The massive boom in computer science enrollment over the last 20 years has been driven mostly by people chasing tech salaries, not by any real interest in computing itself. These students often show up completely unprepared for how difficult CS actually is, and universities have responded by dumbing down their programs to keep everyone happy and enrolled.
If this weeds out the people who are just there for the paychecks, it might actually be a relief to get back to teaching students who genuinely want to learn about computing.
Anecdotally I've heard that very few CS programs even use C++ anymore, and schools now favor Python because students find it more accessible.
But not sure that using Python as the specific tool is so bad--based on the MOOC that's what MIT uses in Intro to Algorithms. May be better than spending a lot of time on the vagaries of C++ which are certainly relevant to system programming (though that's probably slowly switching to Rust) if your focus is on algorithms and other design details.
I think there's still value in starting with C and C++, to see where it's coming from and see how much tooling and DX has improved, but I can't really blame courses jumping directly to the more useful things.
If I were at a school where they are teaching JavaScript or Python, you kind of already know that program is more "money grab" than "study of computing technologies".
Most of them have no actual passion for computing, their scope of knowledge is superficial, and they're asking for six-figure salaries out of the gate.
I had a relatively simple coding assignment (shouldn't take more than 15 minutes) that I would use to weed out those that were just copying and pasting sample code. It required a very large number of values and added an additional profiling step to it. The sample code wasn't performant with a very large number of values, and was painfully slow to use unless you made minor adjustments to a few things.
The hackers and nerds will be just fine. They are like gold when we find them now. But if this makes CS "uncool" again, I am all for it.
This is not at all my experience. One of the problems I face is many of those PMs and companies in general want mindless ticket completers. My current job just wants us to grind through the Jira backlog. They have no interest in anything else and crush it from your will too.
Think about how AI can help students cheat nowadays. You could still cheat previously, but now a CS-degree seeker can have an AI do the entirety of school work for them (with exception of say pen-and-paper tests). Imagine how the quality of new graduates drops with regard to the understanding and abilities you highlight as crucial to being effective in software, and how those that do understand are even more valuable relatively, but perhaps harder to find in the noise.
It's not going to work that way. I was genuinely interested and took many high level electives. I felt the program was very good 15 years ago at the school I attended. I also got an MSIS at a different school, but feel that one was not any more advanced than BS, just a faster pace and weirdly less coding. I did well for years at my job. Now it looks like I might lose my job and probably won't get another IT one. I will probably end up working at Walmart or something.
Still I've been careful to set my life up so I could go many years without employment if I had to. It's hard to trust the rest of the economy in general.
- In principle, it should not matter at all, but there are practical reasons why one PL may be better than another in a particular school or context.
- But, all this "choice of PL" discussion is really a discussion about CS1. A CS degree has at least seven other courses -- assuming 1 CS course per semester -- and in practice many more than that. So, if you're going to ask questions about CS1, the question to ask is, "Does CS1 setup students to succeed in the advanced courses?" Classically, these were courses in compilers, operating systems, networking, and so on. These days, you can add distributed computing, machine learning, etc. (but don't subtract the classics).
Did colleges expand their computer science departments or even just create them to meet the demand for the degree? The pipeline to possible employment with a CS degree is quite short, doesn't require residency and board-certification so it's a quicker route to employment, but then you are competing with peers with stronger backgrounds and educations and seasoned professionals for the same positions.
A good CS education only gives you prestige with fellow nerds.
We had some cleaning up to do. I was a hiring manager during COVID and the resumes I saw were unbelievable. People with "web" boot camps being considered for 6 figure salaries. People who had absolutely no business being in this field were being hired.
It was due to the easy money from low interest rates. This field always had solid salaries but some people were making a million to sit on meetings and integrate frameworks into me-too websites.
The hammer is coming down and is unfortunately hitting many good people too. But they will recover while the people who shouldn't be here will move on. Don't get your HVAC repair certification quite yet. Stop complaining about AI and go study it (the hard stuff not ChatGPT for dummies).
I don't read too much into the fact that unemployment for nutrition science is at 0.4% - that doesn't mean those people are all working as nutritionists or even in a job that requires a degree. You can see this clearly in the underemployment rate which is 45%+.
Likewise, the top unemployment rate (9.4%) of those with an anthropology major probably doesn't mean all those people are living under a bridge - a fair number of them will be pretty well off, living off their parents and knew going in that their field doesn't hire millions.
So what to make of IT grads having high unemployment rates (but low underemployment rates! bottom 5 in those)? I feel some more on-the-ground reporting is needed.
The quotes from randos reacting in this article don't really help. "Every kid with a laptop thinks they're the next Zuckerberg, but most can't debug their way out of a paper bag," because debugging (like Zuck!) is computer science, apparently.
That's a very important observation. It's much better to be in a field with a 6% unemployment rate than a 60% underemployment rate (like criminal justice, performing arts, and, surprisingly, medical technicians).
I feel like I've seen this quote many times over the years.
Also, how do they calculate employment rate? If you get a job at McDonald's while having a civil engineering degree or nutrition science, that counts as employed as well, no?
Would be good to see how many are actually employed in their field of study
That would be under_employment (vs un_employment).
Un_employment refers to people actively seeking work but unable to find it, while under_employment encompasses individuals who are working but not fully utilizing their skills or working fewer hours than they would like
Underemployment as "not working as many hours as you'd like" is the standard definition, and that one actually does seem to respect people's interiority.
Many of the big companies that have been on hiring orgies are advertising dependent. Ads are the thing that gets slashed heading into a bad economy, and we’re in an economic mess that is going to get alot worse.
That's a good part of the reason why hiring processes are so long and you need to re-check everything people are supposed to know. Filtering out hundreds of candidates to get a mediocre one at best, thousands to get a really good one.
There are job openings, but just having a piece of paper is not enough to get to those.
AI tools have made recruiting a miserable experience for everyone involved, there's so much cheating in applicants and you waste so much time filtering those out and sadly, good candidates sometimes get lost in the noise.
Networking is what has the highest signal to noise ratio. A good recommendation from someone you trust helps a lot, but it penalizes people just starting their careers and have smaller networks.
It's a sad state of affairs.
When it came to undergraduate majors with the highest unemployment rates, computer science came in at number seven, even amid its relative popularity.
The major saw an unemployment rate of 6.1 percent, just under those top majors like physics and anthropology, which had rates of 7.8 and 9.4 percent respectively.
Computer engineering, which at many schools is the same as computer science, had a 7.5 percent unemployment rate, calling into question the job market many computer science graduates are entering.
On the other hand, majors like nutrition sciences, construction services and civil engineering had some of the lowest unemployment rates, hovering between 1 percent to as low as 0.4 percent.
This data was based on The New York Fed's report, which looked at Census data from 2023 and unemployment rates of recent college graduates."
Source:
https://www.newyorkfed.org/research/college-labor-market (requires Javascript)
Data: (no Javascript required)
https://www.newyorkfed.org/medialibrary/research/interactive...
https://www.newyorkfed.org/medialibrary/research/interactive...
https://www.newyorkfed.org/medialibrary/research/interactive...
https://www.newyorkfed.org/medialibrary/research/interactive...
Civil Engineering 1.0%
Aerospace Engineering 1.4%
Mechanical Engineering 1.5%
Chemical Engineering 2.0%
Electrical Engineering 2.2%
General Engineering 2.4%
Miscellaneous Engineering 3.4%
Computer Science 6.1%
Computer Engineering 7.5%
I believe "learn to code" is a great advice, nonetheless; the skill is highly applicable. The bad idea is thinking that alone will land you a cushy job.
Maybe it's just a phase?
Or maybe today's juniors are different than the juniors were five years ago. And maybe that's because of AI.
i guess that is a natural dynamic in our economic/belief system in which all central planning must be inherently bad so we must always pay the on-demand price instead of the bulk price and every mis-timing mistake has to cost a lifetime of being wrong afterwards…
"Learn to code" was the scam to address the so-called "skills shortage" BS in programming. Even worse, the skills that was pushed were also the most automatable: HTML, CSS and especially Javascript just to get $250k roles which was the most unsustainable ZIRP era to happen.
Now you won't see the influencers screaming about web developer roles given the current massive flush in those who joined because of the $$$ just to rearrange a <div> or adding accessiblity styling for 6 figures.
Completely disagree. No matter what job you end up with, you will almost certainly be able to do it a bit better if you know how to code. Knowing how to code is basically always a plus when applying for a job. However "just learn to code a little bit, and nothing else" is probably bad advice.
Just look at what is happening in just the last 5 to 6 months since this prediction was made [0]. The definition of "AGI" was hijacked to mean all sorts of things to the companies that operate the AI systems, even conflicting with each other on timeframes and goals.
But what really is the true definition of "AGI" is the blueprint inside the WEF's Future of Jobs Report 2025 [1] with the deadline of 2030 including mass layoffs which 40% of employers admittedly anticipate reducing their workforce where AI can automate tasks, as I said before [2]
So what AGI actually means is a 10% global unemployment increase by 2030 or 2035 and with all those savings going to the AI companies.
[0] https://news.ycombinator.com/item?id=42490692
[1] https://www.weforum.org/publications/the-future-of-jobs-repo...
I'm not even sure those savings will "go" anywhere, they will just stay with the companies. Right now, if I use my $20/mo ChatGPT subscription to automate away my secretary's job ($3,000/mo or whatever), it's not like those $3,000/mo is going to OpenAI. And I don't think in the future they will be able to jack up prices, because foundational LLM models have become a race to the bottom.
However, the "number go up" crowd doesn't give a fuck about the secretaries -- so they will chant "AI! AI! AI!" to juice the stock and make out like bandits, while they still can.
