RE: https://mamot.fr/@pluralistic/116219642373307943
I wish I could recommend this piece more, because it makes a bunch of great points, but the "normal technology" case feels misleading to me. It's not _wrong_, exactly, but radium paint was also a "normal technology" according to this rubric, and I still very much don't want to get any on me and especially not in my mouth
For me, this is the body horror money quote from that Scientific American article:
"participants who saw the AI autocomplete prompts reported attitudes that were more in line with the AI’s position—including people who didn’t use the AI’s suggested text at all"
So maybe you can't use it "responsibly", or "safely". You can't even ignore it and choose not to use it once you've seen it.
If you can see it, the basilisk has already won.
But, as Cory puts it:
"""
It is nuts to deny the experiences these people are having. They're not vibe-coding mission-critical AWS modules. They're not generating tech debt at scale.
"""
I had a very visceral emotional reaction to this particular paragraph, and I find it very important to refute. Here are two points to consider:
1. YES THEY ARE.
They are vibe-coding mission-critical AWS modules. They are generating tech debt at scale. They don't THINK that that's what they're doing. Do you think most programmers conceive of their daily (non-LLM) activities as "putting in lots of bugs"? No, that is never what we say we're doing. Yet, we turn around, and there all the bugs are.
With LLMs, we can look at the mission-critical AWS modules and ask after the fact, were they vibe-coded? AWS says yes https://arstechnica.com/civis/threads/after-outages-amazon-to-make-senior-engineers-sign-off-on-ai-assisted-changes.1511983/
Furthermore, it is not "nuts" to dismiss LLM user experiences. In fact, you must dismiss all subjective experience of LLM use as evidence of objective phenomena, even if the LLM user is yourself. Fly by instruments because the cognitive fog is too thick for your eyes to see.
Because the novel thing about LLMs, the thing that makes them dangerous, is that they are—by design—epistemic disruptors.
They can produce symboloids more rapidly than a thinking mind. Repetition influences cognition.
Could be sample bias, of course. I only loosely follow the science, and my audience obviously leans heavily skeptical at this point. I wouldn't pretend to *know* that the most dire predictions will come true. I'd much, much rather be conclusively proven wrong about this.
But I'm still waiting.
@glyph I'm honestly wondering just how much undiagnosed long COVID is playing into this.
I'm slowly recovering now, well as much as I can, but at the time I was painfully aware weird stuff was happening to my brain because I got caught in the first wave in March 2020.
So I am wondering if the addictive effects of using these LLMs along with existing cognitive damage is a partial cause.
@crazyjaneway @glyph We had a client use it to give them permission to spam out their new thing, after we'd explained (and their local IT guy also explained) that if they did that on our servers we'd lock their account.
Which we then did. The client said, "ChatGPT said I could do it". The sycophancy combined with overconfidence is utterly frightening.
I don't particularly like it when my friends use it in their communication with me either.
@glyph this thread needs to be an essay, and then a research hypothesis.
I very much feel like I’m watching the last 35 years of my ever-enshittifying social network exposure, sped up 10x and replayed.
In 1991 I remember having the flash of insight - without the life experience to really go into it deeply then - that the way nascent social network tech constrained and shaped interaction was going to force a mass cognitive adaptation for which we were not ready.
In 2021, we were still suffering the consequences of that, and still not sufficiently adapted to have avoided whatever the fuck is now driving our geopolitical dystopia engine.
And then suddenly our devolved capacity for social cognition had to deal with the fact that dealing with any humans at any distance far enough away that you couldn’t *lick* them came with no assurance that there even was a human there.
@davidtheeviloverlord @MrBerard @kirakira @glyph
What a fantastic thread.
Not black or white, but flavoursome.
Makes you think huh?
Humans as programmable entities.
Does a keyboard feel the fingertips?
Or does it think it's a content creator?
#Ai is a #Cognitivehazard and we don't have a firewall.
And yet Doctorow thinks LLMs are great for him to use for copyediting. Maybe find a less hypocritical person to quote. All Gen AI horrifies me, I visualize environmental destruction with every "prompt."
@kirakira @glyph
https://floss.social/@sstendahl/116220713455956161
@bluewinds @delta_vee @kirakira @glyph I don't think the analogies are good because asbestos is a fantastic insulator, lead is a really helpful additive for petrol and makes fantastic pigments and is really convenient for piping... and the hidden side-effects are the problem. Whereas LLMs _don't_ deliver that primary benefit
LLMs are more like... cheap laminate flooring, produced with wood pulp harvested unsustainably from old-growth forests and made by grossly exploited factory workers overseas... superficially convenient when remodelling your kitchen and rapidly ubiquitous but also quite unsatisfying and a right faff to work around once it's established
@glyph @nils_berger
this study argues that it encourages cognitive outsourcing on a new level, which in long term period could result in getting used to less cognitive activity, at least for certain tasks.
link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646
@glyph @nils_berger
i think most people are just referring to these blog posts:
This is the link to download it:
https://dora.dev/research/2025/dora-report/
Not sure if there's a mirror
on that topic: i have a hypothesis for why the thing we currently call "chatbot psychosis" (for lack of a better term) happens; and it has to do with the very nature of LLMs, as probabilistic tools. by definition, LLMs encode semantic fields, relationships between words: how different words and phrases correlate. they do that so well in fact, given the absurd amount of data they were fed, that they can effectively de-anonymise people, purely from a few lines of unstructured text: https://arxiv.org/abs/2602.16800 it's no magic: they simply pick up on all the subtle quantifiable details in the way we write: the words we choose, the idioms we like, the way we construct sentences, our typos... sufficiently complex statistical analysis is enough to "fingerprint" anyone, it seems.
@glyph you know what that reminds me of?
Bloodletting and handwashing
@mason because medical practitioners were hard to convince of the impact. And they still don't do it as much as you think.
Science vs human belief, the belief usually wins
@glyph
I think there was a study about programmer productivity with LLMs that found that it's ~20% lower while subjectively being reported as ~20% higher?
I should have bookmarked it...
Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the February-June 2025 frontier affect the productivity of experienced open-source developers. 16 developers with moderate AI experience complete 246 tasks in mature projects on which they have an average of 5 years of prior experience. Each task is randomly assigned to allow or disallow usage of early 2025 AI tools. When AI tools are allowed, developers primarily use Cursor Pro, a popular code editor, and Claude 3.5/3.7 Sonnet. Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%--AI tooling slowed developers down. This slowdown also contradicts predictions from experts in economics (39% shorter) and ML (38% shorter). To understand this result, we collect and evaluate evidence for 20 properties of our setting that a priori could contribute to the observed slowdown effect--for example, the size and quality standards of projects, or prior developer experience with AI tooling. Although the influence of experimental artifacts cannot be entirely ruled out, the robustness of the slowdown effect across our analyses suggests it is unlikely to primarily be a function of our experimental design.
@glyph I like your breakdown in those articles.
I think that some of the more valuable stuff has been not when juniors prompt and don’t get value, but when seniors prompt, go do something else for a bit while the machine churns for a couple of minutes, and then come back to something that is pretty close to a good solution.
Think about a thing that might take you 15 minutes to kinda menially do (add some CLI bo flag that then needs to get passed down 3 layers in some spot for example)
@glyph lowering of activation energy is how I see that. And while I agree that the futzing is way undercounted (and that, IMO, a lot of this falls over in longer sessions and is just not worth it)… a strong dev who knows exactly what the solution is supposed to look like can get paper cut-y stuff cleaned up. A lot.
The “whine on slack about a thing being busted” turns into a fix, and most of that you can just go get a cup of water or review something in the meantime. Cool party trick at least
@raphael @glyph The thing that the LLM is getting you to not think about is that it shouldn't take passing things down three layers (much less more, which is more common). This is the boilerplate that everyone hates and the goal should be to remove the need for it at all, not produce more faster.
"The least worst way to use an LLM is to do something you already know how to do", now with the addendum that we don't know what we don't know.
@glyph “You must dismiss all experiences of LLM users”
This is where you lose me. There’s no universe in which I’m comfortable dismissing the lived experiences of people that categorically. The most important lesson I’ve learned from decades of activism is “believe people when they tell you about their experiences” — and I see no reason to change now. I’m not willing to give up my curiosity and empathy and I hope you aren’t either.
@jacob@social.jacobian.org @glyph@mastodon.social I think I'm currently at a point in my journey where I try very hard to believe people when they talk about what they have experienced internally, and have become increasingly sceptical of people's ability to judge accurately what actually happened and the results (in both cases for pretty much the same reasons as Glyph as I've noticed the difference between my #adhd internal experience and real world what actually happened).
So "using an LLM made me feel a god-like developer!" I'll completely take as your experience. "My productivity went up by 15 times after I started using agents" (actual claim I have seen) will leave me asking for hard evidence and possibly a scientific study.
It's awkward that we use 'experience' to cover both, and I had the same reaction you're expressing when I read that section but assuming (from the context) that Glyph means the second type of experience I think he has a strong argument, if not the clearest wording.
Glyph
Akido37
Esther Payne 
Frances Perkins was right
Niels Abildgaard
Johanna, CanCon variety
alys
happyborg
Tim Ward ⭐🇪🇺🔶 #FBPE
Im Having A Good Day (assertive)
Will Berard 🫳🎤🫶
D. G. Marshall
Wulfy—Speaker to the machines
Baral'heia Stormdancer ΘΔ🐲
Kim Crawley 😷 (she/her)
Raymond Neilson
BlueWinds
jack
nils_berger
BB
Hindley–Milner Panda
George B
Antoine Leblanc 
Thomas Depierre
Mason Loring Bliss
Sam Vines
sabik
Raphael
Russell
LR
jacobian
Michael Newton