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this post was submitted on 08 Apr 2026
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The only way to know if LLM output is accurate is to know what an accurate output should look like, and if you know that, you don't need an LLM. If you don't know what an accurate output should look like, an LLM is equally likely to confidently lie to you as it is to help you, making you dumber the more you use it. The only other situation is if you know what an accurate output should look like, but you want an inaccurate one, which is a bad thing to encourage.
"Demonstrably useful" is a lie. It's a blatant and obvious lie. LLMs are so actively detrimental to their users, and society as a whole, that calling them useless is being generous. And even if they were the most beneficial thing on the planet, there is still no reason to use the billionaire's toxic Nazi plagiarism machine.
I empathize with your overall standpoint, but that's just plain wrong. There are a lot of problems where verifying an answer is much easier for a human (or non-LLM computer program) than coming up with a correct answer.
Anything that involves language manipulation, for example. I'll have a much easier time checking a translation from English to German for accuracy than doing the full translation myself, assuming the model gets most of it correct and I don't have to rewrite anything major (which is generally the case with current models). Or letting an LLM proof-read a text I wrote - I can't be sure it got everything, but the things it does find are trivial for me to verify, and will often include things that slipped past me and three other people who proof-read the same text. Less useful, but still applicable to the premise: Producing a set of words that rhyme with a given one. Coming up with new ones after the first couple that pop into your head gets pretty hard, but checking if new candidates actually do rhyme is trivially easy.
Moving on from language-stuff, finding security issues in software is a huge one - finding those is often extremely hard, but verifying them is mostly pretty straightforward if the report is well prepared. Models are just now getting good enough to reliably produce good security reports for actual issues.
Answering questions about a big codebase, where the actual value doesn't lie in the specific response the model gives, but pointing me to the correct places in the code where I can check for myself.
Producing code or entire programs is a bit more debatable and it depends heavily on the goal and the skill level of the operator whether complete verification is actually easier than doing it yourself.
Just a couple of examples. As I said I get where you're coming from, but completely denying any kind of utility does not help your cause at all, it just make you look like an absolutist who doesn't know what they're talking about.
If you know enough to verify a translation as accurate, or you have the tools to figure out an accurate translation through dictionaries or some such, then you know enough to do the translation yourself. If you don't, then I cannot trust your translation.
And if you can't trust the output to be comprehensive or correct, then why would you trust something like system security to an LLM? Any security analyst who deserves their job would never take that risk. You don't cut those corners.
Quick reminder: rhyming dictionaries exist. LLMs solved a solved problem, but worse.
Once again, even if the billionaire's toxic Nazi plagiarism machine was useful, it is so morally repugnant that it should never be used, which makes it functionally useless. This is an absolute statement, but trying to "um actually" that makes you look like either a boot-licker, a pollutant, a Nazi, a plagiarist, an idiot, or some combination of those.
I would rather look like an absolutist. How about you?
Correct. But it's going to take me a lot more work and time, possibly to the point of not being feasible and probably even matching the energy cost of using the LLM over the entirety of the task.
I wouldn't. I don't know where you got that. Adding LLM-based analysis to your toolkit to spot important issues that otherwise might not have been found is just that: an addition. Not replacing anything. And it is demonstrably useful for that at this point, there's just no denying that.
My point is that if you are this confidently wrong about the capabilities of LLM-based tools, then why should I believe you to be any less wrong about the moral and ethical issues you're raising? It looks like you're either completely misinformed or deliberately fighting a strawman for a part of your argument, so it gives anyone on the other side an easy excuse to just not engage with the rest of it and just dismiss it entirely. That's what I'm trying to get across here.
Surely, the energy cost to verify the translation would be the same as translating it? If you're struggling that much, why are you translating it at all? I cannot trust your translation.
If you tell an LLM to generate reports, it will, regardless of the actual quality of the environment. It doesn't know what's secure and what isn't. All you've shown it to do is convince the kinds of security analysts with a system so insecure as to have a LOT of good reports that their system is more secure than it is. Which is useless at best, detrimental at worst.
It's useless for translation. It's useless for security analysis. It's useless for rhyming (I notice you didn't mention that one). You're trying so hard to prove how useful it is, and your failure demonstrates how useless it is.
You can't condemn confident wrongness and defend LLMs. And you can't defend the billionaire's toxic Nazi plagiarism machine while questioning someone else's morals. You can't cherry-pick my argument and claim I'm the one fighting a strawman. ...Well, not if you're arguing in good faith.
Look, I'm not trying to argue against your moral stance. I'm neither saying it's wrong nor that it's outweighed by any usefulness, real or not. What I'm trying is get you to see that your claims about uselessness are undermining your moral argument, which would be a hell of a lot stronger if you were not hell-bent on denying any kind of utility! Because in the eyes of people that do perceive LLMs as useful (which is exactly the kind of people that need to hear about the moral issues), that just makes you seem out of touch and not worth listening to.
Have you looked at any of the four links I provided? You might be working on old data here because it's a very recent development, but a lot of high profile open source maintainers are saying that AI-generated security reports are now generally pretty good and not slop anymore. They're fixing actual bugs because of it, and more than ever. How can you call that useless?
Uh, no? Have you ever translated something? Verifying a translation happens mostly at attentive reading speed, double it for probably reading it twice overall to focus on content and grammar separately, plus some overhead for correcting the occasional flaw and checking one or two things that I'm unsure about from the top of my head, so for the sake of argument let's say three times slower than just reading normally. I don't know about you, but three times slower than reading is still a lot faster than I would be able to produce a translation from scratch, weighing different word options against each other, how to get some flow into the reading experience, etc. If I'm translating into a language that I'm fluent but not native in that takes even longer, because the ratio between my passive and active vocabulary is worse. I can read (and thus verify) English at a much more sophisticated level than I'm able to talk or write, because the words and native idioms just don't come to me as naturally, or sometimes even at all without a lot of mental effort and a Thesaurus. LLMs are just plain better at writing English than I have any hope of achieving in my lifetime, and I can still fully understand and verify the factual, orthographic and grammatical correctness of what they're outputting easily. Those two things are not mutually exclusive.
Yeah, because I'm focusing on the more relevant things. I disagree that it's completely useless for rhyming, but it is a much weaker and more contrived point than the others, and going into that discussion would just derail things more for no added value. Also, funny that you call me out for that, when you just fully ignored two use cases I mentioned in my initial comment (LLM proofreading texts, and answering questions about unfamiliar code bases). Those have a lot of legitimate utility for someone who's not aware of or doesn't care about the moral issues. And once again, that's my point here - those people will not listen if they perceive you as talking about a fictional world where LLMs are completely useless, which fails to match up with their experience.
Sometimes i use AI even if i know the answer because i am a lazy person, and holy shit, i can confirm that it lies a lot and tells wrong shit