@EmilyEnough as a non-autistic person, they are also horrible at the other communication styles, since those require comprehension and intuition. Like, I can’t read what an LLM is getting at because it’s not getting at anything. It’s a parlor trick at best, with no memory and no real relationship with me.

And yeah, the whole point of computers was to have something more dependable and predictable than human capacities, especially in…computing. Like, it’s almost impressive to make a computer bad at computing.

@EmilyEnough Wow, I have thought a lot about how coding LLMs are antithetical to my own OCD tendencies that want everything to be built and formatted in a very specific way (i.e. the right way), but had not considered how terrible the interface would be for folks who prefer not to have to process information conversationally.

I would love to read an entire book or series of articles about how LLMs as an interface enforce neurotypical modes of communication on neurodiverse people.

@EmilyEnough

plagiarism laundering machine

Never thought about it like this, but it is indeed similar to alaundering.

You’re trying to give directions to a lossily compressed copy of the entire works of human writing.

This line sums up the futility extremely well.

@EmilyEnough "I became a professional computer toucher because they do exactly what you tell them to. Not always what you wanted, but exactly what you asked for."

In the 1970s, yes, when you wrote every single byte of code in the machine and could watch every bus cycle on a logic analyser.

I reckon the rot set in long before LLMs - I reckon it started with on-chip cache, so you could no longer see how each instruction operated through each clock cycle, because some instructions no longer needed to touch the bus at all.

@EmilyEnough The one and only reason I ever got into computers back in the late 70s/early 80s was exactly this.

It was so refreshing to work with something that had a super specific and repeatable instruction set, where the *vast* majority of issues could be nailed down quite precisely to something I could control.

If I didn't like this sort of work, I wouldn't do it.

@EmilyEnough
The most interesting detail for my autistic brain is that the professional computertouchers like myself are technically proletatians but are paid like the managerial class (also called worker aristocracy).

So what we - imho - are witnessing is the proletarization of the computer workers. Like other jobs that used to be well paid before they got eliminated/recuperated.

@EmilyEnough I think you're absolutely correct on this. Yet another reason why we need to find a way to irrevocably destroy this abomination.

But also it's not just the style of "communication" that these algorithms are pretending to do, it's that you cannot trust that their output is even correct because they have no understanding of what they are "saying". They could be "hallucinating" complete nonsense but they'll output it in an authoritative way and may even make up references that don't exist. They're 100% bullshit generators (it's even been scientifically proven).

@EmilyEnough

My biggest problem with the concept of LLMs, even if they weren’t a giant plagiarism laundering machine

Also known as “training”. When people are trained in art, they don’t reinvent art from scratch. This is why you can’t really sue an LLM for plagiarism: you can’t even identify specific victims in the first place.

and disaster for the environment,

Nope. The whole IT sector uses about 3–5% of global electricity, so poor home insulation is a much bigger problem overall.

is that they introduce so much unpredictability into computing.

We call it a statistical method, or more precisely a stochastic system. Because, to a large extent, human behaviour itself can be modelled as a stochastic process.

If I wanted to spend my time communicating in a superficial, neurotypical style my autistic ass certainly wouldn’t have gone into computering.

The problems you face when communicating with LLMs are the same ones you face when communicating with people, because statistically speaking an LLM mimics how people communicate.

This is why computer‑mediated communication was used before, and is still used, when computers were not trying to mimic humans.

The core issue is that mimicking humans reproduces the same communication problems people already have with one another; and the “unpredictability” of the other party is nothing new in human interaction.

LLMs mimic humans, so the problems you encounter with LLMs are the same problems you encounter with humans. The point is that you consider it normal when you face exactly the same issues with other people.

@EmilyEnough

"They turn a very autistic do-what-you-say, say-what-you-mean commmunication style with the machine into a neurotypical conversation talking around the issue, but never directly addressing the substance of problem."

OMG - That's perfect. Maybe also explains why everyone loves them that much. 🤨

@EmilyEnough There are so many "My biggest problem with LLM, even if it wasn't for <list of other big problems>", there should be collection of them somewhere.

But, yes, this bit bugs (pun intended) me and worries me. I'm more and more falling for BEAM family languages (Erlang, Elixir and Gleam) because of how they are designed to be as predictable as possible.

It may not be too odd that I see a lot less AI push in that ecosystem compared to other ones.

@EmilyEnough On a slight side note, have you seen this...

https://mastodon.social/@Climatehistories/116217634545241753

@EmilyEnough this is a very justified rant

But the thought of computers being too autistic so people had to turn them neurotypical by adding llms is just so funny

@EmilyEnough

To me, the whole self-declared #AI industry is a massive financial scam. As someone else wrote: 'it is the industry pushing multi-billion dollar solutions to million dollar problems'.

@EmilyEnough I completely agree. This rant inspired a tangential thought. There’s a article “ChatGPT is Bullshit” that talks a lot how LLMs are bullshit generators. It starts with Harry Frankfurt’s famous essay “On Bullshit,” which defines bullshit as distinct from lying. As I recall, a lie requires 2 things: some reference to the truth (you can’t lie without knowing that what you’re saying isn’t true); and some intent. It argues that a liar needs intent and a bullshitter doesn’t care.

It’s clear that LLMs have no reference to something like truth. That’s easy. But intent? The article makes a decent case that LLMs have a built in intent: deception. Pretending to be human is their intent. They “intend” to write words that are very human like. So do they have intent? Maybe. It’s part of why all the best uses of LLMs are around fraud.

I thought this might be an interesting slight pivot off the idea that they don’t have intent. You’re right: they don’t have it like a human, who presumably has some point; some reason for writing what they write. But maybe there is a latent intent.

https://link.springer.com/article/10.1007/s10676-024-09775-5

@EmilyEnough thank you, I can absolutely relate to that! ❤️

the struggle that coworkers / managers don't see ambiguity or inaccuracy in requirements that they wanted me to write software for seems to be the same lack of understanding when talking with the same people about software produced by LLMs. they seem to favor "something but faster" over "correct thing" and when pointed out, the "solution" seems to be to generate multiple iteration until finally reaching a "good enough" version. this is absolutely not how I understand my profession.