It’s going to be a sad day when Linus finally leaves the kernel
Ehhh, probably the most pragmatic option for someone in his position, but I’m not gonna take that as an even-handed analysis of AI in open source, the software industry, the economy, or civilization writ large.
There was a post earlier today that directly counters the “just a tool” trope. (And if you’re thinking “but this is Linus! What credentials could this rando possibly have?”, allow me to preface their essay+video with a note that this guy has experience at high levels in the industry and then quit the industry to get a PhD with a focus on the social impacts of software development tools.)
And Cory Doctorow has a book (and many blog posts and speaking engagements covering the same content) about the precise harms (and non-harms) of AI.
Dr. Fatima (on Youtube) also has a pretty well-rounded take.
And Baldur Bjarnason makes some good points from a cognitive science perspective, though I think he’s ultimately out over his skis quite a bit.
The analysis in the post remains firmly at the level of phenomena, failing to address the fundamental contradiction of the capitalist mode of production. The blog post correctly points out that tools are not neutral since they shape people and social relations. All tools are material manifestations of specific production relations. However, the blog post treats AI as a tool or technology itself, failing to question why AI exists in this specific form at the current historical stage. The reason there is a tendency towards large scale models which are centralized and commercialized is that they are an inevitable product of the logic of capitalist accumulation.
From the perspective of the base and the superstructure, after the highly developed capitalist productive forces, capital urgently needs a new means to accelerate circulation, reduce labor costs, and open up new areas of accumulation. So, the inefficiency and high energy consumption of AI are not technological defects, but rather a price that capital is forced to pay under specific historical conditions because true efficiency in form of distributed, open-source, and democratized AI cannot serve the maximization of monopoly profits. The waste, environmental damage, and ethical crisis of the AI industry are essentially inherent contradictions of the capitalist mode of production. The problem stems directly from the contradiction between social production and private ownership.
The post also discusses the idea of tools shaping people, but fails to clearly distinguish the different shaping forces of use value and exchange value on technological development. Under capitalism, AI primarily serves the needs of capital accumulation rather than the comprehensive development of a society. The whole AI makes humans stop thinking and stop creating argument is just describing the deepening of capitalist labor alienation in the digital age where workers are alienated from creative labour. The push to replace rather than enhance human capabilities is driven by the need for replaceable, standardized labor, rather than independent thinking subjects.
Merely demanding rational use or ethical norms without addressing the private ownership of the means of production can only alleviate symptoms while doing nothing to address the root cause. The laws and ethics of capitalist society are themselves part of the superstructure and their fundamental function is to safeguard the interests of the bourgeoisie. As long as the means of production remain in the hands of a few monopolistic capitalists, any calls for ethical use are just empty moralizing.
Finally, it’s worth noting that there is little room for letting us do what machines cannot do like appreciating predecessors and fighting for policy within the capitalist framework because such behaviors are systematically marginalized. True liberation lies in breaking down the social relations that determine the direction of technological development. The goal has to be to move the development of AI from serving capital accumulation to serving the free and comprehensive development of humanity.
The core problem with the critique in the blog post is that while it is emotionally charged, it fails to rise to the level of a systematic analysis of the capitalist mode of production. Merely calling for critical use or humanistic concern is insufficient because it is essential to understand the relations of production in order to see past the illusion of tools controlling people.
I don’t think there’s anything wrong with the author sticking to the level at which he’s an expert. If everyone had to chase down the lowest possible level, we’d all be physicists (or maybe philosophers, depending on your take there).
Besides, isn’t the “materialism” portion of “dialectical materialism” about interrogating the implications of present world you find yourself in, rather than evaluating what-ifs of alternate histories?
However generative AI might have emerged differently under a different regime, this is the version that we have access to inspect and, crucially, the version we must contend with if we want to influence its future trajectory under any regime.
Edit: But I do have to agree that he is much better at diagnosing the problem than he is at prescribing the solution. That seems to be the way of things. People tend to be good at either analyzing problems in detail, or rallying people around a tractible plan of action. It’s very very very rare to see someone who is good at both. So I don’t mind it too much.
I am talking about interrogating the implications of the present world we live in. What I was pointing out is that the author makes a shallow analysis of the symptoms without following the threads to identify the root causes. You don’t need to be a philosopher to do that.
I’m also not talking about an alternative history where AI might’ve emerged in a different form. I was pointing out the underlying causes of the negative effects associated with how this technology is used, and we need to be clear on that in order to do anything about the problem. The issue is capitalist control, and the solution is to develop this technology under public ownership the same way other open source technology is developed. Open alternatives from China are already the biggest threat to the whole model, so this is already starting to happen.
I think people who are opposed to the way this tech is used should be thinking of how to wrestle it away from corporations, and to build it in the open. This is the whole concept behind having ownership of the means of production. In my opinion, that’s the only realistic solution to the problem in the long term.
the issue on ai is actually about tradition vs. modernity, in most cases. if you add up to that the fact that it’s coupled with automation, which a lot of people consider a bad thing because it eliminates jobs from the market. it was capitalism all along…
exactly, pretty much every serious argument against this tech boils down to capitalist relations rather than the tech itself
How separable are the two when scale is needed to run llms effectively? If you’ve used ollama on your own computer you know the limitations of alternatives. When you use big tech’s offerings you are helping to train their models further. Adding to their control. My suggestion isn’t necessarily abstention, but here tech and capitalism seem to be inseparably intertwined.
Socialism takes advanced, industrial production beyond the profit motive and into a consciously planned and pro-social direction. You can have industrial scale without having capitalism.
We’re basically in the mainframe era of this tech, but if you have used local models then you know that progress has been absolutely breathtaking in the past year. Qwen 3.6 27b that you can run on a laptop is straight up better than frontier models that were available just a couple of years ago and required a data centre to run. Also, you don’t have to use American models. You can use open models from China, they’re very capable.
Based. But the AI slop machine is something to be aware of. AI can get you 90% of the way there nowadays but without the remaining 10% error checking you’re not gonna have a good time.
I’d argue it’s more than 10% checking. You really do have to be engaged in the process, and you can’t farm out thinking to the LLM. It’s a great tool for generating code, but you have to be making conscious decisions at the developer. My process has been to come up with a step by step plan, where there are clear and focused deliverables at each stage, and then do commits for each one and review the diff. This way I have a clear context of what the task is doing, and a reasonable amount of code I can read through to do a proper code review. And it’s easy to actually test the functionality out to see that it’s working. If you take this approach, then the tool really can save you a lot of time.
It was a totally measured and well thought argument. Not singing Nirvana nor Apocalypse when it comes to AI but embracing technological progress in a measured way
