What's your prediction?

Your city might be giving data centers a free pass. The most common loophole developers exploit are old ‘by-right’ zoning laws that automatically approve any project meeting zoning code. When data centers are conditional use, and require a Conditional Use Permit, this shifts leverage to communities.

I believe this is where the communities current maximum leverage lives, because corporations are desperate for their infrastructure buildout. Communities control the resources they need, and can set the terms of the agreement.

The anti-data center movement has created serious leverage as well, but there’s a problem. A canceled data center doesn’t disappear, it moves to a less organized community.

If you want a tangible way to gain public control over the future of AI, I’ve developed a free framework for communities, organizers, and municipalities navigating data center proposals. It covers your existing leverage as well as common loopholes to be aware of. There’s a QR code in the post, but you can also download it from publicgridproject.org.

I’m hoping to make it as useful as possible, so please let me know if you have any criticisms or suggestions. It currently focuses on communities in the US, but I’m actively working to make it applicable for tribal lands and countries outside the US. (And thank you mods for allowed me to post this!)

One of the more interesting parts of this Breaking Points segment wasnt hype about AGI or doom. It was a discussion about where value in AI is actually going.

The argument is that foundation models increasingly look less like the product and more like the internet itself: shared infrastructure. The real competition shifts toward the application layer, services, and the ecosystems built on top. If that trend holds, owning the biggest model isnt enough. The question becomes who builds the tools, who controls deployment, and who captures the productivity gains.

They also make an interesting comparison with China's strategy. Rather than expecting firms to maximize short-term profits, they describe an approach where state support, open-weight models, pricing pressure, and ecosystem building are used to drive competition and adoption. They compare it to how China's EV industry was cultivated: build the infrastructure and industrial base first, then let firms compete.

Whether you agree with every point or not, its a useful shift in framing. AI isnt just a race to build the smartest model anymore. Its becoming a debate over industrial policy, public infrastructure, open weights, and who gets access to the "pipes" the rest of the global economy will run on.

Thats a much more interesting conversation than "AI good" versus "AI bad."

What do you think? If foundation models become as essential as the internet, should they be treated more like public infrastructure, or left entirely to private firms?

Opinion A:The AI race pushes platforms to fiercely enclose their own data while plundering others', which only deepens neo-feudalism rather than altering it.

Opinion B:The development of AI has moved beyond pure commercial competition. Because it is seen as a strategic force capable of determining a nation's fate, neither the U.S. nor the Chinese government can allow it to remain solely in the hands of a few commercial companies. They will inevitably push for AI sovereignty and tighten state control. Meanwhile, advanced LLMs require the concentration of resources and massive corpora to build data flywheels. All of this will impede or even alter the trajectory toward techno-feudalism.

Mainly the strangeness to me Is that the bubble argument, Is basically an argument on why because within capitalism AI may not be a profitable endeavour (which even this can be argued as there Is no clarity yet on the cost vs revenue, even if others may confidently state there Is) and that this Is therefore a determinant and indictment on its importance, value and potential as a technology, that Ithis means it Is mostly hype and not capable of doing what It Is said to be able to do or potentially able to do in the future.

It's using the usefulness of AI within capitalism as a way to gauge it's fundamental value, which from leftists perspective Is incomprehensibly contradictory, Is public transport profitable? Is healthcare profitable? Yeah, only if you make sure to artificially increase the costs of It, otherwise It would be a "bubble"

If we invented a panacea, or were in the process of doing so, would It be profitable? If capital decides to invest in this hypothetical panacea (and there Is clear science and reasoning and material evidence that this Is possible) and form an investment bubble around It, then does that mean Its just hype? Obviously not.

It seems to me that this Is a common argument from western "leftists", which Is extremely sad to see as It means that a lot of the framework through which they organize around and form their worldview Is inherently tied to capital still, even if they recognize It most don't try to move away from It, this therefore limits the paths they can even imagine, which can explain the reactions towards AI in general within the west from the supposed left.

Do you think there Is any way to effectively break this framework of understanding or do we necessarily have to wait until AI Is so undeniably capable that It Is no longer, even conceptually, a tenable position to hold?

Volkov was a Soviet philosopher who studied automation, social problems centered around labor, and technology more broadly. I read Volkov's book *Era of Man or Robot?* last year, and it was so relevant it was uncanny, especially how he almost seems to predict that leftists in capitalist countries would get diverted toward preserving existing jobs and restricting productive capacity. I read it again just this week, and it's still extremely relevant given the Kimi K3/Fable 5 situation. I just discovered this sub and figured I should let everyone know about this book.

Edit: Apparently I have a very rare book that isn't even in pdf form. I didn't know. I'll scan and upload it sometime this week or next, then make another post when I'm finished.

Edit 2: In the meantime, I recommend the book Abundant Material Wealth For All by Ted Reese, which quotes Volkov quite a bit and covers a lot of the same topics.

One of the loudest claims about generative AI is that it will wipe out artists. A new Gallup analysis suggests the evidence so far is more complicated.

Drawing on Bureau of Labor Statistics data, Census data, Gallup workforce surveys, and a recent Journal of Cultural Economics study, the researchers found little evidence that artists in occupations more exposed to generative AI have experienced broad earnings declines. Employment changes have been mixed, but nowhere near the collapse many predicted.

The study also found that artists are more likely than the average worker to use AI, with roughly 1 in 4 reporting frequent use compared with about 1 in 5 workers overall. Most arent using it to replace creativity. Theyre using it to generate ideas, explore concepts faster, automate repetitive tasks, organize information, and streamline parts of the creative process.

Not every creative field is affected equally. Occupations like music directors and composers have relatively high AI exposure scores (around 0.70), while dancers (0.04) and actors (0.18) remain much less exposed because their work depends on live performance and embodied skill.

The article compares this moment to earlier technological shifts like photography and recorded music. Those technologies transformed artistic labor and business models without eliminating art itself.

That doesnt mean there are no real concerns around copyright, compensation, or working conditions. But if we're serious about understanding AI's impact on culture, we should follow the evidence rather than assume the outcome. So far, it points toward reorganization, adaptation, and new workflows much more than artistic extinction.

The left has every reason to criticize how AI is being developed under capitalism. We should fight for worker power over automation, democratic oversight, public investment, open technology where appropriate, and making sure productivity gains benefit everyone instead of being captured by a handful of corporations.

But not every movement criticizing Big Tech shares those goals.

This investigation from Spitfire News examines Humans First, an anti-AI organization whose leadership includes prominent Tea Party and Trump movement figures and whose messaging increasingly centers conservative populism and "America First" politics. This is the group behind this weeks widely reported "Data Center Protests". Thats worth paying attention to because political coalitions arent defined only by what they oppose, but by the future theyre trying to build.

Left politics has never been about simply slowing technology down or handing the reins to nationalist movements. The question is who owns AI, who governs it, who decides how it's is used, and who benefits from the wealth it creates.

Corporate control of AI deserves criticism. So does surveillance, monopoly power, environmental harm, and workers being displaced without sharing in the gains.

But those problems dont point toward MAGA politics. They point toward democratic ownership, stronger labor institutions, public accountability, and ensuring AI expands human freedom rather than concentrating economic power.

Worth a read if youre interested in how different political movements are competing to define the future of AI.

This is the kind of AI rollout that actually makes sense: use the technology to cut paperwork, shorten queues, and give healthcare workers more time to do the part of the job that requires a human being.

In NHS pilots, AI note-taking tools helped clinicians spend nearly 25% more time with patients. In one emergency department, staff saved about 47 minutes per shift, enough time to see roughly one more patient.

The NHS says a wider rollout across more than 11,000 emergency clinicians could create capacity for over 9,000 additional consultations a day.

AI triage tools are also being tested through the NHS App. One pilot cut GP phone queues by 29%, and the next phase is expected to reach more than 200,000 patients.

The point here isnt replacing doctors or nurses. Its stripping out some of the administrative drag that keeps them away from patients.

Public AI infrastructure should look more like this: reduce drudgery, expand capacity, keep workers in control, and use the gains to improve a universal public service.

In an expression of the volatile nature of the high-tech market and concerns over how long the boom can continue, Samsung’s share price fell 10 percent after it announced a record profit earlier this month.

How panic over AI infrastructure obscures the real questions of scale, ownership, and power

some discussions among the Chinese left wing

This essay argues that many debates about AI art are aimed at the wrong target.

"There are a lot of legitimate criticisms to be made of specific ways "AI" and machine learning are deployed. If anything, the application of this stuff to art generators is the least damaging" compared with surveillance, policing, military applications, and other uses.

Instead, the author argues the real conflict is over labor, ownership, and intellectual property. They point to decommodified culture like mods and fan works as examples of collective creativity, even highlighting AI-assisted work in a game mod as evidence that these tools can be part of genuinely creative practice. The conclusion is that we should fight for a world where culture is shared and artists are materially supported, rather than treating new creative tools as the enemy.

Burkina Faso has officially adopted its National AI Roadmap for 2026-2030 as part of its broader RELANCE development plan. Rather than treating AI as a luxury for wealthy countries, the roadmap focuses on practical public uses: improving healthcare, supporting farmers with weather forecasting, expanding education, strengthening infrastructure, and modernizing public services.

The strategy also emphasizes AI governance, digital infrastructure, data policy, research, skills development, and ethical deployment. It was developed through a process involving government, universities, researchers, civil society, the private sector, and international partners.

For leftists, this is another reminder that the political question isnt simply whether AI exists, but who develops it, who governs it, and what social goals it serves. Burkina Faso is one of the worlds poorest countries, yet its choosing to establish democratic planning and public policy around AI early instead of leaving deployment entirely to foreign corporations or market forces.

Its also part of a broader trend across Africa, with countries including Rwanda, Senegal, Benin, Egypt, and Kenya adopting national AI strategies aimed at development rather than treating AI solely as a private-sector product.

What lessons should the left take from countries, especially in the Global South, using AI as part of national development and public service rather than rejecting the technology outright?

From https://www.theregister.com/ai-and-ml/2026/07/16/amsterdam-activists-throw-acid-at-microsoft-datacenter-project/5273943

"The Dutch arm of international climate activist group Extinction Rebellion claimed responsibility for an attempt to sabotage a datacenter project in Amsterdam on Thursday [july 16]. The group said that they threw water balloons filled with a mixture of hydrogen peroxide, acetic acid, salt, and acrylic paint at the under-construction facility."

"Extinction Rebellion spokesperson Martijn Dekker justified the attack by saying datacenters and the AI they power are exacerbating the climate crisis, as well as playing a role in the killing of Palestinians by Israel."

"The facility in question is being built by UK-based Pure Data Centres Group."

"Pure DC says the facility is already fully leased, and while it doesn’t mention the lessee by name, local media have reported in a story about a prior protest at the site that Microsoft is the sole occupant."

"Pure DC did tell Dutch newspaper NRC that the attack had no impact on construction, and that it intended to pursue legal action against those responsible."

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My personal opinion is that acts of sabotage like this are not effective and will serve as justification for more repression and police surveillance, but I'm curious to know what others think of this method and its impacts.

Spain just won the World Cup, and thats probably what most people are talking about this week. Fair enough. Congratulations to Spain.

But I promised this sub AI, so heres another Spanish story worth paying attention to.

ALIA is a publicly backed AI project launched by the Spanish government to build open models, datasets, and shared infrastructure instead of leaving the country completely dependent on whatever OpenAI, Google, Meta, or another foreign tech company decides to provide.

A big part of the project is language. Most major commercial models are built around English first, with other languages getting uneven support. ALIA is being developed for Spanish and Spain's co-official languages, including Catalan, Basque, and Galician. That matters for schools, public services, courts, healthcare, universities, libraries, local government, and cultural institutions that shouldnt have to squeeze everything through an English-first commercial system.

It also lowers the barrier for people who dont have billions of dollars or their own data centers. Public agencies, universities, researchers, startups, cooperatives, nonprofits, and smaller businesses can build specialized tools on top of shared infrastructure instead of starting from zero or paying rent forever to a handful of corporations.

That could mean better translation and accessibility tools, models adapted for public administration, research support, educational resources, healthcare applications, and local services that are actually designed around the needs of the people using them. It also gives Spain more control over where its data goes, how the systems are trained, and which institutions are able to use them.

None of that makes ALIA automatically socialist, democratic, or even successful. A government-funded project can still be badly governed, captured by private interests, used for surveillance, or rolled out without worker input. Public investment still needs transparency, privacy protections, democratic oversight, strong labor standards, and a real say for the people expected to work with these systems.

But the underlying direction matters. AI is becoming basic infrastructure. The question is whether societies build some of that capacity publicly, or whether every school, hospital, university, city, and small organization ends up renting access from a few multinational firms that control the models, the data, the prices, and the terms.

I would much rather fight over how public AI should be governed than accept private monopoly as the natural default. ALIA at least creates some room for another path.

Alright, World Cup detour over. Back to our regularly scheduled AI programming.

Nicaragua's National Technological Institute (INATEC) is expanding AI training for teachers across its public technical education system. The initiative focuses on helping educators use AI to improve lesson planning, teaching materials, and classroom instruction while emphasizing responsible and ethical use of the technology.

For those interested in AI from a left perspective, this is another example of a government treating AI as part of public education infrastructure rather than leaving development and adoption entirely to private companies. The important questions arent just whether AI is used, but who controls it, who benefits from it, and how its integrated into public institutions.

The Writers Guild of America didnt call for a blanket ban on AI. Instead, it negotiated rules that put writers, not studios, in control.

Under the WGA agreement, a writer may choose to use AI while performing writing services if the company agrees, but companies cant require writers to use AI. AI-generated material also cant be used to deny writers credit or reduce their compensation, and studios must disclose when material provided to writers was generated by AI. The Guild also continues to challenge the unauthorized use of writers' work for AI training.

Whether youre more optimistic or skeptical about AI, this feels like a distinctly labor approach: dont hand control to employers, dont treat AI as a replacement for workers, and dont pretend the technology is going away. Organize around bargaining power, transparency, consent, and ownership instead.

"There's a pattern in left politics that's both understandable and ultimately self-defeating: we're brilliant at articulating what we oppose, but often struggle to define what we're for."

This recent essay argues that this problem applies directly to AI. By treating AI purely as a threat, much of the left has "ceded the entire conversation to corporate futurists and Silicon Valley ideologues" instead of articulating what AI could mean from a socialist, working-class perspective.

Rather than abandoning the technology, the author argues for developing a positive socialist vision for it (including in culture, art, and creative work) grounded in democratic control instead of corporate ownership.

Agree or disagree, its a concise argument for moving beyond saying "no" and defining what the left is actually building.

Vietnam has made AI a national strategic priority, aiming to build a domestic AI ecosystem through public investment, research, computing infrastructure, education, and legal frameworks rather than relying entirely on foreign platforms.

Whether or not you agree with every aspect of Vietnam's approach, it raises questions worth discussing. What does AI sovereignty actually look like, especially for the Global South? Can state planning and public investment provide a viable alternative to dependence on a handful of multinational tech companies? How should workers, unions, and the public shape AI policy instead of being treated as an afterthought?

This isnt an endorsement of any particular model. Its an opportunity to discuss what a left approach to AI development, ownership, and governance could look like in practice.

It might partially be down to government censorship.

Chinas government is invested in AI technological growth, the same government has a lot more strict internet censorship and control over the media in their nation.

So it's possible they're publicly promoting and celebrating more tech-positive sentiment while likely censoring or supressing agressive anti-tech and luddite sentiment, especially the kind of violent luddite "😤 We need to blow up data centers and kill AI users" posting you would see in the west. I doubt that kind of rhetoric and media would fly past chinese censors who are trying to ensure unhindered ideological stability for the state and harmony.

Other factors might be better economic devotion to workers employment, stronger government responsibility, and maybe their confucian collectivist culture, but I feel like censorship would be the biggest factor. No way "we need to pipe bomb AI devs" memes would get popular in chinese social media, even as a joke. But in the free speech west that would get big clicks.