"the very foundation of modern academia has been blown to bits"
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My bet: a lot of the things we used to do were habit, ceremony and gatekeeping much more than being necessities.
Not to everyone though...
You fail at being pedantic. If you wanted to be pedantic about this, it would first be necessary to define what it is a necessity for. Are the things being swept aside a necessity for the universe to continue existing? No, definitely not. But perhaps they could be a necessity for the (academic) culture to prosper. Which do you think is more likely that the person you responded to meant, that they were talking about things being necessary for the universe to keep existing or things being necessary for our culture to flourish?
There is nothing worse than a half-assed pedant who can't even be sufficiently pedantic to make a point correctly. Really, that's closer to autism, not pedantry. There are inferred clauses when people speak, but you (choose to?) intentionally disregard them and interpret them in the wrong way, thereby arguing against things that weren't said. Even programs can infer unstated clauses by context (eg. can successfully infer from `var x = 2` that x is an int despite it not being said, without explicitly declaring `int x = 2`).
I wonder what it is about this subject that makes people so angry? I think I’ll settle on status. People are afraid of having their social status taken away by AI and become irate at the thought of it.
Going back to my programming example, suppose your compiler decided to interpret 'var x = 2' as a string and then told you you were wrong, throwing an error instead of compiling your program, even though it's the compiler being defective and not adhering to the established language rules for type inference. That's you, in this conversation. That does not add to the conversation. The compiler needs to be fixed so it stops doing that.
Air is a necessity. If you don't have it, you'll die within a few minutes.
Water is a necessity. If you don't have it, you'll die within a day or two.
Food is a necessity, too, but if you don't have it, you'll live much longer than you would without water!
Vitamin C is a necessity. If you don't have it, but you have other food, you'll live much longer than you would with no food!
So, yeah, you fail at being pedantic in any remotely useful fashion. All you're doing is a quick, dirty, "um, actually" type gotcha, and you're not even correct about it.
Whether you meant it to or not, your post sounded snide and arrogant.
You don't specify what you think "no longer matters." And so there's no way to judge what you think is the impact.
> My bet: a lot of the things we used to do were habit, ceremony and gatekeeping much more than being necessities.
Yeah, right. "I've got a calculator, so we no longer need to learn arithmetic." It's the way of the ostrich.
What is possible as ground-truth, if the "tarbabies" of society get sidelined can be seen in Ukraine.
And so on. I could bet that some of his scientific questions where generated, and that's no surprise to me, it's just SO easy this way and if the PhD advisor just says "ok that's good" and no one ever complain during the PhD defense then for sure this will keep going.
But regarding OP's link, when Lemire says I kept my mouth shut. I am never rude on purpose. You can't say that and complain that academia "is blown to bits". It's your responsibility as a scientist to step up and say that some research is garbage when you see it.
The only case I personally know of someone doing that during their PhD didn't end well.
My friend couldn't replicate the results from a known professor in the field, asked for the data + model to re-run because he assumed his own work was wrong and wanted to benchmark against the known study. Got stonewalled for more than a year, brought it up with supervisors because he started getting the feeling the results were tampered and the professor didn't want to be found out. He pushed it but got ridiculed by the professor's university ethics committee.
After a couple of years he could show that the research was at least sketchy and he depended on that model/results for his own work, he lost 2 years of research and completely left academia after finishing the PhD (delayed by almost 2 years).
> Consider that most PhD theses were never good. How often do you rush to read a PhD thesis? The vast majority of them are painful to read. You learn little if anything.
So, it sounds like nothing of much value has been lost.
I think what he really complains about is that AI is starting to show that the emperor called academia has no clothes. So much of working your way through that system has always been about being able to master largely pointless rituals.
Yet, the people on the inside have no interest in making any improvements, because academia has always been institutionally conservative. But now AI is starting to put pressure on them to rethink their way of doing things, and they really don't like it.
But now, it could simply be all a couple of prompts to an LLM.
The bar is just lower for not doing the work, now.
But really, that's the fact everywhere.
That's one of the concepts this process is supposed to handle. Validation that you can transfer knowledge. Broken or not, that's the point of it, and what you're replying to indicates that at least in the past, you had to "do the work" to express knowledge, and also demonstrate that you could transfer that knowledge.
I agree though, we'll have to look forward, not backwards to solve this.
The whole point of a PhD is not to create a thesis - that's just a mechanism to measure - it's to be trained as a scientist or researcher.
Doing a degree in chemistry for example, is largely a knowledge building phase - and in my view it doesn't make you a scientist - being a scientist is about discovering new things about the world that nobody else has - ever - that's what you are learning how to do when doing a PhD.
Yes - my wife’s advisor literally told her that the goal should be getting as close as you could to stapling your published papers together with an introduction. They saw this as recognizing that you had learned how to ask good questions, run experiments, and iterate on the results — and since their field had fairly expensive overhead requirements everyone was mindful of the need to repeatedly get grants to keep the experiments running.
Indeed - in fact some countries ( I think Scandinavian ) do exactly this - the equivalent to a thesis is simply your publications.
Has it's Pro's and cons - you can learn a lot as a scientist but be unlucky in not having an publishable results ( as the answers to your scientific questions were either 'no' [1] or somebody scooped you ).
[1] https://en.wikipedia.org/wiki/Betteridge%27s_law_of_headline...
Very soothing and moves fast.
Thanks for the highlight, I read Okazaki's the first time about 2014/15 IIRC.
Another great read is "A Theory of Regularity Structures" - https://arxiv.org/pdf/1303.5113. by Martin Hairer.
It builds on his thesis, Comportement Asymptotique d’ ´Equations `a D´eriv´ees Partielles Stochastiques. - https://www.hairer.org/papers/these.pdf
The English language preprint from just prior to the French is at https://arxiv.org/pdf/math/0109115 "Exponential Mixing Properties of Stochastic PDEs Through Asymptotic Coupling" great, but I read them in revers order from publication and kind of prefer them in that order.
I cant disagree with the premise of the OC, however, there's a feel to Hairer's and Okasaki's insights and presentation that simply is not going to be reached via the lossy compression that is at the heart of LLM.
If that sets a high bar for who gets a PhD going forward, this would be a good thing.
Do you actually mean this? To me this sounds like someone said "you never learn anything by reading a high school essay", and you reply "so stop writing them". The point is not the product, you obviously train people by making the product.
> AI is starting to show that the emperor called academia has no clothes.
Seriously, what are you talking about. Academia in the last century has been the most successful engine of knowledge and technology in human history. Lots of papers are junk, like lots of businesses are junk, lots of books are junk. But I don't know how any serious person can say academia has no clothes.
Why single out academia? We're seeing vast majority of knowledge work had no clothes.
>working your way through that system >pointless rituals >rethink their way of doing things, and they really don't like it
A lot of Innovations or insights are obvious in hindsight, but no one thought to consider the problem, and put the pieces of the solution together. In this sense a well defined problem is a large portion of the solution as well.
I mention this because I feel AI software agents have a huge advantage due the body of prior work available to them and how provable solutions can be. This I feel gives the impression that the agents are more generally intelligent than they actually are.
Is this another example of that perhaps?
That's just lack of observation. Which PhD candidate is going to say "Chat wrote it for me?" We know a lot of academic articles are AI written. And a very, very large part of the student essays. Unless intercepted, they'll end up in the thesis. And in sociology, the texts are so vague, that it becomes even harder to pick out slop.
There are good reasons to assume PhD students see an advantage to using AI, so they will.
The issue here is that academia forgot what it was about a long time ago and is now having to face the consequences for a hundred years of bad decisions.
In Oxford. That hardly counts as universal.
1. Use AI to review a thesis for its validity and to obtain candidate concerns for further probing.
2. Require valid proofs for theorems and such.
3. Require open code for software claims. Assess it with AI.
4. Stop issuing PhDs for reviews. Original research must be required.
5. Encourage physical data gathering from the real world rather than just data analysis of existing data.
I submitted my thesis this month at a QS top 10 uni after nearly 4 years of work. LLMs were available for most of that time. I don't really feel that it has diminished the value of my thesis by much really.
It’s an interesting subject. Makes me want to vibe code a PhD generator just like in the tweet. Maybe I will.
> your thesis had no value to begin with, because it’s mainly a teaching exercise
And that’s the problem in your understanding. Thinking that a teaching exercise has no value while OP was saying that IS the value. It’s missing the forest for the trees. The point of homework isn’t to solve the problems. I bet you the teacher assigning the homework already knows the answers. Just like the point of a marathon isn’t to travel 26 miles because you could just take a bus.
Except, if machines can do the exercises up to the PhDs, you probably don't need those brains in the future, at least not as many as before. You might need only the brightest ones, and who knows for how long? The next ten years?
> at least not as many as before. You might need only the brightest ones, and who knows for how long? The next ten years?
Then those with power will keep it and pass it on to their heirs, and some without will try to finesse it but the masses will be told “we don’t need you”. I think in a lot of ways, this is similar to how feudal societies were. Maybe humanity will pass through another phase of that. Maybe we already are. But I think it won’t last either.
We don't??
> we don't claim that undergrad education has been blown to bits
But it has been. People pass CS classes without knowing how to write even a simple program. How do you think they'll fare?
As a meme said: you'd better start eating real healthy, because your future doctor will graduate using chatgpt.
Let me fix it: pen and paper. There you go, bada-bing bada-bum. In our uni the exam for Algorithms and Data Structures (one that most people struggle with) is done on paper in an exam room. You better know your binary search.
People, especially wealthy, have been coasting through education paying someone to write their papers since Great Pumpkin knows how long. Now you can do same thing cheaply with LLM’s. The solution is pretty simple, let them fail. Have them show what they can do live in front of examiners. Here’s a computer without network card, only Python and SQLite installed with the Python basic documentation, build me X and prove it works in Z, Y, and Q.
I am studying my second degree and although there’s million and one ways to cheat, I won’t, since A) I want to learn this shot B) I am not sure LLM’s will be available with these capacity and with theses prices in the future, at least I won’t count on it.
Writing an essay, or a thesis, with LLM assist, is difficult to avoid in this scenario, though. It would require your prof, TA or examination committee to read the thing fully and understand the topic deeply. For 101 courses, that's doable, but for a PhD, that's so much work, that it'll break the system immediately.
Essay is a fairly recent invention and perhaps it was not very good for testing students un the first place, since it kinda was not meant for that originally? So maybe we should test knowledge and understanding in different ways? In STEM-subjects this is not very hard, since basically you either can do the thing or not (like my example of coding above), but I have no idea how one would do this in history or philosophy. Should we go back to having long walks in the garden of the academy, where the professor guide’s you towards knowledge like some 21st Century Socrates? That doesn’t seem doable at this level of university students.
And how would you test PhD -level knowledge? You have to build a nuclear reactor from scratch in front of live audience? Or perhaps the oral examination have to become a real exam, not just a pointless ritual? Anyway, I think my point on using essay as a testing structure still stands. Maybe the examination should be like BJJ belt exam, where you have to show what you actually can do in front of peers and your teachers. A lot more people are likely to fail, but so be it. Maybe having a PhD stop being a joke then.
But actually nothing changed. Or maybe a path to "resilience, resourcefulness and critical thinking". Because human brains still needs to be shaped by years of training on some quality "literature", of some form.
We still must/want to human-[re]check important results, right ? And that require years of students time dedicated to memoizing facts and doing exercises in discovering already discovered results - learning and weights tuning, in the brains.
Yes, demotivator factor is very high or maybe just more visible then usual. Especially for brain paths forming - an that process is not quite stated in university and other education...
I think that when LLMs finish words and sentences shuffling and finds most of low hanging fruits in cutting edge of research ;) then only humans can move things forward, via abstractions, syntesis or old good paradigm abandoning. Hard to imagine LLM on their own "discover" something and then drops all that "literature" it was trained on as obsolote :) In next prompt it will happily return you old texts without any influence of just discovered paradigm shift.
In XIX century we got quite stagnation in science - it was belived that everything was already discovered, explained, just some few experiments are needed because some numbers do not adds up... And that proliferated to philophy and culture via some "proofs" for atheists. But in 1905 a paper was published... Too bad politicans do not get implications of that and still was pushing communism decades later...
So we realy want humans with brain pathways shaped mostly "old way" - the only one way available for human beings - by that training called "education". As always there is resistance and pain and attempts to find a shortcuts by cheating. Maybe this is time to clearly state that brain workings training is big part of education ? Just like in gym you are repeating to trying to lift weights up to your limit and even little above, with supervisor oversight.
In my opinion, we will continue to need fully educated people who read books and peer-reviewed articles. We need literature, not "'literature', of some form."
Sure, who know things do not need to consult talky chatbots.
But totaly dismising '"literature", of some form' is not an opion. It already works like simple "consulting manual".
Of course as long as texts used for LLMs training start to be outdated and noone will bother to update models.
And we always want as much as possible educated peoples but not always can afford everyone higher material expe^W^W^W^Wdemands.
The photoelectric effect/quanta? I'm not sure I understand the supposed connection to communism.
And, IMO, Einstein, Godel and more discoveries should be reason to not continue communism stupidity. Especially to not continue - after year 1905 - social engineering plans of "world-wide GENOCIDE until everybody is good citizen".
Of course I'm talking about best-wanting-for-humans but still naive communism and not about a way to destabilize other countries by any means necessary. Such move did almost insta-karma effect on Germany: sponsoring commies in Russia resulted in nazi being sponsored in Germany...
Don't think someone want to deny societes, philosophers and politicians are drived by overall science view on reality. And what else could drive atheistic minds ? Not judging here, logic is everyones duty.
Also my "too bad politicians..." was obviously expression of a wish. Not only science influents politicians. But discovered facts (counterarguments in this case) about reality could be taken for consideration, right ?
If AI disrupts your field, the culprit is most likely not AI.
It's an act of coordinated methodology in showing respect to previous peers by acknowledging that you read what they wrote when they were acknowledging even more previous peers.
Every attempt to do something new is rejected unless you take 99% of something that has been done and try to add your 1% to it.
But the thing is that you don't even want to do that, you need to either have a publishable/defensible thesis, or if you already have a PhD, pursue a tenurable track and grants which never collides to productive human progress.
So yes, AI could very well run tenure track career more efficiently and with better results. It's not AI the problem: it is the checks and performance indicators that are in place that make it very easy for AI to dominate and very exhausting for a human to follow.
A good researcher with good AI knowledge would (and should) dominate their field.
* Medicine is luckily saved from this, with some exceptions.
Or replace AI/algorithmic targeting with tech in general and the disruption target with whatever it targets and you’d realize the problem with the sentence.
Technological advances have disrupted plenty of fields. That doesn’t mean those fields were fundamentally flawed. Every arena has a certain degree of dysfunction. AI has its own massive share of issues already. But that doesn’t negate the whole field.
Take the classic example of the Travel Agent. They are all but extinct because of technology. Yet they did serve a legitimate purpose before. Yes, plenty of them were middlemen who didn’t care, but also plenty were passionate about organizing travel plans and helping people arrange their travels and vacations. Plenty of people using AI today are also middlemen between you and Claude who also don’t care
In the end it depends on whether one considers technological progress or human flourishing to be the end goal. Surprise—they are not always aligned, and sometimes are at odds with each other.
Like I had many bad experiences in cabs in my younger years. It was just bad luck really, but I hated cabs for the longest time because of that and completely dreaded needing them. When Uber was first coming on the scene and cab drivers were protesting against it, I did think to my self something along the lines of “if an app can destroy your business, the problem was in your business” but I really just didn’t like cabs for other reasons. And the irony is now Uber is the same. When I land in my airport, I see crazy lines for rideshare with people waiting on cars to come pick them up, while there is a cab on the other side that is ~$15 cheaper somehow and ready to go with no lines. And I get to tip the driver those saved 15 bucks
Thinking back, when I first started teaching myself programming, I didn't know what to learn, so I explored the history of programming and organized it as I went.
One of the most striking things I remember is that when Stack Overflow first launched, quite a few people opposed it.
Also, I recall that in ancient Greece, Socrates criticized writing, saying it would weaken human memory.
When SO first appeared, there were many who insisted that the only proper programmer's way was to RTFM, deeply understand the system's fundamentals, and then write code. I wasn't from that generation—I belonged to the copy-paste-from-SO generation—so I can't say for sure, but I found it quite fascinating.
The cost of that friction could only be borne by a very small minority, and that minority could guarantee quality. That's why scholarship was something only the elite could pursue—and to some extent, it still is.
In the past, tasks were painful and high-friction. The results were filtered through that process, accessible only to the few who could endure it. But we tend to mistake those inefficient drops of sweat for quality. In reality, just as writing didn't diminish philosophy but rather created systems like law and philosophy, this might just be another turning point
I think Mr. Lemire's post is similar in spirit. In other words, when friction increases, the cost of production for producers also rises. So back then, everything produced through that high-friction process was easier to quality-control. But that's no longer the case.
And actually, universities were originally about 'holistic education,' but these days, they've become more about training talent for industry and managing human resources for the job market. That shift has caused problems.
In that sense, it's only natural that these problems arise at the intersection of academia and industry.
Industry usually demands 'people and technologies that can boost productivity right now.' Meanwhile, academia should ideally pursue problems worth exploring over the long term, even if they have no immediate utility. But the current state is a product of compromise.
Once university evaluations, student recruitment, research funding, and employment rates become tightly linked to industry demand, the latter starts to pressure the former. And under those conditions, the current outcome is almost inevitable—because industry increasingly wants to churn out degree stickers at lower and lower costs.
In the end, a different methodology will be needed, and whoever proposes it will become the game changer. Then new schools of thought and methodologies will emerge based on that person, and they'll gain enormous fame. I'm curious who that will be.
New things are always born by laying the past to rest. I'm always waiting for that new methodology.
Industry demands a giant sorting machine and that is what they got. If we acknowledged and accepted this we could come up with a much better solution than what we have.