This happened when I was in grad school back in the late 90s. Clinton increased the budget of the NIH significantly (thanks Bill) which led to a huge increase in training grants allowing PhD programs to expand. However, faculty positions did not expand, so many PhDs had to find alternate careers (most people go into PhD program to get a faculty/researcher position). This actually worked out really well for bigtech, which hoovered these folks up. I worked with tons of ex-physicists who were great programmers especially at machine learning. It turns out that many of the things you need to thrive in a PhD program translate to bigtech engineering needfs.
I have a PhD and I felt that I had to deprogram myself to fit in with BigTech. With a PhD, I would uncompromisingly pursue a single goal. Ideas were worth something. In Big Tech, ideas are in abundance but time is short, and I must compromise to follow through on my commitments. The only thing I really have an advantage over non-PhDs is that I get suspicious of good results
Edit: totally unrelated, but PhDs in the West basically seem to be immigration schemes, and universities are happy to play along.
Money brought in by foreign students is greater than money brought in by out of state students, which is greater than money brought in by local students. The way tuition is set up as a general concept will lead to this situation if your institution lasts long enough.
Many graduate students get tuition waivers, so this is largely irrelevant.
The difference is that in graduate school, there's little or no bias in favor of in-state candidates, whereas for state universities, it's basically their mission statement to make dedicated space for in-state undergraduates.
Keep in mind that graduate school admission is controlled by the individual academic departments, but individual academic departments don't directly get tuition money from its students. The professors on the admissions committee don't care how much tuition the students pay.
> It turns out that many of the things you need to thrive in a PhD program translate to bigtech engineering needfs.
This is contrary to my life experience (even for math or physics PhDs).
What makes a great PhD thesis is to question an insane lot of assumptions of deep results in the field of your PhD thesis, and show that if you base these on a very different foundation, these results generalize to whole different areas; e.g. you found a bridge between seemingly unrelated areas of studies.
On the other hand, managers deeply hate it if you question a lot of assumptions behind the work that you do, whether it is some special case of something deeper, and aren't obedient to the manager's leadership.
In other words: a great PhD program teaches you to think and work all the time on things managers will hate you for.
Certainly a subset of PhDs who work at bigtech fail to have any impact. I've seen a few brilliant but inflexible people hit up against the immovable parts of a corporation. I've also seen brilliant PhDs who refuse to study for a software engineering interview... and then fail miserably. But by and large, based on hundreds of individuals, I've found that quantitative PhDs can drop into many SWE roles and contribute- both mundane improvements to code quality, and massive improvements to the foundations of projects.
The number of PhD completions has been steadily growing over the past two decades, from about 4,000 to about 10,000 per year.
According to our calculations* based on the information available, the cumulative number of people in Australia with a PhD has increased from about 135,000 in 2016 to about 185,000 in 2021.
The incentives are for Universities to get smart young people to do their work cheaply.
What happens to the graduates afterwards ceases to be the University's problem.
The only strange thing about it is that the smart young people are taking so long to figure it out.
> The only strange thing about it is that the smart young people are taking so long to figure it out.
I don't think it's so strange. They're smart in their chosen fields, but intelligence is not wisdom or hard experience. Moreover, intelligence breeds confidence, often overconfidence, the idea that you'll be the one to beat the odds. I suppose the same thing happens to young, talented athletes, for example.
1) Mental illness is not the opposite of academic confidence. And graduate school applicants must demonstrate undergraduate academic achievement in order to be accepted, so there is a clear basis for confidence.
2) IQ is pseudoscience.
3) "Karpinski and her team emailed several members of a group named “American Mensa” OMG just stop right there.
4) "The authors of this study could not find a similar group of average intelligence people to utilize as a control group, so they used national data regarding disorders of people with any range of intelligence and assumed overall intelligence would be average." Garbage.
That sure applies to maths/physics PhDs, not so much for arts ones, these are still competing for a handful of academic jobs and the rest go to menial jobs with huge debts.
That's a great question. To the extent that increasing the budget caused more smart people to get PhDs and more of them were able to contribute to the scientific effort (as well as help bigtech develop ML and contribute back to science), I think it was a good idea.
It might have been better executed- somehow matching the increased supply of grad students with increase supply of faculty positions, or perhaps just growing it more slowly to let the inequalities equilibrate a bit more. But ultimately, I think it was a good thing, in that it increased the total science being done.
Yeah, NIH had two guys (Lauer and Collins) that tried to do all kinds of things to spread out funding to junior researchers and increase the number of jobs. The entrenched investigators fought them every step of the way and Trump has since run both off.
One of the problems is that universities exploit graduate students as cheap labor in teaching and research while they're in school, so the universities have an incentive to admit more incoming students than can be placed in academic jobs.
I'm puzzled by this response to my comment about the cheapness of grad student labor.
Grad students are doing work that would otherwise have to be performed by full professors, who are vastly, vastly more expensive than grad students. So in my opinion, to blame undergraduate tuition on graduate students just seems... bizarre?
Some grad students are finding a third path, remain a grad student. The pay is poor, but sometimes the work is interesting enough. After 8-10 years you've made enough contacts and gotten enough job interest that you have choices for doing something else. If you invent something truly new and useful that can lead to an income as well. It is quite obvious that getting a PhD is not a sustainable path to working as a professor once the number of PhD's exceeds the retirement rate of the profs.
Einstein did not get an academic job after his PhD.
If it can happen to Einstein, it can happen to the average PhD of today. But, PhDs are over-qualified for the average job (as was Einstein when he worked as a patent clerk), and employers may be reluctant to hire over-qualified folks.
For someone thinking about grad school who does not want to go into academia as a career, a PhD advisor with industry experience is not a bad idea. They will understand what you need to succeed in industry and have connections. Might be easier to find in engineering departments.
> PhD advisor with industry experience is not a bad idea. They will understand what you need to succeed in industry and have connections.
My industry experience taught me the following things:
- In industry, there exist quite some deep, interesting (e.g. math, programming) problems that (unluckily) many people in academia don't have on their radar. These kinds of problems often don't fit into the "boxes" of academic disciplines.
- People in industry are not interested that you attempt to work on a breakthrough on some of these problems (even in your free time) - even if this would give the company millions or even billions of money. They will instead actively be fighting you if you question anything non-shallow.
So to answer your implicitly stated question what you need to succeed in industry: keep your mouth shut, question nothing, and shut off your intelligence. Otherwise you are considered to be a troublemaker.
> In industry, there exist quite some deep, interesting (e.g. math, programming) problems that (unluckily) many people in academia don't have on their radar. These kinds of problems often don't fit into the "boxes" of academic disciplines.
I have reasons for being a bit cautious on giving details, but some hints on example areas are:
- Understanding the dynamics (mathematics) of some exotic markets that are currently outside of the focus of investors. Very interesting mathematics is involved, but this is too "mathy" for many economists, and (currently, because the rules of the market dynamic still have to be sufficiently understood) too "vague" for many mathematicians who work in academia.
- If you work on data integration problems and/or LoB business applications of some big, conservative companies, you begin to see that many of these problems are instances of deep abstract mathematical structures that are outside of the focus of the academic mathematicians who work in the respective academic area (think for example into the direction of algebraic geometry or algebraic topology): it is too "applied" for them. On the other hand, people in industry have a hate for people seeing these deep abstract patterns that could simplify the applications.
- If you look deeply into some business calculations, you might think that the mathematics that is used there is "easy". But if thus some "theory" describing the business calculations does not need to describe "complicated" things that (academic) mathematicians love to think about - wouldn't this mean that there could exist a great abstraction that simplifies these business calculations a lot in computer programs?
- If stochastics is used in, say, insurance industry in a much more "simple" way than in probability textbooks: couldn't there exist a much "simpler" (but likely very different) theory of stochastics that is sufficient to describe and solve the kind of questions that people in the respective industry care about (though for sure not the kind of questions that academic mathematicians who work in probability theory care about)? Again: people who work in industry hate employees who think about such questions. On the other hand, people in academia are interested in different questions.
- If you look at the source code of some historically grown (but business-critical) business application, you begin to understand that there is no known data structure documented in academic literature that can describe all these things. So you start deriving it on your own. The problem is: business people don't like such deep thinking about the "correct data structure" for their business problems. On the other hand, academic computer scientists are not interested in this question either, because the things that the data structure describes is deeply intrtwined with how the business processes of the respective company work.
Which industry and in what role and context? From someone I’ve hired to design a CRUD or mobile app, I’m not all that interested in a proof that a particular two-symbol Turing machine happens to do the job. It may be an interesting result from a research perspective, but it’s not what I’m paying for or on the hook to deliver. Instead, it looks like procrastivity that makes my job more difficult.
As a professor, I believe virtually all profs should have industry experience and occasionally go back for a year or two. (I’ve bounced back and forth!)
> As a professor, I believe virtually all profs should have industry experience and occasionally go back for a year or two. (I’ve bounced back and forth!)
For quite some professors I imagine that going back to industry would make them a lot more arrogant. In academia, being surrounded by very smart people dampens the arrogance a lot because you realize that you may be smart, but not that smart. On the other hand, in industry you have much less people around you that can intellectually stand up against you, which easily makes you smug.
How did that affect getting tenure? My experience watching my advisor go through that process is that an industry stint would negatively impact the process.
There are a lot of variables, but from personal experience it also depends on how you talk about that experience in your tenure dossier. I was able to spin a research finding into a commercial product. Due to intracompany politics, that product never shipped. But my tenure committee talked glowingly about my ability to take a research idea and polish it into something that a major software company would pay me to commercialize.
In bupiotech/pharma, including software support for modeling, the PhD is the entry level degree. Non research degrees are usually technicians, valuable but lesser stature and pay. Unless their hands are superb in the lab. This consumes much of the production particularly with the boomer cohort actively retiring.
Where there are students willing to pay, and government willing to back up their loans, there will always be schools telling students they should spend more. It seems like it used to be harder to get a Phd..
It was the verbatim title of the article, and it contains
> A 2023 study2 of more than 4,500 PhD graduates in the United Kingdom found that over two-thirds of doctoral graduates were employed outside academia.
This is false. Many PhD graduates struggle to find jobs in the US. And even if it were true, that would be fine. These people were trained here, understand the American style of research, and want to contribute. It is a massive loss to the US to blindly turn them away.
I’m beginning to think we need to change academia to be driven more by employer demand than by student demand. Stop lying to people, like I was lied to. You probably can’t live your dream. You probably can’t grow up to be what you want. The vast majority of people have to do what society needs.
Let various industries tell the universities what kind of labor force is needed. Then universities should set the numbers of students they accept for those majors accordingly. The time to tell people no is before they spend several years of their lives and a fortune of tuition money in training to do something that will be a dead end.
With a decent general education as a prerequisite, most adults are able to do most jobs well. That is the best way for most people to hedge against things being disrupted.
It's impossible to know what the future will hold for one's profession. Industry recently demanded "coders" and now a generation of compsci majors are finding the jobs of the present aren't the jobs of the past. A similar thing happened to secretaries and typists. Meanwhile people who were perhaps language or history majors and ended up with stronger communication skills often end up as executives. There are many paths.
Part of Accreditation Board for Engineering and Technology (ABET) accreditation is having an Industrial Advisory Board (IAB). Whether it is a box to be checked or a source of input for thoughtful consideration is another question.
Asking career academics to adapt to industrial environments with which many (clinical professors or professors of practice excepted) have limited experience seems like a bridge too far.
What is the source of the assumption that all PhD students want academic posts? The article cited a survey that concluded PhD holders were largely satisfied with their careers, so that population don’t appear to be the squeaky wheels. Other motivations for pursuing a PhD include climbing the mountain because it’s there, moving up the labor schedule, going for a senior position later in one’s career, good relationship with a particular advisor, or delaying entry into the real world.
This is called proposing a short sighted solution to an incredibly complex problem, and you should ask yourself some serious questions about why this is what you think should happen. Then look up the many times others suggested this and the overwhelming arguments that people have made to go "absolutely not, because education does not serve industry, is not paid for by industry, and is not appreciated by industry" in many, many variations.
Academia will never go for this of its own volition, because "higher education is about learning for its own sake and becoming a more complete individual and citizen" is key to academics' self-conception. They never want to admit to being "mere" vocational training, now matter how clear it is that's what they are and have been for a while. If your proposed change does happen, it will have to be forced on them from without.
Even in some sort of hypothetical sotuation where money isn't an issue, if you have 3 schools, and only need 1, you can see none of the schools wanting to be the ones to be shut down.
Shakespeare is read in middle school. It’s also available for purchase in any bookshop along with supplementary material, not to mention various free materials on YouTube, forums, study groups, etc. It’s not some sort of sacred knowledge only available to PhD students.
This happened when I was in grad school back in the late 90s. Clinton increased the budget of the NIH significantly (thanks Bill) which led to a huge increase in training grants allowing PhD programs to expand. However, faculty positions did not expand, so many PhDs had to find alternate careers (most people go into PhD program to get a faculty/researcher position). This actually worked out really well for bigtech, which hoovered these folks up. I worked with tons of ex-physicists who were great programmers especially at machine learning. It turns out that many of the things you need to thrive in a PhD program translate to bigtech engineering needfs.
I have a PhD and I felt that I had to deprogram myself to fit in with BigTech. With a PhD, I would uncompromisingly pursue a single goal. Ideas were worth something. In Big Tech, ideas are in abundance but time is short, and I must compromise to follow through on my commitments. The only thing I really have an advantage over non-PhDs is that I get suspicious of good results
Edit: totally unrelated, but PhDs in the West basically seem to be immigration schemes, and universities are happy to play along.
Money brought in by foreign students is greater than money brought in by out of state students, which is greater than money brought in by local students. The way tuition is set up as a general concept will lead to this situation if your institution lasts long enough.
Many graduate students get tuition waivers, so this is largely irrelevant.
The difference is that in graduate school, there's little or no bias in favor of in-state candidates, whereas for state universities, it's basically their mission statement to make dedicated space for in-state undergraduates.
Keep in mind that graduate school admission is controlled by the individual academic departments, but individual academic departments don't directly get tuition money from its students. The professors on the admissions committee don't care how much tuition the students pay.
> It turns out that many of the things you need to thrive in a PhD program translate to bigtech engineering needfs.
This is contrary to my life experience (even for math or physics PhDs).
What makes a great PhD thesis is to question an insane lot of assumptions of deep results in the field of your PhD thesis, and show that if you base these on a very different foundation, these results generalize to whole different areas; e.g. you found a bridge between seemingly unrelated areas of studies.
On the other hand, managers deeply hate it if you question a lot of assumptions behind the work that you do, whether it is some special case of something deeper, and aren't obedient to the manager's leadership.
In other words: a great PhD program teaches you to think and work all the time on things managers will hate you for.
Certainly a subset of PhDs who work at bigtech fail to have any impact. I've seen a few brilliant but inflexible people hit up against the immovable parts of a corporation. I've also seen brilliant PhDs who refuse to study for a software engineering interview... and then fail miserably. But by and large, based on hundreds of individuals, I've found that quantitative PhDs can drop into many SWE roles and contribute- both mundane improvements to code quality, and massive improvements to the foundations of projects.
> I've seen a few brilliant but inflexible people hit up against the immovable parts of a corporation.
With such an attitude it would have only been a matter of time before they hit up the immovable part of academia as well.
It's global.
Here is something on Australia :
https://theconversation.com/australia-has-way-more-phd-gradu...
Key quotes :
The number of PhD completions has been steadily growing over the past two decades, from about 4,000 to about 10,000 per year.
According to our calculations* based on the information available, the cumulative number of people in Australia with a PhD has increased from about 135,000 in 2016 to about 185,000 in 2021.
The incentives are for Universities to get smart young people to do their work cheaply.
What happens to the graduates afterwards ceases to be the University's problem.
The only strange thing about it is that the smart young people are taking so long to figure it out.
> The only strange thing about it is that the smart young people are taking so long to figure it out.
They find out very fast, but come to the conclusion that academia is one of the few places where their intelligence is valued.
> The only strange thing about it is that the smart young people are taking so long to figure it out.
I don't think it's so strange. They're smart in their chosen fields, but intelligence is not wisdom or hard experience. Moreover, intelligence breeds confidence, often overconfidence, the idea that you'll be the one to beat the odds. I suppose the same thing happens to young, talented athletes, for example.
> Moreover, intelligence breeds confidence, often overconfidence
Quite the opposite: intelligence is linked to depression: https://engl105sp2020.web.unc.edu/2020/02/is-there-a-link-be...
1) Mental illness is not the opposite of academic confidence. And graduate school applicants must demonstrate undergraduate academic achievement in order to be accepted, so there is a clear basis for confidence.
2) IQ is pseudoscience.
3) "Karpinski and her team emailed several members of a group named “American Mensa” OMG just stop right there.
4) "The authors of this study could not find a similar group of average intelligence people to utilize as a control group, so they used national data regarding disorders of people with any range of intelligence and assumed overall intelligence would be average." Garbage.
My understanding is that there are lots of industry jobs in NIH's ambit that tacitly require PhD's (very much unlike the technology industry).
That sure applies to maths/physics PhDs, not so much for arts ones, these are still competing for a handful of academic jobs and the rest go to menial jobs with huge debts.
You think it was a bad decision to increase NIH budget?
That's a great question. To the extent that increasing the budget caused more smart people to get PhDs and more of them were able to contribute to the scientific effort (as well as help bigtech develop ML and contribute back to science), I think it was a good idea.
It might have been better executed- somehow matching the increased supply of grad students with increase supply of faculty positions, or perhaps just growing it more slowly to let the inequalities equilibrate a bit more. But ultimately, I think it was a good thing, in that it increased the total science being done.
Yeah, NIH had two guys (Lauer and Collins) that tried to do all kinds of things to spread out funding to junior researchers and increase the number of jobs. The entrenched investigators fought them every step of the way and Trump has since run both off.
Thanks for the clarification.
One of the problems is that universities exploit graduate students as cheap labor in teaching and research while they're in school, so the universities have an incentive to admit more incoming students than can be placed in academic jobs.
Underpaid grad students and postdocs are the dirty-but-not-exactly-secret source of research productivity per dollar in the US.
But the pyramid is unsustainable even if each PhD only trains one or two new PhDs every 5 years.
And then charge undergraduates more, making them take classes they don't need, in order to justify paying those graduate student GTAs.
I'm puzzled by this response to my comment about the cheapness of grad student labor.
Grad students are doing work that would otherwise have to be performed by full professors, who are vastly, vastly more expensive than grad students. So in my opinion, to blame undergraduate tuition on graduate students just seems... bizarre?
Some grad students are finding a third path, remain a grad student. The pay is poor, but sometimes the work is interesting enough. After 8-10 years you've made enough contacts and gotten enough job interest that you have choices for doing something else. If you invent something truly new and useful that can lead to an income as well. It is quite obvious that getting a PhD is not a sustainable path to working as a professor once the number of PhD's exceeds the retirement rate of the profs.
https://archive.is/VqD9K
Einstein did not get an academic job after his PhD.
If it can happen to Einstein, it can happen to the average PhD of today. But, PhDs are over-qualified for the average job (as was Einstein when he worked as a patent clerk), and employers may be reluctant to hire over-qualified folks.
For someone thinking about grad school who does not want to go into academia as a career, a PhD advisor with industry experience is not a bad idea. They will understand what you need to succeed in industry and have connections. Might be easier to find in engineering departments.
> PhD advisor with industry experience is not a bad idea. They will understand what you need to succeed in industry and have connections.
My industry experience taught me the following things:
- In industry, there exist quite some deep, interesting (e.g. math, programming) problems that (unluckily) many people in academia don't have on their radar. These kinds of problems often don't fit into the "boxes" of academic disciplines.
- People in industry are not interested that you attempt to work on a breakthrough on some of these problems (even in your free time) - even if this would give the company millions or even billions of money. They will instead actively be fighting you if you question anything non-shallow.
So to answer your implicitly stated question what you need to succeed in industry: keep your mouth shut, question nothing, and shut off your intelligence. Otherwise you are considered to be a troublemaker.
> In industry, there exist quite some deep, interesting (e.g. math, programming) problems that (unluckily) many people in academia don't have on their radar. These kinds of problems often don't fit into the "boxes" of academic disciplines.
Can you give some examples?
> Can you give some examples?
I have reasons for being a bit cautious on giving details, but some hints on example areas are:
- Understanding the dynamics (mathematics) of some exotic markets that are currently outside of the focus of investors. Very interesting mathematics is involved, but this is too "mathy" for many economists, and (currently, because the rules of the market dynamic still have to be sufficiently understood) too "vague" for many mathematicians who work in academia.
- If you work on data integration problems and/or LoB business applications of some big, conservative companies, you begin to see that many of these problems are instances of deep abstract mathematical structures that are outside of the focus of the academic mathematicians who work in the respective academic area (think for example into the direction of algebraic geometry or algebraic topology): it is too "applied" for them. On the other hand, people in industry have a hate for people seeing these deep abstract patterns that could simplify the applications.
- If you look deeply into some business calculations, you might think that the mathematics that is used there is "easy". But if thus some "theory" describing the business calculations does not need to describe "complicated" things that (academic) mathematicians love to think about - wouldn't this mean that there could exist a great abstraction that simplifies these business calculations a lot in computer programs?
- If stochastics is used in, say, insurance industry in a much more "simple" way than in probability textbooks: couldn't there exist a much "simpler" (but likely very different) theory of stochastics that is sufficient to describe and solve the kind of questions that people in the respective industry care about (though for sure not the kind of questions that academic mathematicians who work in probability theory care about)? Again: people who work in industry hate employees who think about such questions. On the other hand, people in academia are interested in different questions.
- If you look at the source code of some historically grown (but business-critical) business application, you begin to understand that there is no known data structure documented in academic literature that can describe all these things. So you start deriving it on your own. The problem is: business people don't like such deep thinking about the "correct data structure" for their business problems. On the other hand, academic computer scientists are not interested in this question either, because the things that the data structure describes is deeply intrtwined with how the business processes of the respective company work.
Which industry and in what role and context? From someone I’ve hired to design a CRUD or mobile app, I’m not all that interested in a proof that a particular two-symbol Turing machine happens to do the job. It may be an interesting result from a research perspective, but it’s not what I’m paying for or on the hook to deliver. Instead, it looks like procrastivity that makes my job more difficult.
As a professor, I believe virtually all profs should have industry experience and occasionally go back for a year or two. (I’ve bounced back and forth!)
> As a professor, I believe virtually all profs should have industry experience and occasionally go back for a year or two. (I’ve bounced back and forth!)
For quite some professors I imagine that going back to industry would make them a lot more arrogant. In academia, being surrounded by very smart people dampens the arrogance a lot because you realize that you may be smart, but not that smart. On the other hand, in industry you have much less people around you that can intellectually stand up against you, which easily makes you smug.
How did that affect getting tenure? My experience watching my advisor go through that process is that an industry stint would negatively impact the process.
There are a lot of variables, but from personal experience it also depends on how you talk about that experience in your tenure dossier. I was able to spin a research finding into a commercial product. Due to intracompany politics, that product never shipped. But my tenure committee talked glowingly about my ability to take a research idea and polish it into something that a major software company would pay me to commercialize.
In bupiotech/pharma, including software support for modeling, the PhD is the entry level degree. Non research degrees are usually technicians, valuable but lesser stature and pay. Unless their hands are superb in the lab. This consumes much of the production particularly with the boomer cohort actively retiring.
This just in - pyramid schemes eventually collapse!
But it seems like we still have a lot of tough, unsolved problems. Might be nice to have some smart people working to help solve them.
Where there are students willing to pay, and government willing to back up their loans, there will always be schools telling students they should spend more. It seems like it used to be harder to get a Phd..
Title edited by me from "How many PhDs does the world need? Doctoral graduates vastly outnumber jobs in academia"
It was the verbatim title of the article, and it contains
> A 2023 study2 of more than 4,500 PhD graduates in the United Kingdom found that over two-thirds of doctoral graduates were employed outside academia.
If 67-33 isn’t a vast difference, what is?
> It was the verbatim title of the article
I had to shorten the title to fit HN's character limit.
phd programs are largely immigration backdoors
This is false. Many PhD graduates struggle to find jobs in the US. And even if it were true, that would be fine. These people were trained here, understand the American style of research, and want to contribute. It is a massive loss to the US to blindly turn them away.
How does this work?
This is a problem in many industries, for example animation.
https://www.cartoonbrew.com/ideas-commentary/annecy-exposes-...
I’m beginning to think we need to change academia to be driven more by employer demand than by student demand. Stop lying to people, like I was lied to. You probably can’t live your dream. You probably can’t grow up to be what you want. The vast majority of people have to do what society needs.
Let various industries tell the universities what kind of labor force is needed. Then universities should set the numbers of students they accept for those majors accordingly. The time to tell people no is before they spend several years of their lives and a fortune of tuition money in training to do something that will be a dead end.
With a decent general education as a prerequisite, most adults are able to do most jobs well. That is the best way for most people to hedge against things being disrupted.
It's impossible to know what the future will hold for one's profession. Industry recently demanded "coders" and now a generation of compsci majors are finding the jobs of the present aren't the jobs of the past. A similar thing happened to secretaries and typists. Meanwhile people who were perhaps language or history majors and ended up with stronger communication skills often end up as executives. There are many paths.
Part of Accreditation Board for Engineering and Technology (ABET) accreditation is having an Industrial Advisory Board (IAB). Whether it is a box to be checked or a source of input for thoughtful consideration is another question.
Asking career academics to adapt to industrial environments with which many (clinical professors or professors of practice excepted) have limited experience seems like a bridge too far.
What is the source of the assumption that all PhD students want academic posts? The article cited a survey that concluded PhD holders were largely satisfied with their careers, so that population don’t appear to be the squeaky wheels. Other motivations for pursuing a PhD include climbing the mountain because it’s there, moving up the labor schedule, going for a senior position later in one’s career, good relationship with a particular advisor, or delaying entry into the real world.
This is called proposing a short sighted solution to an incredibly complex problem, and you should ask yourself some serious questions about why this is what you think should happen. Then look up the many times others suggested this and the overwhelming arguments that people have made to go "absolutely not, because education does not serve industry, is not paid for by industry, and is not appreciated by industry" in many, many variations.
Academia will never go for this of its own volition, because "higher education is about learning for its own sake and becoming a more complete individual and citizen" is key to academics' self-conception. They never want to admit to being "mere" vocational training, now matter how clear it is that's what they are and have been for a while. If your proposed change does happen, it will have to be forced on them from without.
Correction: higher education will never go for this because it's not profitable
Even in some sort of hypothetical sotuation where money isn't an issue, if you have 3 schools, and only need 1, you can see none of the schools wanting to be the ones to be shut down.
Perhaps we should do the same in schools and let local industries choose the curriculums most suitable to their needs.
Children in coal towns don't need to know Shakespeare and shouldn't have aspirations./s
Shakespeare is read in middle school. It’s also available for purchase in any bookshop along with supplementary material, not to mention various free materials on YouTube, forums, study groups, etc. It’s not some sort of sacred knowledge only available to PhD students.
>Shakespeare is read in middle school.
Sounds wasteful.
The children do not need this to serve my coffee or work in the mines.
Business First.
You need a lot of children in the mines to support so many Shakespeare PhDs, so I am not sure you are making a point you are trying to make.
> Children in coal towns don't need to know Shakespeare and shouldn't have aspirations.
That's a pretty astounding assertion.
I know, i was trying to bring the idea of business controlling education to a "reductio ad absurdum"
> That's a pretty astounding assertion.
Or obvious sarcasm.
Ah — point taken; I missed the "/s" at the end (it might not have been there when I read the comment).
In your defence i added the /s later, after I realized it there are people that would genuinely hold that opinion.