Why I may ‘hire’ AI instead of a graduate student
science.org
science.org
As a tax payer, I am very concerned if the people I fund with my taxes to do a job unilaterally declare they are no longer going to do the half of it.
[1] https://asteriskmag.com/issues/10/the-origin-of-the-research...
Nowadays, promotions of professors for different levels (Assistant, Associate, Professor) is solely dependent on number of papers they are publishing in Q1 journals. But the research maybe entirely bogus, same ideas repurposed hundreds of times by different professors.
The entire concept about "systematic knowledge" has gone downhill.
UK universities do currently hire people to do research and teach. And tenure is based on research not teaching. Teaching is seen as something that funds the operation to an extent. Some are excellent teachers. Some merely provide the material.
It works as is because researchers are not meaningfully impacted by having to do a few hours a week. And student get access to people in touch with the field. But it is not optimal having people who often are not good at teaching and/or don't particularly want to do it, taking lectures and tutorials.
But I do agree that the ability to produce and procure research is not at all coupled with the ability to teach.
In a similar vein, it is recommended that if you are in a business meeting you hear what the junior positions have to say about something first and work your way up the chain of command rather than the other way around due to the junior positions being less familiar with internal processes and thus more likely to flag or suggest something completely out of left field that the higher ups might miss.
Note, I'm saying all of this as someone outside of academia who is passionate about science and had a very mixed bag of teachers in undergrad.
Assuming we have time to do this in some post-having-jobs world, of course.
I think in some subjects (e.g. literature) the greater prestige of research leads to a lot of pointless research and we need more teaching.
Of course, there are many good researches who are bad teachers. I am not so sure about vice-versa, but, nonetheless good teaching should be rewarded more, as should the ability to communicate knowledge in other ways (e.g. by writing books).
I've worked with good and bad at both. Some of the most difficult problems when you have students who have had excellent teachers and then get dropped into the real world. If they don't learn themselves how to apply what they're learning (the other side of the coin of training) then they're often no better than an llm stuck in a loop, they know the textbook but don't know the gray areas...
Also professors and researchers are required to be able to communicate otherwise they're useless to the field. They need to better.
I'm not saying every lecturer will hold any interest in every lecture course. I've had the ones who are there lecturing core material to avoid the dept losing its accreditation and I've done electives where the professor is off the wall and spends half of the time going on about their research instead of the address material (fun but painful come exam time).
This is like saying peasants growing vegetables in the field should not mix with philosophers questioning the secrets of the Universe.
Problem is most research is just pissing in the wind. No real results. Show me the cure for cancer. Show me the warp engine.
So it's very nice to sit in their ivory tower doing ivory tower stuff while the peasants feed them with the vegetables they grow plowing the fields.
In reality, let them also teach. That's real, palpable work. I can't do all nice things and never touch shit work, so should professors because unless they cure cancer or invent the warp engine now, they are not a privileged cast.
On the other hand the course I learnt the most from was taught by a passionate lecturer who isn't even a professor, and he gets the highest ratings every year. (Yes we have a "rate my prof" event)
But this exists in many educational + research institutions already. Where it runs into problems is in resource constrained environments, where there aren't the budgets to support research-only positions that aren't 'less than' roles or the institution can't support the grant ambitions of highest 'performing' teaching researchers, stuck that they don't go to those institutions and more less research-focused (or at least smaller grant value) teachers populate those schools.
I'm trying not to make any value-judgements here, so please ignore and bias vibes that gives off.
The problem is about the fresh talent pipeline for researchers (i.e. PhDs). In many ways, elementary school and a Master's degree are more alike than a Master's and a PhD in the sense that you're learning prior art with clearly defined exam/project assessments and no expectation of making something truly novel in both elementary school and the Master's, while a PhD is all about discovering something nobody uncovered before. So, calling this a problem of not wanting to teach isn't quite right.
IMO, the article is rather highlighting a different problem; the former problem in this area was that only a tiny sliver of the best engineering/CS undergrads wanted go into research given the far more lucrative industry careers, and now the supply part of that market is about to vanish too due to agentic AI. This will basically kill the concept of an academic career as we know it and the point of the article is that we need to find a different model of advancing and funding science.
If we split them up, then the teachers will only be able to teach what they have theoretically learned from literature only. What we need is for institutions to reward teaching, reward students who excel and most importantly, reward teachers who produce excellent students.
Disdain for teaching should not be the norm. After all, what are they doing if not teaching when they publish a paper, or give a talk at conferences? Might as well be a hermit scientist then.
So this article is really not saying anything controversial in the strictly ontological side of things, in fact it's already a relatively common stance to prefer supervising few (or, more rarely, none at all) students.
This researcher is saying "when I consider hiring someone as a workhorse, I might prefer AI instead"; what's the harm in that? Too many PhD students are used as disposable cheap labor, seeing little personal growth in their PhD journey and being generally neglected and abused.
The authors itself writes:
>I would recruit a graduate student into my lab and allow them to run with the project, providing guidance along the way.
You say to many phd students are used as disposable cheap labor, but what is the amount of people still learning stuff maybe bigger?
Even completely egoistically replacing students with AI is shooting yourself in the foot in the long term.
I did my PhD in France where we were legally employees like any other and did 100% research with like 100 hours training over the three years which could be 5min MOOCs counting for hours or classes the professors would sign us off on. We were hired by a specific researcher for a specific topic, unlike US students who join a broader program and explore their own directions more. My mentoring was drinking coffee with my advisor and colleagues and the odd e-mail exchange the day before turning in a paper.
I believe Germany and quite a few other European countries are similar. Any country that does 3 years PhDs is bound to cut on the student part of things.
[Source: https://www.reddit.com/r/AskReddit/comments/o6hlry/statistic... ]
While funny, it does nothing to prove your assertion.
Unless that citation was generated by AI.
No, I had no intention of trying to offer a real source for the accuracy of AI generated citations. It is not hard to Google, search HN or even (ironically) use AI to search, to find numerous relatively recent studies discussing the problem or highlighting specific cases of respected journals/conferences publishing papers with junk citations.
1) Automated fetching of papers is difficult. API approaches are limited, and often requires per-journal development, scraping approaches are largely blocked, and AI- approaches require web fetch tools which are often blocked and when not, they consume a lot of credits/tokens very quickly.
2) AI generates so many hallucinated citations it’s very hard to know what a given citation was even supposed to be. Sure you can verify one link, but when you start trying to verify and correct 20 to 40 citations, you end up having to deal with hundreds or thousands of citations just to get to a small number of accurate and relevant ones, which rapidly runs you out of credits/tokens on Claude, and API pricing is insane for this use-case. It’s not possible to just verify the link, as “200 Status” isn’t enough to be confident the paper actually exists and actually contains the content the AI was trying to cite. And if it requires human review anyway, then the whole thing is pointless because a human could more quickly search, read and create citations than the AI tool approach (bearing in mind most researchers aren’t starting from scratch - they build up a personal ‘database’ of useful papers relevant to their work, and having an AI search it isn’t optimising any meaningful amount of work; so the focus has to be on discovering new citations).
All in all, AI is a very poor tool for this part of the problem, and the pricing for AI tools and/or APIs is high enough that it’s a barrier to this use case (partly due to tokens, and partly because the web search and web fetch tools are so relatively expensive).
> The issue is not whether my students are valuable. In the long run, they are invaluable. The issue is that their value emerges slowly, whereas AI delivers immediate returns.
I had the thought that it's more like hiring only autistic/on-the-spectrum employees that will on whims do exactly what their interpretation was, or possibly worse literally what you said without considering further consequences.
This is why firms that do actual training have clauses written in the employment contract that says if you receive x months of training from them then you have to work for them for at least y number of years otherwise if you leave then you have to pay them for the cost of training you (which is written as a dollar amount in the contract).
Companies that don't have that kind of clause in the contract are going to get screwed over when their newly trained employees get poached by other firms.
The shortage of senior engineers will be even worse than it is today.
Not sure your argument really holds any water over a 10+ year period as I originally described.
I started my career with a graduate program from a larger company. I stuck around in that company for close to 5 years and would have liked to stay longer. My reason for leaving were the absence of a career progression. The first 3 years, the company had a great career progression path. Clear outlines what it needs for a promotion, fair and transparent pay, etc.
That changed and despite hitting/exceeding my goals, I was denied a promotion twice with no good reason. My boss, who is fantastic, told me that he cannot give me a good reason because he himself did not receive one. So I left.
Generally speaking, my cohort of the program was part of the company much longer than most employees. I don't think a single person left in the first 3 years. Attrition only started now that there was a general shift in the companies culture and communication.
Those sorts of clauses are not legal everywhere. They would certainly be at least heavily restricted in the UK (on the other hand there are subsidies for some employer training and education here - which is why my daughter has an engineering degree without paying any fees). The author of the article is in Israel, and as an academic is in a different position to people in businesses.
> “The companies three to five years from now that are going to be the most successful are those companies that doubled down on entry-level hiring in this environment,” Nickle LaMoreaux, IBM’s chief human resources officer, said this week.
This is like the classic "I'll do it myself because its quicker".
In the current environment and likely more so into the future, those that hire and develop graduates skills are going to be looked at more favorably. Furthermore, the people you work with and coach become peers and typically help build a network of people who can bat for you.
It's tricky and its a balancing act and I appreciate that AI is becoming the easier quicker less fuss option
i.e. they shifted the cost of training from the employer to the employee.
What makes you think that will suddenly reverse course, or that society will suddenly start to care?
People want the cheapest, fastest shit possible. Companies too, generally.
In my line of work I was coaching and now I am senior I am expected to delegate tasks and coach, not to increase my own workload for doing simpler tasks myself.
You may be able to go fast with AI, but you can only go far with humans.
We are definitely seeing a lot of anti-human behavior around AI adoption, because all anyone seems to care about is going fast
> If you want to go fast, go alone, if you want to go far, go together.
Even if all AI progress grinds to a permanent halt today, there's already enough utility in its current capability to force these questions. As a result, how we train and educate graduates and young people needs to change.
I have no doubt you need to have actual experience to be able to ensure AI output is at a production standard but if we accept that reality, then a shift in how we educate and train young people could make an enormous difference in ensuring employers still see value in hiring people with no real commercial work experience.
At least for publicly funded work, it was always an assumption that you would need students to hit some goal; so by funding it you would get both the outcome, and more people skilled in that field. If the scope of what one team/senior can handle has grown with ai, we will either need explicit staff numbers as a requirement or bigger scope to the point where the ai can't handle it.
Or we find that AI can do so much the whole system implodes...
A lot of my work with AI involves questions where I have an intuitive direction and sense of the data or model, but where explaining why takes almost as much work as doing it. (Commonalities: weird interdisciplinary nexuses and idiosyncratic data sources.) Adding a human translator, much less someone without field experience, seems worse than giving the task to a human or AI wholesale.
Where humans still reign supreme is in interacting with other humans. Paradoxically, this might make grad students’ roles attending staff meetings as their professors’ proxies and/or filling out paperwork.
Apparently the same question is being asked at different levels and abstractions...
Implementation can differ (e.g. ratio of interns vs total headcount and so on), but it is the time for governments to intervene and force corporations to train people, humans are resource for the government, they need to polish that resource to thrive.
1. the wait time is too long for the company to fill a position, it is difficult to predict what happens in the next 4 years
2. difficult to match the students with companies. For example, you are interested in CS, but company wants specifically React developer (assuming there was no AI and there was still demand), would the student change all their courses based on the requirements and live like a robot who is forced to take courses they are not much interested in. Now imagine when gap is higher between topics (CS vs React is closer, compared to MBA vs procurement, both are somewhat subset of same topic)
The professor's jobs are to TEACH students.
Research grants are given by governments mainly to first TEACH students and secondly to get something useful.
If they are not doing their job they should be fired.
That's not DEI or anything of the sort. That's common sense.
They can do their research at private companies if it's worth it.
Government's goal is obvious and correct, but if you have done a research and tried to get a grant you should know grants are very "political" as well, if you are researching a thing which is not trendy or takes another 10 years to yield results, but there is another lab who is telling we are researching LLM, it will be very difficult to get a grant even if you promise to TEACH/hire 20 students for that research.
Justifying long term benefits is difficult problem
Both avoids the tragedy of the commons (why would a corporation pay to train a junior when they can just let their competition do it then poach the experienced senior) and gives more opportunity to a new generation that are frankly getting economically screwed over enough as-is.
What is wrong with this guy? Of course he knows where that will leave those students. Why did he even choose to be in the business of developing people? Nobody forced him. Anyway, the ladders were pulled up in 2020–2021.
The motivation to take on juniors to grow your long term capabilities equation is shifting, to the point where its harder to justify.
However, the person is also sufficiently self-aware to share their thought process (and candid about its shortsightedness).
To me, that made it worth reading (even though it has a sad message).
These institutions have a duty to educate humanity. PhDs are also supposed to be able to help the public understand complicated science. To guide ethical decisions.
But no, we measure the number papers, and not even their quality (very well).
It's all a matter of incentive alignment, what gets measured gets done. The state of academic science is sad in most places. This contemplation by OP being case and point.
Unfortunately, as other comments here have pointed out, the incentive structure for academia right now is misaligned, leading some faculty to focus just on publish or perish. This is a huge shame on so many counts.
My hope and also slight expectation from the AI era is that academic writing becomes so commodified that we see a total devaluing of papers as a metric, even in prestige venues. Perhaps this would help the community find better things to focus on.
The article really is about "education seems directionless without economic goals", and again as comments have pointed out, it only seems so.
It doesn’t surprise me to see such articles coming from academia, in which juniors are treated like dirt to such an extreme that is unimaginable in any other industry, save for maybe Michelin star cuisine.