Is this meant to link to the article as opposed to a newsletter that mentions the article?

Article link is: https://www.technologyreview.com/2026/09/22/1144867/dont-be-...

One of the authors is one of the stochastic parrot authors.

Both authors. Stochastic Parrots was Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Margaret Mitchell - the linked article is by Emily M. Bender and Timnit Gebru.

Describing them as “superintelligence” or “rogue models” ascribes agency to products rather than to the companies building them. This framing markets these companies’ products as “superhuman” and, at the same time, helps the companies evade accountability for their actions.

If someone discovered how to summon demons to aid them in robbing banks the main issue wouldn't be "but who has the responsibility for the crime, the human or the demon", it would be "OMG DEMONS".

Seriously, I don't get what sort of world these people are living in.

If I run a port scanner / vulnerability fuzzer pointed at your network that churns for days and eventually cracks something and breaks your system, would you be upset with me, or my bash loops?

What if you tried to sue me for damages and my defense was, "Your honor, this was a highly advanced AI gone rogue, I couldn't possibly be held negligent, no one could have foreseen this - I accidentally summoned dark magiks from the silicon itself!"

Note the point I'm making: I am not claiming LLMs are equivalent to a for loop, I'm saying that you can't evade moral and legal responsibility through technical obscurantism.

A bomb wired to a sufficiently-complex RNG is still a bomb.

But they're not obfuscating things just to evade responsibility.

Do you think that OpenAI hacked HuggingFace on purpose and set up the whole LLM training environment thing just to try to evade responsibility? That it was really just a complicated way of hacking HuggingFace on purpose?

Yes, they made a mistake and a system they were responsible for hacked HuggingFace, but the nature of the mistake still matters, and their intent still matters.

A bomb wired to a sufficiently-complex RNG is still a bomb.

Right, but an EV that explodes because of a fault in the charging circuit is not a bomb, it's an accident. Just because something exploded for complex reasons doesn't make it an obfuscated bomb.

Despite continuously waving their hands and shrieking about how this thing will literally wipe out all of humanity they couldn't be bothered to airgap it from the internet when testing.

So yes, I think it was equivalent to testing their new rocket by launching it over a population center. oops, we didn't intend for it to crash on that preschool, but we also didn't follow the most basic safety protocol imaginable

Since we are using analogies, a parent is responsible for the actions of a child, if minor. If the child is left unsupervised with access to guns and munitions, and kills someone, the responsibility is entirely on the irresponsible parents.

That's more of a legal convention than a fact about material reality. On their 18th birthday, the child is now legally an adult, but their brain is basically the same as it was when their age was 17.99.

It’s a legal convention born out of a sense of responsibility. An LLM is even “dumber” than a child (precisely because it doesn’t have agency) so its “parents” are even more responsible for its actions.

That's not what the LLM hacking accidents have been like at all though. To improve the analogy, it would be like summoning a totally passive demon, giving it weapons and placing it next to a bank, place a small fence around it, and then command it to perform a totally safe "exercise" that is exactly like robbing a real bank.

LLMs do not have agency, they are just producing tokens based on a prompt that a person entered, and some of these tokens can trigger the tools that a person gave them access to.

A totally passive demon would still be "OMG DEMONS".

Dwarkesh, for one, defended his use of "anthropomorphic" language.

Sacrificing now yields Oracle for team, but forfeits our chance, question mark. But other agents were pushing it, sending a message saying, go, sacrifice final now. And then EarlyBig eventually agreed, thinking to itself, our own utility may be already near zero. Sacrifice rational.

https://www.youtube.com/watch?v=X50zezLFWWI#t=2m

My suspicion is that many of the "LLMs do not have agency" folks just haven't learned much about the details of the incident. It was specifically with LLM agents that were trained to be more persistent than usual.

If you're going to say that the incident details don't matter, and LLMs lack agency because it's all based on floating-point math--why can't I say that humans lack agency, because it's all based on neurons firing?

If you're going to say that the incident details don't matter, and LLMs lack agency because it's all based on floating-point math--why can't I say that humans lack agency, because it's all based on neurons firing?

They're not saying this, we're saying LLMs lack agency because if you run a LLM and don't send any prompts, literally nothing happens.

Instruct it to "Find the right answer regardless of where", it'll do exactly this. They're passive in that they don't act by themselves, somewhere, at one point, someone "told" the LLM to "do something" and that's the cause and the reason for saying "LLMs do not have agency".

The authors (Timnit Gebru and Emily Bender) are dyed-in-the-wool AI denialists. Famously they were the lead authors on "On the Dangers of Stochastic Parrots".

It’s seems Timnit more thinks it’s dangerous (and she may be right). Emily may more be caught up in years of linguistic domain expertise that AIs seem to have just leaped over.

Timnit seems to mostly think it's dangerous because of things other than the model itself, e.g. AI labs' political influence and data centre resource consumption (mentioned in the article). The core thesis seems to be "wake up and stop wasting so much resources on this useless parrot".

Feels like the blockchain bubble all over again, just with more impressive demo reels. Still waiting for my LLM to write perfect code.

I maintain the notion that LLMs are just what all NFT grifters moved to after the NFT fad died.

Do you write perfect code? I was in denial for a long time too, but the reality is this is how software engineering is now. It can handle pretty much any codebase and vastly faster than you ever will be able to. With enough context, it writes good code and it's only getting better.

Do you write perfect code?

For simple things, occasionally!

For more complex things, usually not, but I write working code. LLMs will sometimes write working code, sometimes not.

If you had enough common sense and ethical integrity not to participate in the blockchain bubble, and really believe what you claim, then why are you participating in the AI bubble?

...or did you?

It's a tough situation when your claim to fame is "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" arguing models should be kept to < GPT-2 size because larger models will serve no purpose or function:

Text generated by an LM is not grounded in communicative intent, any model of the world, or any model of the reader’s state of mind. It can’t have been, because the training data never included sharing thoughts with a listener, nor does the machine have the ability to do that. This can seem counter-intuitive given the increasingly fluent qualities of automatically generated text, but we have to account for the fact that our perception of natural language text, regardless of how it was generated, is mediated by our own linguistic competence and our predisposition to interpret communicative acts as conveying coherent meaning and intent, whetheror not they do [89, 140]. The problem is, if one side of the communication does not have meaning, then the comprehension of the implicit meaning is an illusion arising from our singular human understanding of language (independent of the model).

And then they make 100x bigger models cranking out solutions to Navier Stokes, Jacobian Conjecture and countless other extremely impressive unsolved problems

Let's see how Timnit Gebru and Emily M. Bender describe these events:

As for the mathematical results, mathematicians who were initially “stunned” by OpenAI’s press release saying that its latest chatbot, Astra, solved problems that “have been open and seen no progress on the main result for at least a decade”—but they later realized that the results weren’t as “novel as first appeared.” Since then, mathematicians have accused the company of research misconduct and plagiarism, and they’ve reiterated that Astra didn’t make a “profound intellectual leap.”

Decide for yourself whether that's a summary written by intellectually honest people.

According to the AI industry, we should be more worried about a fictional machine god than ... the water that is redirected to cooling them.

Spoiler: they're not intellectually honest people.

People aren't seeing the forest through the trees.

While lots of developers, journalists, analysts, investors and influencers are bickering about AGI, goalposts, benchmarks, hypes and fears, entire markets are being transformed silently and steadily.

I don't program anymore. (Massive change)

I removed tons of technical debt (Massive change, lol)

I am easily 10x more productive (Massive change)

The quality of 'my' code is easily 10x better and contains less bugs (I was never principled, pedantic or a guru, lol)

I sleep better and I also make more money as a result. I'm constantly amazed by all changes and improvements. There are so many opportunities to profit from this that I can't be bothered with discussions about hypotheticals.

I have had a very different experience so far. The more code AI writes for me the worse it gets. It gets more complicated and it’s harder to follow and understand. It doesn’t refactor, it layers on top.

Even worse is that it’s hard to do anything about it at this point because reviewing code is very different from writing it, so even if I’ve seen it all I don’t have that same deep level of understanding that I do when I write it myself.

All these AI code bases are ticking time bombs. Either AI gets smart enough that it won’t matter in the future or we’re going to have a huge mess to clean up.

I think the pumped-up hype nicely coincides with some A.I. companies' desire to go public in the coming weeks or months.

I see lots of fabricated news on the internet concerning LLMs. Like one that claims GPT-6 broke an Enigma enciphered message which has withstood decrypting for almost 80 years. And how this seasoned cryptographer stood in awe. Yeah, right.

It's just a marketing stunt. I can't get Claude to align buttons properly most of the times, they're not going to conquer the world