The Impact of Generative AI on Critical Thinking [pdf]

Indeed. I started using Sonnet for coding only about a month ago. It's been great in that I've finally written scripts I had floating around my brain for years, and very rapidly.

But the feeling of skill atrophy is very real. The other day I needed to write a function that recursively traverses a Python dictionary, making modifications along the way. It's the perfect task to give an LLM. I can easily see that if I always give this task to an LLM, a few years down the road I'll be really slow in writing it on my own, and will fail most coding interviews.

Also, while there is a high in producing a lot in a short amount of time, there is no feeling of satisfaction that you get from programming. And debugging its bugs is as much fun as debugging your coworkers' bugs - except at least with the coworkers you can have a more intelligent conversation on what they were trying to do.

I think this is the primary reason I have difficulty with management: my brain simply doesn't really work out (in the fitness sense) in the cognitive way it is used to, but instead has to track all sorts of problems, many of which are emotional/political. Those problems are often emotional/political and thus not really something I can readily solve by thinking real hard about things.

I think this is a really good analogy. Delegating problems to others is nothing novel or new to human experience.

Perhaps the biggest difference is the lack of feedback AI gives that humans can give: a subordinate can communicate if they feel like their manager is being too hands off. AI never questions management style.

This is a good analogy, and not just because of skills atrophy.

Managers grow the skills needed for their organization. Their team affects them.

A process-oriented team with quality/validation mindset has replaceable roles; the action is in the process. An expert team has people with tremendous skills and discretion doing what needs doing; the action is in selection and incentives. Managers adapt to their team requirements, in ways positive and negative: becoming rule-bound, privileging favorites, etc.

With AI this might be a positive insofar as it forces people to state the issues clearly, identifying relevant context, constraints, objectives, etc.

Agile benefitted software development by changing the granularity of delivery and planning -- essentially, helping people avoid getting lost in planning fantasies.

Similarly, I believe that the winner of the AI-for-development race (copilot et al) will not just produce good code, but build good developers by driving them to state requirements clearly and simply. A good measure here is the number of iterations to complete code.

An anti-pattern here, as with agile, is where planning devolves into exploring and exploring into incremental changes for no real benefit - polishing turds. Again, a good measure is the number of sessions to completion; too many and you know you don't know what you're doing, or the AI cannot grasp the trees for the forest.

> Ie. most managers can't help their team find a hard bug that is causing a massive outage.

Strategy vs tactics. Managers aren't there to teach their reports skills, they hire them because they already have them. They're there to set priorities and overall direction.

What if you use it to handle boring BS work you don't care about and focus on what you actually want to do? I offload my work tasks to GPT and do other stuff during work hours. Play with my dog. Stretch. Paint. Work on other creative projects. I don't give a fuck about work as long as they keep sending me a paycheck. Oh no! My brain is going to atrophy from not manually synthesizing info from this report that no one reads anyway.

Fellow manager, it will do you good to realize that we are not in an "age of AI". Out there it's the age of disinformation.

Yeah, but the calculator analogy is apt. In the past, anyone who went to grade school could answer 6 * 7 off the top of their head, and do basic mental math. We've pretty much lost that.

With that said, I do worry that losing the ability to craft sentences (or code) is more problematic than losing the ability to do mental math.

"The Impact Of Taking A Survey About AI On Answers To A Survey About AI" doesn't have the same ring to it.

[dead]

https://programs.sigchi.org/chi/2025/program/content/189154

https://www.semanticscholar.org/paper/The-Impact-of-Generati...

It really doesn't though. Even when google was at its best, and showed you relevant non-spammy results, a degree of critical thinking was required when sifting through the results, evaluating the credibility of the author, website, etc. Do you fact check everything the AI spits out? The ability for people to critically think is basically gone. That's been trending since before AI, but it's really clear to me at this moment in time how bad it has gotten. It's a laziness of thinking that I don't think was the same with Google.

No, not even close.

Google helps you find things that you process later on with your brain.

With AI your brain shuts off as you offload all thinking to asking questions. And asking questions is not thinking. Answering them is.

Well, that's just a summary of a much, much older paper. Still a relevant paper, but somewhat disingenuous to attribute it to MS researchers.

[1]: https://en.wikipedia.org/wiki/Ironies_of_Automation

Certainly a common enough concern in people critiquing use of ChatGPT here. I'm more worried about "softer" problems, though—morality, values, persuasion, including deciding which of two arguments is more convincing and why.

But these have always been issues that humans commonly struggle with so idk.

> suspect/hope that most employers do not want to see these automatable skills atrophy in their employees, for the sake of long-term efficiency, even if that means a small reduction in short-term efficiency gains from automation.

I wish you were right, but I don't think any industry is realistically trending towards thinking about long term efficiency or sustainability.

Maybe it's just me, but I see the opposite, constantly. Everything is focused on the next quarter, always. Companies want massive short term gains and will trade almost anything for that.

And the whole system is set up to support this behavior, because if you can squeeze enough money to retire out of a company in as short a time as possible, you can be long gone before it implodes

[dead]

This would be a valid POV if there was any solid evidence that LLMs truly increased worker productivity or reliability - at best it is a mixed bag. To stretch the food analogy, it seems like LLMs could be pure corn syrup, without any disease-resistant fruits and unnaturally plump chickens that actually make modern agriculture worthwhile.

Or, since LLMs seem to be addictive, it's like getting rid of the spinach farms and replacing them with opium poppies. (I really hate this tech.)

People pay a fortune and expend endless hours to replace the basic physical activity that used to be a default part of the human experience. Also a huge chunk of the population that doesn't suffers from life-altering metabolic disorders.

Let's... not do that for brainrot.

> Is this any different than saying that nowadays most people in the USA are physically weaker and less able to work on a farm than their predecessors?

Yes, far different, because we can still go to the gym and throw medicine balls around or swing kettle bells and do dead lifts and squats if we want to stay fit.

There is no substitute for exercising our ability to logically construct deterministic, hardened, efficient data flow networks that process specific inputs in specific environments to produce specific changes and outputs.

Maybe I'm the only one who understood the most important factor the eminent Leslie Lamport explained in grisly detail the other day, that, namely, logical thinking is both irreplaceable and essential. I'll add that that nerdiest of skillsets is also withering on the vine.

"Enjoy." --Daniel Tosh

I remain perplexed that everyone is so focused on using LLMs to automate software engineering, when there are language-based professions (like Spanish tutor, in your example) that seem more directly threatened by language models. The only explanation I've heard is that the industry is so excited about reducing spend on software engineering salaries that they're trying to fit a square peg into a round hole, and largely ignoring the square holes.

  the topics are constrained