I think the bigger issue is skipping the process through which you learn. Personally I learn the most when I am stuck on something for hours trying to figure it out and I miss all of that when AI gives a solution right away.
You get more done without realising you're learning less.
> You get more done without realising you're learning less
Unfortunately, I think many folks now just don't place any value on learning or knowing things because they can "just ask AI".
That's probably my biggest fear with AI is that people just don't see any value to knowing things anymore. And quite ironically, AI is amazing for learning new things.
I'm either not seeing something or I do not see the point of this study.
Amount of "critical thinking" is basically amount of oversight, no? What's interesting is when the amount of oversight is inappropriate, leading to overconfidence in bad results (or, if too much oversight, lack of efficiency).
This paper does not seem to discuss results and correctness at all, ONLY the amount of critical thinking.
Critical thinking is actually something that people exercise (or don't) all the time. It is a skill and practice that is inarguably valuable in all situations. This paper is not about the effects of critical thinking on "AI results", but the exact inverse of that.
Do you value the capacity for critical thinking in yourself? In others? If so, the effect reported by this paper is probably of interest to you.
This paper doesn't say ANYTHING about _capacity_ for critical thinking, and by using the words "critical thinking" yes it makes it sound like "more is better", but look at what they're actually doing. What they're measuring I would much more call "oversight".
If I want to know when Obama was born, and check wikipedia and believe what it says, by their measure I am practicing less critical thinking than if I found independent verification. Independent verification is the main way they measured critical thinking. They are NOT measuring that I thought about how much I could trust the result, and decided that yes I could.
And, well, yes, they're right. But for most purposes, wikipedia is pretty credible for something like that, and it's just a waste of time to follow up on it. What's important is that my calibration is correct.
I'm not even saying I disagree with the idea that there is likely a problem here, with people offloading thinking. But I'm thinking critically about this particular study, which seems totally useless.
Personally, I've done more critical thinking in the past 2 years than the rest of my life combined.
Early LLMs spit out easily identifiable nonsense. Now, it's much more subtle, but it's still absolutely everywhere, even with the best models.
You have to constantly be on your toes to detect it. Some people won't, but I suspect that's mostly the people who were never capable of critical thinking anyways. I'd say it's an upgrade if those people blindly trust an AI over some random person on the internet like they did previously.
But ai chats are brilliant places to practice your thinking. It is a like a human with zero ego, so just gives you counterexamples to what you said, without any care to your feelings. It tells you your novel idea was written down by some thinker 100 years ago, and doesn't care about the crestfallen look on your face. You can use this to strengthen your argument, it will tell you when you did, and when you just did the opposite. It doesn't care if you change places and argue from the other side either. Or if you say, I feel like x is true but could this just be my bias from years of y, it argues back.
To try, go and type a weakly argued point into Claude and watch it take you apart. Try these:
People only post on hn for the pathetic dopamine hit of upvotes
Hn comments are getting weaker
James Acaster is the best commedian of the last 200 years.
Your challenge is to turn it into an argument strong enough to not get an instant rejection
I'm pretty sure thinking is practiced by attempting to argue the opposite viewpoint yourself. Here, you're telling me that you "practice" your thinking by having it actually create the argument for you.
I agree that AI is a useful tool, but it's arguably a very easy tool that people can offload their thought process to - which you should not be doing.
AI has an obvious issue with incorporating how happy users are in its responses. It LOVES to "take your argument seriously", push back lightly, and then tell you you are really smart and make amazing points. If you start with an argument out of left field, you will shift the Overton window very easily.
Using AI is similar to delegating a task to another person. Are the brains of all managers atrophied? Some people might think so but really you just learn different skills. Better communication, strategic thinking, etc
"Specifically, higher confidence in GenAI is associated with less critical thinking, while higher self-confidence is associated with more critical thinking." - that's just the Dunning-Kruger effect
In the eyes of the ruling class: it's a feature, not a bug.
If students in the public k-12 system were actually being taught critical thinking, the schools would be the targets of strategic bombing by the US military.
Anecdotally, does this match anyone's actual experience?
Everyone I know who is working closely with LLMs is doing some of the most acute critical thinking of their lives these days.
I'm very skeptical of these kinds of takes; I'm reminded that Socrates railed against books on the basis that they were going to rot the brains of the youth.
I have seen a significant number of excellent engineers just seemingly turn their brain off entirely and resort to just spitting out "but AI said <blah>" or "AI reported <foo> which I found surprising but I didn't analyze or dig into that result whatsoever". So anecdotally, yes, this absolutely matches my experience.
Socrates was worried that books would prevent people from developing their memories, and his prediction was correct. How many people you know use mnemonic devices to remember entire Greek epics (or something equivalent) by heart? Probably very few.
I always compare it to satnav: how many people bother checking maps and figuring out the route to go anywhere nowadays, just punch it into your satnav and hit "Go!". It'll get you there, but when there are unexpected things some people do panic, or even turn into roads that are actually rivers, etc.
Or course "everyone you know" might be doing something different, but AI is offering the same delegation possibilities for critical thinking. Do you think there won't be people who'll do the equivalent of driving into the river when using AI?
One must distinguish people whose lives were spent thinking critically, and then who subsequently adopted LLMs, and those who will grow up with the technology and will never have to think critically to get a program to run. Or do whatever.
Perhaps more skeptical on certain tasks, but in general; no. Instead of reasoning with colleagues it's more common to hear "Claude said I found the best solution to task X" without questioning that. Anecdotally, the dopamine rush of validation is real.
There's people who use it as a tool, and there's people who use it as a brain surrogate. Most of the people using it as the latter aren't people who were deep thinkers to begin with.
I think the problem with these sorts of studies is that the industry is moving so fast, and by the time your paper gets peer reviewed and published it is no longer relevant.
In this paper, the participants are using mostly ChatGPT - well, there's a HUGE difference in free chatGPT, gpt 6, gpt 4o, gpt 3.5?
What might have been the case for say, GPT 4, is probably no longer the case with GPT 6.
My experience with Google's gemini right now makes this obvious, as I run out of Gemini 4 Astra in a conversation, and then it switches me to Gemini flash lite.
On a micro scale, yes I see this regularly at work: some devs blindly put up ai generated PRs that are fundamentally flawed or don’t actually complete the work in the ticket. It’s often trivial to check this. Similarly some tickets are written by ai that make incorrect assumptions about our product, resulting in nonsensical requirements.
You could argue that these are just examples of laziness, but I think these are both tasks that require critical thinking, and it’s easier to hand them off to an llm that at least purports to do this for you.
I’d argue that both setting requirements, and self code review are both things that need careful attention. (What _exactly_ do you need doing? Does your work correctly do the thing that needs doing?).
I have no fundamental issue with using ai, but there’s no doubt that applying critical thinking to both these tasks directly, and to the broader question of “should I use ai for this job” should result in a different outcome.
Personally I would also not agree with your take that working with llms has allowed me to do “acute critical thinking”. It’s sped up my development time, sure, but I would argue that my evaluation of, say a new sdk now using Claude is far less detailed than it would’ve been in the past when I did it by reading docs. As a side note, I’ve been rereading Douglas Hofstadter’s GEB recently in paperback, and I’ve found a lot of joy in wrestling with paragraphs and writing notes in the margins. This is way more focussed attention than I really give anything when working with llms.
You get more done without realising you're learning less.
Unfortunately, I think many folks now just don't place any value on learning or knowing things because they can "just ask AI".
That's probably my biggest fear with AI is that people just don't see any value to knowing things anymore. And quite ironically, AI is amazing for learning new things.
Amount of "critical thinking" is basically amount of oversight, no? What's interesting is when the amount of oversight is inappropriate, leading to overconfidence in bad results (or, if too much oversight, lack of efficiency).
This paper does not seem to discuss results and correctness at all, ONLY the amount of critical thinking.
Critical thinking is actually something that people exercise (or don't) all the time. It is a skill and practice that is inarguably valuable in all situations. This paper is not about the effects of critical thinking on "AI results", but the exact inverse of that.
Do you value the capacity for critical thinking in yourself? In others? If so, the effect reported by this paper is probably of interest to you.
If I want to know when Obama was born, and check wikipedia and believe what it says, by their measure I am practicing less critical thinking than if I found independent verification. Independent verification is the main way they measured critical thinking. They are NOT measuring that I thought about how much I could trust the result, and decided that yes I could.
And, well, yes, they're right. But for most purposes, wikipedia is pretty credible for something like that, and it's just a waste of time to follow up on it. What's important is that my calibration is correct.
I'm not even saying I disagree with the idea that there is likely a problem here, with people offloading thinking. But I'm thinking critically about this particular study, which seems totally useless.
Regardless, confidence in oneself is hardly measured, self report is likely as good as it gets.
Now that it can be outsourced,we will slowly lose this ability that we barely had.
Early LLMs spit out easily identifiable nonsense. Now, it's much more subtle, but it's still absolutely everywhere, even with the best models.
You have to constantly be on your toes to detect it. Some people won't, but I suspect that's mostly the people who were never capable of critical thinking anyways. I'd say it's an upgrade if those people blindly trust an AI over some random person on the internet like they did previously.
and here is a direct link to the pdf without all the rigamarole:
https://www.microsoft.com/en-us/research/wp-content/uploads/...
To try, go and type a weakly argued point into Claude and watch it take you apart. Try these:
People only post on hn for the pathetic dopamine hit of upvotes
Hn comments are getting weaker
James Acaster is the best commedian of the last 200 years.
Your challenge is to turn it into an argument strong enough to not get an instant rejection
I agree that AI is a useful tool, but it's arguably a very easy tool that people can offload their thought process to - which you should not be doing.
AI has an obvious issue with incorporating how happy users are in its responses. It LOVES to "take your argument seriously", push back lightly, and then tell you you are really smart and make amazing points. If you start with an argument out of left field, you will shift the Overton window very easily.
https://www.rxjourney.net/how-artificial-intelligence-ai-is-...
If students in the public k-12 system were actually being taught critical thinking, the schools would be the targets of strategic bombing by the US military.
Everyone I know who is working closely with LLMs is doing some of the most acute critical thinking of their lives these days.
I'm very skeptical of these kinds of takes; I'm reminded that Socrates railed against books on the basis that they were going to rot the brains of the youth.
Or course "everyone you know" might be doing something different, but AI is offering the same delegation possibilities for critical thinking. Do you think there won't be people who'll do the equivalent of driving into the river when using AI?
Yes. In contrast to you, I really think many of my coworkers seem to get dumber by the day. Not all of them yet, fortunately, but many.
Geometry existed for centuries before Euclid's formalization. Similar for algebra before Al'Khwarizmi. People were using logic before Boole.
"External Intelligence" is not new. But we are still in the informal stage of LLM use.
I think the problem with these sorts of studies is that the industry is moving so fast, and by the time your paper gets peer reviewed and published it is no longer relevant.
In this paper, the participants are using mostly ChatGPT - well, there's a HUGE difference in free chatGPT, gpt 6, gpt 4o, gpt 3.5?
What might have been the case for say, GPT 4, is probably no longer the case with GPT 6.
My experience with Google's gemini right now makes this obvious, as I run out of Gemini 4 Astra in a conversation, and then it switches me to Gemini flash lite.
You could argue that these are just examples of laziness, but I think these are both tasks that require critical thinking, and it’s easier to hand them off to an llm that at least purports to do this for you.
I’d argue that both setting requirements, and self code review are both things that need careful attention. (What _exactly_ do you need doing? Does your work correctly do the thing that needs doing?).
I have no fundamental issue with using ai, but there’s no doubt that applying critical thinking to both these tasks directly, and to the broader question of “should I use ai for this job” should result in a different outcome.
Personally I would also not agree with your take that working with llms has allowed me to do “acute critical thinking”. It’s sped up my development time, sure, but I would argue that my evaluation of, say a new sdk now using Claude is far less detailed than it would’ve been in the past when I did it by reading docs. As a side note, I’ve been rereading Douglas Hofstadter’s GEB recently in paperback, and I’ve found a lot of joy in wrestling with paragraphs and writing notes in the margins. This is way more focussed attention than I really give anything when working with llms.
According to them.