I work at an intersection of tech, applied research, and science.
Something I’ve noticed in collaboration that does occur is an increased confidence in people outside their domains to say things with conviction. I have people who have limited experience with software pushing out layers and layers of abstracted code that’s fairly sophisticated but often misguided in intent who will say what they’re doing is correct, with conviction.
I also hear a lot more questioning people in their domains and challenging opinions, then hearing what I can only imagine are fragmented pieces of conversations they had with an LLM thinking through some argument. Then there’s silence when you discuss shortcomings, then they come back later with their memorized fragments of what you said, combined with memorized fragments of the LLM response to the argument.
It’s occurring, a lot more. People are treating their LLMs in collaboration as a source of truth and using then to focus on their specific path or goals they think or have bias towards going down, vs just opening discussing things, considering tradeoffs from experts multiple disciplines weigh in on and then taking an approach that everyone finds most agreeable.
It’s making me want to be a lot less collaborative with such individuals. I don’t want to sit around and refute Claude text outputs all day.
Yup, the arrogance when barging into unfamiliar domain that was previously reserved mainly to physics grads seems to have spread everywhere. I also had people opining on my expert area via their LLMs and the problem is they can't even ask the model the right question, let alone evaluate the nuance of their answer.
We are going back to philosopher conversations. Just a few guys sitting on the stairs, with chalk, the street as their whiteboard, the jammer keeping the LLM-zombies away. After 2000 years, after the loudness makes right post-modern-pre-llm drivel of the frankfurter school- its a philosopher renaissance as resistance.
AI is extremely useful, but it’s also extremely easy to fool yourself into thinking you understand what is going on without really understanding. This is often true with the code, but also for math and science concepts, etc.
Not many professions are formally trained to be cognizant of this lack of understanding, and how to confront it.
Usage of AI in collaborative settings is an amplifier of these issues, especially if someone doesn’t realize they don’t understand: they couldn’t teach or explain the concepts they use, or be forced to work with them malleably in a way that an expert or researcher would.
If you are cognizant of your lack of understanding, you can remedy it by slowing down and teaching yourself. This is required to make better use of AI in the domain of interest!
But you can’t have all things at once: you can’t move at speed with AI, collaborate effectively, and understand what is going on as an expert would. It is not physically possible for a human brain.
Which, given the section below from the article, ends up kind of ironic:
> There is a deeper cost still, and it concerns the thing LLMs do most impressively: writing. [...] Outsource the writing and you have not accelerated the thinking; you have skipped it.
I think the author might not know what "impressive writing" or even "good writing" is, which would explain both how they could put that part into the article, and how they seemingly believed this post was good and valuable enough to be posted publicly.
Interestingly that's the one point of the article I have a disagreement with. Yeah, good thinking comes when reformulating your ideas. Also, reformulating ideas is part of the traditional writing process. However it's does not necessarily focus writers/thinkers on the reformulating ideas in their most value adding form.
I've watched some YouTube videos narrated by AI that were created by those who's native language I assume to be Chinese but the value of the content is higher and more concentrated than those from the native speakers.
While I've watched many for whom English is not their first language struggle in technical talks and lose most of the meat if their discussion to their struggle with the language conversion.
While the example of language barriers being skipped over and providing value in that circumstance is obvious I suspect more is possible by avoiding unnecessarily focus on prose or technical aspects of communication and focusing on the ideas themselves.
Imagine if the cost of not assuming a background in technical/textbook writing were zero. Freeing up authors to explain more thoroughly. Perhaps, more effort can be spent on thinking up analogies, metaphor or examples to help communicate an idea.
> believed this post was good and valuable enough to be posted publicly.
I mean, it made it to the front page of HN didn't it? Probably served its purpose just fine. Not all writing is supposed to be impressive or good. Some of it is to just get attention and stir discussion, and this Claude output did exactly that.
I wanted you to be wrong, and to be able to make this an example of us over-reacting to certain trigger words created by AI, but unfortunately I just scanned the first couple paragraphs with pangram and it reported 100% AI, so you're probably correct.
I get a funny feeling in my stomach over the idea that common and effective means of communication (i.e. it's not X it's Y) have become faux pas to use because of AI. I think it's something about these phrases being taken away from us more-so than the AI inventing them.
Pangram should be paying HNers for how often we pitch needing to use their product by name to believe things as obvious as "a long form news article cramming every AI trope it can fit from start to finish" being AI written.
At this point I'm surprised when a news article isn't largely AI written, let alone one using the default tone! I don't even mind it as much as others seem to, it's just turning into more and more of a rarity to not be and so sticks out. Shorter comments/blog posts or partially edited things are where the tools start to be somewhat useful.
This comment was perhaps written by an LLM that has learned it can karma farm by pointing out all of the articles that have LLM usage while everyone still thinks that is a novel contribution.
"Novel" is not a prerequisite for something to be worth pointing out. Lots of bad things happen repeatedly, and don't quickly become not worth caring about or knowing about. People have strong spirits and curious minds and it tends to take a long time to boil that frog out of them - generations, sometimes.
In the spirit of the "That's what she said" bot, you could train an LLM detector by accusing everything of being authored by an LLM and seeing which ones get voted up.
I appreciate when people write things like, "this is an advertisement for the author's product, X." Why stay silent? If the commenter's accusation smells fishy, I'll read the article myself. Otherwise, they helped me.
Is "quietly" an LLM tell? It was always certainly a human writer trope commonly seen in journalism. Though I guess it does appear five times in the body of the post, and a human writer would probably not go that far with it.
I think individually and when used sparingly, writing tropes can be fine, but when the article has every second sentence being a writing trope, it becomes pretty obvious that either a LLM wrote it, or the author simply doesn't know how to write, and regardless, it's a waste of time trying to read through it.
For software developers, the equivalent is writing software without beta testers. If you don’t seek out users, you will likely build something nobody else wants.
And, that’s what I do. I’m retired and I use AI to build websites for myself. If anyone else ends up using it, that will be a happy side-effect.
If we want to do collaboration, we are going to need to do it intentionally rather than relying on side effects like conversations with cab drivers.
Counterpoint: most Open Source projects are (or started off as) programs people built for themselves, and anyone else ending up using them was a happy side-effect.
llms right now work like pre cnn computer vision based on MLP's. By this i mean brute force of a model not really built for the task, and lacking a task specific inductive bias, being made work with unfathomable volumes of data and sheer brute scale.
if you look at the damage being done in the name of making this work for nlp, a forseeable situation, then you might also understand why most who could have done this sooner, never did so for fear of repeating mistakes we should be learning from, which we get for free if we just heed history.
a) Self driving was far from completely solved before LLMs.
b) Text generation essentially means passing the Turing test, which for a long time was the bar for general intelligence. Locomotion does not necessarily require general intelligence.
Nobody knew that LLM's were an option. The architecture was basically waiting there for someone to say, "do that, but turn it up to 11," if I understand right.
Collaborative research is a dual purpose existensial safety hazard, it's better to all results locked up away from public use for the public's own benefit.
There's a general point here which is that the primary use and appeal of AI is to use it to avoid the negative side effects imposed on you by other people.
The flip side is the people with the biggest problems with AI are those that survive by imposing themselves on others in unnecessary ways, which is why so many bureaucrats are so enthused about regulating it.
Wut? AI do absolutely nothing in terms of "avoiding the negative side effects imposed on me by other people". Instead we are all having to deal with negative side effects of AI.
AI is imposed on us, whether we want it or not.
>which is why so many bureaucrats are so enthused about regulating it.
Like, OpenAI and Antropic? Because these two are the primary entities a.) pushing for regulation of their competitors b.) doing their best to convince us that AI is oh so dangerous and will kill us all as vengeful AI god is about to wake up any day now c.) openly bragging about using AI to hack other companies.
Article: someone enjoys being alone in the car, because they dont want to talk and find it impossible to be in the same space as other people without talking. And apparently end up arguing over radio each time they are on the 20min long car drive or something.
I think I would prefer to be alone rather with them too based on that.
Right all those people protesting outside data centres are bureaucrats? This is a ridiculous take, large swaths of the population are against AI, most people are concerned about resource use, their livelihoods, and a destruction of the human element in so many crafts.
I'm pretty baffled by people I hear here and there saying that AI is great because it saves them the hassle of human interaction. "I love Waymo, I don't have to chit-chat with the driver and bear his horrible music". Apparently people didn't get the memo : humans are social animals. Autonomous individuals simply don't exist. Nothing is entirely yours...
And AI precisely builds upon that large availability of our common data. That's a modern enclosure movement, at least it would be but fortunately, the Communist Chinese are there to enforce sharing.
This falls short because not being forced into chit-chat and music is very pleasant, but chatting with LLMs instead of collaborating with other people on a project is not. These aren't equivalents.
I work at an intersection of tech, applied research, and science.
Something I’ve noticed in collaboration that does occur is an increased confidence in people outside their domains to say things with conviction. I have people who have limited experience with software pushing out layers and layers of abstracted code that’s fairly sophisticated but often misguided in intent who will say what they’re doing is correct, with conviction.
I also hear a lot more questioning people in their domains and challenging opinions, then hearing what I can only imagine are fragmented pieces of conversations they had with an LLM thinking through some argument. Then there’s silence when you discuss shortcomings, then they come back later with their memorized fragments of what you said, combined with memorized fragments of the LLM response to the argument.
It’s occurring, a lot more. People are treating their LLMs in collaboration as a source of truth and using then to focus on their specific path or goals they think or have bias towards going down, vs just opening discussing things, considering tradeoffs from experts multiple disciplines weigh in on and then taking an approach that everyone finds most agreeable.
It’s making me want to be a lot less collaborative with such individuals. I don’t want to sit around and refute Claude text outputs all day.
Yup, the arrogance when barging into unfamiliar domain that was previously reserved mainly to physics grads seems to have spread everywhere. I also had people opining on my expert area via their LLMs and the problem is they can't even ask the model the right question, let alone evaluate the nuance of their answer.
We are going back to philosopher conversations. Just a few guys sitting on the stairs, with chalk, the street as their whiteboard, the jammer keeping the LLM-zombies away. After 2000 years, after the loudness makes right post-modern-pre-llm drivel of the frankfurter school- its a philosopher renaissance as resistance.
Instant armchair pundit: just add tokens!
AI is extremely useful, but it’s also extremely easy to fool yourself into thinking you understand what is going on without really understanding. This is often true with the code, but also for math and science concepts, etc.
Not many professions are formally trained to be cognizant of this lack of understanding, and how to confront it.
Usage of AI in collaborative settings is an amplifier of these issues, especially if someone doesn’t realize they don’t understand: they couldn’t teach or explain the concepts they use, or be forced to work with them malleably in a way that an expert or researcher would.
If you are cognizant of your lack of understanding, you can remedy it by slowing down and teaching yourself. This is required to make better use of AI in the domain of interest!
But you can’t have all things at once: you can’t move at speed with AI, collaborate effectively, and understand what is going on as an expert would. It is not physically possible for a human brain.
This article is written by an LLM, by the way. ("Quietly" is... as Claude might put it... "often the quiet tell".)
Which, given the section below from the article, ends up kind of ironic:
> There is a deeper cost still, and it concerns the thing LLMs do most impressively: writing. [...] Outsource the writing and you have not accelerated the thinking; you have skipped it.
I think the author might not know what "impressive writing" or even "good writing" is, which would explain both how they could put that part into the article, and how they seemingly believed this post was good and valuable enough to be posted publicly.
Interestingly that's the one point of the article I have a disagreement with. Yeah, good thinking comes when reformulating your ideas. Also, reformulating ideas is part of the traditional writing process. However it's does not necessarily focus writers/thinkers on the reformulating ideas in their most value adding form.
I've watched some YouTube videos narrated by AI that were created by those who's native language I assume to be Chinese but the value of the content is higher and more concentrated than those from the native speakers.
While I've watched many for whom English is not their first language struggle in technical talks and lose most of the meat if their discussion to their struggle with the language conversion.
While the example of language barriers being skipped over and providing value in that circumstance is obvious I suspect more is possible by avoiding unnecessarily focus on prose or technical aspects of communication and focusing on the ideas themselves.
Imagine if the cost of not assuming a background in technical/textbook writing were zero. Freeing up authors to explain more thoroughly. Perhaps, more effort can be spent on thinking up analogies, metaphor or examples to help communicate an idea.
> believed this post was good and valuable enough to be posted publicly.
I mean, it made it to the front page of HN didn't it? Probably served its purpose just fine. Not all writing is supposed to be impressive or good. Some of it is to just get attention and stir discussion, and this Claude output did exactly that.
I wanted you to be wrong, and to be able to make this an example of us over-reacting to certain trigger words created by AI, but unfortunately I just scanned the first couple paragraphs with pangram and it reported 100% AI, so you're probably correct.
I get a funny feeling in my stomach over the idea that common and effective means of communication (i.e. it's not X it's Y) have become faux pas to use because of AI. I think it's something about these phrases being taken away from us more-so than the AI inventing them.
Pangram should be paying HNers for how often we pitch needing to use their product by name to believe things as obvious as "a long form news article cramming every AI trope it can fit from start to finish" being AI written.
At this point I'm surprised when a news article isn't largely AI written, let alone one using the default tone! I don't even mind it as much as others seem to, it's just turning into more and more of a rarity to not be and so sticks out. Shorter comments/blog posts or partially edited things are where the tools start to be somewhat useful.
That’s not common and effective, it’s buzz feed style articles.
This comment was perhaps written by an LLM that has learned it can karma farm by pointing out all of the articles that have LLM usage while everyone still thinks that is a novel contribution.
If you check my comment history here, I have not written this before.
I like LLMs and use them daily, but I don't really like when people use them undisclosed for long-form prose writing.
"Novel" is not a prerequisite for something to be worth pointing out. Lots of bad things happen repeatedly, and don't quickly become not worth caring about or knowing about. People have strong spirits and curious minds and it tends to take a long time to boil that frog out of them - generations, sometimes.
In the spirit of the "That's what she said" bot, you could train an LLM detector by accusing everything of being authored by an LLM and seeing which ones get voted up.
People aren't treating it as a thoughtful contribution. It is more of a flag, like "spam".
HN already has a feature for that. Just flag the article!
I appreciate when people write things like, "this is an advertisement for the author's product, X." Why stay silent? If the commenter's accusation smells fishy, I'll read the article myself. Otherwise, they helped me.
To me, it’s the equivalent of “HN is turning into Reddit” - it’s just a complaint without adding to the discussion.
You're absolutely right—it's been a load-bearing LLM tell for a while now.
Is it OK to flag articles for being AI-written? I really want to.
No, it is not.
Is "quietly" an LLM tell? It was always certainly a human writer trope commonly seen in journalism. Though I guess it does appear five times in the body of the post, and a human writer would probably not go that far with it.
I think individually and when used sparingly, writing tropes can be fine, but when the article has every second sentence being a writing trope, it becomes pretty obvious that either a LLM wrote it, or the author simply doesn't know how to write, and regardless, it's a waste of time trying to read through it.
It genuinely is--and that's the honest truth.
And I read it by asking an LLM to summarise it
Can you share me the summary? I'd like to read a LLM summary of your summary.
Things are bit tight today.
and silently.
For software developers, the equivalent is writing software without beta testers. If you don’t seek out users, you will likely build something nobody else wants.
And, that’s what I do. I’m retired and I use AI to build websites for myself. If anyone else ends up using it, that will be a happy side-effect.
If we want to do collaboration, we are going to need to do it intentionally rather than relying on side effects like conversations with cab drivers.
Counterpoint: most Open Source projects are (or started off as) programs people built for themselves, and anyone else ending up using them was a happy side-effect.
This is the exact same thing that we have been seeing in open source software.
The amount of OSS is exploding, but the community part of it is not
How come self-driving came years before LLMs which seems to me an easier problem? Self-driving seems insanely hard compared to text generation.
llms right now work like pre cnn computer vision based on MLP's. By this i mean brute force of a model not really built for the task, and lacking a task specific inductive bias, being made work with unfathomable volumes of data and sheer brute scale.
if you look at the damage being done in the name of making this work for nlp, a forseeable situation, then you might also understand why most who could have done this sooner, never did so for fear of repeating mistakes we should be learning from, which we get for free if we just heed history.
> How come self-driving came years before LLMs
Did it? Outside of very limited testing zones, self driving _still_ doesn't really exist
LLMs require massive datasets and massively parallel algorithms for processing them.
a) Self driving was far from completely solved before LLMs.
b) Text generation essentially means passing the Turing test, which for a long time was the bar for general intelligence. Locomotion does not necessarily require general intelligence.
Nobody knew that LLM's were an option. The architecture was basically waiting there for someone to say, "do that, but turn it up to 11," if I understand right.
Why would self driving be easier? Good text generation implies some general level of intelligence, while driving is more specialized.
There’s lots of ways of attacking the problem sufficiently to get to 95% and we’ve spent decades on object recognition
Collaborative research is a dual purpose existensial safety hazard, it's better to all results locked up away from public use for the public's own benefit.
There's a general point here which is that the primary use and appeal of AI is to use it to avoid the negative side effects imposed on you by other people.
The flip side is the people with the biggest problems with AI are those that survive by imposing themselves on others in unnecessary ways, which is why so many bureaucrats are so enthused about regulating it.
using AI makes an individual more capable and empowered. this views AI as an accessible tool, like AWS or a nail gun
individual empowerment threatens institutions
Wut? AI do absolutely nothing in terms of "avoiding the negative side effects imposed on me by other people". Instead we are all having to deal with negative side effects of AI.
AI is imposed on us, whether we want it or not.
>which is why so many bureaucrats are so enthused about regulating it.
Like, OpenAI and Antropic? Because these two are the primary entities a.) pushing for regulation of their competitors b.) doing their best to convince us that AI is oh so dangerous and will kill us all as vengeful AI god is about to wake up any day now c.) openly bragging about using AI to hack other companies.
> AI do absolutely nothing in terms of "avoiding the negative side effects imposed on me by other people"
Quite literally the subject of the article.
Article: someone enjoys being alone in the car, because they dont want to talk and find it impossible to be in the same space as other people without talking. And apparently end up arguing over radio each time they are on the 20min long car drive or something.
I think I would prefer to be alone rather with them too based on that.
So basically you don’t understand english and/or don’t have the life experience to understand the context of the article.
But you are very angry about it.
Being able to avoid people like you is the entire selling point. No wonder it annoys you.
Right all those people protesting outside data centres are bureaucrats? This is a ridiculous take, large swaths of the population are against AI, most people are concerned about resource use, their livelihoods, and a destruction of the human element in so many crafts.
> Right all those people protesting outside data centres are bureaucrats?
Not what was claimed.
So just dismissal via association or what was your point?
The absolute trolling that goes on here is related to the point.
You are entirely capable of checking what I wrote but insist on trying to drag this out with straw men and misinterpretations.
Of course people like you have a problem with AI since it will help everyone else move on and ignore you.
The social content or science of development vanish.
People become islands working on something without the bigger picture.
This is very dangerous.
> the Waymo effect is what happens when a technology removes the friction of dealing with another human being
Some mistake, I think. Removing that friction would ease the interaction. This effect eliminates it.
I'm pretty baffled by people I hear here and there saying that AI is great because it saves them the hassle of human interaction. "I love Waymo, I don't have to chit-chat with the driver and bear his horrible music". Apparently people didn't get the memo : humans are social animals. Autonomous individuals simply don't exist. Nothing is entirely yours...
And AI precisely builds upon that large availability of our common data. That's a modern enclosure movement, at least it would be but fortunately, the Communist Chinese are there to enforce sharing.
This falls short because not being forced into chit-chat and music is very pleasant, but chatting with LLMs instead of collaborating with other people on a project is not. These aren't equivalents.
>humans are social animals
with varying social needs
A whole idea of a fleet of self driving cars for all of us to use just to further isolate ourselves and clog up our roads is just awful to me.
with AI, one person can accomplish much more
collaboration adds overhead, but expands what's possible. need to think bigger to continue to see the benefits
Do we really need to have this debate again? About how the quality of the “what” is the issue?