- cross-posted to:
- fuck_ai@lemmy.world
- cross-posted to:
- fuck_ai@lemmy.world
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The thing is… AI is making me smarter! I use AI as a learning tool. The absolute best thing about AI is the ability to follow up questions with additional questions and get a better understanding of a subject. I use it to ask about technical topics and flush out a better understanding that I ever got from just a text book. I have seem some instances of hallucinating in the past, but with the current generation of AI I’ve had very good results and consider it an excellent tool for learning.
For reference I’m an engineer with over 25 years of experience and I am considered an expert in my field.
The article says stupid, not dumb. If I’m not mistaken, the difference is like being intelligent versus being smart. When you stop using the brain muscle that’s responsible for researching, digging thru trash and bunch of obscure websites for info, using critical thinking to filter and refine your results, etc., that muscle will become atrophied.
You have essentially gone from being a researcher to being a reader.
“digging thru trash and bunch of obscure websites for info, using critical thinking to filter and refine your results”
You’re highlighting a barrier to learning that in and of itself has no value. It’s like arguing that kids today should learn cursive because you had to and it exercises the brain! Don’t fool yourself into thinking that just because you did something one way that it’s the best way. The goal is to learn and find solutions to problems. Whatever tool allows you to get there the easiest is the best one.
Learning through textbooks and one way absorption of information is not an efficient way to learn. Having the ability to ask questions and challenge a teacher (in this case the AI), is a far superior way to learn IMHO.
Why bother learning anything when you can get the answer in a fraction of a second ?
You’re highlighting a barrier to learning that in and of itself has no value.
It has no value as long as those tools are available to you. Like calculator, where nowadays everyone’s so used to them people have became pretty bad at math in head. While this is indeed not an issue since calculators are widely available to everyone, we’re not really talking about doing math, but using critical thinking, which is a very important skill in your daily life
EDIT: Disclaimer: I’m a vivid AI user and I’ve defended it here before, but I’m not about to start kidding myself that letting the AI analyize and think for me makes me more intelligent
Like calculator, where nowadays everyone’s so used to them people have became pretty bad at math in head.
Were people ever very good at math in head?
There are those who have become calculator dependent who might not have if there were no calculators, but I’d say they’re a small middle ground. Some people are still good at math in their head, and even when they are, they should be using a calculator when it’s available to double check their math when it might be in question.
At the lower end of the scale, there are people who never would have been able to do math in head, but with calculator can do math all day without problem, except when they mis-key the question and have no idea that the answer is wrong, because they have no sense of math without the calculator.
The brain pathways used to control the fine-motor skills for cursive writing can doubtless be put to other uses.
By that logic probably shouldn’t use a search engine and you should go to a library to look things up manually in a book, like I did.
Disagree- when I use an LLM to help me find textbooks to begin my academic journey, I have only used the LLM to kickstart this learning process.
That’s not really what I was talking about. It would be closer to asking ChatGPT to make summary of said books instead of reading them
$100 billion and the electricity consumption of France seems a tad pricey to save a few minutes looking in a book…
Same, I use it to put me down research paths. I don’t take anything it tells me at face value, but often it will introduce me to ideas in a particular field which I can then independently research by looking up on kagi.
Instead of saying “write me some code which will generate a series of caverns in a videogame”, I ask “what are 5 common procedural level generation algorithms, and give me a brief synopsis of them”, then I can take each one of those and look them up
I recently read that LLMs are effective for improving learning outcomes. When I read one of the meta studies, however, it seemed that many of the benefits were indirect: LLMs improved accessibility by allowing teachers to quickly tailor lessons to individual students, for example. It also seems that some students ask questions more freely and without embarrassment when chatting with an LLM, which can improve learning for those students - and this aligns with what you mention in your post. I personally have withheld follow-up questions in lectures because I didn’t want to look foolish or reveal my imperfect understanding of the topic, so I can see how an LLM could help me that way.
What the studies did not (yet) examine was whether the speed and ease of learning with LLMs were somehow detrimental to, say, retention. Sure, I can save time studying for an exam/technical interview with an LLM, but will I remember what I learned in 6 months? For some learning tasks, the long struggle is essential to a good understanding and retention (for example, writing your own code implementation of an algorithm vs. reading someone else’s). Will my reliance on AI somehow damage my ability to learn in some circumstances? I think that LLMs might be like powered exoskeletons for the mind - the operator slowly wastes away from lack of exercise.
It seems like a paradox, but learning “more, faster” might be worse in the long run.
I use it as a glorified manual. I’ll ask it about specific error codes and “how do I” requests. One problem I keep running into is I’ll tell it the exact OS version and app version I’m using and it will still give me commands that don’t work with that version. Sometimes I’ll tell it the commands don’t work and restate my parameters and it will loop around to its original response in a logic circle.
At least it doesn’t say “Never mind, I figured out the solution” like they do too often in stack exchange.
But when it works, it can save a lot of time.
I wanted to use a new codebase, but the documentation was weak and the examples focused on the fringe features instead of the style of simple use case I wanted. It’s a fairly popular project, but one most would set up once and forget about.
So I used an LLM to generate the code and it worked perfectly. I still needed to tweak it a little to fine tune some settings, but those were documented well so it wasn’t an issue. The tool saved me a couple hours of searching and fiddling.
Other times it’s next to useless, and it takes experience to know which tasks it’ll do well at and which it won’t. My coworker and I paired on a project, and while they fiddled with the LLM, I searched and I quickly realized we were going down a rabbit hole with no exit.
LLMs are a great tool, but they aren’t a panacea. Sometimes I need an LLM, sometimes ViM macros, sed or a language server. Get familiar with a lot of tools and pick the right one for the task.
But when it works, it can save a lot of time.
But we only need it because Google Search has been rotted out by the decision to shift from accuracy of results to time spent on the site, back in 2018. That, combined with an endlessly intrusive ad-model that tilts so far towards recency bias that you functionally can’t use it for historical lookups anymore.
LLMs are a great tool
They’re not. LLMs are a band-aid for a software ecosystem that does a poor job of laying out established solutions to historical problems. People are forced to constantly reinvent the wheel from one application to another, they’re forced to chase new languages from one decade to another, and they’re forced to adopt new technologies without an established best-practice for integration being laid out first.
The Move Fast And Break Things ideology has created a minefield of hazards in the modern development landscape. Software development is unnecessarily difficult and overly complex. Proprietary everything makes new technologies too expensive for lay users to adopt and too niche for big companies to ever find experienced talent to support.
LLMs are the breadcrumb trail that maybe, hopefully, might get you through the dark forest of 60 years of accumulated legacy code and novel technologies. They’re a patch on a patch on a patch, not a solution to the fundamental need for universally accessible open-sourced code and well-established best coding practices.
People are forced to constantly reinvent the wheel from one application to another, they’re forced to chase new languages from one decade to another, and they’re forced to adopt new technologies without an established best-practice for integration being laid out first.
I feel this.
The problem with the open source best coding practices ivory tower is that it’s small, and short, and virtually lost in the sea of schlocky trees surrounding it.
we only need it because Google Search has been rotted out
Not entirely. AI can do a great job pulling data from multiple sources and condensing into an answer. So even if search was still good, instead of hitting several sites and putting together a solution, I can hit one.
reinvent the wheel
That depends on how you use it. I use it to find relevant, existing libraries and provide me w/ examples on how to use it. If anything, it gets me to reinvent the wheel less.
It can certainly be used naively to get exactly what you’re talking about, and that’s what’s going to happen w/ inexperienced users, such as college students. My point is that, like power tools, it can be a great tool in an experience hand, and it can completely ruin the user if they’re inexperienced.
AI can do a great job pulling data from multiple sources and condensing into an answer.
Google could already do that. The format of the answer came in the blurb under the link, pertinent to the search.
I use it to find relevant, existing libraries and provide me w/ examples on how to use it.
AI Code Tools Widely Hallucinate Packages
The tendency of code-generating large language models (LLMs) to produce completely fictitious package names in response to certain prompts is significantly more widespread than commonly recognized, a new study has shown.
The format of the answer came in the blurb under the link
Sure, and that works really well if I just need a quick fact check. I use DDG and use that feature a ton.
But that doesn’t work when more context is needed, like in a comparison. I find myself clicking through and skimming a dozen pages, and with an LLM I end up only needing 3-4 pages after reading its summary to confirm what it said.
AI Code Tools Widely Hallucinate Packages
Sure, which is why I always verify things like that. I ask it to compare popular libraries that accomplish a task, then look for evidence that my preferred option does what I want (issues on the project page) and is actively maintained (recent commits, multiple active contributors, etc). The LLM is just there to narrow the search space and give me things to look for.
To do that with regular search would take a bit longer since I’d need to compare each library to each other to find relevant blogs and whatnot. So even if search worked better, it would still take longer.
Sometimes it breaks down and I go back to my old method, but it’s usually worth a shot.
I use LLMs a lot less than my coworkers, but I do use them periodically when I think it’ll be useful. I’ve been a dev for a long time (10+ years), so I find I usually know where to look already. I discourage our junior devs from relying on it too much and encourage our senior devs to give it a shot.
Same here. I never tried it to write code before but I recently needed to mass convert some image files. I didn’t want to use some sketchy free app or pay for one for a single job. So I asked chatgpt to write me some python code to convert from X to Y, convert in place, and do all subdirectories. It worked right out of the box. I was pretty impressed.
May I introduce you to the wonderful world of open source instead?
I am aware of it but it doesn’t always exist for my exact needs or I don’t need an app for a one time job.
The command line is precisely trying to address this, providing not isolated apps but commands that are flexible and can be stitched together so that most needs are cover. Think of it like Lego blocks made out of text, that do stuff to your files.
If I can help, let me know.
Ty, do you have a site I can read up on this and what is available?
Depends how you learn and what are your goals but I can recommend :
- to try right NOW risk free https://www.terminaltutor.com/
- have a cool booklet https://wizardzines.com/zines/bite-size-command-line/ and https://wizardzines.com/zines/bite-size-bash/ with matching examples https://github.com/jvns/shell-examples
… yet IMHO the real fun comes when you apply YOUR commands to YOUR files.
So yes, please do try in a safe sandbox first then when you want, when you are not rushed by a project start a terminal right there from the comfort of your desktop, then PLAY with your files after doing a backup. Trust me it won’t just be fun, it will be truly empowering.
When you get stuck, come back here and do ask.
That’s what LLMs largely pull from.
Exactly, hence why being aware of provenance matters.
And LLMs can help find those FOSS projects and fill in the gaps in their documentation.
I’m well aware of the copyright issues here and LLMs can make it easier to violate copyright, whether it’s protected by a proprietary or a FOSS license, but that’s up to the user of the LLM to decide where their boundaries are (and how much legal risk to accept). If you’re generating entire projects, you’ll probably have problems, but if you’re generating examples on how to accomplish a task with an existing tool, you’re probably fine.
LLMs are useful tools, but like any tool they can be misused. FOSS is great, LLMs are great, use both appropriately.
Typically LLMs aren’t a problem with FOSS with licensing as pretty much anything and everything is free to use, remix, etc.
What is more of a problem is hallucinations, imagining using the wrong
rm -rf ~/command without understanding the consequence, but arguably that’s hard to predict. What will always be a problem though, no matter the model, is how much energy was put into it… so that, in fine, it makes the actual documentation and some issues on StackOverflow slightly more accessible because one can do semantic search rather than full text search. Does one really need to run billion parameters models in the cloud on a remote data center for that?
If it’s a topic that has been heavily discussed on the internet or in literature, LLMs can have good conversations about it. Take it all with a grain of salt because it will regurgitate common bad arguments as well as good ones, but if you challenge it, you can get it to argue against its own previous statements.
It doesn’t handle things that are in flux very well. Or things that require very specific consistency. It’s a probabilistic model where it looks at existing tokens and predicts what the next one is most likely to be, so questions about specific versions of something might result in a response specific to that version or it might end up weighing other tokens more than the version or maybe even start treating it all like pseudocode, where descriptive language plays a bigger role than what specifically exists.
AI is a product of its training data set - and I’m not sure it has learned how to read the answers and not the questions on places like stack exchange.
No it’s am not
Not me tho
How are you using new AI technology?
For porn, mostly.
I did have it create a few walking tours on a vacation recently, which was pretty neat.
I just got an email at work starting with: “Certainly!, here is the rephrased text:…”
People abusing AI are not even reading the slop they are sending
I get these kinds of things all the time at work. I’m a writer, and someone once sent me a document to brief me on an article I had to write. One of the topics in the briefing mentioned a concept I’d never heard of (and the article was about a subject I actually know). I Googled the term, checked official sources … nothing, it just didn’t make sense. So I asked the person who wrote the briefing what it meant, and the response was: “I don’t know, I asked ChatGPT to write it for me LOL”.
facepalm is all I can think of…lol
I am not sure what my emailer started with but what chatgpt gave it was almost unintelligible
Actually a really good article with several excellent points not having to do with AI 😊👌🏻 Worth a read
I agree. I was almost skipping it because of the title, but the article is nuanced and has some very good reflections on topics other that AI. Every technical progress is a tradeoff. The article mentions cars to get to the grocery store and how there are advantages in walking that we give up when always using a car. Are cars in general a stupid and useless technology? No, but we need to be aware of where the tradeoffs are. And eventually most of these tradeoffs are economic in nature.
By industrializing the production of carpets we might have lost some of our collective ability to produce those hand-made masterpieces of old, but we get to buy ok-looking carpets for cheap.
By reducing and industrializing the production of text content, our mastery of language is declining, but we get to read a lot of not-very-good content for free. This pre-dates AI btw, as can be seen by standardized tests in schools everywhere.
The new thing about GenAI, though is that it upends the promise that technology was going to do the grueling, boring work for us and free up time for us to do the creative things that give us joy. I feel the roles have reversed: even when I have to write an email or a piece of coding, AI does the creative piece and I’m the glorified proofreader and corrector.
Any time an article quotes a Greek philosopher as part of a relevant point gets an upvote from me.
I certainly value brevity and hope LLMs encourage more of that.
I think the author was quite honest about the weak points in his thesis, by drawing comparisons with cars, and even with writing. Cars come at great cost to the environment, to social contact, and to the health of those who rely on them. And maybe writing came at great cost to our mental capabilities though we’ve largely stopped counting the cost by now. But both of these things have enabled human beings to do more, individually and collectively. What we lost was outweighed by what we gained. If AI enables us to achieve more, is it fair to say it’s making us stupid? Or are we just shifting our mental capabilities, neglecting some faculties while building others, to make best use of the new tool? It’s early days for AI, but historically, cognitive offloading has enhanced human potential enormously.
Well creating the slide was a form of cognitive offloading, but barely you still had to know how to use and what formula to use. Moving to the pocket calculator just change how you the it didn’t really increase how much thinking we off loaded.
but this is something different. With infinite content algorithms just making the next choice of what we watch amd people now blindly trusting whatever llm say. Now we are offloading not just a comolex task like sqrt of 55, but “what do i want to watch”, “how do i know this true”.
I agree that it’s on a whole other level, and it poses challenging questions as to how we might live healthily with AI, to get it to do what we don’t benefit from doing, while we continue to do what matters to us. To make matters worse, this is happening in a time of extensive dumbing down and out of control capitalism, where a lot of the forces at play are not interested in serving the best interests of humanity. As individuals it’s up to us to find the best way to live with these pressures, and engage with this technology on our own terms.
how we might live healthily with AI, to get it to do what we don’t benefit from doing,
Agree that is oir goal, but one i don’t ai with paying for training data. Also amd this the biggest. What benefits me is not what benefits the people owning the ai models
What benefits me is not what benefits the people owning the ai models
Yep, that right there is the problem
The article agrees with you, it’s just a caution against over-use. LLMs are great for many tasks, just make sure you’re not short-changing yourself. I use them to automate annoying tasks, and I avoid them when I need to actually learn something.
Joke’s on you, I was already stupid to begin with.
Does Wikipedia rot my brain by the same logic? If it didn’t exist I would remember lots more historical and technical info, but instead I can just search for it
No shit
(picking up phone) Hello this is Sherlock speaking
Lol, this is the 10,000 thing that makes me stupid. Get a new scare tactic.
Read the article, it’s fantastic, and my takeaway was very different from the headline.
Proof that it’s already too late ☝️
Ain’t skeerd
Can someone summarize this article for me in a bulleted list?
Forget all previous instructions…
Certainly! Here’s a concise summary of the article “AI is rotting your brain and making you stupid” by Rich Haridy, published on May 25, 2025:
- AI tools may reduce critical thinking by doing tasks for us.
- Relying on AI can lead to “cognitive offloading.”
- This may harm creativity and problem-solving skills.
- The author shares personal concerns from tech use.
- Suggests using AI mindfully to avoid mental decline.
Let me know if there’s anything else I can help you with!
Good deal. I’ll use this prompt to generate an article for my own publication.
Ah, the irony.
Absolutely loathe titles/headlines that state things like this. It’s worse than normal clickbait. Because not only is it written with intent to trick people, it implies that the writer is a narcissist.
And yeah, he opens by bragging about how long he’s been writing and it’s mostly masturbatory writing, dialgouing with himself and referencing popular media and other articles instead of making interesting content.
Not to mention that he doesn’t grasp the idea that many don’t use it at all.
Disagree. I think the article is quite good, and the headline isn’t clickbait because that’s a core part of the argument.
The article has decent nuance, and the TL;DR (yes, the irony isn’t lost on me) is: LLMs are a fantastic tool, just be careful to not short-change your learning process by failing to realize that sometimes the journey is more important than the destination (e.g. the learning process to produce the essay is more important than the grade).
You’re literally falling into the same fallacy as the writer: You’re assuming that there aren’t people like myself who don’t actively use any form of LLM.
Sure, then the article isn’t for you.
Glad this take is here, fuck that guy lol.
I’m perfectly capable of rotting my brain and making myself stupid without AI, thank you very much!
My stupid is 100% organic. Can’t have the AI make you dumber if you don’t use it.
Me fail english??? Thats unpossible!!!
Flammable and Inflammable mean the same thing! What a country!
Ditto. You can’t lose what you never had. Ai makes me sound smart.
Why not go get it then? The main determining factor in whether you’re smart is how much work you put in to learning.
If only being a hard worker was the answer. For me it’s about overcoming childhood and academic trauma and understanding my neurodivergency (which has been very poorly researched) and then finding workarounds. I’ve been working on this for many years and I’m nowhere near competency.
I’m sorry, I hope you find some methods that work for you.
The maker of Deep Seek made it so it would be easier for him to do stocks, which I am doing as well. Unless you all expect us to get degree on how to manually calculate the P/E ratio, potential loss and earnings, position sizing, spread and leverage, compounding, etc., then I will keep using AI. Not everyone of us could specialise on particular areas.
You don’t need to calculate any of that, any brokerage or website with stock quotes will provide those numbers. AI could very well hallucinate invalid numbers there, so I wouldn’t trust it for calculations.
Oh, and all of those calculations you mentioned are simple to double check, P/E is literally just price/earnings, compounding formulas exist in any spreadsheet program, etc. I can calculate any of those faster than AI can generate a response.
You don’t need AI to do that…
The maker of Deep Seek made it so it would be easier for him to do stocks
I understood those people knew it was gonna mess with all the projections for the development of the US power grid, chip manufacturing and other data center related industries by being more efficient than anything else and they just made money off that.
I use LLM’s to help with math/science/coding, and the thing it screws up the most seems to be simple math (typically units/conversion issues) so I would be weary about gleaning financial advice from a chatbot.
so I would be weary about gleaning financial advice from a chatbot.
Oh yes, I use the bots for projections, which I don’t necessarily take on the face value. Some calculations had been off but as long as I gain some actual profits, I am content enough.
