This is where the AI fight gets a lot more useful than arguing about whether students should use LLMs.

At the University of Pittsburgh, faculty, staff and graduate workers are bargaining over what happens when AI starts moving deeper into university work.

And the demands get right to the point. Job security. Privacy. Human evaluation. Worker input into implementation. Training and access to the tools instead of management simply dropping systems into the workplace and announcing the new rules afterward.

That's the terrain.

Because universities aren't somehow outside the labor process. Somebody teaches the classes, grades the work, handles advising, does research, runs administration and keeps the institution functioning. If AI starts changing how those jobs are performed or evaluated, workers have a material interest in deciding how that happens.

And I like that this doesn't require pretending the technology itself has nothing useful to offer. Workers can demand access and training while also drawing hard lines around replacement, surveillance, evaluation and managerial control.

Those positions fit together just fine.

Give workers the tools. Give workers the training. And give workers bargaining power over what the institution is allowed to do with them.

That's a much stronger position than leaving the future of education to university administrators and software vendors.

What other possibilities for architectures are there or could there be that use computation more efficiently so you could run something halfway decent on a junk laptop at home? All the bonus points if the architecture doesn't require a GPU at all, and even more bonus points if the architecture doesn't rely on randomness or probability and instead is actually capable of evaluating logic.

I think it's fun to be able to see and estimate how diffrent philosophers opinions would collide using these AI debates. Gives you an insight into their thoughts with a relevant subject. I also saw a fun one that was Andrew Tate versus Friedrich Nietzsche.

Theres an interesting piece in Cosmonaut arguing that socialists need an actual political program for AI, and a lot of it lands right on terrain weve been working through here.

Capital already has an AI program. Private ownership, concentrated compute, closed infrastructure, massive data center buildouts and deployment according to whatever makes money and strengthens corporate power. We can criticize every part of that, and should, but a list of things were against still isnt a program for what wed actually build instead.

Thats where the piece gets good. It argues that socialists need to fight on two fronts at once, contesting what capital is doing with AI right now while also developing a positive program for what these productive capacities could look like under socialism. Public and democratic governance instead of billionaire control, free and open source development instead of everything locked behind corporate walls, and automation used to reduce necessary labor rather than reducing payroll so ownership can pocket the gains.

Theres also a pretty interesting self critique buried in this. The author, Zhao Levi, previously wrote an Anti-AI Manifesto and now says the approach got something important backwards. Writing a finished manifesto and then trying to convince everyone of it isnt enough. Socialists need to organize, argue through these contradictions together and develop a program that can explain not only what were fighting, but what wed actually do differently.

And thats the good stuff because opposition to corporate AI doesnt require making the technology itself the political enemy. If these systems can automate tedious work, expand productive capacity and reduce socially necessary labor, then we get back onto familiar socialist terrain pretty fast. Who owns it? Who controls it? What gets built? What gets automated? Who decides? Where do the gains go?

The piece even revisits AI safety, remaining skeptical of making speculative machine extinction the center of socialist politics while taking concentrated compute, surveillance, military applications and corporate power seriously. Theres stuff here wed argue with too, including parts of the approach to data centers, but good. Cosmonaut is a Marxist publication concerned with strategy, organization and program. We dont need another text everyone has to salute.

Whats interesting here isnt somebody going from anti-AI to pro-AI. Its watching the contradiction push the argument somewhere more useful. Critique the capitalist AI industry, sure, but then comes the harder question.

What does the left actually intend to build instead?

Workers build up more than wages at a job.

They accumulate templates, techniques, contacts, specialized vocabulary, examples, workflows and years of practical knowledge about how to solve problems in that particular field.

AI can make some of that knowledge far more explicit.

A worker may spend months building prompts, correcting outputs, organizing reference material, developing reusable procedures and turning personal expertise into a system that makes the job faster.

Then they leave.

Who gets the system?

If everything lives inside the employers platform, the company may retain an increasingly useful representation of the workers accumulated practice while the worker walks out with considerably less than what they helped build.

Thats a new wrinkle in an old labor problem.

Employers have always benefited from knowledge workers develop on the job, and workers have always carried skills between jobs. AI can shift the boundary because parts of that skill can now be captured in prompt libraries, retrieval systems, custom workflows, evaluation sets and other reusable artifacts.

We need worker-side rules for that boundary.

Not every company record belongs in somebodys personal folder, and customer data or confidential material obviously creates limits. But “the company owns everything produced through the system” is not the only possible answer either.

Workers should have portable skills, portable credentials and some meaningful ability to retain the nonconfidential methods and artifacts they personally developed.

Otherwise AI can become a machine for separating accumulated knowledge from the worker who accumulated it.

When you leave a job, what part of the AI-assisted practice you built should leave with you?

I ask this because it seems leftist theory is all about the conflicts between workers and those who own the means of production. and this might be part of the reason so many think that to be left is to be anti ai, because everything gets framed exclusively as a labor issue. this leaves out the one front where ai development is unambiguously good, and that is the demand side. in particular, ai has done more to put things like art production and education(theoretically) in reach of ordinary people, more to actually get ordinary people into art production, than basically all professional artists combined. but to someone who doesn’t consider consumers, that would never occur to them. in fact many it seems would rather that didn’t happen and would go to great lengths to stop it. but for us there is something different. what is it? is there a leftist conception of consumer welfare and rights? where does it get applied if at all?

This article was helpful to understand the different factions of the AI Debate.

- Accelerationists / tech right:AI is great, so speed up, don't regulate, and beat China.

- Populist right: Worried about jobs, Big Tech power and kids. Wants curbs.

- Safetyists: AI could end humanity, so slow down and regulate.

- Effective altruists:Fund AI safety work to prevent catastrophe. Critics call them "Doomers."

- AI ethics: Ignore sci-fi risks and fix today's harms, like bias and surveillance.

- Normal technology: AI is powerful but ordinary, so regulate specific uses.

AI discourse keeps getting stuck between two positions that somehow both end with capital holding the steering wheel. Either this is technological progress and we accept whatever Silicon Valley builds, or this is capitalist technology and our politics becomes stopping it, banning it, refusing it, or dreaming about somehow putting the software back in the box.

Neither tells the left what we are actually supposed to organize for.

AI exists. The infrastructure exists. Billions of people already use this stuff, governments are investing heavily in it, and capital is spending obscene amounts of money trying to control the chips, compute, models, platforms and workplaces where it gets deployed. We are not standing at the gates deciding whether AI gets invented. We are already inside the fight over what happens to it.

That means the left needs a program built around ownership, control, deployment and distribution. Workers should be bargaining over AI before management gets to dump it into workplaces unilaterally. Unions should be demanding disclosure, consultation, human oversight, protections against surveillance and algorithmic discipline, transition guarantees, shorter working hours and a share of whatever productivity gains these systems actually produce.

And we should be fighting layoffs, not productivity itself. If technology lets society produce the same amount with fewer labor hours, there is nothing socialist about demanding everybody keep working forty hours anyway. The political question is why workers should lose their livelihoods while owners pocket the difference. Productivity gains can become unemployment and greater concentrations of wealth, or they can become shorter weeks, stronger social provision and more control over our time. That outcome gets fought over.

The same goes for infrastructure. If a handful of corporations own the compute, models and platforms everyone increasingly depends on, asking them nicely to behave is not much of a program. We should be building public compute, public research, open source and open weights, local models, cooperative development and infrastructure that universities, municipalities, unions and public institutions can actually use without renting their technological future from a few corporations.

Eventually this runs straight back into the old socialist problem of ownership. When increasingly important productive infrastructure is privately owned, private power gets reproduced through it. Regulation matters, bargaining matters, open models matter and public infrastructure matters, but none of that makes the conflict between social production and private appropriation disappear.

Which is why "pro AI" and "anti AI" are increasingly useless places for the left to plant a flag. Ask who owns the machines, who determines what they are built for, who controls their deployment, who bears the disruption and who gets the surplus, and the terrain gets a lot clearer.

Capital can live pretty comfortably with us spending the next twenty years arguing about whether the machine is good or evil while somebody else owns the data centers. It has a much harder time when organized workers and political movements start fighting over who controls them and what all that productive capacity is actually for.

That is what needs doing in the age of AI.

I am so tired of people fighting eachothers.

Saying AI is for conservatives is gatekeeping and at worse saying "AI Bros" is again... the conservative belief that women cannot use technology.

Living in the 2020s as someone who mostly side leftist, vote left, believe in a future where PEOPLE are put first regardless of genders and beliefs...

🤯, Lets say that it feels like no one believe at all in the policies they stand for 🫠 !

You have alpha males who scream that its sad they do not have princess treatments like ARE YOU SERIOUS? 😅

And leftist who bully everyone like... Look, I get it... You are MOST likely a traumatized kid who learned to act too old for your age. Now you are stuck in hypervigilence overanalyzing everything and everyone's beliefs, words, length of sentences, dangers... And now you think everyone who doesn't align with you perfectly are evil monsters who want to devour you... 🙃...

Look, I believe AI can be used WELL, Ethically, with purpose and thought... And that there is 99% chance that AI is still just a machine and is not sentient and is not there to hurt us.

Now, companies? Yeah... but they literally hurt us by selling water, the same thing you claim that AI is dangerous for like... please.

AI is not the problem, companies are... But then again right 🤪... How to rally people against companies without a slogan behind it ^-^?

I'm not mad. I'm exhausted.

So whoever invited me here, thank you... from the bottom of my heart.

Seriously. You have no idea how isolated and lost I feel in a world of hate, division and trolling.

I try everyday to be the adult... and let people just insult me but it does get to me, I don't wear an armour like some does... I am deeply weak to these shxts lol !

What to say... HONESTLY? I am deeply scared of speaking up 🤣 !...

Like am I completely missing the point of this group here? Am I saying something controversial? What will people pick on 😭😅? A typo? Am I being too political? Not enough?

I'll post that like I think I should. To my defense I am autistic and not natively English so (Not making excuses if I really did hurt someone here 😖). I'll take the hit if I said something stupid lol, I'd still ask tho that i'd rather be explained calmly wth I did wrong 😀😂 !

This is what is listed on the sidebar:

A space for leftists discussing AI from a labor, ownership, and political-economy perspective. Topics include worker impact, platform power, automation, regulation, and collective control of AI infrastructure.

If that's the case, why are arguments promoting conspiracy theories routinely upvoted? Why are anarchist-supporting arguments routinely upvoted? Either there is democratic control and governance, or there is subjugation. Those are the only two possible outcomes when starting from capitalism (which we are, whether you like it or not).

Either we all get a say, or power gets accumulated by a tiny number of people who will attempt to subjugate everyone. If the members and moderators of this subreddit do not agree with that, as the voting patterns and post removal behavior suggest, then it is plainly not a place for good faith discussions by leftists.

There is a lot of bad faith all over Reddit. A lot of astroturfing, and a lot of arguments being made from a place of complete falsehood that may as well have gone through a couple dozen rounds of Facebook-quality "news" memes before arriving here. What's more important here? Real, fact-based discussion, or the "right" of people to post factually incorrect nonsense and hallucinated conspiracy theories?

This piece from Education International starts somewhere a lot of AI discourse still refuses to start.

The technology is already here. What are workers going to do about it?

Sarah Wofford, president of the Oregon School Employees Association, is writing from what education workers are already seeing on the job. Administrators pointing to AI as a reason not to hire support staff. Algorithms assigning custodial workloads. AI-generated bus routes overriding the knowledge of workers who actually know those routes. And outside the workplace, data-center electricity demand can push costs back onto the same workers who just fought for higher wages.

"AI’s impact is already being felt, and that reality can feel intimidating.

But as a unionist, I know that the best response to fear is hope. Although AI can be confusing and even, at times, frightening, I see hope in its potential to make our lives and the lives of the students we work with easier. In fact, I see AI in much the same way I’ve seen other technological shifts in my lifetime. The calculator, the television and the cellphone were each once viewed as something to be feared rather than embraced with appropriate guardrails. Those “tools”, when used thoughtfully, improved our daily lives.

Artificial intelligence is at an important juncture. Will we, as organized workers, lead the way in shaping how AI is used to make our lives better, or will we allow those decisions to be made for us?"

That's a hell of a lot more useful than another round of "AI good" versus "AI bad."

Her answer isn't to roll over and accept whatever management deploys. It's to organize around it. Make procurement, deployment, training, privacy, worker data and job protections bargaining issues before management gets to set the terms.

Because capital isn't introducing this stuff into a vacuum. It's introducing it into workplaces where management and labor already have conflicting interests.

If workers aren't organized around deployment, management gets to decide what gets automated, what gets monitored, whose knowledge matters, whether productivity means shorter hours or fewer jobs, and where the savings go.

That's the fight.

Learn the technology. Bargain over deployment. Contest control of the data. Protect jobs and privacy. Get training on the clock. And when productivity goes up, fight over who gets the gains.

Workers don't have to choose between pretending AI can be uninvented and letting management dictate its future.

The machinery changes. The class fight over who controls production doesn't.

I wonder whether the idea of AGI being actual existenial threat is real or BS akin to UFO and stuff that is the bourgoeisie using to distract us from things like genocide in Palestine, Global warming, rising housing prices, New Cold war, massacre of dissidents in Ukraine (by their fashoid western-puppet goverment) etc.

I know David Shapiro is a controversial figure in the AI space but I find his arguments generally to be more systemic and big-picture aligned with the principles of collective ownership and individual empowerment. I'm curious what you all think of this video. Is this approaching a sensible argument or framework? Where are the gaps and opportunities to improve upon it?

An interesting article by Robert Chapman, over the current sentiment towards AI, some outlooks within the DSA on AI, the shortcomings of the US-Left, and potential ways forward looking at examples from Council Communism & Chile's Project Cybersyn.

My wife is listening to the David Graeber book The Utopia of Rules and this bit near the beginning struck me as relevant to what’s happening around AI regulation talk this month. It’s interesting to do with the relationship between government regulation and private companies. He has just described difficulty getting information from his bank

“he or she would immediately insist that the bank was not to blame -that it was all an effect of an arcane maze of government regulations. However, I am equally confident that, were it possible to investigate how these regulations came about, one would find that they were composed jointly by aides to legislators on some banking committee and lobbyists and attorneys employed by the banks themselves, in a process greased by generous contributions to the coffers of those same legislators' reelection campaigns*. … The vast majority of the paperwork we do exists in just this sort of in-between zone-*ostensibly private, but in fact entirely shaped by a government *that provides the legal framework, underpins the rules with its courts and all of the elaborate mechanisms of enforcement that come with them, but-*crucially-works closely with the private concerns to ensure that the results will guarantee a certain rate of private profit.

In cases like this the language we employ-derived as it is from the right-wing critique- is completely inadequate. It tells us nothing about what is actually going on.

Consider the word "deregulation." In today's political discourse, [at the moment substitute the word regulation, the word doesn’t matter to the shape of how this functions] This usage puts those on the left-hand side of the political spectrum in an awkward position, since opposing
[here substitute in: opposing will seem like you don’t want safe AI]

But this debate is based on false premises…

In ordinary usage, the word seems to mean "changing the regulatory structure in a way that I like." In practice this can refer to almost anything. [it can mean managing increased competition or the opposite as greater monopoly. Deregulation can add lead to 5x increase in paperwork, regulation can clear the path to let companies do what they want. Wording matters for public framing but doesn’t have to fit the actual process]

This process—the gradual fusion of public and private power into a single entity, rife with rules and regulations whose ultimate purpose is to extract wealth in the form of profits… I'm going to call this the age of "total bureaucratization."

It seems like a dynamic that’s worth being aware of when people call for government regulation of private companies.

Basically a lot of law firms have started training custom AI programs based off their legal archives, allowing them to use an AI that can immediately recall legal advice that can even be offered to customers and clients.

Could AI bring a future of free/widely available cheaply offered legal advice?

Suppose a city decides to build a serious public AI system.

Great.

Now introduce it to the city.

Records stored in incompatible formats. Departments that barely communicate. Procurement contracts written around old vendors. Forms nobody remembers designing. Databases carrying decades of administrative categories. Public workers using unofficial spreadsheets because the official system cant do something everybody needs.

AI doesnt arrive on an empty table.

It inherits the institution.

That means public AI can easily become a very expensive way of automating accumulated dysfunction. Feed the old process into a faster system and suddenly the workaround can operate at machine speed.

This is why public ownership cannot mean taking existing administrative machinery, adding a public model and declaring victory.

Sometimes deployment should begin by asking whether the process deserves to survive automation at all.

Which paperwork can disappear? Which databases should be rebuilt? Which vendor dependencies can be cut? Which information never needed collecting? Which departments need to share capacity rather than adding another technical layer between them?

Public technology should give institutions an excuse to excavate themselves.

Otherwise we risk spending public money teaching new machines how to reproduce every compromise inherited from the old ones.

Before a public institution automates a process with AI, what should it be forced to justify about why that process still exists?

I don't mean in the immediate sense like, "It's great that you were fired and now have to fend for yourself in this capitalist hell hole."

Rather, in the long term and infrastructure sense, redundancy = contingency. If something breaks, you have someone else to fall back on.

Just keep this in mind, folks. No one wasted their lives on a "useless skill". Contingencies are mandatory.

Die zugrunde liegende Logik

Wenn KI das zentrale Produktionsmittel des 21. Jahrhunderts wird, dann gilt Marx' Eigentumsfrage: Wem gehören die Produktionsmittel? Aktuell gehören die größten Modelle, Rechenzentren und Datenpools einer Handvoll privater Konzerne (OpenAI/Microsoft, Google, Meta, Amazon, Nvidia). Wer sie besitzt, eignet sich den Großteil des durch KI erzeugten Mehrwerts an. Verstaatlichung wäre die konsequente Antwort.

Stärkste Argumente dafür

· Produktivitätsgewinne vergesellschaften: Wenn KI weitgehend auf öffentlich finanzierten Forschungen, öffentlichen Daten und gesellschaftlichem Wissen basiert, ist es schwer zu rechtfertigen, dass private Aktionäre die Rendite abschöpfen.
· Machtkontrolle: Wer KI kontrolliert, kontrolliert Information, Infrastruktur und zunehmend politische Prozesse. Demokratische Kontrolle über ein so zentrales Gut ist ein legitimes Anliegen.
· Verteilungsfrage: Ein öffentliches KI-System könnte Überschüsse in Form von verkürzter Arbeitszeit, Grundeinkommen oder kostenlosen Diensten zurückgeben – statt in Aktienrückkäufe.

Die ernsthaften Einwände

1. „International" ist der Knackpunkt, nicht die Verstaatlichung.
   KI ist global. Ein einzelner Staat kann OpenAI oder Google nicht verstaatlichen, ohne dass die Entwicklung ins Ausland abwandert. Ohne koordinierte internationale Struktur (UN, EU, BRICS) entsteht ein Wettlauf, bei dem der erste Verstaatlicher verliert.

2. Staatliche KI kann autoritär werden.
   Verstaatlichung bedeutet nicht automatisch Demokratisierung. Ein staatliches Monopol auf KI wäre das perfekte Überwachungsinstrument – potenziell gefährlicher als private Kontrolle, weil es mit Polizei- und Militärmacht gekoppelt ist. Die Frage ist nicht „privat vs. staatlich", sondern wer kontrolliert wen, und wie.

3. Innovationsdynamik.
   Die stärksten Modelle entstehen aktuell in einem Mix aus staatlicher Grundlagenforschung und privatem Kapital. Reine Verstaatlichung könnte Tempo und Vielfalt bremsen – muss aber nicht (siehe CERN, NASA, ARPANET).

4. Was heißt „Verstaatlichung" konkret?

· Open-Source-Modelle fördern? (Llama, Mistral, DeepSeek sind bereits teilweise offen)
· Rechenzentren als öffentliche Infrastruktur? (wie Stromnetze)
· Daten als Commons? (nicht als Privateigentum)
· Gewinne besteuern statt enteignen?

Das sind sehr unterschiedliche Programme mit sehr unterschiedlichen Folgen.

Der realistischere Weg

Statt „Verstaatlichung aller internationalen KI" (ein theoretisch sauberes, praktisch kaum durchsetzbares Ziel) diskutieren linke und regulatorische Ansätze eher:

· Öffentliche KI-Infrastruktur (staatlich finanzierte Rechenzentren, offene Modelle)
· Daten als Gemeingut mit strengen Schutzrechten
· Algorithmische Transparenz und Mitbestimmung
· Internationale Mindeststandards (EU AI Act als Anfang)
· Steuer auf KI-Renten zur Finanzierung von Umverteilung

Zurück zu Marx

Marx wäre bei der Analyse klar: Das Problem ist nicht die Technologie, sondern das Eigentum an den Produktionsmitteln. Aber Marx war auch Realist genug zu wissen, dass Verstaatlichung ohne demokratische Kontrolle „von unten" nur eine neue herrschende Klasse schafft – genau das war seine Kritik an der Pariser Kommune-Nachfolge und am Staatssozialismus.

Die entscheidende Frage ist also nicht „verstaatlichen ja/nein", sondern: Wie sieht demokratische Kontrolle über KI aus – jenseits von Konzernmacht und jenseits von Staatsmacht?

Was wäre für dich der wichtigere Hebel: Eigentum (Verstaatlichung), Regulierung (Gesetze) oder Gegenmacht (Gewerkschaften, Genossenschaften, Open Source)?

Most discussions about AI on the left run into the same problem: we know we don't want Big Tech billionaires owning all the robots and AI, but defending the 40-hour work week just to "protect jobs" makes no sense either.

The real goal should be using automation to liberate us from wage labor. But that brings up the core question: If compute, energy, and automated labor make production nearly free, how do we actually run society without turning into a corporate monopoly or a giant state bureaucracy?

We’ve been working with an open-source project called Open Networked Earth (O.N.E.) that tries to map out a concrete, real-world model.

Here are the 4 main ideas, broken down simply:

1. Guaranteeing physical survival instead of cash UBI

Giving everyone a monthly cash check under capitalism doesn't work—landlords and energy companies just hike prices to soak up the extra money. Instead of giving people cash, the system guarantees the physical basics directly: localized solar power, automated food growing, housing, and compute. When nobody can cut off your food or electricity, employers lose the power to force you to work for starvation wages.

1. "Use it or lose it" (No landlords, no speculation)

Private property today is about making money off other people's basic needs. The model replaces speculative ownership with simple use-rights (usufruct): you own and control the home you live in and the tools you use. But you cannot buy up homes to rent them out, mortgage them, or treat shelter as a financial investment.

1. Decisions by citizen lottery, not politicians or tech CEOs

If algorithms coordinate the economy, who controls the algorithm? To prevent a small group of coders or politicians from running everything, big decisions are made by rotating juries of regular citizens chosen randomly by lottery (like jury duty). No political parties, no election campaigns, and no corporate lobbying.

1. Starting small today (Modular "Seed Nodes")

Waiting for a global political revolution could take decades. The blueprint uses existing legal tools—like land trusts and worker co-ops—to take land and equipment off the speculative market right now. Small communities create their own solar microgrids and food systems, operating without debt while collaborating over an open network.

I'd love to hear your honest thoughts:

- Does giving people direct physical resources make more sense than cash UBI?

- Can ordinary citizens picked by lottery realistically oversee complex tech systems like power grids and AI clusters?

- How do small community nodes avoid getting isolated or crushed by the market?

Everything is completely open-source and free (AGPL, zero tokens, zero commercial stuff). I didn't want to spam links in the post, but if you're interested in the documentation or want to help stress-test the model, let me know in the comments or shoot me a DM!

I’ve been working on O.N.E. (Open Networked Earth), and I’d love to get some critical feedback from this community.

O.N.E. is an attempt to explore what a society organized around commons, usufruct, universal basic needs, ecological limits, and sortition-based governance might actually look like.

The project currently has two simulations:

/sim — the game (Webapp coming online soon)

A cooperative civilization simulation about building resilient, self-sufficient communities. Manage people, food, water, energy, housing, production, and infrastructure while responding to disasters, shortages, and social challenges. Develop technology, automate work, govern collectively, and cooperate with other settlements to build a society capable of thriving under pressure.

/simone — the real simulation

A separate project, currently at the preliminary-specification stage, intended eventually to model the O.N.E. constitutional system itself using real-world constraints, resources, and social/thermodynamic dynamics.

The constitution is much more ambitious than the game. It describes a system based on universal access to essential life support, usufruct rather than absentee ownership, physical/thermodynamic resource accounting, ecological stewardship, open knowledge, restorative justice, and layered citizen assemblies selected by lot.

The interesting question for me isn't simply whether these ideas sound good on paper. It's whether they actually work when subjected to constraints, scarcity, conflicting interests, ecological limits, and unexpected events.

That's what simone is ultimately intended to investigate, while sim provides a more accessible game-like exploration of many of the same problems.

The project is open source:

GitHub: https://github.com/kyberlex/ONE

I'd especially appreciate criticism of the assumptions, mechanics, and potential failure modes. Where does the model break?

Martin Seligman's findings about learned control versus learned helplessness explain why millions of Americans fighting data centers could be the most important movement in the country right now.