The ongoing AI apocalypse is hitting prices for high-end components from RAM to GPUs to storage hard, which is bad enough when you have a job to try and budget for those now-pricier items — but what if you don’t? Once upon a time, it might have been good advice to tell a jobless friend to “learn to code,” but is that still true in the era of AI? [Brian Jenney], writing for IEEE Spectrum, says the death of the CS degree has been vastly exaggerated, but your take might differ. Let’s look at the numbers.
Unemployment is higher amongst new Computer Science grads than ever: in the US, it’s at 6.1%, while 7.5% of Computer Engineering graduates are on the dole. That’s a record high, and while various EU countries have their own numbers, they all have one thing in common: they’ve all shot up like a rocket in the past few years. In the USA, Philosophy grads report only 3% unemployment. Let that sink in: the folks you used to bully as being the most useless on campus are twice as likely to get a job as you would be if you were in school today.
Granted, one of the ways future BAs were bullied when we were on campus was with photocopies of job applications to McDonald’s, and [Brian] points out that that is a big part of the discrepancy in the USA: Philosophers are far more willing to accept underemployment — that is, to work at a job that doesn’t require their degree-designated skills. Recent graduates in the USA are, on average, underemployed at a rate of 42% — clearly a sign of a highly efficient free market system in action — while CS grads who have jobs are only underemployed 20% of the time. To pick CS today is to halve your chance of getting a job, in order to double your chance of getting a good one.
So, is the lesson to be more like the dude who never shut up about Nietzsche and go flip burgers? Maybe as a temporary measure; more realistically, [Brian] offers some advice for new grads to keep themselves out of that unlucky 6%. Unfortunately, it’s all the sort of common sense they should have already heard dozens of times by graduation: cultivate a network, since most want ads are fake; create your own, non-job experience to polish and demonstrate your skills — we hear projects submitted to Hackaday are great for this — and make sure you’re building the skills that are in demand right now.
To [Brian], that doesn’t mean you should learn to code really well without the help of LLMs; nor does it mean embracing the vibe. It means really understanding the black box that we call AI and the workflows that can leverage its strengths. Like it or not, “AI” is the boom right now, and that’s where the startup jobs are, which is, of course, another tip — find a startup. If the company just started, they have to be hiring, right?
“the folks you used to bully as being the most useless on campus are twice as likely to get a job as you would be if you were in school today.”
3.3% More likely, according to the numbers given.
A CS major with poor math skills would be very unlikely to get a job
You really do need to learn to code well without the help of LLMs. That’s the only way you’re going to distinguish yourself from other candidates. Why would someone hire you if you don’t know how to do anything better than the coding assistant?
Maybe this article needs some processing by AI to make it more understandable. It looks like stock exchange reports: this is high and that is bearish and anyway nobody knows where the values will be tomorrow. What is DOA, department of agriculture?
And the math is a bit off, which AI tends to botch surprisingly often: 7% unemployment would mean 93% employment.
DOA stands for “Dead on Arrival”, which I would have guessed is used a lot more than the US-specific “Department of Agriculture”.
I think you should at the same moment also look at some statistics about the numbers of people who recently finished their CS degree – those numbers are also up.
My take on this is that more people chose to pursue a CS degree some years ago, probably because of the previously good payment and chances of employment. But this also means that there are most probably now more among them who aren’t really that passionate about CS and for whom this job isn’t that good of a fit. Those might finish their degree, but job interviews, live coding sessions and the like will filter them out.
At least in my company we had a rising number of applicants that have good grades on paper, but are useless at solving practical CS tasks, with help of AI or without.
This is nothing new. Since the dot com era, cs has been a ‘get rich’ target, rather than a destiny. We have suffered as a result.
One thing I can tell you about Microsoft’s across-the-board layoffs, is not that “they are replacing CS majors with AI” (okay, maybe they are doing that TOO), but it’s more that they currently need so much cash to build CoPilot AI data centers to MEET DEMAND, that they were looking absolutely everywhere for cost savings. This included giving severance packages even to high performing, 20 year veteran employees.
Hmm… Brian Jenney (the source author) gets referred to as both [Brian] and [Bryan].
Whoopsie doosie.
Fixed.
I didn’t RTFA but it sounds like the best MO is for CS is to CYA by being an ENTJ.
Don’t learn coding, learn actual software engineering.
That is unfortunately also what is most likely not well covered by computer science degrees.
You need to learn how to build software, how to architect it, what makes sense, what does not make sense. These are all decisions which only humans can do, not an LLM.
The writing of the code is in itself is cheap. That is now a mostly automatable skill. But doing this is right is not.
That doesn’t mean that classes on the data structures or algorithms are useless. Absolutely not.
What you will not need is another implementation of a stack or to invert another tree. Most likely that the machine can do it for you now.
But you still will need to understand what a tree even is and what are the complex complexity limits and things like that. And mainly you need to understand when to use which data structure in which context and for what purpose.
The weirdest thing about this story was learning that Computer Engineers have less luck in the market right now than Computer Scientists. I would have thought a degree with “engineering” in the name would give you those skills and make you more desirable, but I guess not.
In addition, the hard part of software design is integration:
Module-A works, has a great feature set, and is based on a loose interpretation of the previous standard. Module-B works, has features module-A doesn’t, and is based on a strict interpretation of the current standard. They can interact without problems about 95% of the time.. the remaining 5% is a bog of edge cases.
Then there are leaky abstraction problems:
There are a thousand ways to represent any kind of data, and in theory they all support the same operations. But some will scale to large data sets easily because they have good data locality, while others will slow down because the system has to swap pages in and out of memory. Some can be broken into parallel operations easily, while others have bottlenecks where they need to be serialized. Some make adding a new feature easy, while others make the same feature nearly impossible:
https://imgs.xkcd.com/comics/tasks.png
From what I’ve seen, vibe coding and agentic tools have automated the creation of systems barely on the functional side of a Big Ball of Mud. We haven’t seen them collapse when faced with evolving or maintaining software — yet — because they’re still too new.
A 94% chance of being employed is not half of a 97% chance of employment. Your analysis of the numbers is not only wrong, it’s so wrong you should be ashamed to post this column.
“Recent graduates in the USA are, on average, underemployed at a rate of 42% — clearly a sign of a highly efficient free market system in action”
Seriously? you think colleges in the USA are a “free market system”? They are, by and large, not. They take huge subsidies from all over the place, and as everyone knows, subsidies for me are taxes for thee. This is reflected in the skyrocketing levels of administrative staff (non-teachers) that gather around the trough of free money, with little to no incentive to deliver actual useful learning. Snark aside, the 42% underemployment rate actually is a sign of an efficient free market system – the market knows what those graduates are worth.
I do wish you had put that comment nearer the top though, so I could know to ignore the whole article.
I would have thought that statement so farcical no one would miss the sarcasm, but I was wrong as usual. My bad.
For the record, it was sarcasm. If anyone actually thinks higher ed in the US– or anywhere in the world– operates on free market principals, I hope they get in touch because I have a bridge to sell them.
Dont worry mate, some of us did appreciate the sarcasm !!!!
Maybe we’re holding it wrong?
https://youtu.be/y72rKtx08vo
CS, as a recent degree is DOA for reasons other than LLMs. One of my degrees is CS. I was required to write a compiler. Write a relational database. Write actual systems in assembly. Learn Linear Algebra, Discrete Math, Physics, and Chemistry. Write coherently and correctly (did not do so well on the latter) and be well-read within the context of English literature. Much of this is no longer in a recent grad’s intellectual tool-kit; and it is obvious.
You want a legit STEM education that more likely to screen out the wannabe and fiscal pretender? Then complete an ABET-accredited undergrad program for an engineering degree. Go work in industry for a few years, then go back to school for a MS CS program.
Anecdotal story from the 1950’s:
“CIO President Walter Reuther was being shown through the Ford Motor plant in Cleveland recently.
A company official proudly pointed to some new automatically controlled machines and asked Reuther: “How are you going to collect union dues from these guys?”
Reuther replied: “How are you going to get them to buy Fords?””
Of consideration, vibe coding still requires technical proficiency bc no LLM model can simply output a running program over a given level of complexity. If people stop learning ide, compilation, etc, then vibe coding dies along with CS. If anything I hope devs reject this and opt for more traditional/biological approaches against the AI hype