The secret to mastery remained unchanged for a thousand years: books, lectures and homework. All of this can be done with pen and paper level of technology.
Given that AI exist maybe we can roll back some of the school/university and just let people do the work and learn while doing?
Yes not for a 7yo but with 18 you could just work and learn what is required or what you find exciting.
Companies should be doing their own training for their jobs, and university can be freed up to actually be about intellectual pursuit rather than economic pursuit.
It was companies themselves who created this issue anyways, by demanding degrees for every damn job, regardless of whether a degree could prepare you in the first place, and slashing entry level jobs to almost nothing. Then they started using degrees as a proxy for work experience (and I mean that in the literal sense; "bachelor or 4 years of experience" is common to see in job reqs, despite no bachelor degree actually being equivalent to 4 years of full-time job experience), which just further pushed incoming students to expect that to be the purpose of their time at University.
This would be great of course, but the reason that 'what actually happens' is so different than 'what should happen' are the usual economic incentives. How can we change the financial calculations to separate formal education from job training in a way that drives the ship in the better direction.
One way could be to regulate degree requirements to only jobs that really require them like engineering, nursing, etc. Another might be allow student loan bankruptcy if certain criteria are met such such as x number of years below y income.
Make it illegal to discriminate based on degree status in hiring (it's not like anyone is hiring an SWE without doing technical interviews anyways, so if you prove out their skills why does the paper matter?), and you remove both the backdoor socioeconomic discrimination route (which is itself a backdoor route to discriminate against protected attributes), and solve the degree 'inflation' incentive.
Universities predate capitalism (despite the author's absurd assertion that they were founded to serve the interests of businesses), and will exist after it, if any humans survive it.
Mediocre student that sits through lectures, does the homework and submits assignment on due dates will get a good level of mastery in the subject. The very same student would be totally lost relying only on self-studying - he would not even know what he doesn't know.
I fully admit that for efficient time spend and production of sufficiently educated students it is not effective method.
definitely try out:
galaxy s9 ultra tab (wacom! edit: also, 14.6 inch: bigger than any ipad series)
+ LAMY s-pen
+ paper-feel screen protector
(and optionally felt-tip nibs)
miles better than MPP or AES or other crap: those can't draw diagonal lines without wobbling, thought I was getting parkinsons
The issue you’re describing is a mindset/cultural one, not a technological one.
The same cheating machine can be used as a tutor. Those same cheating students understand, that at the gym, they themselves have to lift the weights to get strong, but that mindset doesn’t carry over to their classes.
Perhaps LLMs are a forklift.
Of course, side effects are a different story.
We haven't yet got to the downstream question of what white collar jobs are going to look like in the AI era.
Before we get ahead of ourselves and hype up AI as a tool for making people smarter, let’s first demonstrate that AI really does help them learn better. Otherwise we risk wasting a lot of time and money on silicon snake oil.
As for proof, I think it’s self evident for anyone who has tried to us it in that way.
If you’re studying math ask it to generate more questions for you to try. If you don’t understand a concept, have it use the Socratic method on you. Learning a language, talk back and forth with it over voice. Writing an essay, have it mark and proofread it and provide feedback based on known good criteria.
Meaning that they didn’t just fail to demonstrate that these supplements could lead to superhuman performance. They didn’t even just fail to demonstrate that they enhance performance. They failed to demonstrate that their overall effect isn’t deleterious.
And yet everyone involved believed quite firmly, based in part on personal experience, that it was self-evident that these supplements would make them better athletes.
A lot of the arguments for AI in education aren’t far off from the reasoning behind the kinds of popular supplements they used in the Enhanced Games. The limits of that style of thinking are demonstrated quite nicely in the 2010 Canadian Medical Association Journal article “Cigarette smoking: an underused tool in high-performance endurance training”: https://pmc.ncbi.nlm.nih.gov/articles/PMC3001541/
> Than to put character in him. No one
> Has ever found a way to make a fool
> Wise or a bad man good. If god had taught
> This to the children of Asclepius—
> How to cure badness or a muddled brain—
> What handsome fees they'd earn!"
That was Theogenis from the 6th century BC. I don’t think we’re any closer today than they were back then.
Of course, it's a highly selected group of students. I very much doubt it's scalable in the way one would hope.
In other words, it made more sense to 'frontload' hardthought and pondering so one was prepared [for whatever may come].
People also thought aqueducts were the best way to move water for thousands of years.
They still do because they still are? I'm hard pressed to think of a better way to move water than creating a gently sloped channel(this includes any pipelines that don't use pumps, by the way) for it to follow from where it is to where you need it. Many places that don't have sufficient local groundwater are still supplied by aqueducts to this day. If you have to pump it, then you're paying for the channel and the energy, which is worse than just using gravity.
And gravity-feed systems are the best way to move large amounts of water. That's even how nature works, and nature moves much more water than humans do.
Numerical methods, however, would require at least minimal computing hardware.
I think there should be a guiding principle of using the least amount of tech in teaching any subject, just like principle of least privilege in cybersecurity.
Particularly the cheating. Many students are flagrantly using it + the detection tools either aren't configured to check for it, or, if they do have something like TurnItIn, it doesn't work, and flags legitimately created content sans AI.
AI is a tool like internet was and it's the responsibility of the curriculum to teach proper usage of that tool rather than fighting against it.
Universities are supposed to primarily teach understanding, not basic tool use. Yes, tool use should be part of your education as well, but that's only a small fraction of it. A single "prompting AI to do X" course is probably more than enough. But if you completely skip the fundamentals and make the students fully dependent on the tools, how could they possibly contribute to building the next generation of tools, verify the output of the tools, or transcend the tools?
Yeah, they should indeed be teaching proper AI use as well, but in practice the easy access to AI is making it virtually impossible to teach the fundamentals, and that's the real problem here.
That's all I'm saying. If a student wants to cheat then they are going to do it regardless if AI exists or not. That's not something anyone can control. It's a decision made by the student and they would face the consequences down the line in their life.
However, if the proper usage of AI tools are taught in university and and the usage is allowed, any student that actually wants to learn, that would be a gold mine. I wish we had AI when I was in college. Being a visual learner, that would have made my life so much easier to understand complex concepts and algorithms with nice animations and diagrams generated with AI.
until it was overrun by unverified AI slop. Let's just get the slop from the source!
A generation ago you saw similar resistance to the internet from HSS programs.
you then make sure it behaves and doesn't let them cheat too much. guide them to answers, don't just spit out code like Claude is want to do
- Students want a credential because business and society demands a credential
- Universities want income to support their missions of research, education and other "motives"
- Professors want to do research, and they don't really want to teach (in general)
- AI is a resource for learning, assessment and project development
- Society needs educated people
What ideas do you have to make everyone satisfied and maximally functional?
Someone will ask, what about people who are incapable of motivating themselves to study? Well they'd feel a lot more motivation to study if it meant saving tens of thousands of dollars. As for people completely incapable of independent learning, they'd likely have little employability in the future in any case, because people would rather hire an AI than that kind of person.
In my opinion, most of Academia's pains are wholly self-inflicted.
Academics has its many issues but universities are hardly the only sources of criticism about AI, and for all its benefits AI is poorly understood and often applied in relatively half-assed ways, even when it's well-intended. I would worry if thoughtful individuals weren't skeptical at all about AI.
It also seems reasonable to, say, want to evaluate students on their own merits free of the influence of a "homework machine" (to borrow a phrase from Shel Silverstein).
I'm reluctant to make predictions, and wouldn't describe myself as "anti-AI" but this sort of piece reminds me uncannily of the dot-com bubble.
LLMs exist and are extremely useful in academia. I am currently riding a productivity wave, where I can spit out formalised proofs – not quite at the pace at which I can think of the theorems to prove, but almost. The thing braking my progress is that I have to build all the existing theory too, not just my own new stuff.
But for students, who do not yet know anything, it is a danger. From observing my students, it seems to take a certain amount of willpower to do the exercises without letting ChatGPT give them (or "explain them") the answer. And reading an explanation is not the same thing as working it out yourself. You just don't learn doing it, by not doing it!
Some students have this will power, some students don't. And it is also situational. Some students have stuff going (work or other factors) which makes it really hard too.
Yes, they can of course keep asking ChatGPT later in life, but they will not have the fundamental understanding which is required to even use LLMs for the advanced stuff. ChatGPT cannot explain you advanced concepts if you don't understand the fundamentals!
So, to test the students' understanding, we are back to having on-site exams, with the old-school supervision. And more students will fail, because there is now a way to solve exercises without learning.
But it also indirectly cheats their peers who are being surpassed by the cheating students (at least in school). Similarly for cheating in interviews.
Unfortunately the cheating students can cause a race to the bottom where the non-cheating students are pressured to cheat in order to keep up. This pressure to cheat to keep up can become an even bigger issue if teachers try to make tests longer or harder, whether to challenge the cheaters, or if the teachers don't recognize that LLMs are being used.
This doesn't happen if they're only assessed based on well-invigilated on-paper exams.
Uh in what universe? Obviously physical books are helpful but are not most of the new ones being written with the assistance of an LLM?
Einstein once said physics is like looking at the outer movement of a watch and attempting to understand its internal mechanisms.
LLMs watch the outer movement of our keyboards in an attempt to comprehend our varieties of intelligence (intuitive, rational, symbolic, logical, ...)
But then as soon as the author rolled out complaints about DEI and ethics, you knew what was going on. Okay, please leave higher ed and work for the industry you love. As you say, they are doing just fine.
Tbf, the vast majority of institutions also suck.
State flagships and some of their second rung, a couple ivies and ivy tier privates, and military academies provide the bulk of talent that you need. And these universities have dedicated pipelines for people who start off at community colleges.
These universities are also much larger - UC Berkeley's and UCLA's 2025 undergrad population is almost double it's 1960 population [0].
And those who had skill or educational deficiencies can remediate them via non-trad or working professionals masters like GT, UT Austin, and CU Boulder's OMSCS for less than $15k.
[0] - https://www.universityofcalifornia.edu/about-us/information-...
The top 20 CS/EE/CE/ECE/EE degree programs (MIT, CMU, Stanford, Cal, UIUC, GT, UT Austin, Purdue, UW, UCLA, UCSD, Ivies, UChicago, NYU, UNC Chapel Hill, Duke, USC, UMinn, UMich) graduate around 15k-20k undergrads a year.
Throw in the next rung of well respected universities (eg. the rest of the state flagships like ASU or IU, the respected regional public programs like CalPoly, NCSU, or SUNY Buffalo, and the handful of regionally respected privates like WPI, Cincy, or both Rochesters) and that number likely doubles.
If you're graduating almost 50k grads a year from target programs, there just isn't enough room for the rest.
Choosing to go to (randomly choosing two universities to pick on) USF or TCU for CS straight out of HS instead of going to your local CC and then transferring to UC Davis or UT Dallas is dumb.
In 1980 you had a little under 2,000 4-year colleges in the US. In 2010 you had almost 3,000 4-year colleges after which the number of institutions started declining. Making more colleges while existing colleges were expanding headcount did nothing to help.
Overall, the US graduates around 125k-150k CS/EE/CE/ECE/EE/EECS majors a year.
Overall we graduated a little under 5 milllion college graduates in 2025 compared to a little under 4 million in 2015.