this post was submitted on 22 Feb 2026
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Same with the internet. Fuels billionaires, destroys the environment with data centers and cables, kills libraries and textbook research, spreads nazi propaganda. We need to stop using technology in general.
There are things you can do with the Internet that are impossible to do without the Internet. Everything you mentioned is very real harm that the Internet does to humanity in the world - even if you meant it sarcastically - but that harm has to be weighed against the benefits the Internet provides that can't be replicated by anything else.
There's nothing a LLM can do that a human can't. The only thing LLMs are good at is convincing managers to replace human employees with LLMs. Because even though LLMs do a worse job than any human employee, they're cheaper and won't unionize.
The cost-benefit analysis for society is very different.
Lets see a standard problem I'm randomly making up using a free AI, you tell me if this kind of thing can be useful to someone:
If I have a bucket that is 1 meter tall and 1 meter wide how much volume can it hold?
The volume V of a cylinder can be calculated using the formula:
V=πr2h
Where:
r is the radius, h is the height.
In this case, the bucket is 1 meter tall and 1 meter wide, which means the diameter is 1 meter. Therefore, the radius r is:
r=21 meter=0.5 meters
Now substituting the values into the volume formula:
V=π(0.5m)2(1m) V=π(0.25m2)(1m) V≈0.7854m3
Thus, the volume the bucket can hold is approximately 0.785 cubic meters.
Using llms for math questions is probably the worst usage for llms.
And all of this is easily calculated without ai. You can literally google it and let google do the math for you without ai.
Perhaps your right, though the AI also allows natural language or voice, and further explanations.
Its also eroding all the bullshit we used to do, like cover letters and things that had no reason to exist besides wasting someones time. So truth be told I'm a fan, even if it is a massively unprofitable bubble, I also recognize its limitations given its hallucinations so I understand it shouldnt be relied upon for useful work.
I won't argue about the value of explanation from a ~~lying~~ hallucinating machine.
But I like how your use case is "it does the things that I believe to be useless and time wasting for everyone involved. But instead of, pushing for the end of these time wasting acts, I waste a little less time with llms (instead of all of the time by not doing these time wasting acts) while still wasting the time of the reader." What an efficient use case! We should violate IP law, waste drinking water and energy for it!
The problem is many people liked how it was, it makes more work to do, makes it seem official. I believe in that book bullshit jobs, and think most people are winging it with performative bullshit.
What I saw recently at my work is people received something that looked like AI slop from the head boss and they laughed about it, which got back to the boss, who then defended himself that it wasn't AI.
So I'm hopeful that people are called out for wasting peoples time, and that long winded blobs of meaningless text become a firable offense.
What you've given is an example of a problem where an LLM is, by design, the wrong tool.
See, variation is built into LLMs. They're programmed to evaluate probable responses and select from them on the basis of probability - to simplify ridiculously, if a particular word follows another 90% of a time, in 90% of the content it generates the LLM will have that word follow the other, and in the other 10% it won't.
If you give an LLM the exact same prompt multiple times, you will get multiple different responses. They'll all be similar responses, but they won't be exactly the same, because how LLMs generate language is probabilistic and contains randomness.
(And that is why hallucination is an inherent feature of LLMs and can't be trained out.)
But math isn't language. Math problems have correct answers. When you use a software tool to answer a math problem, you don't want variation. You want the correct answer every time.
To solve a math problem, you need to find the appropriate formula, which will be the same every time. Then you use a calculator, which always gives the correct result. You plug the numbers into the formula and calculate the result.
What I'm getting at is, if you use a calculator to do the math problem yourself, and you put in the correct formula, you'll always get the correct result. If you use a LLM to generate the answer to a math problem, there is always a non-zero chance it will give you the wrong answer.
If you haven't looked up the formula yourself, you have no way to check the LLM's work, which means you can't trust the answer for anything important - so you have to look up the formula and check it with a calculator.
And if you have looked up the formula yourself, it's just as easy to use a calculator the first time and skip the LLM.
Right? This is what I'm getting at. An LLM can do some of the same things a human does, but it's always going to be worse at it than a human, because it's not conscious, it's not reasoning its way to a correct answer, it's just generating a string of linguistic tokens based on probabilities. And math problems might be the clearest possible example of this.
Thats well put, I'm under no naive assumption that LLMs are AI. Though I do think youre discounting the usefulness, as it did give the right answer, which is a fine use for average people doing basic math or whatever project theyre working on. I'm under no delusion that its replacing workers, unless someones job is writing fancy emails or building spreadsheets, and I do still think its a massive bubble.
Yeah, I get that it seems like a fine use for average people doing basic math. The nonzero chance of error could end up not mattering. But it could matter very much, depending on the use case. If you're asking an LLM the volume of a bucket, it's not a big deal. If you're asking an LLM "how many milligrams of this drug is the correct dose for a 80 kg man", that's a big fucking deal.
If people don't know LLMs can't be trusted to give the corect answer, they're not going to realize they need to do the math themselves in important use cases. And that is certainly not something Microsoft and Google are encouraging people to learn.
Then there's the efficiency issue - Big Tech spent trillions of dollars to develop and train machine learning processors, which perform quadrillions of energy-intensive processes per second, and they're being marketed to do a job that a 99 cent solar powered calculator from the 1980s can do better.
God, I just realized tax season is coming up. And after all the layoffs and political firings and general dogebaggery at the American IRS, they're going to have to deal with people using AI to do their taxes 😆
Found the Mennonite.