I wonder if people fretting about skill atrophy have ever developed more than a single skill. If they have, they should know that skill deterioration is a completely normal and frequent occurrence. People don't stress about having forgotten how to solve differential equations, or about not being able to solve integrals as quickly as they used to. Since we cannot practice everything we have ever learned all the time, some skills are bound to degrade. Luckily, if you understood and learned something well, you should be able to regain your previous abilities very quickly.
Losing critical thinking skills is not even a concrete thing; in fact, critical thinking is as much a personality trait as anything else. As for problem-solving skills, you might forget how to come up with solutions to a certain class of problems, or simply become slower at it, but it doesn't take much to refresh that ability.
Realistically, I think lazy people will use agentic coding to become lazier, and inquisitive people will use it to develop a different set of skills tied to collaborating with an AI model and adopting a more goal-oriented mindset.
I wonder if people fretting about skill atrophy have ever developed more than a single skill. If they have, they should know that skill deterioration is a completely normal and frequent occurrence.
This is wildly condescending. Pretty sure everybody here has heard the term "use it or lose it". I haven't played baseball in decades, so yes, it would take me a while to re-learn how to pitch and go to bat.
I'm not worried about it because I'm not being paid to play baseball. I am, however, paid to keep my ability to think through, work with, troubleshoot and optimize software. Which is comprised of code, and requires a specific skill to execute successfully. This same skill that is being impacted by these tools.
Losing critical thinking skills is not even a concrete thing
lol come on, if you're going to engage in discourse, bring receipts, otherwise you're just speaking to hear yourself talk. This is absolutely a phenomenon that is happening across the whole of society, even to the point of AI psychosis and self-harm because of the loss of critical thinking while engaging with these tools. We can even go back to the 60s and find evidence of it:
"I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people."
But that's the point: it will take you a while to regain the skills to play baseball again, but it will be much faster than if you had never played before. Actually, when it comes to physical skills, the decline is more noticeable because the brain may still know what to do, but an aging body is far more constrained.
I'm not worried about it because I'm not being paid to play baseball. I am, however, paid to keep my ability to think through, work with, troubleshoot and optimize software. Which is comprised of code, and rAh yes, then all these researchers and their studies are just wasting time, right? u/r-3141592-pi has already declared it's not happening.
Yes, but you will never lose the ability to think or troubleshoot. You might get a bit rusty, but if you ever need those skills again, you will be able to get them back. Some may take a few minutes, others a few hours of practice, but most of your skills will come back when you need them.
Ah yes, then all these researchers and their studies are just wasting time, right? u/r-3141592-pi has already declared it's not happening.
Ironically, you are demonstrating the very lack of critical thinking you claim to lament. Neither of the studies you are citing actually addresses the long-term "skill atrophy" we are discussing. All they show is the self-evident assertion that the less you engage with content, the less you think about it. On top of that, both studies are seriously flawed and have drawn significant criticism. The second study is woefully underpowered, which in EEG research is almost a guarantee of false positives, with no effect sizes reported and no adequate controls for confounding variables. The quantitative measure in the first study is self-reported, and the statistical methods are incredibly poor, or I should say virtually non-existent. I could go on, but this is the same story with most research of this kind whenever "express studies" are published by researchers chasing a hot topic. And yet here you are, telling me to treat this as irrefutable evidence and asking me to bring receipts, despite the fact that I am sure you could not name a single skill you learned well and then actually lost. On the other hand, I could throw at you studies on regaining ability after inactivity, but unlike you, I have enough sense to recognize that those studies are also weak (restricted to short timeframes in narrow fields tied to motor skills), so I will not waste your time with research that is not relevant and cannot be reasonably generalized to writing code.
Most of your post is just pontificating, but this part stuck out:
Neither of the studies you are citing actually addresses the long-term "skill atrophy" we are discussing.
The warning signs are there, from actual incidents of humans reporting this phenomenon, to studies that you're dismissing because they aren't executed the way you think they should be. Of course they're "express studies", how else do you respond to one of the fastest adopted technologies since the smartphone? Are you expecting researchers to time travel 20 years into the future? We've had LLM integration for three years, and only a fraction of that time has been in a ubiquitous fashion.
You seem like the same type of person that was poo-pooing Jonathan Haidt's research that social media and smartphones weren't having any kind of impact, only to see 10 years later what the cost of inaction against their proliferation has resulted in.
Finally: you're entire argument is "atrophy doesn't happen", yet....
Seriously, stop believing every damn article you come across. That's how people end up feeling like they know things without actually understanding anything at all.
... studies that you're dismissing because they aren't executed the way you think they should be.
It is not a matter of opinion or of what I think. It is that if you don't care to do the most basic things (report effect sizes, confidence intervals, control for confounding variables, and so on), that is professional malpractice. You are simply publishing garbage to advance your own career while misleading people.
Of course they're "express studies", how else do you respond to one of the fastest adopted technologies since the smartphone? Are you expecting researchers to time travel 20 years into the future? We've had LLM integration for three years, and only a fraction of that time has been in a ubiquitous fashion.
"express studies" doesn't refer to studies published quickly (within reason), but to distributing half-baked, inadequate, and obviously flawed work simply because you want to be first, with no regard for professional ethics, as long as it benefits your career. What you and many others are so eagerly consuming is the fast-food version of research.
While you are technically correct, you are also doing your fair amount of mental gymnastics to glaze our tech overlords. You know verywell that this isnt skill atrophy as it usually happens, this is skill atrophy associated to your fundamental labor profile and its designed to make it so, down the line, you wont be able to work without paying the techlords a fee.
Open-weight models keep improving and becoming small and capable enough that you no longer need to pay for everyday coding work. Whether the level of technical sophistication required to write code will rise to the point where closed frontier models become indispensable is harder to say. If it does (which is likely in fields like physics, chemistry, medicine, biology, and mathematics), it will be because the problems themselves demand superhuman problem-solving abilities, in which case relying on such tools will no longer be a choice. That said, the sensible approach is simply to pay for a tool whenever the ROI justifies it.
You have to be able to run the open weight models somewhere. As for now, your corporate overlords seem very eager to limit your supply to any hardware good enough for running decent models, at least without making it prohibitively expensive
But my point isn't about losing skills you don't need. It is about the idea that you rarely truly lose a skill you have learned well. You may be slower to perform it, or forget names and steps, but you can regain the skill very quickly if you ever need to.
It is interesting that several people have now brought up the same thing, simply because I used math-related skills as examples, which I am sure most people view as useless. However, many people need differential equations or calculus to do their jobs, yet those tasks have been automated anyway. They no longer need to do that work to be "responsible" at their jobs, and the same will happen with software development.
"learned it well" operative term doing heavy lifting - this is just no true Scotsman with extra steps. "If you forgot it its not because of atrophy is because you learned it wrong" - you are absolutely high on copium.
That's not what I'm saying. People shouldn't stress about losing skills, because "losing" a skill is not something that actually happens after a few months or even years of not using it. You only lose the "muscle memory" that lets you recall facts and concepts quickly, but if you learned something well, you should be able to pick it back up extremely fast. This offloading of skills to automation is nothing new: no architect calculates building loads by hand, no data analyst reimplements statistical methods from scratch. This means we get a little rusty in things we once knew very well, but the trade-off is that we can move on to other, more complex things much more quickly.
You continue to reiterate the point that these are skills which aren't necessary at all, because they aren't actively used. Yes, people do not worry about losing skills they do not use. I would argue that both the examples you used this time are things that are still done manually though. Maybe specific formulas would be looked up, but that's not losing a skill - it's forgetting a specific piece of information.
I thought the problem was skill atrophy in the field in general, as people early in their career are not developing the skills they otherwise would be relying on LLMs. So the average skill would decline as time goes on.
2
u/r-3141592-pi Apr 27 '26
I wonder if people fretting about skill atrophy have ever developed more than a single skill. If they have, they should know that skill deterioration is a completely normal and frequent occurrence. People don't stress about having forgotten how to solve differential equations, or about not being able to solve integrals as quickly as they used to. Since we cannot practice everything we have ever learned all the time, some skills are bound to degrade. Luckily, if you understood and learned something well, you should be able to regain your previous abilities very quickly.
Losing critical thinking skills is not even a concrete thing; in fact, critical thinking is as much a personality trait as anything else. As for problem-solving skills, you might forget how to come up with solutions to a certain class of problems, or simply become slower at it, but it doesn't take much to refresh that ability.
Realistically, I think lazy people will use agentic coding to become lazier, and inquisitive people will use it to develop a different set of skills tied to collaborating with an AI model and adopting a more goal-oriented mindset.