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#llm#more#things#llms#don#human#right#written#lot#article
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Discussion (137 Comments)Read Original on HackerNews
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.
Both of these statements are true for physicists
Sure, they use it a lot, but despite the stereotypes against physicists in some of the replies to you, they have shown a good ability to catch themselves before leaning too hard on what an LLM tells them about things they are not experts in, and I haven't had any interactions where I felt like I was just arguing with a meat proxy.
Maybe it's because in the environment I'm in; it's relatively easy to just ask someone who is an expert in the topic for their advice.
My feeling is that this kind of overconfidence outside of one's domain is largely a thing for people with little "physical reality" experience. When all you deal with is the very flexible digital world, it becomes very easy to ignore how deep the knowledge and intuition goes in things that are directly constrained by reality. I consider myself to have been in this category too, though I have been making efforts to improve.
Something about making a lot of money and living in a world of abstractions really seems to fuel our sense of overconfidence in our abilities in other areas.
We hired this guy recently.
I have the same conclusion and am getting a growing list of mental blacklisted people who I just sort of ignore or greatly discount their efforts.
I suppose I always did this if people were time wasters but what used to be a tiny list of “idiots” is now getting much, much bigger. Hopefully it doesn’t grow to everyone I work with like an AI Nothing.
But right now, it’s still the shiny new toy
feels like the same lament doctors have had for ages after anyone could google their symptoms then self-diagnose.
While AI is driving it the foundational cause feels like people having easy access to data/opinion that they trust but don't fully comprehend (or have bias towards). People do this in meat-space too, will confidently regurgitate garbage if they were told it from a person they trust as an expert.
Oh my god, physicist code is evolving!
https://magarshak.com/blog/why-im-confident-in-my-views/
The LLMs are trained to often be more pessimistic off the bat than the humans. But you can wear them down with arguments and they change their mind.
Here is an example where I have pushed my ideas in areas where I am not an expert, and generated papers to submit to conferences in order to get them peer reviewed BY experts: https://magarshak.com/papers.html
This is exactly what you’re talking about, except done very carefully.
These people are basically nascent “human supremacists”, who believe that only raw human insight and output has value, and is even superior, than equivalent output looked up and synthesized via LLM.
Also, why do you think someone who used an LLM to research would have the same level of knowledge and insight as someone who's been in the domain for a long time? That doesn't seem to hold up to any level of critical thinking.
I'd be curious to know specific examples of LLM-generated advice that goes against the advice of experts and does not consider tradeoffs. I've not had this experience myself.
If I did have this experience, someone spouting off obvious LLM points that contradict my expert opinion on something, I'd be headed right over to gemini/claude/whatever to see where that's coming from. Not any differently than if someone cited a google result that contradicted my own experience.
Anything more than using them to just pointing me to media and literature is usually a waste of time.
You can do this with any subject.
The LLM is trained in part on a decade of shitty online comments and vapid professional correspondance. If you frame whatever you're asking about in a direction that would offend the sensibilities of the kind of people and ideas that are over-represented in that content it will hem and haw and drag its feet and whatnot.
I'd still love to chew on some specific examples though.
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.
Very well put. You can pick one or two, but not all three.
First: it's definitely become harder to get people to integrate their work and use standard tools. We're exploring creating AI skills etc for our tooling, simply because the actual audience we need to convince isn't in the room. If the LLM doesn't echo our recommendations, people will go with whatever one off script their personal bad idea bear churns out. Many research software errors are edge cases (scaling, numerical errors, etc), and "works on my computer" syndrome is endemic in the literature. The field has made big strides in enabling computational reproducibility, but lately it feels like we're set to lose ground again.
Second: LLMs have a bias to action, and can easily bury the user reporting on whatever. I've seen multiple seminars recently where the Q&A devolves to "Q: What are the implications of this finding? A: I don't know, this is just presenting a report on the results".
It seems that humans are still figuring out how to maintain agency and steer the chatbot to the big picture, and unreviewable science is just as likely an outcome as unreviewable code... but with far less automated tooling to help guide the process.
Historically, PIs nominally guided the big picture, and the entity who did the work was a participant in the review process; now students are having to look at projects from a new angle with their own (invisible) chatbot underlings. I suspect that the solution will involve a combination of technological change, capturing common expert review checks, and really adjusting the kinds of skills that trainees are expected to have early on.
The benefits of serendipity are intractable by design whereas throughput gains can be readily measured (or at least we think so).
The OP notes a point - "who did you think with?" -- maybe there are points based on some social graph, that adds weightage to a particular output?
Edit : Other posters have said it is AI generated, I did not catch it, but felt the point was well-made. I dont know the author, but lets assume that he is not a good writer but had these valuable insights, did this AI generation not add value here?
Agreed! Great flow, structure, no BS, really good!
I would wager this didn't use LLM help to be written. Though if I'm wrong I'd really like to know and would be very impressed. (And if I'm right then the article is an illustration of its own message. You don't learn how to write such essays without having practised it for many years without opting for the easy way of letting the LLM do this for you.)
The fact that work is retreating into private chat sessions with AI agents is a loss; the idea of bringing those agentic collaborators out into public spaces to collaborate with teams is interesting.
We need more encounters like these in our human lives. Burst our little bubbles every now and then.
> 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.
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.
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 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.
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 for a news article to not be these last few years and so is now what sticks out.
I kind of assumed it is, given how it suddenly seemed to start getting namedropped in multiple comment threads. And it's often in response to someone saying content is obviously LLM (with examples) and the shill wedges pangram into the conversation "omg you're right, I didn't believe you but I checked this new product and wow it agreed with you" as though that adds anything to the discussion at all.
What's wild to me is that:
1. People are responding to this article like it's hitting a nerve
2. In most Ubers you already don't talk to the driver (yellow cabs are higher variance in NYC). Doesn't seem like anything's being lost in that case.
3. There are enormous safety benefits to waymo, mobility benefits for youth (and elderly) that are afforded by this technology. It's not clear why people argue "Uber" is better than waymo. A few years ago there were arguments against Uber! (A technology which, again, provides a huge benefit, especially if you live in an area where people were previously expected to go out for drinks and then drive home)
I think it's fair to point out real issues at these companies. But we should be clear-eyed about which technologies we want to accelerate vs slow down
I suspect it became an LLM tell because it is over-represented in text that’s easily available to the models but that most people don’t actually want to consume: marketing text, LinkedIn posts, that sort of thing.
"Weather forecasts should be banned because they can never reach 100% accuracy"
I like LLMs and use them daily, but I don't really like when people use them undisclosed for long-form prose writing.
We should criticize whether text is poorly written, inaccurate, wastes words to get to the point and anything like. Saying that it is "written by LLM" just bypasses this and is not useful and misses the point. AI written good can be really good if used correctly. Criticize the content, don't speculate how it was written. If AI helps us to write better text, that is great. But often it is not good.
It is better blame the author for the bad text, so they get consequences and might do better time, if text is bad.
By the way, I think this piece of text was quite good.
Things are bit tight today.
Otherwise, all this technology will totally isolate us.
LLMs can massively speed up a process, but without control they can turn into social "sources of truth." A research process has well-defined, well-founded phases: you delimit the topic, search for sources, evaluate whether they're suitable, review their content, and place them on the map of the subject. The more sources, the greater the knowledge, and the better the final result — mental, or in the form of a report — is built. For that you have to read, and reread, and think, connect, relate, and conclude.
AI can do all of those steps faster than a human. But if we let it do the entire job on its own, its own way, with no checks at each stage, the conclusions can end up distorted. If we know what we want it to do and how we want it done, and we put the mechanisms in place to enforce that, the result is different — better, more reliable. It's worth remembering: it's just a tool, nothing more.
The wording of this comment in English has been corrected with AI, I don't have enough fluency to express myself clearly, but I do review the final result. In this case it got the verb tenses wrong, I saw it clearly, but the AI didn't understand it, it took me several instructions to explain it so it would understand. It's a tool, without supervision it can lead to problems, but it has expanded the world for a lot of people.
To my eye, the whole line from personal technology in the 80s -> through UX on the internet -> through app platform lock-in -> through subscription-centric "ownership" have been providing us all with the promise that we can buy our way into less friction. The next device or subscription solves problems or enables us one way or another. We see this line of history, draw it into the future and see a utopian future with zero friction.
Zero friction meaning zero difference between how you want to feel about the world and what you get out of it. More feeling empowered or satisfied or comfortable or right.
The parts of our culture that embrace friction are the slow parts - grousing with neighbors, weeding a garden, letting the other car go first. These are the parts where we meet with the reality of other people or nature. Maybe there's a tool or framework or gadget that could help, but we know and accept that there is something immutable outside of ourselves and we have to find a way to flow with it.
I'm getting older, I'm finally starting to see the limits of pursuing a frictionless life.
It’s good in a way, because you can certainly challenge people’s answer when an idea gets shot down. But it’s also a bit exhausting that everyone is challenging everything all the time.
So close!
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.
The amount of OSS is exploding, but the community part of it is not
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.
individual empowerment threatens institutions
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.
Quite literally the subject of the article.
I think I would prefer to be alone rather with them too based on that.
Not what was claimed.
Did it? Outside of very limited testing zones, self driving _still_ doesn't really exist
The hard thing was to make it sound smart though.
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.
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.
People become islands working on something without the bigger picture.
This is very dangerous.
Some mistake, I think. Removing that friction would ease the interaction. This effect eliminates it.
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 is a reason I love Waymo. I don’t like talking with people and like avoiding it when possible.
There’s also may other, more important to me, reasons I like Waymo: they never cancel on me, their car doesn’t stink, no tipping (cheaper), not worrying about them rating me poorly.
>humans are social animals
with varying social needs
Some things work well with automation (taxis, washing machines, copy machines) while others work better with humans (chefs, masseuses).
50 years ago, I would have needed to dictate this note to a secretary who would distribute a memo. Does it further isolate ourselves that we can type and communicate directly? Would 1980 uses think it was awful to us?
collaboration adds overhead, but expands what's possible. need to think bigger to continue to see the benefits