The Left Doesn't Hate Technology, We Hate Being Exploited

Source: Hacker News

Overview

Over the past week I’ve watched left‑wing commentators on Bluesky—the niche short‑form blogging site that serves as an asylum for millennials driven insane by unfettered internet access—discuss the idea that “the left hates technology.”
The conversation has centered around a few high‑profile news events in the world of AI:

• A guy who works at an AI startup wrote a blog claiming that AI can already do your job.
• Anthropic, the company behind the AI assistant Claude, has raised $30 billion in funding.
• Someone claimed an AI agent wrote a mean blog post about them, and then a news website was found to have used AI to write about this incident and included AI‑hallucinated quotes.

Somewhere in this milieu of AI hype a blog posted on Monday declared that “the left is missing out on AI”, positioning generative AI as the only technology that matters.

Why the Claim Is Confusing

As a hard‑leftist and gadget lover, the idea that my political ideology is synonymous with hating technology is baffling. Every leftist I know has a hard‑on for high‑speed rail, mRNA vaccines, and other progressive tech. Yet the “left is missing out” blog treats generative AI as the sole yardstick of techno‑optimism.

I will spare you some misery: you do not have to read the original blog—it is, frankly, fucking stupid as hell, constantly creating ideas to shadow‑box with and then losing to them. It appears to be an analysis of anti‑AI thought primarily from academics, especially Professor Emily Bender, who dubbed generative AI “stochastic parrots,” but it fails to actually refute her argument.

The Blog’s Core Argument (and My Response)

“[Bender’s] view takes next‑token prediction, the technical process at the heart of large‑language models, and makes it sound like a simple thing — so simple it’s deflating. And taken in isolation, next‑token prediction is a relatively simple process: do some math to predict and then output what word is likely to come next, given everything that’s come before it, based on the huge amounts of human writing the system has trained on.”
“But when that operation is done millions, and billions, and trillions of times, as it is when these models are trained? Suddenly the simple next token isn’t so simple anymore.”

My response: It is still exactly as simple as it sounds. Doing the same math billions of times does not magically make the base process more substantial. It remains a machine performing statistical prediction—fancy pattern‑matching, not reasoning.

The blog continues:

“All of this blathering is in service to the idea that conservative sectors are lapping the left on being techno‑optimists.”

By the time I reached the end of the page I was longing for sweet, merciful death. The crux of the author’s argument is that academics have a monopoly on terms like “understanding” and “meaning” and that they’re too slow (peer‑review, publishing) to grasp AI’s potential value.

“Training a system to predict across millions of different cases forces it to build representations of the world that then, even if you want to reserve the word ‘understanding’ for beings that walk around talking out of mouths, produce outputs that look a lot like understanding,” the blog reads, without presenting any evidence of this claim.
“Or that reserving words like ‘understanding’ for humans depends on eliding the fact that nobody agrees on what it or ‘intelligence’ or ‘meaning’ actually mean.”

Sure, words like understanding and meaning have philosophical definitions, but philosophy is an academic discipline that goes back to ancient Greece. There are a few commonly understood, lay‑person‑friendly theories of existence—e.g., if I ask a sentient being how many “R”s there are in the word “strawberry,” it should be able to use logic to determine that there are three, not two. Generative AI frequently fails this test (see example).

Other Points the Essay Raises (and Leaves Unaddressed)

• Credibility problem in the tech sector: The author notes that “it’s hard to argue against that,” but offers no concrete rebuttal.
• Critique of Bender: The essay says Bender is “entitled to her philosophy,” yet provides no substantive counter‑argument.

If the goal is to prove that the left is lagging on techno‑optimism, the essay does not succeed. It merely forces the reader to wade through a lot of unsubstantiated blather.

The Real Political Landscape

All of this blathering is in service to the idea that conservative sectors are lapping the left on being techno‑optimists, but that’s not the whole story.

• It is true that forces of capital have generally adopted AI as the future, whereas many workers have not.
• However, this is not a simple left/right distinction.

I’ve lived through an era when Silicon Valley presented itself as the gateway to a utopia where people work less and machines automate most manual labor. When tech‑sector companies monopolize an industry—think rideshare giants Uber and Lyft—instead of less work and more relaxation, the result is often more work: workers are forced to compete with robots that are specifically coming for their jobs (AP News article).

Conclusion

The claim that “the left hates technology” is an oversimplification.

• Many left‑leaning people embrace progressive technologies (high‑speed rail, mRNA vaccines, renewable energy).
• The debate over generative AI is nuanced and cannot be reduced to a partisan litmus test.

The blog I critiqued fails to provide solid evidence, relies on vague philosophical jargon, and ultimately does not prove that the left is “missing out” on AI. The real issue is who controls the technology and who benefits—a question that cuts across the traditional left/right divide.

Note: The original piece ends abruptly (“Regardless of political leanin…”).

People vs. Business Attitudes Toward AI

• General public: People in general don’t like AI – see the Pew Research study.
• Businesses: Companies are increasingly forcing AI on their workers and clients – see the Stanford AI Index report.

“Fully Automated Luxury Communism” vs. Cyberpunk Reality

Instead of creating an environment for “Fully Automated Luxury Communism,” an incredibly optimistic idea articulated by British journalist Aaron Bastani in 2019, these technologies are creating Cyberpunk 2077.

“Part of the reason I made a hard left‑wing turn was because I was burned by my own techno‑optimism.” – Aaron Bastani

Note: Although the author of this blog references Bastani’s vision of an automated communist future as the position leftists should be taking, Bastani does not appear to be on board with generative AI – see his tweet.

Advertising in the AI Hype Cycle

Friend of Aftermath Brian Merchant points out something important about all this discourse: most of this conversation serves as advertising.

“We’re in the midst of another concerted, industry‑led hype cycle, this time driven more visibly by Anthropic, which just landed a $30 billion investment round. This time the hype must transcend multibillion‑dollar investment deals: it must also raise the stock of AI companies ahead of scheduled IPOs later this year and help lay the groundwork for federal funding and/or bailout backing.” – Merchant writes

Personal Journey from Techno‑Optimism to Critique

• Hard left‑wing turn: I was burned by my own techno‑optimism.
• Generational context: I am part of a generation that believed it could change the world – see the Ringer article.
• Political disappointment: The first presidential election I voted in featured a platform of “Hope and Change” that failed to deliver, and that administration embraced Silicon Valley in its ambitions – read the NY Times piece.
• Techno‑cynicism: Techno‑cynics are all just wounded techno‑optimists.

Why I Criticize AI

1. Money and power: Following those two things has made me a critic of AI and the claims of corporations like Anthropic and OpenAI.
2. Corporate self‑interest: Tech companies say things because it may benefit their bottom line.
3. Political continuity: After President Obama allied with Silicon Valley, these same companies have been happy to suck up to President Trump – see the Data & Society analysis.
4. Beneficiary question: “Who benefits from this?” is the core of my criticism. The proliferation of the technology mainly benefits the people making money off it, whereas a robust, fast train network would provide far more obvious benefits to working people in my country.

The Luddites Re‑examined

Like Merchant, I increasingly feel the Luddites were right, a view bolstered by leftist theory. However, as Merchant argues, Luddites did not hate technology – they were skilled workers who understood its potential to exploit them.

• Illustrative moment: Watching Brian Merchant destroy a consumer‑grade printer with a sledgehammer at a book reading several years ago unlocked this understanding for me.
• Printer critique: Does that printer actually make printing easier, or is it primarily a device that eats up proprietary ink cartridges and begs me for more? (See the printer‑suck article.)

Leftist Questions About AI

1. Does this improve my life?
2. Does this improve my livelihood?

So far, the answer for everyone who doesn’t stand to get rich off AI is no. I’ve been working as a writer for the past decade and watching my industry shrivel up and die as a result. You’ll excuse me if I, and the rest of the everyday people who stand to get screwed by AI, aren’t particularly excited by what AI can offer society.

“From each according to his ability, to each according to his need.” – Karl Marx

The creation of a world where that principle is possible is not dependent on advanced technology but on human solidarity.