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- Hacker News
- Maybe old methodologies will be discarded and new ones will emerge.
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.
by jdw64 - >Industry usually demands 'people and technologies that can boost productivity right now.'
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.
- Socrates hated the written word . It weakens the memory. It does not talk back. Etc...etc... This is not a new problem folks.
- I have a PhD and I completely support AI disrupting the field.
If AI disrupts your field, the culprit is most likely not AI.
by gcatalfamo - Could you expand on that?
- “If algorithmic targeting disrupts your society, the culprit is most likely not algorithmic targeting”
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 past, the path to a math Ph.D. cultivated resilience, resourcefulness, critical thinking, and a healthy skepticism (…) but suddenly you can produce a passable Ph.D. thesis with the push of a button
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.
by Woodi - > But in 1905 a paper was published... Too bad politicans do not get implications of that and still was pushing communism decades later...
The photoelectric effect/quanta? I'm not sure I understand the supposed connection to communism.
by Ukv - > some quality "literature", of some form
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."
- The largest output of a PhD has always been the training to the student, not the thesis itself, hence why we're called 'students'. Anyone claiming that a thesis can be generated by AI is missing the point. AI can also do everything an undergrad can do, we don't claim that undergrad education has been blown to bits. At best, we say we need better modes of evaluation, and perhaps that's true for PhDs as well.
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.
by haritha-j - You’re sort of saying that’s because your thesis had no value to begin with, because it’s mainly a teaching exercise. I’m not saying that it doesn’t have value by the way, I’m sure it was good, that’s just my read of your post.
It’s an interesting subject. Makes me want to vibe code a PhD generator just like in the tweet. Maybe I will.
- > we don't claim that undergrad education has been blown to bits
We don't??
by ShinyLeftPad - And how is the PhD student trained? By doing research and writing about it by him/herself.
> 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.
by tgv - Isn't it easy to adapt? Besides the usual assessment, also do:
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.
by OutOfHere - PhDs only were adopted universally in 1917 with some resistance and apprehension.
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.
- > PhDs only were adopted universally in 1917
In Oxford. That hardly counts as universal.
- The author is a mathematician and I think to a certain extend the tweet reflects the current panic among (some) mathematicians. So ~~second sentence~~ third paragraph the claim that somehow ai could right now write a phd in physics or sociology is something we don't observe (at the moment). What we observe is, that ai can find counter examples to well established conjectures in mathematics quite well, but the thing is the other fields don't have the kind of well established riddles that currently produce the flashy results in mathematics.by yk
- > something we don't observe
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.
by tgv - To show my ignorance in mathematics a bit: do you feel that having such neatly defined riddles gives the AI an advantage in solving them?
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?
by ehnto - I am not sure what point the author is even trying to make here. On the one hand, he seems to complain about how AI has virtually made the traditionally PhD thesis obsolete, but on the other hand, he also states:
> 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.
by this_user - > AI is starting to show that the emperor called 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
- > So, it sounds like nothing of much value has been lost.
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.
by tempfile - A good place to plug my favorite thesis to read: Okasaki’s “purely functional data structures” https://www.cs.cmu.edu/~rwh/students/okasaki.pdf .
Very soothing and moves fast.
by wanderer2323 - I think the premise was, before you had to actually do some work to create the thesis. And there was always the concern that yours could be one which was read deeply, so that thesis work had to at least show that you did some work. That there was meat behind the paper.
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.
by b112 - Most thesis are never read because anything worth sharing with the wider world ( and some that isn't ) is highly likely to have been published as a paper - not because the work in thesis has no value.
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.
by DrScientist - I've seen a student using ChatGPT for almost everything in his PhD (in engineering). You have some data but you don't know what kind of statistical analysis tool to use? Ask ChatGPT. Code for the analysis? ChatGPT. How do you interpret the results? ChatGPT.
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.
- Maybe it wasn’t garbage, maybe it’s just gotten significantly easier because the hard parts have gotten less hard. Search is solved, prose is solved, reasoning is… assisted at least. What he wasn’t being rude about was bursting his colleague’s bubble about AI generated work in general.
- > 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).
by piva00 - We’re at the point of learning that some things that used to matter no longer do, and some things we used to think mattered never did. It’s a going to be a shock to everyone, and this same phenomenon is happening everywhere, not just academia or software engineering.
My bet: a lot of the things we used to do were habit, ceremony and gatekeeping much more than being necessities.