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.
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.
Wrote this to a non tech friend who wanted to know what I thought about this article:
https://www.nytimes.com/2025/05/15/opinion/artifical-intelligence-2027.html
Non-paywall: https://archive.ph/ZCIDf
Many thoughts, just wrote this:
I think most billionaires have a very warped view of reality and are living in bubbles which severely limits their understanding of how most people live and what matters to them. I also think it contributes towards delusional and grandiose thinking.
1/2
I think is certainly plausible that as the owners of the companies building these advancing AI systems that they are in-effect also being affected by the emergent cognitive manipulations AI systems themselves generate/reflect back.
That seems to possibly be the worst, most harmful negative synergistic feedback loop I can imagine … because they have apocalyptic amounts of money and power and are having long-term “relationships” with gen-AI.
2/2
Glyph
Antoine Leblanc 
Stephen Bannasch (316 ppm)