A thought that popped into my head when I woke up at 4 am and couldn’t get back to sleep…

Imagine that AI/LLM tools were being marketed to workers as a way to do the same work more quickly and work fewer hours without telling their employers.

“Use ChatGPT to write your TPS reports, go home at lunchtime. Spend more time with your kids!” “Use Claude to write your code, turn 60-hour weeks into four-day weekends!” “Collect two paychecks by using AI! You can hold two jobs without the boss knowing the difference!”

Imagine if AI/LLM tools were not shareholder catnip, but a grassroots movement of tooling that workers were sharing with each other to work less. Same quality of output, but instead of being pushed top-down, being adopted to empower people to work less and “cheat” employers.

Imagine if unions were arguing for the right of workers to use LLMs as labor saving devices, instead of trying to protect members from their damage.

CEOs would be screaming bloody murder. There’d be an overnight industry in AI-detection tools and immediate bans on AI in the workplace. Instead of Microsoft CoPilot 365, Satya would be out promoting Microsoft SlopGuard - add ons that detect LLM tools running on Windows and prevent AI scrapers from harvesting your company’s valuable content for training.

The media would be running horror stories about the terrible trend of workers getting the same pay for working less, and the awful quality of LLM output. Maybe they’d still call them “hallucinations,” but it’d be in the terrified tone of 80s anti-drug PSAs.

What I’m trying to say in my sleep-deprived state is that you shouldn’t ignore the intent and ill effects of these tools. If they were good for you, shareholders would hate them.

You should understand that they’re anti-worker and anti-human. TPTB would be fighting them tooth and nail if their benefits were reversed. It doesn’t matter how good they get, or how interesting they are: the ultimate purpose of the industry behind them is to create less demand for labor and aggregate more wealth in fewer hands.

Unless you happen to be in a very very small club of ultra-wealthy tech bros, they’re not for you, they’re against you. #AI #LLMs #claude #chatgpt

"I'm sorry! I'm a technology writer, which means I'm supposed to be encouraging you to throw hundreds of billions of dollars at the money-losingest technology in human history, AI. No one has ever lost as much money as the AI companies.

There is no way to operate one of Nvidia's big AI-optimized GPUs without losing money. The owners of these GPUs who have lost the least money are the ones who rushed into buying GPUs without ensuring they'd have electricity to power them, and have been forced to leave their GPUs to age in warehouses. The minute they plug in those GPUs, they'll start losing money, and the more they use them, the more money they'll lose.

I'm sorry. As a technology writer, I'm supposed to be telling you that this bet will some day pay off, because one day we will have shoveled so many words into the word-guessing program that it wakes up and learns how to actually do the jobs it is failing spectacularly at today. This is a proposition akin to the idea that if we keep breeding horses to run faster and faster, one of them will give birth to a locomotive. Humans possess intelligence, and machines do not. The difference between a human and a word-guessing program isn't how many words the human knows.

I'm sorry. I know that when we talk about "digital sovereignty," we're obliged to talk about how we can build more data-centres that we can fill up with money-losing chips from American silicon monopolists in the hopes of destroying as many jobs as possible while blowing through our clean energy goals and enshittifying as much of our potable water as possible.

I don't have any advice for how to do that. I'm sorry!"

https://pluralistic.net/2026/01/13/not-sorry/

#AI #GenerativeAI #LLMs #BigTech #AIBubble #Canada #USA

"I'm sorry! I'm a technology writer, which means I'm supposed to be encouraging you to throw hundreds of billions of dollars at the money-losingest technology in human history, AI. No one has ever lost as much money as the AI companies.

There is no way to operate one of Nvidia's big AI-optimized GPUs without losing money. The owners of these GPUs who have lost the least money are the ones who rushed into buying GPUs without ensuring they'd have electricity to power them, and have been forced to leave their GPUs to age in warehouses. The minute they plug in those GPUs, they'll start losing money, and the more they use them, the more money they'll lose.

I'm sorry. As a technology writer, I'm supposed to be telling you that this bet will some day pay off, because one day we will have shoveled so many words into the word-guessing program that it wakes up and learns how to actually do the jobs it is failing spectacularly at today. This is a proposition akin to the idea that if we keep breeding horses to run faster and faster, one of them will give birth to a locomotive. Humans possess intelligence, and machines do not. The difference between a human and a word-guessing program isn't how many words the human knows.

I'm sorry. I know that when we talk about "digital sovereignty," we're obliged to talk about how we can build more data-centres that we can fill up with money-losing chips from American silicon monopolists in the hopes of destroying as many jobs as possible while blowing through our clean energy goals and enshittifying as much of our potable water as possible.

I don't have any advice for how to do that. I'm sorry!"

https://pluralistic.net/2026/01/13/not-sorry/

#AI #GenerativeAI #LLMs #BigTech #AIBubble #Canada #USA

"Now, I know what you’re thinking. Ed, isn’t that exactly what’s happening here? We’ve got overvalued startups, we’ve got multiple unprofitable, unsustainable AI companies promising to IPO, we’ve got overvalued tech stocks, and we’ve got one of the largest infrastructural buildouts of all time. Tech companies are trading at ridiculous multiples of their earnings-per-share, but the multiples aren’t as high. That’s good, right?

No. No it isn’t. AI boosters and well-wishers are obsessed with making this comparison because saying “things worked out after the dot com bubble” allows them to rationalize doing stupid, destructive and reckless things.

Even if this was just like the dot com bubble, things would be absolutely fucking catastrophic — the NASDAQ dropped 78% from its peak in March 2000 — but due to the incredible ignorance of both the private and public power brokers of the tech industry, I expect consequences that range from calamitous to catastrophic, dependent almost entirely on how long the bubble takes to burst, and how willing the SEC is to greenlight an IPO.

The AI bubble bursting will be worse, because the investments are larger, the contagion is wider, and the underlying asset — GPUs — are entirely different in their costs, utility and basic value than dark fiber. Furthermore, the basic unit economics of AI — both in its infrastructure and the AI companies themselves — are magnitudes more horrifying than anything we saw in the dot com bubble.

In simpler terms, I’m really fucking worried, and I’m sick and tired of hearing people making this comparison."

https://www.wheresyoured.at/dot-com-bubble/

#AI #GenerativeAI #LLMs #DotComBubble #AIBubble #VC #VentureCapital #BigTech

"We shared details about Daniel’s story with psychiatrists, who said that the Meta AI-generated messages they reviewed displayed a concerning level of #sycophancy to a user expressing delusional thoughts."

https://futurism.com/artificial-intelligence/meta-ai-glasses-desert-aliens

#AI #LLMs #MentalHealth #AIPsychosis

A thought that popped into my head when I woke up at 4 am and couldn’t get back to sleep…

Imagine that AI/LLM tools were being marketed to workers as a way to do the same work more quickly and work fewer hours without telling their employers.

“Use ChatGPT to write your TPS reports, go home at lunchtime. Spend more time with your kids!” “Use Claude to write your code, turn 60-hour weeks into four-day weekends!” “Collect two paychecks by using AI! You can hold two jobs without the boss knowing the difference!”

Imagine if AI/LLM tools were not shareholder catnip, but a grassroots movement of tooling that workers were sharing with each other to work less. Same quality of output, but instead of being pushed top-down, being adopted to empower people to work less and “cheat” employers.

Imagine if unions were arguing for the right of workers to use LLMs as labor saving devices, instead of trying to protect members from their damage.

CEOs would be screaming bloody murder. There’d be an overnight industry in AI-detection tools and immediate bans on AI in the workplace. Instead of Microsoft CoPilot 365, Satya would be out promoting Microsoft SlopGuard - add ons that detect LLM tools running on Windows and prevent AI scrapers from harvesting your company’s valuable content for training.

The media would be running horror stories about the terrible trend of workers getting the same pay for working less, and the awful quality of LLM output. Maybe they’d still call them “hallucinations,” but it’d be in the terrified tone of 80s anti-drug PSAs.

What I’m trying to say in my sleep-deprived state is that you shouldn’t ignore the intent and ill effects of these tools. If they were good for you, shareholders would hate them.

You should understand that they’re anti-worker and anti-human. TPTB would be fighting them tooth and nail if their benefits were reversed. It doesn’t matter how good they get, or how interesting they are: the ultimate purpose of the industry behind them is to create less demand for labor and aggregate more wealth in fewer hands.

Unless you happen to be in a very very small club of ultra-wealthy tech bros, they’re not for you, they’re against you. #AI #LLMs #claude #chatgpt

Do #AI "reasoning" models think reflectively?

Prompting #LLMs to reflective on and make a plan to correct their faulty intuitions on reflection tests resulted in "chance" improvement, lacking "principled application of reason".

"Illusions of reflection": https://doi.org/10.48550/arXiv.2510.18254

New preprint!
I've written a paper examining the notion of 'reasoning' across psychology, philosophy, and AI (focussing on use prior to the advent of LLMs!) in order to help clarify the debate about whether #LLMs can 'reason'.

Specifically, it's not just trying to explain why different people come to such radically different assessments, but also why proponents of diametrically opposed views might find their own assessment obvious in ways that will be not shared by others.

all comments welcome!

https://zenodo.org/records/18231172