> 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".

> 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. This is probably not true for majority of people. Most go to school because it is mandatory, pushed by parents and society, and university gives you credentials and better job opportunities. Homework and tests are a way to get a number grade on 'how well you memorized something', it doesn't really measure a deep understanding of the topic.

> Homework and tests are a way to get a number grade on 'how well you memorized something', it doesn't really measure a deep understanding of the topic. As I said: they are goalposts. Typically homework and tests are sufficiently easy (yes, there are exceptions) that if you fail them, you can assume that you didn't make sufficient progress in improving your understanding. But I do agree that at least sometimes the difference between being good and exceptional at homework and tests can indeed be rote, "unnecessary" memorization.

> 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.

It is really about time we thought about what universities are for in the 21st century, since there has been significant scope creep wrt labour markets, particularly roles which do not actually require university education but do require a degree for CV reasons. It is nonsense in the 21st century to require a bachelor's degree for such roles. Not to mention the huge societal pressure that you have mentioned, which no 18 year old can really be expected to see through. With CS students this is one thing. Medical students? Air traffic controllers? That is to say, there is a huge gap in the educational integrity of degrees, and this is probably partly driven by people who do not really want to be at university for educational reasons (and, believe it or not, there are other ways to party in your early twenties) and for whom a degree in XYZ is not rationally connected to 80% of their options after school. And there are many such people. This really needs to be thought through, because education is expensive, and it is an enormous waste of money to pay for a couple of years of university and end up failing out or being sanctioned for AI cheating, or being educated for something you do not really want or need to be taught. That is true whether or not education is paid for privately or by the public.

> 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 use 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.

It's a much more socially beneficial system and I think a large part of this is probably differences in culture regarding education and one's career. The availability of these modes of teaching is downstream from that.

> 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. I think this was true a long time ago. Perhaps with LLMs this can become true again in the future. But definitely that was not why I went the first time, nor most of my classmates. (Second time I did post-secondary, sure, 100% -- but I was almost 30, not an average student)

What a delightful fantasy world you live in. Doesn’t sound very predictive of actual human behavior though.

> You go to a university because you are deeply interested in understanding the subject that you study. This is a bit of a naive or maybe affluent take? Like, theoretically, I agree. And I myself was curious. But most people, by and large, are going to university because they know they need a degree to get a job, unlike their parents or grandparents. And even "the degree" is quickly becoming devalued in this current AI age. I would guess that if all basic needs were met through UBI, the fraction of individuals going to school would drop and the makeup of subjects they pursue would change. Probably more cooking and art classes and less stem. Although, if UBI existed and AI did not, we'd probably see more educated individuals in the first place so maybe there would be an uptick in stem attendance and general curiosity in such a utopian world.

When left to their own devices, 99% of children are not interested enough in math, history, literature, languages, or almost any other school subject to engage with it willingly. Only teaching "interesting" things that kids are "interested" in is both impossible (too many varied kids per class for that to work 100% of the time) and even if possible, would leave kids with zero practical knowledge, because learning most of that stuff is not something kids inherently want to do. College is different, because theoretically you should be taking classes that are relevant to your field (although there are still "core" requirements that are somewhat high-school adjacent).

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.

My son just finished his first year in college, and had no trouble getting decent grades without using AI while many of the kids around him were using it. At least in his humanities track, class participation is a lot of his grade, and he said the "AI kids" tended to suck at participation because they hadn't actually thought about the material, and couldn't dynamically work with it in class. He also said their AI assisted writing that he'd read was dull and unoriginal, and all sounded the same, which he thought likely helped his essays stand out. His English composition teacher said he was "probably too advanced for this class" when he told her he didn't use AI to write his essays, which made him roll his eyes, as he has clinically diagnosed dysgraphia (learning disability in writing).

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?

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.

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.

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...

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.

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.

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.

Memorize trivia and formulas, regurgitate trivia and formulas. This summarizes my experience with our system of education. Yale saying test scores predict performance reads to me as, “students’ history of being able to regurgitate trivia and formulas in high school is the lead predictor of their ability to do so here.”

Unpopular opinion: turning public universities into an academic hunger games is diametrically opposed to their purpose for existing, which is to create an educated populace. Intentionally lowering the quality of instruction, as well as deliberately trying to trip students up on exams, is not improving educational outcomes for anyone. People who complain about "grade inflation" have completely lost sight of why public education exists in the first place.

The material outcome is what should be the goal. Tests are a relatively brute way to try and determine how well the student understands the material, but conversations about grade inflation and "back in my day getting a grade was hard", and professors purposefully putting difficult questions (not in content but in presentation of the question) all betray the inherent goal being pursued. Its all Goodhart's law problem, but we are missing the forest for the trees talking about grades and tests when what we want is people to be educated, and critical thinkers and competent in their area and due to a comprehensive way to evaluate that we end up talking about grade inflation or how Yale vs Berkeley gives letters at the end of a semester

There are 10 different public universities in the UC system and 23 in the CSU system. The majority of them are not difficult to graduate. If you don't want a demanding education, don't go to a demanding university. >Intentionally lowering the quality of instruction, as well as deliberately trying to trip students up on exams I was happy with the quality of the instruction, and I didn't feel I was being "tripped up" on exams. It's not about "hunger games", it's about challenging students to learn a lot of material and learn it well. Again, if that's not what you want, just don't attend. The number of places where this environment exists is getting smaller every year: https://xcancel.com/CJHandmer/status/2060144837157118307#m I'm glad the professors at Cal are working to preserve it there.

This is valid, and I would add that these academic hunger games are a result of College Degrees being needed to get what remains of well paying jobs. Maybe we can use AI to create new exams that grade people on professional capability, and then gate entry into other professional degrees? Hmm, Where would the teachers come from, and how good would the education actually be?

A famous MIT professor did a sabatical at our AI lab. He said it was "a joy to teach here, as you can rely on students being proficient in basic math as opposed to the US where you have to teach those explicitly or lose the class completely". That was in the 1980s. My first math exam as a CS undergraduate, 123 out of 129 students failed. The math department professors refused to dumb down their classes for CS students. Math was core to the CS curicullum in those days. It would fade away over the next few decades to almost nothing. The main reason being the CS department wanted to popularize its uptake, and remove barriers that kept students from passing. There was also a major dose of interdepartemenral rivalry and academic politiking involved.

It's interesting that it's specifically math-within-CS being discussed here. I can imagine a lot of students "just want to learn programming" (or similar), and see the math as a tedious distraction. As a naturally curious person, nothing will stop me from learning about the topics that interest me. But school also taught me a lot of things that didn't interest me, and a lot of those things turned out to be useful anyway. I think if I had access to AI from a younger age, I'd have used it to skip learning the things I didn't care about, which would not have done me any favours.

I also think that's one reason. Where I'm from (Norway), the majority of computer science and software engineering studies do not have the same math requirements as, say, engineering or math/physics/etc. - nor do they have the same amount of math as the latter ones. When I did my CS classes as an engineering student, I did meet a bunch of students that viewed math as some niche subject only relevant to those that wanted to work with computer graphics, computational stuff, or similar.

Back in the university, I took both math and CS courses and a significant percentage of students seemed interested in neither math nor programming but rather in the jobs they would get afterwards. I didn't notice the same thing with math majors.

Well, that’s because for math majors any monetary incentive is nonexistent (modulo some rather specific careers). Just about nobody majors in math for any reason other than math itself.

AI has a way of exposing people. In this example, students who are there to get a degree from a prestigious institution, rather than to learn, are prone to take perceived shortcuts and proceed to come unstuck when their AI isn't there to do their work for them, such as in an exam.

These people would’ve failed with or without AI.

Pretty ironic that these kids are failing a non major requirement called "the beauty and joy of computer science"

Could it be that CS attracts a different population of students in the current genAI era?

In a broad sense, this distinction between Harvard and Cal is the distinction between an old money Ivy and a flagship state school. One exists to propagate a social hierarchy, and the other aims to allow all entrants to succeed. Ironically, the techniques of the latter yield the results of the first, but everybody gets to keep a pure heart.

It’s not that they can’t think deeply, these are smart people. It’s that there is no reward for doing so and in fact there is punishment . The punishment is that for all the thinking you do, someone else will arrive at the same result as you in less time, or maybe even a better result. You don’t get rewarded for the effort of thinking, only for the end result. Naturally, even if you are an intelligent individual, you can still be conditioned in this way to take the easy way out, unless you purposely like to suffer. But suffering is only worth it if you know in the end you come out ahead. But now, you do not come out ahead. People will be using AI in the workforce for the rest of your life anyway, might as well just join the trend. It’s like if everyone started taking a magical steroid and growth hormone to build muscle and look great instead of actually working out in a gym and possibly getting worse results anyway.

It depends how you use it. You can either get it to explain a concept, or do your homework for you. Its a bit like the decision students have to make as to whether to review their material before exams or go out partying. Overall it just seems like a huge waste of money to piss away the huge tuition cost your parents probably paid.

As an educator, this is exactly what I struggle with. I'm pulling out all the stops to give students every chance to do the hard work and not lean on AI. But there's a good chunk of the class who don't listen to reason. I haven't figured it out yet. They know, logically, they can't pass an interview, but that's apparently a "tomorrow" problem. The smart ones either use it not at all, or use it to positive effect, like you're saying.

Sorry, but I don't think AI is entirely to blame here. When I graduated from a CS program at a top-10 school, I felt frustrated that the professors didn't ever teach. They had slides. They read off slides, verbatim. They explained things sometimes if you asked them, but most often in a very elitist and condescending tone. Like in the movie Good Will Hunting, you could have learned nearly all of it and more by borrowing those books for free from the library. Or, just opening a complex OSS project and learning to contribute. And quite honestly. It shows in the CS grad population too. A lot of us are condescending toward anything that doesn't make sense to us. But, I digress. The best engineers I've worked with are all non traditional backgrounds, non degree or degree holders from non elite schools. They think differently, they tinker, they are incredibly nice and patient, and do it for the love of connecting humans to technology. Look up the names mentioned in the article. Garcia, Ranade, Nelson. All of them are involved with highly theoretical mathematics and scientific computing. Just because you're good at 1 thing does not mean you are qualified to teach. And none of these professors are trained or taught or graded or performance managed on how they teach. For most of them, its just required that they spend 10% of their time in the classroom lecturing. Let's be honest about another thing. 99% of EECS graduates, even from elite schools, are wrangling objects and their relationships to a graph. Simply put, we're all just a bunch of glorified JSON massage therapists. It just so happens that we get paid well for it, and we hold that over people. The same happens in the classroom. I think in order to facilitate a healthy, educational environment for young adults, we as adults must encourage, motivate and make that environment fun and practical. We force feed binary trees and the compiler AST's, but we need to make it fun. It's like the commonly accepted saying: Schools kill creativity :(.

I read something interesting yesterday on the subject of AI in education (though, it has consequences to broader society too): The goal of education is to impart knowledge in the student, preferably correct knowledge. The goal of an LLM is to produce an output that is convincingly human. It's not even that they're opposed, as much as they're ships for whom Polaris is in a completely different direction. "Hallucinations" as they're called, or more plainly stated when the machine makes some shit up, are perfectly understandable in this context, as are the struggles of every single AI firm to get rid of them. Namely: the machine is functioning exactly as it is designed to, so how can you possibly fix it? It's working. The goal of an LLM is to produce text that passes for human, and apart from the obvious LLM tells, it largely does. Like say what you will about their lack of intelligence, the writing is solid. It's grammatically correct, spelling is dead on, what have you. It reminds me of the famous phrase from Chomsky: Colorless green ideas sleep furiously. A sentence which is perfectly grammatically valid but is also completely devoid of meaning. An LLM would write that sentence, and it would be working correctly. All of that to say: for all the things they CAN do and CAN be used for, I think we have to draw a hard line at education. I just don't think AI has a place in it. Of course that presumes that the goal of education is to, well, educate people, and especially here in the States but also abroad, we have been putting other interests, especially capital, far ahead of that for decades. I expect no different here. And before someone comes in to go "WELL HOW DO YOU THINK YOU'RE GONNA STOP IT LUDDITE IT'S THE FUTUUUUUURE" yes, I'm sure as long as these exist and are available to people tech literate enough to access and use them, whatever that means into the far flung future, they will be a factor. Just like cheating, just like plagiarism, just like everything else that will get you kicked out of school. And the answer is the same: it will be stopped by institutions, imperfectly, and it will also happen anyway and with the same consequence: those responsible will mostly be harming themselves for short-term gains.

"According to Berkeleytime, 35.3% of CS 10 students and 10.6% of CS 61A students received F’s in spring 2026" Alternatively, more students are taking CS10 and CS61A irrespective of aptitude. Anyone can code, but not everyone can become an employable SWE. Anyone who has first or second hand experience with Cal or any other university knows how impacted CS majors have become, and how everyone is attempting to become a CS major because it's the easiest path to multiple high paying white collar careers. And in all honesty, it's not like CS@Cal never had weedout classes (I remember CS70, CS61B, and Math54 had reputations of being the L&S weedout classes).

This is orthogonal to standardized testing. At UC Berkeley L&S, students are undeclared by default, and everyone is incentivized to take the intro CS classes (CS10, CS61A) irrespective of aptitude because worst case they can declare a CS minor or use the classes for other adjacent degrees (eg. Applied Math, Data Science). Additionally, while Cal doesn't require standardized tests, most students who applied and attended already took the SAT, ACT, and APs becuase they cross-applied to other universities as well. This is reflected in UC Berkeley's HS Weighted GPA being in the 4.31-4.65 range [0], which means most students will have taken at least 6 AP classes. Hell, I attended an Ivy and even then Cal was a target program for me, as well as my peers. If I didn't get into my Ivy I would have ended up at Cal and ended up in the same position. [0] - https://admissions.berkeley.edu/apply-to-berkeley/student-pr...

I'm not denying that. I'm just wondering if anyone measured if there is a correlation effect being induced by CS major declaration requirements. Barely over a decade ago, CS tended to be a large but not too large major by enrollment in most universities yet nowadays it is the most in-demand major in most universities. You can see this at Stanford [0], but most other programs as well. [0] - https://stanforddaily.com/2020/04/25/stanford-in-the-2010s-t...

Probably not a bad thing, the coursework is antiquated and meeting students with new advanced tools and the awareness of AI's impact on things in the coming future I imagine there is some apathy and laziness here but idk how unjustified it is "Noooooo you need to manually code on paper in assembly" Alright, well maybe the CS grads need to, but why expect that of everyone else