u/Salty_Country6835

AI debates often get reduced to "pro vs anti AI," but there's more going on than that. Some people want AI to move faster, some want it slowed down, and others are mainly focused on who should own it, govern it, and benefit from it.

This isnt meant to be scientific, just a snapshot of where the community falls.

Pick the option thats closest to your view. If none of them fit, explain your position in the comments. Im interested in the reasoning as much as the results.

View Poll

The UNHCR recently shared how its using an AI-assisted system called CareLine to answer common questions from refugees, route requests to the right teams, and reduce the backlog facing aid workers. Human staff still handle complex cases, but the repetitive administrative work can be handled much faster.

What caught my attention wasnt just the technology. It was the possibility.

Imagine community-led versions of this. Tenant unions using AI to connect renters with legal resources. Food banks matching donations to neighborhoods with the greatest need. Mutual aid networks triaging requests after storms. Community clinics helping people navigate services in multiple languages. Neighborhood organizations answering common questions 24/7 while volunteers focus on the work that actually requires people.

AI isnt only something corporations or governments can deploy. Communities, cooperatives, nonprofits, and open-source projects can build and govern these tools too.

The more we talk about democratic AI, the more we should be talking about community AI.

This debate gets framed as if AI support or opposition belongs to one political camp, but Im not sure thats actually true.

This isnt meant to be scientific or exhaustive, just a snapshot of who is actually participating in AIWars.

A few notes:

"Leftist" means socialist, communist, anarchist, or similar.

"Centrist/Moderate" covers people who don't strongly identify with either side.

"Rightist" includes conservatives, libertarians, nationalists, and similar currents.

"For AI" and "Against AI" are broad self-descriptions. Pick whichever you think fits you best, even if your views are more nuanced.

If none of the options quite fit, explain your position in the comments. The discussion will probably be more interesting than the poll itself.

View Poll

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?

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.

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.

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.

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?

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.

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.

>"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.

In this episode, we use Marx’s infamous “Fragment on Machines” from the Grundrisse as a starting-point for a wide ranging discussion about the emancipatory and regressive potentials of AI technologies. Marx thought that automated systems of machinery are incredible embodiments of highly developed human knowledge, which render labor increasingly unnecessary in processes of production, opening the door for unprecedented liberation. Of course, tied to the imperatives of capital accumulation, even the most amazing machines do little more than increase the rate of exploitation and expose untold millions to desperate poverty. There’s no reason in principle why machines, including AI systems, couldn’t instead free up our time for the active development of our capacities and the pursuit of our personal and collective goals. Abolish the drudgery of gruntwork! But which way we go with these technologies is a political, not a technical matter; a little historical materialism goes a long way.

leftofphilosophy.com | u/leftofphil | u/leftofphilosophy.bsky.social

References:

Karl Marx, “Fragment on Machines”, in Grundrisse, trans. Martin Nicolaus (New York: Penguin Books, 1993), pgs. 690-712.

Music:

“Vintage Memories” by Schematist | schematist.bandcamp.com

“My Space” by Overu | https://get.slip.stream/KqmvAN

One thing I appreciated about this new paper from researchers at Princeton and USC is that it refuses to treat "AI" as one thing.

Instead, they distinguish between displacement (replacing workers), augmentation (helping workers do their jobs), and monitoring (expanding managerial surveillance). Those are different technologies with different political consequences, so they shouldnt all be lumped together.

The paper combines worker survey data from 15 European countries collected between 2012 and 2024 with a text analysis of more than 40,000 Canadian collective bargaining agreements from 1993 to 2025. One of the findings is that augmentation and monitoring tend to coincide with higher unionization and more bargaining over training, governance, notice, and surveillance, while displacement technologies tend to be associated with weaker protections.

Thats a much more useful framework than just asking whether AI is good or bad. Different deployments create different contradictions. Different contradictions require different organizing strategies.

What does everyone think? Should labor movements be approaching augmentation, surveillance, and automation as separate bargaining issues rather than treating AI as a single political question?"

The Trades Union Congress (TUC), the UK's national federation of trade unions, just published a piece on how education unions are organizing around AI. Not by throwing up their hands or pretending the technology can be wished away, but by building worker power around how it gets deployed.

The focus is on collective bargaining, workplace consultation, professional standards, and making sure workers have a say over AI adoption rather than having it imposed from above.

Thats the kind of politics I think the left should be developing. AI is becoming part of the workplace whether we like it or not. The question is whether workers organize around it, shape it, and win material gains, or leave those decisions entirely to employers.

More unions, more bargaining, more democratic control. Less magical thinking that refusing to engage with the technology is a strategy.

How should labor movements be organizing around AI where you live?

Most of the headlines about AI and Palestine are about Israels use of AI for surveillance and military operations. That reporting is important. This story is about something different: Palestinians using AI themselves.

A group of young Palestinian women in Gaza are learning to use generative AI to create short films based on their own memories and experiences. Despite constant power outages, poor internet, and the destruction around them, they are using the technology to document their lives in their own words instead of letting others speak for them.

Stories like this are worth paying attention to because they remind us that AI isnt one thing. The same technology can be used for war or for helping people create, communicate, and preserve their own voices. The politics arent in the model itself, but in who controls it, who has access to it, and what social ends it serves.

While a lot of the AI conversation is dominated by OpenAI, Google, Meta, and the US-China race, Cuba is trying to chart a different path.

Its government is advancing a strategy for sovereign AI centered on public services, education, healthcare, ethics, and technological self determination, despite decades of sanctions and severe resource constraints. Rather than treating AI as just another product to maximize shareholder value, the emphasis is on building domestic capacity and putting the technology in service of social needs.

Whether you agree with every aspect of Cuba's political system or not, this is exactly the kind of discussion the left should be having. Who owns AI? Who controls the infrastructure? Who decides how it is deployed? And who benefits from the productivity gains?

AI is becoming critical infrastructure globally. Leaving it entirely in the hands of a few multinational corporations is a political choice, not an inevitability.

Xi Jinping used the World AI Conference to argue that AI shouldnt end up controlled by a handful of countries or corporations. He called for open source AI, greater international cooperation, and warned against unequal access creating new historical injustices.

China also put some concrete proposals on the table. Over the next five years it plans to provide 5,000 AI training and seminar opportunities for developing countries, establish AI cooperation centers with ASEAN, the African Union, the League of Arab States, CELAC, the Shanghai Cooperation Organization, and BRICS, and expand AI powered weather early warning systems to 30 countries.

Theres a lot to debate here. Open source by itself doesnt solve who owns the compute, the infrastructure, or who captures the productivity gains. But it does push back against enclosure and monopoly, and that matters alot.

As leftists, what should our position be? Is open source enough, or should it be tied to public ownership, democratic governance, and worker control over how AI is deployed?