9 ms·

I have some sympathy for these kids. If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to f

• GoblinSlayer 4mo ago
  At this rate humans will become avatars remotely controlled by LLMs. Ironic conclusion of the consciousness debate.
  • cultofmetatron 4mo ago
    obligatory https://smbc-wiki.com/index.php/2014-12-17 https://smbc-wiki.com/index.php/2014-12-17
  • repelsteeltje 4mo ago
    Distopian, what an insightful frame
  • genxy 4mo ago
    We are already remote sensors and manipulators for the corporate and economic structures we operate under. You can't see it, but we are ants in a superorganism.
  • sph 4mo ago
    More evidence of the philosophical concept of 'technology is a life form.' Humans would be the perfect host, at least for the time being. They are certainly a willing host.
  • greenchair 4mo ago
    Yes, ask AI to produce a plan for me to do x like design an travel itinerary. It creates the plan and I execute it.
  • gom_jabbar 4mo ago
    [dead]
• altmanaltman 4mo ago
  > Many of them can no longer sit quietly for even 30 minutes just thinking on their own Sorry, but I highly doubt that. Has a very "old man yells at clouds" vibe.
  • ImPostingOnHN 4mo ago
    I doubt that you doubt that. I think you actually believe they're speaking truthfully and in good faith.
    • Finbel 4mo ago
      I doubt it. I'm stupid and I use LLMs a lot but I can still meditate for 30 minutes. But apparently some of the smartest people in the world have lost the skill? But the commenter haven't, because why, they're 15 years older and thus immune to the same LLM-effects? Plus, the issue with people having trouble sitting still for 30 minutes precede LLMs with decades.
      • ImPostingOnHN 4mo ago
        > I'm stupid and I use LLMs a lot but I can still meditate for 30 minutes. > apparently some of the smartest people in the world have lost the skill? > But the commenter haven't > why? Perhaps because a correlation you assumed was there (more smartness = more ability to sit still alone with one's thoughts), is not actually as strong as you thought? If one does not start with that assumption, there is no inherent conflict in the 3 pieces of evidence you cited. Or perhaps because you are smarter than you give yourself credit for :)
      • camelmel 4mo ago
        I didn't say I'm immune to those effects, I'm including myself in this as well. (also, I'm not older than my colleagues). Most people definitely can't meditate for 30 minutes, so if you can do this, it's very impressive. Regardless, being able to think about poorly-defined problems and build completely new mental models from nothing is genuinely a really hard and uncomfortable task. If you don't use the skill you'll lose it.
• adi_kurian 4mo ago
  Do any of said PhDs gain anything positive from LLM usage? Or does it only lead to declining thinking skills in your view?
  • thedevilslawyer 4mo ago
    They're incredibly more productive. LLMs are amplifiers, so where they'd have branched and tried out N things, they can easily try 5N pathways of RnD. LLMs are extending the frontiers of science fast -- math -> phy -> chem -> bio in that order.
    • cootsnuck 4mo ago
      I'm hearing different from PhDs. The bottleneck with much research isn't "trying out ideas" so much as it's all the bureaucratic minutiae, grants, mentoring PhD candidates, collaboration with other researchers, etc. I've heard LLMs can be helpful in limited targeted ways. But not as some kind of "game changing" accelerant.
      • sandeepkd 4mo ago
        Understanding in what ways it can be useful and in what ways it can be counterproductive in long run requires a certain degree of experience itself.
    • steve_adams_86 4mo ago
      In my own experience, the only path I truly gain intellectual benefits is the one where I work closely with the LLM, test very narrow hypotheses, and leverage it for learning over producing. Trying 5N paths is useful and sometimes yields interesting insights I’ll retain, but it’s not the rich, challenging, deeply engaging kind of process I find I need in order to develop useful knowledge and skills. So yes it’s an accelerant for people who want stuff from me, but that doesn’t map directly to learning and building skills. I think that mismatching is really important.
      • 4mo ago
• qsort 4mo ago
  I'm dumb as a rock and I don't have a PhD, but since ~1 year ago I started forcing myself to do small bits of coding and math manually. I'm not noticing a "cognitive decline" per se, but I do see I'm a lot "lazier", even stuff that used to be routine when I started coding now feel heavy.
  • asimovDev 4mo ago
    I do a similar version of this, where if I notice a mistake in generated code, I fix it manually (or at least attempt to) instead of telling Claude to fix it.
    • Cthulhu_ 4mo ago
      Same, but also because it feels like it takes longer for an LLM to do it. I think that's something people who are into gathering personal metrics should do - measure how long it takes to type a prompt / have the LLM fix things vs just doing it yourself.
      • princegift98 4mo ago
        [dead]
    • MyelinatedT 4mo ago
      This is the right balance for me as well. I use an agent to generate a first-pass attempt, and then (deadlines willing), I manually read every line at least once so I understand what the code actually does. Then I manually fix the inevitable slop that is mixed in with the good stuff, and only once the code is up to my personal standards do I send it. This probably reduces my “AI performance boost” to 30-50% instead of the huge gains reported by others. But I retain the ability to reason about the codebase and use AI much more precisely when I’m trying to troubleshoot production outages or subtle bugs — something I notice the rest of my team struggles with, since adopting “agentic workflows” everywhere. I think actively working to retain some cognitive flexibility and “muscle memory” around coding tasks is going to be rather advantageous in the long run.
• threatripper 4mo ago
  I'd argue that this is an adjustment period that society has to go through. The way we are using electronic devices today, in some years it will probably be looked at like smoking cigarettes. And I'd argue that a lot of the "decline" is due to a shift of skills away from things that mattered more in the past toward other things that are not measured/perceived by the older generation.
  • Forgeties79 4mo ago
    > I'd argue that this is an adjustment period that society has to go through. I used to think like this until social media proved there are some tech innovations we just can’t adjust to. 10 years ago you would’ve never caught me supporting any sort of age based social media ban. Now? I don’t think it goes far enough. Fake news (actual fake news) and misinformation has only gotten worse with it as well. It’s so destructive.
    • mylastattempt 4mo ago
      The human is designed to interact with small groups, to understand several smaller groups, and perhaps to imagine a big group of smaller groups. In a literal sense, let's say 100 people per group. At that level the human can actually know and interact with them still. In a city of 100.000 it's still managable to feel you are related and involved to this group-of-groups. In a city of a million, you'll revert to only your own small group and have lost the connection to the collective. The same goes for speed and quantity of input, as to what the human is designed for (not literally designed). Be it social media with it's infinite scrolling, cars racing by as opposed to looking out the window a few times per hour because you see someone/something, constant sound input if you live anywhere remotely busy or work in a busy office. The point I'm trying to make is that the world used to be comprehensible for the human. Some understood a little complexer things, some only the simpler things. Now there is an overload of everything. So, most humans are in survival mode wether they know it or not. Hence the many seekin mindfullness etc No matter, it's an observation, not a judgement or opinion on it. The world will just keep rushing forward. Some have a slight hand in the direction it goes for better (never) or for worse, but spiral it will.
• Rekindle8090 4mo ago
  [dead]
• trhway 4mo ago
  >Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well; tomorrow most regular people's thinking skills will definitely be weaker than those of the LLMs of tomorrow. And physical skills in most cases will be weaker than those of the robots. That leads to the question - what would most people do?
• anon291 4mo ago
  I feel the opposite. My brainstorming has increased rapidly. I can now just throw ideas at an LLM to rapidly validate.
  • deleted 4mo ago
    [deleted]
  • gspr 4mo ago
    [flagged]
    • anon291 4mo ago
      Not judge no. Implement and create a working MVP, yes of course. And yes, I fire off ideas all over. Many require predicting the future to decide what to focus my individual effort on. This is a terrible way to do things because humans (and LLMs) are notoriously terrible at predicting the future. The gold standard is to try everything and eliminate what doesn't work. This is impossible using human labor. With LLM labor, it's simply a matter of relatively cheap money. It's amazing. Technical problems are now no longer having to predict what the best implementation is. You can just try each one. Again, no need to have an LLM judge, because the metrics that define 'better' are well-defined, and this is the interesting part of computer science, not the implementation.
• fnordpiglet 4mo ago
  LLMS didn’t invent cheating just made it easier. When you cheat you’re the one who cheats yourself because the point of an education is to learn, not complete the assignments and get high marks on tests alone. No one benefits and no one other than you is materially hurt by cheating, but you are absolutely the one who is hurt. There’s no way to learn than to force the brain into adaptation which it is resistant to do through challenge and stress, just like your muscles. Similarly you can’t play e sports and get into physical condition any more than you can use LLMs to do your homework and learn. It’s going to be a hard adjustment for a lot of people to recognize that letting the machine think for you is as healthy as smoking brain cigarettes. The smart student uses the LLM as a proctor or provide challenges and feedback on attempts rather than an easy button. They make great tools for learning if they’re used as an adversarial or editorial tool. The future belongs to those who work to use the tools in ways that make themselves more efficacious, not those who use efficacious tools so they don’t have to work.
  • WalterBright 4mo ago
    You're right. But I like to add artwork to my presentations. My artistic skills have not advanced beyond 2nd grade. So I'll make a line sketch, and give to AI to "fix" it. The results are nice and I use them. I have no interest in learning how to do art well myself, so using AI for it is appropriate. But I still write my code myself.
    • sph 4mo ago
      > But I still write my code myself. Not for long, if you so easily have caved in to using AI elsewhere. People are lazy. If you see that the 'results are nice', it's game over for your programming/thinking. Waiting for the day the advice will be to "enjoy AI assistance in moderation"
      • WalterBright 4mo ago
        We'll see. I kinda suspect that vibe coding would take the joy out of it.
    • 4mo ago
• adamcharnock 4mo ago
  I've been wondering if there would be a benefit to inverting how we teach subjects now. Previously we would teach from the bottom, and build up. Semi-colon goes here, curly brace goes there, and then build up to architecture, systems, etc. But this doesn't seem to make sense when someone comes to a topic with an LLM in-hand. They need to know high-level techniques, architecture, best practice, etc. As they pursue the topic they start to get down into the details, although probably never learn to do it fully independently. I quite like this view because it paints a somewhat optimistic way forward from where we are now.
  • wesleywt 4mo ago
    I don't think you can learn high level techniques or architectures without first understanding the basics first. This means boring boiler plate coding.
    • adamcharnock 4mo ago
      I’m not sure. We’ve always had to pick the level of abstraction we start teaching at. Voltages, transistors, registers, assembly, C, etc. This feels like it could just be a progression of that.
  • kmac_ 4mo ago
    This idea sounds good at first, but if you look closer, it would just make workers, not experts who really understand. What we could do, and already do, is tweak the learned abstractions. In our field, it's easy to see: most of us first learned about computing abstractions, not how processors actually work, or started with Java, not assembler. Plus, you can't teach math from top to bottom.
  • f311a 4mo ago
    You can ask LLMs about high-level techniques, and their answers will usually be good enough. What you can't get from LLMs is the taste and judgment, which you can only obtain by having a strong CS base and coding manually for years. High-level techniques were never a problem. You could Google tens of articles on this topic. They are useless too, it's like learning how to drive a racing bicycle from reading a book. Sure, you will know a lot about nuances, but you will fail miserably when it comes to a real race.
• drakonka 4mo ago
  I have observed this in myself when I began to over-leverage AI in my workflows. I've since become more deliberate with what kinds of tasks I will use it for, although I still slip up. With writing: Things like brainstorming a plot line for a book with a custom GPT or Claude project that has all of my prior books in its knowledge? Works great. Things like asking it to write a paragraph or chapter for me - I can rapidly feel my own writing skill, motivation, vocabulary, and ability to grasp/remember the resulting plotlines deteriorating. I don't use it for that anymore. With studying: I've been taking a couple of evening uni courses and the thing I found so great is that I've been forcing myself to think through the problems, and take my own notes in every lecture. I may then still get ChatGPT to help explain and reason through some of the concepts with me. And I have it review and 'grade' my assignments. But I refuse to ask it to start drafting answers. With programming: This one is tougher. When I am not very personally invested in a problem or codebase it becomes too easy to offload more parts to Claude, and when the company encourages 'vibing' to speed up velocity and you're reviewing and writing a higher influx of lower quality PRs, investment goes down. I still sometimes catch myself committing solutions I only _mostly_ grasp and the rest is hand-waving. A big part of it is a work culture thing. For my own projects I make sure to understand and have a back-and-forth with the planning agent for each task, or write the first plan myself to go off of. When it comes to producing the code, I have to admit it is much easier to properly review parts of the codebase I am extra interested and knowledgeable in (backend in my case). The frontend I'm less well versed in and also admittedly less interested in, so I do sometimes fall into the trap of "Ehh it works, just commit it" with the goal of doing a thorough quality pass before actual release. With all of the above, I can feel my ability to think, plan, reason, focus (and my vocabulary) suffer if I go over the line too much into agent offloading. For me keeping that balance is as much about maintaining my own long-term brain health as it is about producing good output. I imagine younger people growing up with AI today won't even know what that more capable (in my opinion) brain state feels like - to them, the AI-using brain will be the norm.
  • CuriouslyC 4mo ago
    The place I've come to with AI for writing is to have an idea for a chapter/article/etc, which I take to AI, and tell it to either ask me a bunch of clarifying questions, or try to blow holes in it/challenge it. I'll keep talking to AI and answering questions/handling challenges until the AI runs out of steam, then I'll ask the AI to write out a condensed outline with all the pertinent details of the conversation. Once I have the condensed outline, I'll re-order stuff, clean it up/tune it up, then do the final writing. This keeps my voice and logical train of thought while avoiding blank page syndrome and some of the organizational mess of condensing notes into an outline manually.
• trismus 4mo ago
  On the contrary, with the amount of times I went to ask for help and was failed pedagogically, plus not being able to afford tutoring like my peers had, I think access to an LLM would have genuinely boosted my grades. I still did well, but I had gaps for which there was no help outside of the internet available.
  • antihipocrat 4mo ago
    You're using it to help you study and think, which is great, but the original post was about how many people are bypassing that step entirely.
  • Cthulhu_ 4mo ago
    The risk or difference is that tutoring helped people learn which they can use to do the work, whereas with only one or two different words an LLM will do the work (that proves you have learned) for you. A tutor has limits, but an LLM needs to be asked to set limits. And especially younger people are less likely to "punish themselves" like that.
• conductr 4mo ago
  I’m not noticing the decline in my own abilities any more than I had before using them. I finished undergrad 20 years ago and my once sharp math skills had been severely diminished within only 5-10 years. Just simple arithmetic and percentages that I could rapidly do in my head became dependent on calculators/spreadsheets. For all other trivia type knowledge, my brain has offloaded it to the internet RAM in my pocket. It’s a familiar feeling of when some question comes up and I think “oh, I used to know that, let me look it up”. Maybe I just already hit my personal floor of stupidity before LLMs. However, I personally feel a huge mental burden of the state of communication. The contemporary version of it where I have a million threads and conversations im juggling at any given time. Emails, voicemail, chat, online, texts, personal, business, home, children, other family, friends, then there’s the variants like Messages, Messenger, WhatsApp, etc. And as overwhelming as it is for me, I’m super under connected than everyone else I know. I quit following most news and all sports, as I just don’t have the bandwidth for it. My brain was molded preinternet and I feel like it’s reaching its max on the analog to digital conversion. Or at least it’s just a really lossy process.
  • noduerme 4mo ago
    Yeah, I'm 45 and I'm like you - no social media, relatively under connected, and still feel swamped constantly by emails and calls and especially texts. They eat up half my productive time every day, and most of them are things I'm looped in on that I don't even need to respond to. Okay so let's say that's the new cognitive burden. The new escape hatch is "AI". Now you don't need to read your mail or write responses! Let an LLM handle that for you! And now your friends and coworkers will send you AI generated mail anyway, so if you're actually taking the time to read and respond to it yourself you're a chump, right? Noise machines. Humans are noise machines. Ever try to sleep till noon and notice that everyone else seems like they can't feel alive unless they wake up and make the maximum amount of noise and racket possible? What could be better for a gibbering species of ground dwelling apes than a miraculous machine that gibbers for them, to point back and forth at each other?
    • princegift98 4mo ago
      [flagged]
• rustystump 4mo ago
  I see this too. There is this theme where people are more and more going only as far as the ai does. Asking suggesting or arguing to go deeper is impossible. There is a new path of least resistance and it saddens me.
• noduerme 4mo ago
  Yeah, it's a scary thought. I feel the pull of it every time I'm stuck on a code problem that I don't want to search solutions for and hand-code... and I also feel myself wanting to reach for the crutch of an LLM when I just have something boilerplate and easy to do. It's incredibly tempting to just ask the question and have the "thinking" done for you. Until you have actual skin in the game and realize that it doesn't reason, and its "thinking" is utter shit. Then it's like: you got addicted to cigarettes and now you have to quit, because this habit is poisonous. It really does lead very quickly to cognitive decline if you rely on them, or even think about asking them while you're writing code.
• huijzer 4mo ago
  I recently switched back from a Tesla to an older car without permanently having a map visible. Suddenly my brain has to think about routes again and it definitively feels like my brain has to put in more effort again to handle it.
• jerfjlejr 4mo ago
  I think it varies tremendously from one role to the next. I'm a senior software engineer and LLMs, the way I'm using them, improve almost everything I do. I use them to write most of my code now, but first I spent twenty years writing code before LLMs came into existence and second writing code is like 5% of my job. Most of my job is research, investigation, and architecture. I treat LLMs just like a junior engineer. I give them clearly defined jobs that I could do on my own just fine, that I already spent years doing. The problem here is that students are using LLMs to automate everything BEFORE they become proficient at it themselves. Letting college students use LLMs for homework is like letting kindergarteners use calculators instead of counting on their fingers.
  • krilcebre 4mo ago
    You cannot tell me that letting anyone do something for you does not affect the skills that you outsourced, unless you are some sort of a superhuman. As an example, I have been drawing portraits for quite a few years now, and whenever I go on a hiatus and come back after a few months, I can notice my skill not being anywhere close to where it was before I stopped using it. Sure, after 2 or 3 portraits they mostly come back because of the previous experience, but skill rust is a real thing, and if you think your coding skills are the same because you used to code 20 years but haven't coded for some time, you are probably just lying to yourself.
    • eueje 4mo ago
      Yeah he’s living in denial. His skills are slowly eroding. Given that he spent 20 yrs building it up it won’t happen overnight. But the trade off is happening in real time.
    • mythrwy 4mo ago
      My "digging for roots to eat" skills have also atrophied. Fortunately I don't need those much anymore because of modern agriculture. I wonder how much of this "you are gonna lose your skills!" stuff matters. And if knowing how to properly iterate a for loop with my eyes closed matters all that much anymore.
• himata4113 4mo ago
  This likely varies person by person or the way people adapted AI. For me AI replaced the boring part of writing code, but has not replaced the fun part of thinking about code and problem solving.
• jampekka 4mo ago
  > Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well; many of them can no longer brainstorm, code, think deeply, or write without an LLM present doing 90% of the work. Many of them can no longer sit quietly for even 30 minutes just thinking on their own, which is a required skill for producing original thought. This was my experience even pre-LLMs though (about my own PhD thinking skills too). I blame the amount of random stuff work now involves more than LLMs.
• zelos 4mo ago
  I totally agree about school-level homework: it was many years before my pre-frontal cortex developed enough that I could have forced myself to do the work. That said, though, one thing I don't understand about the heavy users of AI in academia and software development is that the thinking and coding is the fun part. And that's the part so many people seem to be so keen to automate away.
  • qweqwe14 4mo ago
    Isn't the fun part having the thing work how you wanted it to? Why shouldn't I be keen to automate the process away?
    • cryptopian 4mo ago
      I've read enough comments* on HN to know that there are different camps. Some people don't really enjoy the process of development and just want results. Meanwhile, telling me to automate away the problem solving aspect of software dev is like saying "you know you can just copy the answers to the crossword from the back of the book?" *speaking of things I should be doing less of...
    • chasd00 4mo ago
      different strokes for different folks. I'm def. in that end result camp, i get the biggest thrill out of seeing something work. For me, coding agents are awesome because i can bring a lot more to life in much shorter of a time frame. I do enjoy the process and problem solving of coding, it relaxes me. On the other hand, i really really enjoy when an idea i have is on the screen and working.
    • NichoPaolucci 4mo ago
      Depends on the person. I find that it's extremely satisfying to figure out a tricky problem on the way to that end result - to struggle with something for a bit, then finally fix it or fully wrap my head around it. So to me, it's a mixture of both. What I want is the end result, but in the past sometimes that came with thinking in the shower about an approach... Or a wild thought while going to bed that makes me jump up and grab my computer. That doesn't happen for me anymore to the same degree.
• ibmmmm 4mo ago
  As much as I hate to admit it, using agents for too long makes me less able to think for myself. I am dedicating 30 mins to 1 hour everyday writing and thinking without LLMs.
  • danubis 4mo ago
    Shouldn't it be the opposite? 1h max LLM per day?
    • olmo23 4mo ago
      Perhaps, but I'm not sure my boss would appreciate that though.
  • embedding-shape 4mo ago
    > I am dedicating 30 mins to 1 hour everyday writing and thinking without LLMs. Before you did this, was literally every hour of your waking time spend thinking about LLMs? I don't think I could do that even if I tried, and I spend all my development hours with agents, but during meals, showers, walking the dogs, enjoying a coffee outside or whatever, naturally I get time to think about other stuff, sounds out of the ordinary (to me at least) to have to dedicate 1 hour to not think about something. Reminds me of when I was addicted to amphetamines way back when.
    • retsibsi 4mo ago
      > Before you did this, was literally every hour of your waking time spend thinking about LLMs? They said "writing and thinking without LLMs", not "not thinking about LLMs". I think they're talking about setting aside time for fairly focused thought/work.
  • anirv 4mo ago
    [dead]
• yieldcrv 4mo ago
  > For adults the cognitive decline won't be as measurable since there's no exam I think this is true of every affliction that adults criticize children and teenagers of I’ve been out of university for a very long time, and I took a community college course and for the first few sessions I couldn't focus or sit still at all. Fortunately I knew that was abnormal and how to conform to a prior version of myself, but I don’t think children have a frame of reference.
• prawn 4mo ago
  I wonder if AI or something else changing (developing anxiety, etc) has made the pay-off of the degree less certain. If you're confident that your years of effort will pay off, it's probably easier to see it through. If you're worried that AI will wreck your industry before you hit the workforce, maybe the equation changes and you're more inclined to gamble with shortcuts?
  • jeremyjh 4mo ago
    Yes, and this is going to hurt everyone. If everyone knows that you can skate through a college degree without doing any work, it is not going to have much value as a credential.
• bsenftner 4mo ago
  When LLMs and ChatGPT first came out, it struck me as obvious and dangerous to a deep thinker or a knowledge worker the answering capacity. So, from my initial use I did not ask them questions, I have always "done my own work" and then asked the LLMs to criticize that work. This has been an exponential ladder of learning, and my cognitive growth is personally noticeable. I'm not hesitating to scribble out calculus and work it out, as I need for my work, where in the past I'd have found some other way because I felt uncomfortable with my tip-of-my-tongue calc skills. Don't ask AI, do your own work and ask for criticism, and them improve your own work yourself. This creates a learning ladder that you will climb.
  • ab71e5 4mo ago
    That's nice except when you work somewhere where more and more developers are pushed to pump out slop generated by AI as fast as possible. So far I am not there yet but I have plenty of friends in the industry who are basically 'not allowed' to code manually anymore.
• helsinkiandrew 4mo ago
  > If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to fail all my tests. I agree - I would have been toast. I wonder if the teachers/colleges need to change the way they teach and assess. Let the students use the AI tools they like (perhaps guide them how they can use them professionally), but test regularly and early on the skills/knowledge they're meant to be gaining offline and in person. Oh and don't give Fs for cheating - suspend them. I read a few years ago about a teacher (I think highschool) who put his lectures on YouTube for students to view in their own time and then used the in class hours for interaction, questions, tests. EDIT: Claude beat my Googling: This was 2 chemistry high school teachers in 2007 - The Flipped Classroom https://fltmag.com/the-flipped-classroom/ https://fltmag.com/the-flipped-classroom/
  • phantom784 4mo ago
    > I read a few years ago about a teacher (I think highschool) who put his lectures on YouTube for students to view in their own time and then used the in class hours for interaction, questions, tests. That seems like a smart approach. It reverses the traditional model of "lecture in class, homework outside of class".
    • olpad 4mo ago
      I always absolutely hated when a teacher did a reverse classroom and I had to “learn” at home and then practice in the classroom. I think the solution is more engaging lessons and less outside work. I know why homework exists, but homework is a chore that most people want to get done as fast as possible. If kids got to learn something interesting in school and then have their free time after school, there would be less dependence on AI. If they’re interested in the topic, they’ll put more effort into it. If not, they were never going to retain it anyway
      • deleted 4mo ago
        [deleted]
      • TaupeRanger 4mo ago
• bko 4mo ago
  What does this have to do with LLMs? They stopped requiring SAT and ACTs in order to get a student population more representative of the population in general. This obviously allowed students that were not prepared for college into the system. If you do well in your math SATs you'll likely do well in math college. SAT scores and college GPA are highly correlated. No idea why anyone thought it was good to ignore probably the strongest signal of success in college.
  • djeastm 4mo ago
    Isn't GP talking about PhDs here? If they're PhDs I imagine they've already had good enough GPAs/were smart enough to be selected for the program.
• datsci_est_2015 4mo ago
  I don’t buy it. Properly leveraging LLMs to generate stable and extendable systems is mentally exhausting (i.e. highly demanding of intelligent thought), especially given the poor quality and churn within the harness ecosystem. Now, if you’re creating trivial, unstable, or nonextendable systems maybe this doesn’t apply. And maybe I have long overestimated the work that SWEs have done.
  • jansport123 4mo ago
    i use claude a lot and i find that it is best applied in domains in which i am already a master. I tried applying it to domain's im unfamiliar with and i found that i produced stuff but as time went on i understood what i produced less and i almost felt like i do after binge watching a netflix show, 2 weeks later i barely remember any of the details. I wonder how much you need to "do" to learn and remember. LLM's give you a shortcut to doing and so you probably aren't learning either. It's like when you watch a professor write a proof and it makes sense while listening to the professor but at home you have difficulty deriving it. LLM's give me the same sort of feeling. I think the way forward is still going to be doing things manually to learn and using LLM's once you've mastered an area and people who don't understand this fact are going to slowly descend down a hill and forget how to depend on their own thinking.
• cataphract 4mo ago
  We also had exercises for which the solutions were given, and we didn't reach for them immediately...
• rafaelmn 4mo ago
  This is all assuming tests measured anything valuable in the first place. In my experience standardized tests were always flawed and most of my peers knew shit about the subjects they passed in top % a year after. If AI breaks the current education system that's a win in my book.
• DanielHB 4mo ago
  I dunno, I used wolfram alpha a lot during calculus classes. However my uni didn't require any homework assignments to be done and they did not contribute to grades. Only the exam mattered. Maybe the problem is that doing assignments contributes to your grades? The answer from wolfram alpha wasn't so much to get the homework done, but to understand how I would be screwed in the exam.
• CuriouslyC 4mo ago
  LLMs have killed my facility but not my knowledge. I can still read code and write it, I just need to look back at docs a lot more, when I used to just know things. I also have to sit and try to recall how to do things and what abstractions are involved more. I also have more "writer's block" when starting with a fresh program/document if trying not to get AI to seed it with a baseline implementation, where I have to sit for a while thinking about what I really want to build.
• aleph_minus_one 4mo ago
  > If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to fail all my tests. You go to a university because you are deeply interested in understanding the subject that you study. Doing the homework and the tests are just the "goalposts" to check for yourself whether you made progress on this. So, as long as you are not under time pressure (which you in some degree courses unluckily are), there is simply no need to "speed up" any homework assignments. If, on the other hand, LLMs help you with making much faster progress in understanding the subject that you study (which is only loosely correlated to homework and tests), I guess it's fine to use them. Just always keep in mind that very often the pain of attempting to understand the topic on your own often makes you smarter - something that you will miss when you take an "LLM shortcut".
  • dmd 4mo ago
    > You go to a university because you are deeply interested in understanding the subject that you study. This has not been true for something like 70 years now. People go to university because it is expected that that is what you do after high school.
    • aleph_minus_one 4mo ago
      > This has not been true for something like 70 years now. People go to university because it is expected that that is what you do after high school. In Germany, many people indeed say if you are not deeply into the topic that you study, you should rather get a vocational training (Ausbildung), or attend a different kind of tertiary education than a university such as - Fachhochschule - Berufsakademie (these words have no good English translation). Basically these are kinds of tertiary education that are more applied than the much more scientific training that you get at a university. Specifically for mathematics (I guess the same holds for physics), a lot of people say that if you don't consider it to be an ideal life to think about math exercise sheets when you sit in the bathtub while other people are having fun at some party, you simply are not made for studying mathematics and should change your degree course as soon as possible.
• hgoel 4mo ago
  HN is going to eat up this garbage
• otikik 4mo ago
  The LLMs will gradually cramp more and more adds in their responses in an effort to make a profit. At least now we know why we will start watering our plants with Brawndo.
• jazz9k 4mo ago
  I think this would be fine as an adult, if it meant using LLM to churn out the boring work required of you at a corporate gig, to spend more brain cycles on something you actually want to work on. The problem is that it sounds like many people are just using it for everything.
  • a96 4mo ago
    Well, there is the problem that a lot of people don't have things they actually want to work on. They don't know how to self actualize and/or don't want to spend brain cycles on things.
• sumtechguy 4mo ago
  > Now I work mostly with PhDs who were at the top of every academic environment they've ever been in. And yet I can see their thinking skills rapidly declining as well I noticed this before LLMs became a thing. It was by accident. We had a team of programmers. All decent at what they do. The management said 'hey you want to learn another language we are going to be using it for these upcoming projects'. So we set up a self learned at your own pace class curriculum. Maybe 10-20 hours of school work if you sat and really dug in. Maybe 3 to 4 hours if you breeze thru it and do not care much. We set up weekly check-ins doing about 1 hour a week. Easy. Watch a 20-30 min of vid 20-30 mins of do homework come to check-in and talk about what you learned and help others if needed. Now this is where I was disappointed. The first 'class' was 40 people. By the last there were 3. Those 3 I noticed always are the ones who dug in. The rest wanted a proctored classroom and someone to tell them what to do. Actual genuine curiosity is rare I think. We have a lot of people who are decent at what they do. But do not really care about it. IF you do not care you are going to just push the button and get the answer.
  • duskdozer 4mo ago
    I could see myself dropping out even if I was interested in learning. I'd suspect that the time spent would end up with me needing to stay late to make up for it or being penalized in some other way.
• jordanpg 4mo ago
  > If LLMs were around when I was a student, I would've also used them to "speed up" my homework assignments then proceed to fail all my tests. As a counterpoint, I was once a physics grad student. I didn't finish the PhD because at some point I discovered that I was not going to be the next Richard Feynman and this was too much for my ego at the time. But I think that if LLMs were available, I might have finished. Part of my problem was that at some point the math transitioned from stuff I understood to symbols and notation that I knew how to manipulate but didn't really understand. LLMs could have helped bridge that gap. On the other hand, it's hard to imagine I wouldn't have used it for Jackson, etc. but we got Jackson solutions from previous students and the internet anyway. Using LLMs probably would have been more effective, used correctly.
  • tstrimple 4mo ago
    This is also where I had issues advancing in math. For so long I was able to build intuition around mathematical concepts easily. They fit in my head and made sense. I couldn’t understand why my peers were so bad and slow at picking up the concepts. Until my first calculus class where there was absolutely no focus on the intuition or practical utility. It was just formulas for the sake of formulas as exposed by our teacher. It wasn’t until I was curious enough to learn about calculus outside of the classroom that I was exposed to things which helped develop that intuition and made the calculations something other than just symbols and equations to memorize.
• afavour 4mo ago
  > For adults the cognitive decline won't be as measurable since there's no exams, and overall output volume will still be fine due to LLM help The leading indicator for me is the amount of emails and, god forbid, more personal messages (like birthday wishes!) I see that are obviously AI generated. It just keeps on rising. If you’re not able to dash off a quick message without the help of AI I have to assume you’re using it heavily elsewhere too. I have sympathy for the university students too, we’re all bombarded with rhetoric about AI being the future. And I remember being incredibly nervous emailing my lecturer (am I phrasing this right? Is it respectful enough?) that I can imagine leaning on AI myself had it been available back in the day. But I’m glad it wasn’t, it’s an important skill to work out this stuff. They’re going to land an in person interview when they graduate and stumble around unable to effectively answer the questions they’re asked in real time.
  • rckt 4mo ago
    > They’re going to land an in person interview Not necessarily. It can be either an AI interview or a record that will be analysed by AI later. So there’s a chance to cheat here as well.
• efavdb 4mo ago
  When reading and writing became prevalent, the ancients bemoaned our reduced facility to memorize long texts. Are we now “less smart” because of that technology?
• pseudocomposer 4mo ago
  We’re in a world where LLMs are basically going to be extensions of how we think. An additional thing we use to do a lot of thinking tasks. As a piano player, it’s important to work hands separately. Sometimes your right hand will carry the melody and your left hand the harmony, sometimes vice versa. Sometimes there may be more than just two “voices”/melodies/lines between your two hands. Even as a very good (as in getting paid to do it) sight reader, I learn a lot working all the voices/melodic lines separately. Singers do similar things like singing only the vowels to keep themselves in the right placement. Learning handstands, you have to work your wrists, rotator cuffs, core (which is many things), etc. separately. Yoga, Pilates, and running also help us learn to break problems down this way. Anyway, all that to say: If LLMs are gonna be a natural extension of how we think, we need to understand what parts of problem-solving LLMs are good for, and what parts our brains are for. The nice thing about working these bits “separately” is that one side is done for us. So we just need to consciously practice using our brains. As programmers that means, maybe we conscientiously practice writing things ourselves sometimes. Remembering that this even if this sacrifices short-term “velocity” (whose measurement is problematic, but I digress), it preserves our long-term ability to do good work. And I think any of the above physical/artistic practices (or countless others), worked in these ways, will help reinforce this entire mindset. I think kids of the coming generation will be sharply divided on their ability to conscientiously practice things separately. It’s been happening, but I suspect LLMs will accelerate it unless how we actually teach kids can catch up.
  • SoftTalker 4mo ago
    > We’re in a world where LLMs are basically going to be extensions of how we think If that's the case then we're in trouble based on my experience. This week I've been using ChatGPT to help figure out some old linux platform that I need to resurrect. It's very good at quickly searching and surfacing relevant information online, and that's helpful, but if I did not have a lot of experience at linux administration to be able to see where it was suggesting the wrong thing, or initially dismissing the right thing, then I'd just be thrashing. The LLM is helping me because I know what I need, and it can search and read faster than I can. But it's not really very smart.
  • kibwen 4mo ago
• Balgair 4mo ago
  I've got mixed feelings on AI assistance. I'll relate 2 anecdotes. 1 - When I was in grad school (before AI), we had to use Canvas for a class. One day, I got an obvious spam/phishing email in the internal Canvas system. It was so strange. The writer just would randomly hit the capslock button and keep typing away, no salutation, no signature, just a real mess. They were asking for a particular professor to come to their house to teach them about ... something? Again, real strange. So, I email IT and say 'Hey, somehow a spammer got into the system, do your thing'. They email back and go 'Nope, it's a student, that somehow managed to CC the entire system, sorry about that'. Dear Reader, the message was pure garbage. Literally, it looked liked it was written by a 3rd grader without any shame. [0] I happened to know the professor of the class. So later on, I talked with them over symposium coffee about it. They said that they remembered that particular email because of all the IT back and forth. It was for an upperdivision class in the Engineering department. The email itself was not particularly notable otherwise. In that, they saw such emails all the time, in terms of quality. This was a top 100 ranked (whatever that means) university, by the by. Shocking. 2 - My grandfather was an officer and a mechanic for the USAF. A bit of an odd combo, but he was partly responsible for instituting many preventative maintenance checks and protocols, novel in those early days of the AF. His aptitude and memory were quite sharp for many mechanical things. Until the strokes from decades of smoking caught up, he could tell you exact measurements and torque values for a variety of airplane related things (I can no longer remember what exactly, the memory skills did not transfer to me). I do vividly remember standing in that light blue garage of his and him all but yelling at me once. We were looking at the brakes on an old car he was 'restoring' (getting away from Grandma for a little bit). He pointed at the old drum brakes on the axel. He asked me how tight the pads should be on the inner rim of it. I had no idea. So he asked where I might find out. I figured I'd ask him. But what if Grandpa wasn't there? We'll I'd have to look it up somewhere (they had no internet). Fantastic. Now, what about the next time you're working on the brakes? Well, just make sure that the pads are at that spec. And that when Grandpa hit me with the nugget of hard won wisdom: No, you look it up every time. Because these are brakes, and if you are wrong then they might fail, and they might fail when the driver has their whole family in the car at 100 mph. And then because you were lazy, half a dozen people die. --- These two times stand in my head when it comes to AI. For the first one, yes, AI would be such a boon to that very clearly struggling student reaching out for help. It would get them back on the path to the real struggle of getting their degree. That level of assistance would be like a wheelchair to a paraplegic. For the second anecdote, AI is condemning people to death. Using it in life critical situations and care, letting it hallucinate or skip over critical values, that's a recipe for disaster. Where do we set the fine line of using AI and not? For brakes and X-ray machines, obviously not. For helping kids learn to write emails correctly? Sure, sounds great. Unfortunately, I feel the old adage about regulations is going to be true here like it is with every new technology: The rules are written in blood. [0] therh lasdkjenail EMAil was sposmkehting alLIKE HTIS IN THE WAYS THAT IS aw adklhjf writtene sand htenn. sned t sent ASLAOSNG ASLIONG ALONG TO NTHE recipentnts .
• daveaiello 4mo ago
  You make good points here. But I want to point out some issues that I have with what you are saying, because I see a few assumptions that I would not myself make. I graduated from RPI with a degree in Management and a concentration in Information Systems. I began in Computer Science, and didn't like it because RPI CS at the time was loaded with professors who were mathematicians who had transitioned over to CompSci and because the 100 and 200 level courses were excessively math-heavy in my view. Since this was the late 80s, there may not have been an easy way to teach B.S.-level computing without it being heavily math-based, but I digress. No matter what degree we achieved or what work we ended up succeeding at, we have a tendency to look back at people rising in the ranks below us, see differences in their experiences and struggles, and say, Look! That is evidence of a lack of rigor or a lack of understanding of fundamentals that we had to learn in order to succeed. The only thing is that some of what we learned to become successful just isn't necessary to be learned when we learned it. I do a fair amount of low-level software engineering with Claude Code now that was above my level of understanding of data structures and algorithms because I never took those CS courses at RPI because I switched to Management IT. But as someone who could be described as a solopreneur at some level, my new system designs reach a certain level of complexity or code maturity, and I hit problems that I would not hit if I had more understanding of data structures and algorithms. So-- I end up having to learn aspects of those disciplines at that point, rather than before I actually needed them. I run into these situations often enough where I now say to myself, gee, I wish I had taken Data Structures. And I think, could I effectively take Data Structures at this late date and get better at specifying how I want data stored, or perhaps knowing the shortcomings of simplistic database structures that are the ones I end up with initially because of my lack of spec-writing skill? Aren't many of the less experienced folks who come up now, whatever age they are, going to hit problems that show them their weaknesses in this fashion? Is the issue that these people will never get jobs because the seniors and managers who are interviewing them will design interview questions that keep people with their level of understanding out of the workforce? What happens when somebody who sucks at the fundamentals but is really motivated bangs their head against their shortcomings and eventually succeeds in building something that takes off? Aren't those people great assets because they learned some of their critical skills the hard way?
• rob_c 4mo ago
  No, that's the quality of candidates. I wish I was joking as a PhD holder for only 15yr. A lot of skill of is getting bled into the private sector because getting the PhD in a lot of regions doesn't mean the step up it used to. A lot of that comes from awarding them to layabouts doing "a gender critical analysis of ...". Industry doesn't how/what/why they just wanted the 3 letters as a performance barrier to hire competants.
• Hasz 4mo ago
  Counterpoint, I think this is true for some archetypes of people, but certainly not everyone. I personally use it like the socratic method. I am an intermediate user, I spend a ton of time with LLMs at work and personally, both prompting and letting some crappy agents try to automate boring work. I primarily use Gemini and ChatGPT models, along with some Chinese smaller weight models (eg qwen) locally. If you treat the model like an excellent bluffer, it has never been more fun to challenge a model. To me, there is something deeply intellectually satisfying about "proving" it incorrect, and I like being deeply critical of what the model spits back out. I find that refinement process (with the constant sycophancy turned down in the system prompt) creates a really good loop of critical evaluation that would be hard to get in anywhere else. You can treat it just like the Socratic method, but instead of a benevolent teacher, you get a probabilistic bullshit artist. Lots of fun, highly recommend.
  • abustamam 4mo ago
    This, I will use Obra Superpowers brainstorming skill to propose/refine a few viable solutions for a feature or bug I'm trying to solve. After it asks me clarifying questions and presents a spec, I will say "well what about X or Y". The I'll run the grill me skill on the spec to tighten it up, clarifying any assumptions made. I find it to be a really tight loop and results in very high quality code at a high velocity.
  • greenavocado 4mo ago
    > If you treat the model like an excellent bluffer, it has never been more fun to challenge a model. To me, there is something deeply intellectually satisfying about "proving" it incorrect, and I like being deeply critical of what the model spits back out. I find that refinement process (with the constant sycophancy turned down in the system prompt) creates a really good loop of critical evaluation that would be hard to get in anywhere else. You can treat it just like the Socratic method, but instead of a benevolent teacher, you get a probabilistic bullshit artist. Lots of fun, highly recommend. Yes, but eventually the intellectual whack-a-mole gets tiresome unless you get really, really good at simultaneously cornering it and not letting it concede to your point.
    • 4mo ago
• amanaplanacanal 4mo ago
  Maybe you've discovered the great filter.
• jordanb 4mo ago
  I used Google Translate to not learn French in collage. Fortunately for me it was bad enough I had to carefully review all its outputs, but that still didn't help and I managed to pass two semesters without ever developing even basic language skills. Something radical needs to be done. When I was in high school there were still a lot of "no calculator" restrictions in my math classes that I chaffed at because I hated doing longform arithmetic and felt like it got in the way of learning. So I can certainly understand how students would chafe at some kind of paper-only education system but I also don't see how you can learn anything when you have a high-quality homework machine just sitting there.
  • delichon 4mo ago
    All that's needed is a tight feedback loop between learning and applying those skills ... the thing that Google Translate helped you evade. AI can be a tool for evading or optimizing that loop, like a knife can cut your sandwich or your throat. Your choice.
    • failbuffer 4mo ago
      It's the "your choice" that's the problem. The quality of a society is dominated by the choices that other people make.
  • Auracle 4mo ago
    I wish that would have worked for me - we had oral tests. 2 years of French in high school and one semester at college - what an absolute waste of time. How much French do I know now? Basically none. The same goes for everyone in my life that did Spanish instead in high school. Part of what we could do during this upset is re-prioritize.
    • octoberfranklin 4mo ago
      Wow, really? I took four years of Spanish in high school, and thirty-ish years later I can hold basic conversations with people, ask for things, answer their questions.
• sbayg 4mo ago
  How many took the COVID vax? /s
• bwfan123 4mo ago
  > I wanted to be in denial about it before but it's too obvious to ignore now Use-it-or-lose-it is the evolutionary principle, both for cognitive and physical abilities.
• SirMaster 4mo ago
  I don't understand why people take shortcuts in school. You pay a LOT of money to be there to learn. Taking shortcuts seems completely counterintuitive to me.
  • airstrike 4mo ago
    A lot of people view it, rightly or wrongly, as paying a lot of money to earn a degree that opens up certain opportunities, while learning is secondary, so minimizing effort is worth it. And to some people, it's not even a lot of money. In many ways, schools are just the modern day peerage system.
  • djeastm 4mo ago
    - Time is a scarce resource. Students do what they can to learn what they can, but if they're under the gun, they'll take the path of least resistance to make it to the next day (totally not like the business world, right?) - In the interest of having well-rounded students, a lot of degree programs include subjects the student didn't want to sign up for, but have to. Even in something like CS, I knew a lot of people who liked the hardware side of it, but didn't like the software side and vice versa. So I can imagine a student justifying taking shortcuts that way. - Psychological reasons like wanting to protect their ego. Maybe they had always done well in school and are now struggling, but don't want to ask for help, so they think why not just take a shortcut here and promise to do better next time, etc., etc.
• jackgavigan 4mo ago
  I've avoided using AI* for precisely this reason. I don't want my brain to get lazy and rot. (* I can count on one hand the number of time I've used an AI tool.)
• girfan 4mo ago
  I broadly agree with the premise. As a PhD student in Computer Science, I feel there are some significant upsides to my work routine. LLM access has made many new domains more "accessible" to me which I otherwise would be too hesitant in investing my time in. For example, my area of research is computer systems which involves operating systems, distributed systems and more recently systems for AI. Within these, there is a wide breadth of topics/techniques one can employ and up until now, I have not gone deep into theoretical aspects of things like scheduling etc. But with access to LLMs, I feel like I can at least brainstorm from a high-level about these sub-areas that I am not well-versed in and the responses give me some relevant pieces to start exploring on my own, depending on what interests me more or the amount of time I want to spend on that sub-branch of a larger tree of ideas. However, the one thing I do have skepticism is the lack of awareness of blind-spots when dabbling into areas that I am not an expert in, and taking the LLM's lead in applying such techniques to some systems problems that I am working on. I often feel that I am not aware of what alternatives exist that the LLM has not explored for me, or if the directions it has proposed really do apply or have corner cases/assumptions that break in what I am doing. On the other hand, when working on something I have good intuitions about, I am often correcting the model's assumptions and it back-tracks what it told me. Unfortunately, I cannot do that comfortably with topics I don't have good intuition about which limits my confidence in "if this is the right direction to pursue."
  • nsagent 4mo ago
    As someone with a PhD in CS focused on NLP (I started my PhD in 2018 just as Transformers were introduced), and with a strong background in distributed systems owing to the fact that I was a lead developer of an MMO before starting my PhD, I can definitively say that any surface-level understanding you get by interacting with an LLM, is just that: surface level. If that allows you to target your deep dives better, then great. If instead your deep dive into a topic is purely through prompting an LLM, that will almost certainly end with little functional domain expertise. The absolute best experience you can get is by trying, failing, then improving upon your past failures. Remove that friction at your peril.
• keeda 4mo ago
  > Many of them can no longer sit quietly for even 30 minutes just thinking on their own Plummeting attention spans has been a trend for much, much longer than LLMs and is more the result of constant digital interruptions and these days overwhelmingly social media and doomscrolling: https://www.apa.org/news/podcasts/speaking-of-psychology/attention-spans https://www.apa.org/news/podcasts/speaking-of-psychology/att... The effects on children have gotten most of the, err, attention, but the effects on adults are no less deleterious.
  • Theodores 4mo ago
    In 2002 I spoke with a lecturer in the humanities and he told me about how nobody was learning French at university level (in the UK). My own course had been cancelled due to the cost of teaching it, and the era of 'easy degrees' had set in during the early 90s. Before that, I also noticed the decline in newspaper readership in the 80s. It is easy to blame this general decline on the latest tech (or moral panic), whether that be LLMs or even the existence of the internet, however, the trend in dumbing down has been going on for decades. In the context of a declining empire and financialised economies, this makes a lot of sense.
    • keeda 4mo ago
      I think we are talking about two different trends that have similar symptoms. I do agree there has been a noticeable anti-intellectual trend for a long time, especially in the West. (See also: Grade Inflation.) But that is separate from the drop in attention spans, which is relatively recent has been pretty strongly linked to digital stimulation, constant multi-tasking, and now short-form social media. LLMs are an entirely new dynamic with significant cognitive implications, but I fear it will be hard to discern their impact from the falling attention spans and other long-term trends that have led to things like grade inflation.
• maerF0x0 4mo ago
  > many of them can no longer brainstorm, code, think deeply, or write I believe this is the real crux of the issue. We often turn the target to things like "Can johnny Add, Read a book, or recite dates" which are only proxy measures for important things like "Can johnny solve a numerical problem presented to him, can he synthesize information, or can he think critically about what is occurring around him?" . If students use AI to accomplish goals I do not see it an issue. If they cannot figure out how to use tools, or what their goals are-- that is a major issue! An analogy of my point is that I don't want to focus on cursive in the age of computers keyboards, and I dont want to focus on abacus skills when a pocket calculator is like $5.
  • o_nate 4mo ago
    If students are allowed to use AI to accomplish their goals, then I think the real question is why should they go to an expensive university for four years to learn how to ask AI to do something?
    • maerF0x0 4mo ago
      very fair question. But that's on the university not the students, as in the faculty shouldn't be complaining about the students, but adapting with the times.
• spwa4 4mo ago
  I used "AI" in the 2000's to increase my homework assignments, and to correct them. As in I wrote code to generate random exercises, with solutions, using many tricks, to get myself hundreds of problems instead of 1 or 2. Often spent more time on getting these programs right than on the problems. Still did better than the class. Oh and it was AI in the 1980s IBM sense. Ie. it was based around a python version (which I wrote) of a LISP math system based on maple. I even attempted (and largely failed) to rewrite it in C++. Even attempted to have my homework read to have the computer correct the actual pages, but I never got convnets to reliably read entire lines (yes, I understand, well now, why a convolution would mostly not realize whether 2 pieces of text are on the same line or not and so get very confused if you go deep enough for recognition to work well)
• ghaff 4mo ago
  Yeah. I have no doubt that I would have used LLMs “just this one time” to help with problem sets or papers when I got behind or wanted to do something else.
• reducesuffering 4mo ago
  “Better for you if you take me off.” The Whispering Earring: https://croissanthology.com/earring https://croissanthology.com/earring
• yawnxyz 4mo ago
  before AI was around we blamed Covid for doing this to us, and now we blame LLMs... and before that we blamed social media. I'm pretty sure this downtrend has been happening for decades.
• WarmWash 4mo ago
  This is also why AI isn't going away. People will (and already are) leaning hard on it, and will pay in the future for that crutch.
• laboring1 4mo ago
  > I have some sympathy for these kids. where do you see kids? This is a university. These are adults. 100% their fault.
• overgard 4mo ago
  It's a really underrated problem. I don't think my actual cognitive skills have declined by using AI, but I do notice that my patience and attention span are a lot lower. I'm learning a new code base for a new job right now, and I'm finding AI to be a really double edged sword for it. One one hand, it's extremely valuable for asking questions about the code base. On the other hand, if I'm not careful and I just let it apply the fix before I even investigate it, I'm really not learning the code base well at all. I find I need to actually write new code in a code base to exercise the necessary mental muscles to actually retain understanding. Incidentally, I do find that this large new code base I'm learning also shows the limitations of AI. There's no way I can vibe features on this without understanding and not introduce a lot of issues. Even targeted bug fixes have a lot of unintended consequences the LLM doesn't see. This isn't a bad code base at all, but it's definitely at the size where even frontier models struggle. So to me that tells me that the argument that I should just use more AI to solve my AI issues and not bother to understand the code base isn't viable at the moment.
  • epgui 4mo ago
    > I don't think my actual cognitive skills have declined by using AI I'm not speaking about you but... I know most people would not have much awareness of their cognitive decline. I know this because that awareness gap is there with or without LLMs, across all age groups and cultures.
    • timmytokyo 4mo ago
      Especially since attention -- which the parent commenter says has been diminished by LLMs -- is a key part of cognition.
      • xdavidliu 4mo ago
        adding to the irony is the fact that the mechanism used by the NN architecture in LLMs is also called attention
      • fragmede 4mo ago
        For cognition, sure, but that's a fairly weak claim. A dog that chases its tail for 3 hours might be considered conscious, but maybe not highly intelligent. The attention deficit part of ADHD hurts some people, but a high intelligence is able to make up for it in other ways. Attention span is a multiplier for intelligence. Someone with a lower IQ but a longer attention span is able to outperform a higher IQ but shorter attention span, traditionally. What's required though, is the attention span and the memory to really dig deep into a problem, and then go for a run. If AI makes that easier, since it lets you skip the boring parts and get to the meat of the problem, then hey.
• pellucide 4mo ago
  Then its reasonabel to expect someone who is not using LLMs to have an edge in their cognitive abilies. Or will it be overshadowed by the shear magnitude of bruteforcing that LLMs are capable of. I tend to side with the former. If that would be true, then not using LLMs would give an edge in solving novel problems. But we have been dependent on tools, cognjtive and physical, since forever. We cant imagine a world without tools. Why would LLMs be discriminated as a tool
• antonymoose 4mo ago
  We used to prosecute cheating and plagiarism for the moral failure that it is. If we allow lying, cheating and stealing - why bother being a schmuck that does the work.
• joshAg 4mo ago
  Why do you think you didn't do similar when you were a student? We've seen this exact issue with other technology before: calculators for math; typewriters and then word processors for writing assignments; audio books for literacy. In those cases we've collectively realized there's a benefit in getting the manual skill and understanding how to use it before shortcutting things with the technology, even if most of the time you'll just end up using the technology. My best guess is that for most people in those classes who failed because of ai use, they don't care about the understanding (usually) required to get a good grade, they just care about the grade itself and the doors that opens for them.
  • lordnacho 4mo ago
    It's because modern AI promises to relieve you of the tedium, leaving you to consider the important things like higher structure. It actually does deliver on this, but in contrast to older tools, it is unlimited in scope. A calculator - let's expand this to maps, thesauruses, dictionaries, and other lookup tools - was used for a pretty narrow set of problems, and you had to transcribe the result to whatever context you needed. An AI can be all the calculators together, and transport the output of one to the input of the next. You're meant to have the overview, but it's just so enticing to let it simply do that as well.
    • joshAg 4mo ago
      They mean using the AI to do the import things and the higher structure for them, not removing tedium. It's like using a calculator for math school/home-work designed to teach multiplication, which requires no transcription or putting into context. The tool isn't removing tedium. It's removing the very thing they're supposed to be learning. And my question is, in the context of learning something, how in the world is having the AI do the thing you're supposed to be learning enticing unless you don't actually care about learning the thing
• citadel_melon 4mo ago
  I’ve started picking up a new language with the help of LLMs (not the only source, but it helps me make flashcards using Leipzig Glossings) and it’s helped me read through math textbooks on my free time much faster/more thoroughly (ambiguous concepts/proofs that used to require a TA or professor for help now I can sort through on my own without having to laboriously cross reference two other textbooks). I also created a prototype app that creates flashcards automatically for a distributed systems book I am currently working through, making concepts stick longer through active recall. I’ll also use LLMs to learn more about the tangental figures in the history books I am reading that I couldn’t have just learned from the book itself and would have been too much of a hassle to look online or in other books. These are just a few examples of how I use LLMs to learn faster. LLMs are a tool and I have seen massive gains from them personally