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Mechanic and the Luddite: A Ruthless Criticism of Technology and Capitalism
293 pages, Paperback
Published January 7, 2025
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About the author
Jathan Sadowski
4 books18 followersJathan Sadowski is a postdoctoral research fellow in smart cities at the University of Sydney, Australia.
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August 28, 2025
In The Mechanic and the Luddite, Jathan Sadowski, provides a materialist analysis of technology, with a focus on AI, in a way that is both critical and accessible.
I didn’t know Jathan Sadowski or the This Machine Kills podcast he co-hosts. Ironically, I came across this book through GPT. So far this is the only good book I’ve found through an LLM, and it’s a critique of technology and AI itself. What’s your game plan here, GPT?
Another great book applying a materialist lens on AI is Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford, which looks at the material resources, labor, environmental costs, and how “AI” systems are used to reinforce Power (i.e., surveillance infrastructure) etc.
But this one doesn’t only provide an overview or ready-made conclusions, it equips readers with tools (a materialist lens, basics of political economy, etc.) so they can carry out their own analysis, and applies to technology more broadly, not only AI. Which I really appreciated.
We often fetishize technology, seeing only the gadget, the shiny object in front of us, or the promises being sold to us.
Or on the other hand, we may treat technology as if it were a neutral, independent (and often inevitable) force.
For Sadowski, though, technology is a System. And it’s inseparable from the broader social and political relations in which it is embedded.
An idealist analysis of technology focuses on ideas, intentions, visions, and vibes.
It looks at what a machine was intended to do. What its designers hoped for. What it might accomplish in the future. We find idealist readings in startup pitches, in myths of innovation as an inevitable transcendent force, or in stories about the “great men” who supposedly drive progress.
Instead, Sadowski frames materialist analysis through two archetypes: the Mechanic and the Luddite.
- The Mechanic: understands:
How a machine is put together. How it functions. What it can and cannot do.
Among other things, this can protect us against false or over-hyped claims, i.e., the idea that LLMs will soon leap to genius-level intelligence and even become conscious.
(Note: the book doesn’t actually go into the “mechanic” side of things. There’s little or no technical explanation on deep learning, how LLMs or diffusion models are trained.)
- The Luddite: understands:
Why the machine was built in the first place. Who it was designed to serve and benefits from its application. Does the machine improve collective well-being? Or does it primarily enrich a small elite at everyone else’s expense?
And even “when it should be seized—in both senses of stopped or taken, destroyed or expropriated”.
Contrary to common conception, Luddites were not against technology. They were a broad worker movement of skilled mechanics who resisted bosses devaluing their labor by introducing machines that replaced them with low-skilled, often child labor, to produce lower quality products.
After laying the groundwork, the Sadowski moves through Innovation, Data, Labor, Landlords, Risk, and Futures.
Innovation Realism
The real engine of innovation under contemporary capitalism is not lone genius who has a sudden Eureka moment, but primarily, venture capitalists (VCs).
VCs hold the money, decide who and what gets funded, and in doing so, shape which technologies are developed and to what ends.
VCs pour huge sums into their favored new tech; lobby politically to protect their interests; and fuel the hype machine.
We’ve seen this cycle repeatedly with “semiconductors and mainframe computing of the 1960s and 1970s, the personal computing and software apps of the 1980s, the internet and e-commerce of the 1990s, the mobile and social web of the 2000s, the gig economy and x-as-a-service platforms of the 2010s, and the crypto assets and generative AI of the 2020s.”
None of these waves were inevitable. They emerged through deliberate choices made by venture capitalists and tech giants. The driving criterion was never “how can this technology best serve the public good” but rather what aligns with the financial interests, values, and power of a very small elite.
Currently, the business model behind AI is brute-force: capture as much data as possible; feed it into massive servers running models with billions of parameters; wrap it in stories of hype and/or doom. [See: The AI Con]
Sure, there have been real technical advances. LLMs perform better on key benchmarks than they did a few years ago. AI is not a complete speculative bubble like NFTs. But the gap between concrete technical progress and the surrounding hype and levels of investment is enormous.
Riffing on Mark Fisher’s “Capitalist Realism”, Sawdoski introduces “Innovation Realism”, the idea that “venture capital seems like the only viable way to support innovation, making it nearly impossible to imagine, let alone implement, alternative models”.
The Political Economy of AI
Current systems labeled as AI (LLMs, LVLMs, Diffusion Models) all rely on what Raj Patel and Jason W. Moore call “cheap things”: cheap money, cheap labor, and Sadowski adds cheap data to the list. [However, cheap nature and resources should also be on the list! See Kate Crawford's book.]
Data is treated as a new form of capital; driven by the logic of accumulation. And most of the training data for AI is our data: blogs, forum conversations, reviews, social media posts, art, YouTube videos, etc.; scraped without acknowledgement or compensation.
Earlier attempts at large-scale models relied on “good enough” training datasets, such as ImageNet. These were annotated by low-paid, crowd-sourced workers, typically from the Global South (cheap labor). More recent approaches rely on “too big to care” datasets: scrape everything you can and throw them to the model regardless of quality.
Of course, training on massive raw datasets also means the models learn to reproduce toxic, racist, sexist, and otherwise harmful content. Companies like OpenAI deal with this through “reinforcement learning from human feedback”, by outsourcing more low-paid annotators labeling outputs as acceptable or not and then “fine-tuning” the model.
And where did the billions in investments come from to fund this brute-force approach? Enter: cheap money.
- First wave: quantitative easing after the 2008 financial crisis. With austerity and low demand, capital flooded into tech. One outcome was what Sadowski calls the “internet of landlords” of “x-as-a-service”: Uber (mobility-as-service), DoorDash (delivery-as-service), AirBnB (property-as-service), Amazon Mechanical Turk (humans-as-service), etc.
- Second wave: during the Covid19 pandemic, these tech companies capitalized on mass job losses, reliance on online shopping, etc., recording immense growth and embedding themselves even further into our everyday lives.
These platforms don’t sell products; they extract rents. Offering access to services provided by others, taking a fee (and our data) in return. Ownership is replaced by access: through subscriptions, or pay-per-use.
And it’s not just platforms. Increasingly, everyday objects are becoming “smart”: fridges, coffee machines, cars, and even toothbrushes for goodness shake. These may provide some minor conveniences. But the trade-off is: “The smarter our life, the less control we have over it.”.
Sadowski calls this digital enclosure. We may own the physical item, but not the software inside it. And so:
- your gadget may not unless you keep up payments (subscriptions, insurance);
- you’re locked into proprietary ecosystems (the right brand of ink, coffee pods, or replacement parts).
Here, Sadowski pushes back against interpretations of “neo-feudalism” (i.e., Yanis Varoufakis and Jodie Dean). Drawing on Morozov, he argues that rentiers have always been a core feature of capitalism and likens platforms to shopping mall owners. However, Varoufaki’s point is that, yes, platform owners are “digital landlords” but the “digital mall” is no longer a market. Amazon is not a market: its algorithms decide what we see. Each of us may see different products or sellers, depending on what will maximize Amazon’s cut.
In any case. Sadowski also discusses AI as a “Perpetual Value Machine”. AI is sold as the fantasy solution to capitalism’s contradictions: exponential growth, no labor costs, deskilled workers, peak efficiency. But this is not possible. It is one of Capitalism’s contradictions. Even so, AI doesn’t need to deliver on that fantasy to have concrete consequences. It can still be used to threaten workers; or to replace some workers and make others babysit the machine; or more broadly to “manage workers with machines, make them subservient to machines, and ultimately make them more like machines”. (This brought Charlie Chaplin’s Great Dictator speech to mind.)
Politics of Risk
Then, Sadowski turns to the governance. He argues that governments are increasingly reorganized around the logic of FIRE (Finance, Insurance, Real Estate) with “Risk” becoming the dominant drive. Policies are outsourced to “risk scores”, often generated by machine learning systems, built by private corporations, and used to make decisions on welfare, policing, border control, and so on. The old maxim “trust the experts” is replaced or supplemented with “trust the tools”.
And when crises hit, be it financial crashes and popped tech bubbles, the government steps in to absorb the risks, shifting private costs onto the public. And we might see this cycle repeat once again, with mounting concerns of the AI bubble popping.
The Futurist vs the Luddite
In closing, Sadowski frames the “Futurist” as the archetype of technological capitalism. Today’s most influential futurists are tech billionaires like Elon Musk, Peter Thiel, and Marc Andreessen, figures “given the authority to advance grand visions for socio-technical change and the resources to materialize their dreams and desires”. This is framed as the antithesis of the materialist “mechanic” and the “luddite”.
The book closes with a reminder and call to action: “What turned these mechanics into Luddites was knowing when it was time to stop tinkering at home and take to the streets, factories, and wherever else capital was imposing its future upon them. This is the same wisdom that must galvanize us today. Only then can we put the pieces together in ways that work for us, not against us.”
I appreciated the call, but found it a bit underwhelming. Yes, there is no blueprint or “one-size-fits-all” fix. Sadowski provides the tools so readers can apply them as they see fit, and act within the specific contexts they find themselves in.
The “modern Luddites” will engage in organized resistance against AI systems in workplaces that don’t meaningfully benefit workers, or even surveil or harm them, and participate in collective bargaining around technological change.
Yet, I think that the book could benefit from going further in sketching concrete directions; showing how the analysis connects with practical interventions and existing movements around technology and broader emancipatory struggles. This may include:
- Technical / legislative fixes: campaigns for interoperability and data portability on social media, algorithmic transparency (explaining why and how “decisions” are made / outputs produced), “right to repair” laws, etc.
- Ownership alternatives: worker-owned cooperative platforms, municipal or publicly controlled platforms, and public digital infrastructure; serving as counterweights to corporate power and big tech, with workers and local citizens having greater control over their lives.
Cory Doctorow’s The Internet Con: How to Seize the Means of Computation seems to touch on the former, and Trebor Scholz’s Own This!: How Platform Cooperatives Help Workers Build a Democratic Internet on the latter (though I haven’t read either yet) and Varoufakis’ Another Now: Dispatches from an Alternative Present and Technofeudalism: What Killed Capitalism also address the latter to some extent; they should make useful supplements to Sadowski’s book.
I didn’t know Jathan Sadowski or the This Machine Kills podcast he co-hosts. Ironically, I came across this book through GPT. So far this is the only good book I’ve found through an LLM, and it’s a critique of technology and AI itself. What’s your game plan here, GPT?
Another great book applying a materialist lens on AI is Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford, which looks at the material resources, labor, environmental costs, and how “AI” systems are used to reinforce Power (i.e., surveillance infrastructure) etc.
But this one doesn’t only provide an overview or ready-made conclusions, it equips readers with tools (a materialist lens, basics of political economy, etc.) so they can carry out their own analysis, and applies to technology more broadly, not only AI. Which I really appreciated.
We often fetishize technology, seeing only the gadget, the shiny object in front of us, or the promises being sold to us.
Or on the other hand, we may treat technology as if it were a neutral, independent (and often inevitable) force.
For Sadowski, though, technology is a System. And it’s inseparable from the broader social and political relations in which it is embedded.
An idealist analysis of technology focuses on ideas, intentions, visions, and vibes.
It looks at what a machine was intended to do. What its designers hoped for. What it might accomplish in the future. We find idealist readings in startup pitches, in myths of innovation as an inevitable transcendent force, or in stories about the “great men” who supposedly drive progress.
Instead, Sadowski frames materialist analysis through two archetypes: the Mechanic and the Luddite.
- The Mechanic: understands:
How a machine is put together. How it functions. What it can and cannot do.
Among other things, this can protect us against false or over-hyped claims, i.e., the idea that LLMs will soon leap to genius-level intelligence and even become conscious.
(Note: the book doesn’t actually go into the “mechanic” side of things. There’s little or no technical explanation on deep learning, how LLMs or diffusion models are trained.)
- The Luddite: understands:
Why the machine was built in the first place. Who it was designed to serve and benefits from its application. Does the machine improve collective well-being? Or does it primarily enrich a small elite at everyone else’s expense?
And even “when it should be seized—in both senses of stopped or taken, destroyed or expropriated”.
Contrary to common conception, Luddites were not against technology. They were a broad worker movement of skilled mechanics who resisted bosses devaluing their labor by introducing machines that replaced them with low-skilled, often child labor, to produce lower quality products.
After laying the groundwork, the Sadowski moves through Innovation, Data, Labor, Landlords, Risk, and Futures.
Innovation Realism
The real engine of innovation under contemporary capitalism is not lone genius who has a sudden Eureka moment, but primarily, venture capitalists (VCs).
VCs hold the money, decide who and what gets funded, and in doing so, shape which technologies are developed and to what ends.
VCs pour huge sums into their favored new tech; lobby politically to protect their interests; and fuel the hype machine.
We’ve seen this cycle repeatedly with “semiconductors and mainframe computing of the 1960s and 1970s, the personal computing and software apps of the 1980s, the internet and e-commerce of the 1990s, the mobile and social web of the 2000s, the gig economy and x-as-a-service platforms of the 2010s, and the crypto assets and generative AI of the 2020s.”
None of these waves were inevitable. They emerged through deliberate choices made by venture capitalists and tech giants. The driving criterion was never “how can this technology best serve the public good” but rather what aligns with the financial interests, values, and power of a very small elite.
Currently, the business model behind AI is brute-force: capture as much data as possible; feed it into massive servers running models with billions of parameters; wrap it in stories of hype and/or doom. [See: The AI Con]
Sure, there have been real technical advances. LLMs perform better on key benchmarks than they did a few years ago. AI is not a complete speculative bubble like NFTs. But the gap between concrete technical progress and the surrounding hype and levels of investment is enormous.
Riffing on Mark Fisher’s “Capitalist Realism”, Sawdoski introduces “Innovation Realism”, the idea that “venture capital seems like the only viable way to support innovation, making it nearly impossible to imagine, let alone implement, alternative models”.
The Political Economy of AI
Current systems labeled as AI (LLMs, LVLMs, Diffusion Models) all rely on what Raj Patel and Jason W. Moore call “cheap things”: cheap money, cheap labor, and Sadowski adds cheap data to the list. [However, cheap nature and resources should also be on the list! See Kate Crawford's book.]
Data is treated as a new form of capital; driven by the logic of accumulation. And most of the training data for AI is our data: blogs, forum conversations, reviews, social media posts, art, YouTube videos, etc.; scraped without acknowledgement or compensation.
Earlier attempts at large-scale models relied on “good enough” training datasets, such as ImageNet. These were annotated by low-paid, crowd-sourced workers, typically from the Global South (cheap labor). More recent approaches rely on “too big to care” datasets: scrape everything you can and throw them to the model regardless of quality.
Of course, training on massive raw datasets also means the models learn to reproduce toxic, racist, sexist, and otherwise harmful content. Companies like OpenAI deal with this through “reinforcement learning from human feedback”, by outsourcing more low-paid annotators labeling outputs as acceptable or not and then “fine-tuning” the model.
And where did the billions in investments come from to fund this brute-force approach? Enter: cheap money.
- First wave: quantitative easing after the 2008 financial crisis. With austerity and low demand, capital flooded into tech. One outcome was what Sadowski calls the “internet of landlords” of “x-as-a-service”: Uber (mobility-as-service), DoorDash (delivery-as-service), AirBnB (property-as-service), Amazon Mechanical Turk (humans-as-service), etc.
- Second wave: during the Covid19 pandemic, these tech companies capitalized on mass job losses, reliance on online shopping, etc., recording immense growth and embedding themselves even further into our everyday lives.
These platforms don’t sell products; they extract rents. Offering access to services provided by others, taking a fee (and our data) in return. Ownership is replaced by access: through subscriptions, or pay-per-use.
And it’s not just platforms. Increasingly, everyday objects are becoming “smart”: fridges, coffee machines, cars, and even toothbrushes for goodness shake. These may provide some minor conveniences. But the trade-off is: “The smarter our life, the less control we have over it.”.
Sadowski calls this digital enclosure. We may own the physical item, but not the software inside it. And so:
- your gadget may not unless you keep up payments (subscriptions, insurance);
- you’re locked into proprietary ecosystems (the right brand of ink, coffee pods, or replacement parts).
Here, Sadowski pushes back against interpretations of “neo-feudalism” (i.e., Yanis Varoufakis and Jodie Dean). Drawing on Morozov, he argues that rentiers have always been a core feature of capitalism and likens platforms to shopping mall owners. However, Varoufaki’s point is that, yes, platform owners are “digital landlords” but the “digital mall” is no longer a market. Amazon is not a market: its algorithms decide what we see. Each of us may see different products or sellers, depending on what will maximize Amazon’s cut.
In any case. Sadowski also discusses AI as a “Perpetual Value Machine”. AI is sold as the fantasy solution to capitalism’s contradictions: exponential growth, no labor costs, deskilled workers, peak efficiency. But this is not possible. It is one of Capitalism’s contradictions. Even so, AI doesn’t need to deliver on that fantasy to have concrete consequences. It can still be used to threaten workers; or to replace some workers and make others babysit the machine; or more broadly to “manage workers with machines, make them subservient to machines, and ultimately make them more like machines”. (This brought Charlie Chaplin’s Great Dictator speech to mind.)
Politics of Risk
Then, Sadowski turns to the governance. He argues that governments are increasingly reorganized around the logic of FIRE (Finance, Insurance, Real Estate) with “Risk” becoming the dominant drive. Policies are outsourced to “risk scores”, often generated by machine learning systems, built by private corporations, and used to make decisions on welfare, policing, border control, and so on. The old maxim “trust the experts” is replaced or supplemented with “trust the tools”.
And when crises hit, be it financial crashes and popped tech bubbles, the government steps in to absorb the risks, shifting private costs onto the public. And we might see this cycle repeat once again, with mounting concerns of the AI bubble popping.
The Futurist vs the Luddite
In closing, Sadowski frames the “Futurist” as the archetype of technological capitalism. Today’s most influential futurists are tech billionaires like Elon Musk, Peter Thiel, and Marc Andreessen, figures “given the authority to advance grand visions for socio-technical change and the resources to materialize their dreams and desires”. This is framed as the antithesis of the materialist “mechanic” and the “luddite”.
The book closes with a reminder and call to action: “What turned these mechanics into Luddites was knowing when it was time to stop tinkering at home and take to the streets, factories, and wherever else capital was imposing its future upon them. This is the same wisdom that must galvanize us today. Only then can we put the pieces together in ways that work for us, not against us.”
I appreciated the call, but found it a bit underwhelming. Yes, there is no blueprint or “one-size-fits-all” fix. Sadowski provides the tools so readers can apply them as they see fit, and act within the specific contexts they find themselves in.
The “modern Luddites” will engage in organized resistance against AI systems in workplaces that don’t meaningfully benefit workers, or even surveil or harm them, and participate in collective bargaining around technological change.
Yet, I think that the book could benefit from going further in sketching concrete directions; showing how the analysis connects with practical interventions and existing movements around technology and broader emancipatory struggles. This may include:
- Technical / legislative fixes: campaigns for interoperability and data portability on social media, algorithmic transparency (explaining why and how “decisions” are made / outputs produced), “right to repair” laws, etc.
- Ownership alternatives: worker-owned cooperative platforms, municipal or publicly controlled platforms, and public digital infrastructure; serving as counterweights to corporate power and big tech, with workers and local citizens having greater control over their lives.
Cory Doctorow’s The Internet Con: How to Seize the Means of Computation seems to touch on the former, and Trebor Scholz’s Own This!: How Platform Cooperatives Help Workers Build a Democratic Internet on the latter (though I haven’t read either yet) and Varoufakis’ Another Now: Dispatches from an Alternative Present and Technofeudalism: What Killed Capitalism also address the latter to some extent; they should make useful supplements to Sadowski’s book.
May 6, 2025
Gr8 and very accessible introduction to Marx if you don’t want to read Marx… bearing in mind that Marxist arguments are quite specific (system level … lots of isms… essentialist …) and might not be your cup of tea
May 15, 2025
Some chapters a bit dryer than others but this is a nice book for when your coworkers want to talk about AI all day
October 14, 2025
Putting this one on my Xmas gift list so I can mark up my own copy. Extremely clear and compelling analysis of technology and capitalism, I especially enjoyed the chapter on innovation.
May 3, 2025
I’m sorry to report the work is never done. This also means change is not only possible but always happening. The real movement keeps marching.
Materialists know that society does not exist as a series of static events until we reach an endpoint. Even if utopia were achieved, it would also have to be actively maintained against the entropy of decay and disorder. The end of history is a thought experiment turned into a mass delusion. It is neither possible nor desirable. We should never want to reach a stanle equilibrium where the decisions and actions from the past are locked in place forever. Real utopias are found in dynamic mechanisms of social coordination that always secure the changing needs if everybody and meet the changing desires of new generations.
Idealists are adept at selling a different story - one that is much easier and, superficially, more satisfying: where the arc of progress takes us, eventually and inevitably, to our final destination. It’s just up to us how fast we accelerate down the track. But this is a hollow, fleeting vision that depends upon an endless parade of empty promises, ephemeral vaporware, speculative extraction, and unfulfilled expectations - yet also one that is powerful and pervasive. It reveals a deeply flawed relationship to the future. Thise futurists create a marketplace of imaginaries, then eliminate all competition and monopolize it with their own inferior ideas.
I call this the Tinkerbell effect: speculative technologies only exist when we believe hard enough and clap loud enough. If we stop believing and clapping, then they can start fading away, becoming more immaterial by the moment until they disappear.
Ja to zovem car-je-gol efekt, ne znam za tinkerbell.
Nothing is inevitable.
We cannot be afraid to turn their accusations back on them. Their own optimism is based on a belief that they will cone out on top. They restrict agency over the future to themselves and the start-up founders they fund, while pessimistically rejecting everybody else’s ability for self-determination and democratic organisation. The utopia they are building has no space for a publicthat wants to direct itself toward different ends and exert social control over technological change. […] They have become universal and normal; they are simultaneously utopias for the few who are enriched by then and various degreesof dystopia for most other people. […] Refusing to fight does not resolve the conflict. It just make things one-sided. The easiest way to win is by convincing people the battle is over, they have already lost.
Materialists know that society does not exist as a series of static events until we reach an endpoint. Even if utopia were achieved, it would also have to be actively maintained against the entropy of decay and disorder. The end of history is a thought experiment turned into a mass delusion. It is neither possible nor desirable. We should never want to reach a stanle equilibrium where the decisions and actions from the past are locked in place forever. Real utopias are found in dynamic mechanisms of social coordination that always secure the changing needs if everybody and meet the changing desires of new generations.
Idealists are adept at selling a different story - one that is much easier and, superficially, more satisfying: where the arc of progress takes us, eventually and inevitably, to our final destination. It’s just up to us how fast we accelerate down the track. But this is a hollow, fleeting vision that depends upon an endless parade of empty promises, ephemeral vaporware, speculative extraction, and unfulfilled expectations - yet also one that is powerful and pervasive. It reveals a deeply flawed relationship to the future. Thise futurists create a marketplace of imaginaries, then eliminate all competition and monopolize it with their own inferior ideas.
I call this the Tinkerbell effect: speculative technologies only exist when we believe hard enough and clap loud enough. If we stop believing and clapping, then they can start fading away, becoming more immaterial by the moment until they disappear.
Ja to zovem car-je-gol efekt, ne znam za tinkerbell.
Nothing is inevitable.
We cannot be afraid to turn their accusations back on them. Their own optimism is based on a belief that they will cone out on top. They restrict agency over the future to themselves and the start-up founders they fund, while pessimistically rejecting everybody else’s ability for self-determination and democratic organisation. The utopia they are building has no space for a publicthat wants to direct itself toward different ends and exert social control over technological change. […] They have become universal and normal; they are simultaneously utopias for the few who are enriched by then and various degreesof dystopia for most other people. […] Refusing to fight does not resolve the conflict. It just make things one-sided. The easiest way to win is by convincing people the battle is over, they have already lost.
May 14, 2025
My data? Mined. My Crypto? gone. My Value? Extracted.
January 28, 2025
read 4 school but it was great.
August 22, 2025
The book is a collection of essays that Jathan wrote to be standalone, but connects from the underlying theme of how complex technology has interwoven into every crevice of our lives. While not explicitly mentioned, the essays are written to make you think of how the models which the title of the book comes from, are both reacting and partaking in each of the analysis of technological influence Jathan notices in our lives.
It does not read like a traditional book, but it does a great job to provide Jathans profound insight into how technology is both a tool for industrial advancement and also a mechanism to further accelerate capitalistic exploitation, which is meant to allude to the mechanic and the luddite model respectively.
I found it an easy read and after reading technofeudalism, by yanos varoufakis, agreed more with jathan on how capitalism is not evolving into another economic structure but rather technology is just further enhancing the rentier proclivities that capital owners are conditioned into exploiting. This is further proven by Jathans analysis on AI which he makes it clear is not something that will replace literally worker like companies want you to think.
It was a great read and I hope to pick up his other books!
It does not read like a traditional book, but it does a great job to provide Jathans profound insight into how technology is both a tool for industrial advancement and also a mechanism to further accelerate capitalistic exploitation, which is meant to allude to the mechanic and the luddite model respectively.
I found it an easy read and after reading technofeudalism, by yanos varoufakis, agreed more with jathan on how capitalism is not evolving into another economic structure but rather technology is just further enhancing the rentier proclivities that capital owners are conditioned into exploiting. This is further proven by Jathans analysis on AI which he makes it clear is not something that will replace literally worker like companies want you to think.
It was a great read and I hope to pick up his other books!
December 16, 2025
Maybe I should have read this sooner - I'm caught between this book being really prevalent and also being just about the status quo. That being said, it did enforce that we, people of society, are the catalysts for any change, because those in charge of technologic advances certainly won't make changes that are for us.
This book was a lot of "AI bad, big business bad," which we, like, already know? I did learn a bit about what Luddites really did, who they really were. I learned more about VC's, how they work, and how futurists play a role in the technocratic future.
I did feel like someof the language Sadowski used was inflated and a lot of his accusations of systems being biased didn't seem to have stats to back it up - they were "historical". Okay, well, I'd like the history, please.
Some good points about not taking everything the technocrats say as gospel, which is a good point. 3 stars.
This book was a lot of "AI bad, big business bad," which we, like, already know? I did learn a bit about what Luddites really did, who they really were. I learned more about VC's, how they work, and how futurists play a role in the technocratic future.
I did feel like someof the language Sadowski used was inflated and a lot of his accusations of systems being biased didn't seem to have stats to back it up - they were "historical". Okay, well, I'd like the history, please.
Some good points about not taking everything the technocrats say as gospel, which is a good point. 3 stars.
May 29, 2025
A strong and accessible Marxist introduction to "technological capitalism" today. Themes and insights will be familiar to readers of Zuboff, Mejias & Couldry, O'Neil, Ruha Benjamin, etc.
To me the most intriguing take-away: engaging in a ruthless criticism of technology and capitalism today requires the metaphorical skillset of both the mechanic and the luddite. Mechanic, because we need to understand at a basic level the material workings of technology. Luddite, because we need to discern when technology does not operate in the service of societal progress which then requires technological refusal and non-use.
Individual chapters cover the topics of innovation, data, rentiership, labour, risk, and futuring.
To me the most intriguing take-away: engaging in a ruthless criticism of technology and capitalism today requires the metaphorical skillset of both the mechanic and the luddite. Mechanic, because we need to understand at a basic level the material workings of technology. Luddite, because we need to discern when technology does not operate in the service of societal progress which then requires technological refusal and non-use.
Individual chapters cover the topics of innovation, data, rentiership, labour, risk, and futuring.
May 3, 2025
This book is a great introduction to theory without having to read a book from the 1860s. It’s easy enough to comprehend that I think you could hand it to plenty of people who aren’t overtly interested in politics. It puts words to the gut feeling you have telling you that AI, Web3, the Metaverse, etc. are all somehow part of the same scam.
August 7, 2025
Exceptional. A cover-to-cover treasure trove of history, analysis, and useful tools for navigating our techno-capitalist world.
Strong recommendation to everyone, no matter your knowledge level of the tech sector or anti-capitalist ideas, you will come away from this book with new knowledge, perspective, and hope.
Strong recommendation to everyone, no matter your knowledge level of the tech sector or anti-capitalist ideas, you will come away from this book with new knowledge, perspective, and hope.
December 13, 2025
While I enjoyed Too Smart more, there are numerous chapters in this book that provide deep thought provoking criticisms of capitalism enacted through technology. The chapters on Risk and Future in particular are heady, but the chapter on Landlords I was my favorite. Will have to purchase and think about it more.
April 28, 2025
Hard to tell if I only enjoyed this book because it affirms and expands upon many if my prior views, but whatever.
I thought some incisive points were made. I just wish they were more fleshed out at times.
I thought some incisive points were made. I just wish they were more fleshed out at times.
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July 9, 2025Lays out some nice materialist critique of tech. A nice sort of foundational text, it was much more approachable than I anticipated, and I definitely feel more engaged with the methods after this one.
September 26, 2025
by way of library availability, i read this and Empire of AI at the same time, and this was like a way more tedious cousin. really liked the essay on VC and innovation, everything else was too theoretical for my taste. also maybe too much reading about AI at once.
December 15, 2025
Book does not add novel insight into any of the subjects discussed. I like the spirit of the book and it is harmless but does not deliver anything notable. There are more thought provoking and comprehensive treatments elsewhere.
January 26, 2025
The mechanism of Mechanic and Luddite do not appear as a theme in the whole book. Instead a consistent description of the political economy of modern technology companies.
February 16, 2025
Great read to understand the current tech oligarchy
September 20, 2025
Wonderful synthesis of all the different ways tech is being used as capital.
November 25, 2025
Sadowski does a good job at framing these ideas with a fairly predictable tropes of critical theory. I think that this is a strength for readers who are already familiar. The primary issue i have with this work is that it quite badly misrepresents both the technology and the industry at many points from what i understand to be a lack of intimacy with what is actually happening in silicon valley. I think that the scope of this book was probably abit too grand... idk.
July 6, 2025
2.75 Essentially the manner in which the author chose to organize this book neutered any power. Also, it never felt like "A Ruthless Criticism...". It was dry, and felt like a masters thesis. You want examples of 'Ruthless Criticism' of capital and systems, look to Mr. Parenti, Ms Alexander, or the master, Mr. Chomsky.
It may simply be that I have read too many better books that overlap substantially with this subject, and I therefore found nothing new here, especially when the potential of the title was left unfulfilled. You may want to check out Blood In The Machine, Technofeudalism, Superbloom or Weapons of Math Destruction if this topic is of interest to you. Or you may love this book... what does it matter what I think?
Apologies for the brief review but I just didn't have it in me to attempt to rewrite my entire damned review after the app crashed and I lost everything I had written!
It may simply be that I have read too many better books that overlap substantially with this subject, and I therefore found nothing new here, especially when the potential of the title was left unfulfilled. You may want to check out Blood In The Machine, Technofeudalism, Superbloom or Weapons of Math Destruction if this topic is of interest to you. Or you may love this book... what does it matter what I think?
Apologies for the brief review but I just didn't have it in me to attempt to rewrite my entire damned review after the app crashed and I lost everything I had written!
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