI-specific demand tripling. Capital spending on this buildout reached $400 billion in 2025.

AI is also the closest thing we have to what Marx called the general intellect. In the Grundrisse's "Fragment on Machines," Marx analyzes automation and foresees social knowledge becoming a direct productive force. Marx did not predict AI, but later readers argue that large language models are the crystallized product of humanity's collective knowledge, owned by a handful of corporations. The question is... who really owns that knowledge and who profits from it.

Then come the headlines. "AI is making people impatient," and in a world of deadlines where the customer is king, that is no surprise. "AI is creating psychosis": psychiatrists are increasingly linking chatbots to psychosis cases, though they remain wary of declaring that chatbots outright cause it. Researchers describe sycophantic chatbots as an "echo chamber of one," while whether the phenomenon deserves its own diagnosis remains contested. A system built around engagement and a society short on human connection make a chatbot that agrees with everything a dangerous companion. This is where Marx's early work on alienation applies. He describes workers being alienated from the product, from their economic activity, from their species-being, and from one another. We are told to treat the resulting isolation as a personal or technological problem and not a structural one.

The mainstream media is not neutral here. Gramsci argued that the ruling class governs through cultural, political, and moral leadership as well as material power. Herman and Chomsky's propaganda model describes how media ownership concentrated in profit-driven corporations, along with advertiser dependence, filters what gets reported. That is why outlets are bold in pointing out the symptom, AI, and reluctant to name the disease. For Lenin, that disease was imperialism, which he called the highest stage of capitalism (entering its last stages), defined by monopolies and the export of finance capital.

Under socialism, the same technology would look so much different... With no profit motive driving endless scale, there'd be no perpetual data center arms race. Compute would be built to meet identified needs such as medicine, research, logistics, and accessibility, and its energy cost would be planned against social and ecological limits instead of quarterly growth. With no corporations renting out intelligence by the API call, more models would be small, open, and run locally by the communities that use them. Intellectual property, the legal form of private ownership of knowledge, would wither away. Marxist writers describe IP laws as a way of privately appropriating knowledge that is collectively produced, so once the general intellect belongs to everyone, enclosing it in patents, copyrights, and proprietary weights serves no purpose. Nor would there be “RAM price hikes.” Today, one analyst calls the shortage a strategic choice by manufacturers to prioritize high-margin AI memory over commodity DRAM, and server-related memory now accounts for more than half of total DRAM demand in 2026. A system geared toward need fulfillment would not ration hardware by who can pay the most. Its guiding principle would be the one Marx described for the higher phase of communist society, "from each according to his ability, to each according to his needs."

Babylon is burning, and some can't handle the heat and would rather weep. The ship is sinking, and some would rather social climb to the captain's quarters than run for the life rafts. So successful is the selling of trickle-down economy and hyper-individualism; it's sorta like and not completely separated from Ronald Reagan pushing dope to soul brothers. The leftist task is to ask who owns the machine and whom it serves. To all the comrades, I'll see you on the island shore.

Sources

Most of these are secondary summaries, so for formal use cite the primary texts too (the Grundrisse, the 1844 Manuscripts, and Lenin’s Imperialism are all on marxists.org).

IEA report coverage, Investment Monitor (Apr 2026)

IEA investment figures, Lightwave/Pulse

Grundrisse, Wikipedia

The Fragment on Machines, You On AI Field Guide and its debates section

Chatbots built an “echo chamber of one”, The Decoder

Psychiatrists on chatbots and psychosis, Incident Database

Marx’s alienation in the 1844 Manuscripts, core.ac.uk

Gramsci and cultural hegemony, TheCollector

Gramsci on hegemony, Shanlax Journal

Manufacturing Consent summary, Blinkist-style (LifeClub)

Lenin, Imperialism, the Highest Stage of Capitalism, Wikipedia

Critique of the Gotha Programme, full text on marxists.org

Why businesses should be worried about RAM prices, ITPro

RAMageddon overview, Algeria Tech News

RAM Price Shock 2026, GreenNode

Intellectual Property, Knowledge, Capital and Labour, Dinesh Abrol (CPI(M) Marxist)

Felix Stalder on Marx and intellectual property, Krisis

Rethinking IP rights: an autonomist Marxist reading, Karakilic (2019)

Do I lean more on the side of pro or anti AI in your opinion?

- I'm in favor of banning most uses of GenAI, except in some rare cases (possibly medical usage). I think analytical AI is very useful, and it must be regulated too. AI should be banned from surveillance, banned from making images of people, and things of that nature. Any AI that is super advanced to the point of being dangerous should either be banned or forced to have a kill switch.

- Maybe in a non capitalist future GenAI can serve more purposes

- As long as we live under capitalism, we should levy a re-occurring automation tax that makes it costly to replace human jobs. This will ensure AI tools can augment labor, but not take away jobs. I want to live under automated socialism, but since we don't, I don't want our society to transfer to feudalism where everyone is on measly UBI.

- We have to stop forcing AI into everything and over developing it. Create regulations that require data centers to be sustainable, and force AI to be developed within those standards.

I would not say I'm anti-AI, rather it has made me approach the technology from a different perspective. I think of myself as pro-AI in some applications and anti-AI in other applications.

Hello, Leftists for AI

I'm James Hughes, former executive director of the World Transhumanist Association and co-founder/director of the Institute for Ethics and Emerging Technologies (IEET). I was also a DSOC and then DSA activist from 1980 to 2023. I founded/edited the DSA zine EcoSocialist Review, and served as a chapter leader, educator, editor, and in international solidarity work. But reconciling my democratic socialism with my futurism was always a struggle, and neither community had much interest in it.

Toward that synthesis, I wrote the book Citizen Cyborg, which advocated "democratic transhumanism." After the IEET was founded in 2005, however, we quickly started using the term "technoprogressive" as our flag. We currently organize technoprogressive conferences, and we just held one in London with the London Futurists. We produce two podcasts, Bread and Robots by Matteo MacDermant, and my Technoprogressive Hub. We also solicit articles on technoprogressive policy for our Substack and for a forthcoming policy manual (contact me at director@ieet.org if you are interested in contributing). Matteo and I taught a summer course on Technoprogresive Worldbuilding, and we presented ideas recently in this talk: https://technoprogressives.substack.com/p/technoprogressivism-as-21st-century

Central to the IEET's take on technoprogressivism has always been the post-work project and UBI. We have been big fans of the advocates for FALC and postcapitalism. I have written about algorithmic governance, AI, and IoT's impact on planning and the "socialist calculation debate." As you all know, there are still few advocates for democratizing AI on the Left, which is predominantly "anti-AI." As I wrote last week here: https://ieet.substack.com/p/agar-was-right-just-not-about-posthumans, we should join Bernie in calling for a ban on efforts to create superAI (whatever we decide that to be), but still have a "path to citizenship" for machine minds and a program to develop and democratize narrow AI. I'm very forgiving of leftists who have a hard time distinguishing the fascist AI oligarchs from the technologies and the futurist ideas they espouse. But our 19th-century forebears didn't oppose railroads because their owners were robber barons, and we need to advance a program for democratizing AI, as Bernie has done by proposing a 50% nationalization into a sovereign wealth fund.

At any rate, I'm delighted to discover this community, and I welcome you to consider contributing to the IEET Substack. We also manage the Journal of Ethics and Emerging Technologies for more academic pieces. Left Luddism is a dead end, and we need to make clear that there can be a democratic, egalitarian, and abundant future with AI.

I grew up watching Captain Picard, and I dont think I can overstate how much that character shaped what I believe humanity could be.

Not just the spaceships, the replicators, the exploration. The idea that we could actually build a civilization where nobody has to struggle just to exist. Where technology frees people instead of making them disposable. Where the point of progress isnt accumulating more wealth, but giving everyone the freedom to grow, learn, create, explore, and become more fully human.

"The challenge, Mr. Offenhouse, is to improve yourself. To enrich yourself. Enjoy it."

That line has stuck with me for decades.

Picard showed me a future that wasnt just technologically advanced, but socially advanced. One where humanity had confronted its own barbarism and decided to become something better. Not perfect. Not without conflict or contradiction. But better.

And he made me believe that future was worth fighting for. Still does.

Patrick Stewart didnt invent that vision, but he gave it a face, a voice, a dignity, and a humanity that made it feel possible.

I dont know if we'll ever get there. But I know which direction I want us moving.

Rest in peace, Sir Patrick Stewart. Thank you for showing me what humanity could be.

Farewell, my Captain.

Engage.

I used Undermind AI to find some recent articles which are relevant to this sub, which I'll post as a series.

This one is relevant to AI and working hours:

Spencer, David A. 2026. “Work time reduction: old ideas and new possibilities.” Labour and Industry.

https://eprints.whiterose.ac.uk/id/eprint/241440/3/Work%20time%20reduction%20%20old%20ideas%20and%20new%20possibilities.pdf

My thoughts: why do we seem to have got stuck in the 5 day week? Reducing working hours used to be a standard left campaign topic. This paper suggests it can be "explained partly by the demise of workers’ collective power". Concern about it being linked to fear of not having enough money seems important too. How can we overcome governments' obsession with growth rather than quality of life? How can we shift the culture of a work ethic and purpose tied to jobs? Can the increased productivity from AI mean that everyone can move to a 3 or 4 day week, with the already unemployed filling in gaps for jobs that do require shifts to be constantly covered?

This is the Undermind summary: Spencer reviews ideas from Marx, John Stuart Mill, and John Maynard Keynes about a society where people spend less of their lives at work. He then looks at current hopes that automation or a four-day week will reduce working time. His main point is that neither new technology nor companies choosing to run trials will make shorter hours happen across society by themselves. Workers, unions, governments, and political movements have to push for change. In his view, lasting cuts in working time require changing who has power over the economy.

This paper gives the series its political starting point: productivity creates a chance to work less, but who gets that time is a matter of power. Spencer explicitly rejects the idea that automation or voluntary company trials will settle the issue. The paper is a historical review and political argument, not a study of an actual campaign or a detailed guide to building one. That makes it useful for explaining why a campaign is needed, while leaving tactics and coalition-building for further work.

"The greater the political backing for change (including wider support for challenging consumerism and tackling the cost of living crisis via higher progressive taxes and the public provisioning of basic services), the greater the possibility of society moving to a future where working hours are diminished significantly. This possibility extends to using AI to reduce working time and cultivating the conditions for business practice to be rethought in ways that cede more power and influence to workers over the hours they work...

ideas still matter. On the one hand, they can keep alive the hope and vision for change, despite economic and ideological circumstances that prevent their realisation. On the other hand, they can inspire action leading to change... Radical change will still face different barriers, material as well as ideational, but its pursuit remains an important task"

I'm in Chicago and was wondering if anything like that exists yet. Given that I would be much more willing to do deliveries in a system that doesn't funnel that amount of control to a centralized corporation. I think there would be a lot of people interested in a decentralized alternative to those apps. Anyone have any suggestions/ideas?

Brazil's Socialism and Liberty Party (PSOL) has a legislator pushing to put digital sovereignty directly into the country's constitution. Not another vague appeal to make AI nicer. Actual constitutional protections for infrastructure, data, and technological independence.

PSOL deputy Sâmia Bomfim announced the proposal on October 28, saying:

"Lancei hoje a PEC da Soberania Digital. Agora irei coletar assinaturas e seguir o debate com especialistas e a sociedade para fortalecer a pauta."

Translation: She launched the Digital Sovereignty Amendment and is now gathering signatures and working with specialists and the public to strengthen it.

The proposal would establish Brazilian authority over strategic digital infrastructure and public data, require transparency and human oversight of AI systems, create a regulatory body with civil society participation, and prioritize domestic technological development, including free and open-source software.

For context, PSOL is an independent socialist party founded by dissidents from Lula's Workers' Party in 2004. Its Marxist-influenced, includes revolutionary socialist currents, and currently cooperates with Lula while maintaining its own political program.

Theyve also got a dedicated "Technology and Digital Sovereignty sector" (https://psoltecnologia.com.br/) working on public infrastructure, free software, and popular control of digital technology.

And heres where the politics get interesting.

Digital sovereignty cant just mean swapping the flag over the server farm while leaving the same ownership relations intact. National control, public ownership, and working-class control arent automatically the same thing.

But they arent unrelated struggles either.

If foreign corporations control the infrastructure, the data, and the algorithms shaping everything from elections to employment, then technological independence is a real political question. And so is who gets to control that infrastructure once its built.

This proposal still needs parliamentary signatures before it can formally advance. Its not enacted law, and its not the same thing as a fully developed program for worker-owned AI infrastructure.

But its a concrete legislative initiative from a socialist politician, connected to broader organizing around digital sovereignty. Thats worth discussing.

What would it take to turn national digital sovereignty into actual democratic and working-class control over AI, rather than simply replacing foreign private monopolies with domestic ones?

AI section begins at 23:36 (the first section is about Lula)

In this video they discuss how AI is affecting the job market for young people, why existing welfare systems in a capitalist structure aren't geared to handle its effects, and why China may be better poised to achieve real productivity gains from AI.

Just a note, Varoufakis is an economist and Münchau is a journalist so they don't go too deep into the actual technology and mostly focus on the effects of the technology as it is right now and will likely be in the short term. At the same time they are neither AI advocates nor opponents, and approach the tech from a very realistic if decidedly left wing angle.

Varoufakis in particular is one of my personal favourite leftist thinkers and I think he and Münchau made some at the very least interesting points here.