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.
No no no this is incorrect and conjecture with ZERO evidence behind it.
People ABSOLUTELY place a ton of value on. Learning new things? You yourself JUST called this out but somehow “many folks” don’t place value on learning new things? What’s many? 20? 50? A million? Ten million?
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.
I've recently been trying to write a paper with an application in a field that I'm not an expert at. I gave the LLM agents to analyze the methods, the data, the outputs, plus some explanations from me what I want to say and show, and told it to write a section of the paper. It did. Then I asked like 3-4 more different frontiers to do the same.
They all do.. something[1]. They write visually great looking papers. Even good on a quick read.
But once I try porting their proposed Section ideas into the paper, I notice that for each sentence I either need to do a complete rewrite, or a deep dive into it (plus the literature), to confirm or delete that idea/sentence.
If it were my field, it would be much simpler to just write everything directly, rather than attack every sentence of LLMs. As it's not my field, it's a decent way to understand the nuances and learn, but I get increasingly disillusioned by AI writing skills.
[1]: Old and new Gemini models are too categorical, everything is a breakthrough and a marvel; Sol/Astra gets bogged down with too many details, and "it's X, not Y" garbage. For some reason, it's very defending against potential referee questions which don't add anything to the main idea; Opus 5.5 or Fable are basically the same. Maybe it's their way of anti-hallucination..
You almost have to treat these models as a monkey paw, or a maliciously compliant genie. They grant you your wish, but rarely the way you intended. You must be incredibly diligent, or accept the consequences.
It’s also great for testing your own arguments. I will regularly ask Claude, “Is this factual? What are the strongest criticisms?” about something I am about to say. More often than not, I will at least tweak a comment, or sometimes even realize I am completely wrong before posting publicly.
Authors analyzed ~300 workers doing ~1000 tasks. They collected self-reported measure of using critical thinking [yes/no], and estimate of cognitive effort of doing the task. Authors also measured workers' confidence in themselves doing the task or the AI doing the task.
They found: if someone is confident that AI can do the task, they report using critical thinking less, even though they think the task is easy. When someone is confident in doing the task and in evaluating AI responses, they use critical thinking more, even though they think the task is harder.
I think the paper is saying: low-domain expertise (read: confidence) + unrestricted AI tooling can eliminate the human from the loop. The fallout is better automation or unreliable systems. We need to resolve this ambiguity.
The question is: should low-domain expertise be coupled with more restricted AI tooling as a critical thinking forcing function? Are schools/workplaces right in restricting AI so students/new workers can reach the point of high domain expertise?
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.
Well, I could argue that by inviting a comparison between trusting a single fact from Wikipedia and trusting arbitrary generated output, you are practicing less critical thinking than you otherwise might.
The example's not relevant; the two things are not analogous. Moreover your point only works if one accepts your conclusion that:
Independent verification is the main way they measured critical thinking
And this isn't especially true. All this information was self-reported to begin with. Maybe what you're describing is a pattern in the responses where participants associated verification activities with critical thinking.
But they also reported assessing things about the content, like style/personality, logical soundness, relevance to a topic, or suitability for a specific purpose.
Studies don't need to justify themselves with concrete conclusions; gathering the data for future use is a fine goal.
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
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
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.
See https://arxiv.org/abs/2607.13562. AI tends to make people much more confident in their answers. I worry about this for myself, and therefore try to limit my use of AI to either "getting things done" or idle queries. For developing real thought, I think of it as a very political underling who wants you to think it's valuable.
Depends on the model. I’ve found Gemini to have the most silver tongue and Anthropic models to be the most harsh critics to the point of hilarity.
I’ve been burning spare weekly quota on fringe-adjacent physics. I often copy-paste the LaTeX format “paper” back and forth for “peer review of a friend’s work”.
Gemini: “Your friend’s insight hits the nail right on the head!”
Opus: “Tell your friend to stop wasting his time now, it’s more kind than to keep indulging him.”
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.
"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.
"We surveyed 319 knowledge workers who use GenAI tools (e.g.,
ChatGPT, Copilot) at work at least once per week, to model how
they enact critical thinking when using GenAI tools, and how GenAI
affects their perceived effort of thinking critically. Analysing 936
real-world GenAI tool use examples our participants shared, we
find that knowledge workers engage in critical thinking primarily
to ensure the quality of their work, e.g. by verifying outputs against
external sources. Moreover, while GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term overreliance on the tool and diminished skill
for independent problem-solving. Higher confidence in GenAI’s
ability to perform a task is related to less critical thinking effort.
When using GenAI tools, the effort invested in critical thinking
shifts from information gathering to information verification; from
problem-solving to AI response integration; and from task execution to task stewardship. Knowledge workers face new challenges
in critical thinking as they incorporate GenAI into their knowledge
workflows. To that end, our work suggests that GenAI tools need
to be designed to support knowledge workers’ critical thinking by
addressing their awareness, motivation, and ability barriers."
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.
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.
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?
Who cares? Honestly, there will always be people who use things recklessly. There will always be products designed to encourage people to use things recklessly.
Thing is, it won’t be most people. Won’t even be many.
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.
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.
The problem is that AI is a lot like taking out a loan you can't repay. It gives you money now, only to cause serious problems later.
No no no this is incorrect and conjecture with ZERO evidence behind it.
People ABSOLUTELY place a ton of value on. Learning new things? You yourself JUST called this out but somehow “many folks” don’t place value on learning new things? What’s many? 20? 50? A million? Ten million?
Contemptible suppositions.
lol get real.
Try talking to normies sometime to learn how little they give a shit.
[dead]
People have always been bad at critical thinking, it's a high level cognitive skill that requires practice.
Now that it can be outsourced,we will slowly lose this ability that we barely had.
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.
I've recently been trying to write a paper with an application in a field that I'm not an expert at. I gave the LLM agents to analyze the methods, the data, the outputs, plus some explanations from me what I want to say and show, and told it to write a section of the paper. It did. Then I asked like 3-4 more different frontiers to do the same.
They all do.. something[1]. They write visually great looking papers. Even good on a quick read.
But once I try porting their proposed Section ideas into the paper, I notice that for each sentence I either need to do a complete rewrite, or a deep dive into it (plus the literature), to confirm or delete that idea/sentence.
If it were my field, it would be much simpler to just write everything directly, rather than attack every sentence of LLMs. As it's not my field, it's a decent way to understand the nuances and learn, but I get increasingly disillusioned by AI writing skills.
[1]: Old and new Gemini models are too categorical, everything is a breakthrough and a marvel; Sol/Astra gets bogged down with too many details, and "it's X, not Y" garbage. For some reason, it's very defending against potential referee questions which don't add anything to the main idea; Opus 5.5 or Fable are basically the same. Maybe it's their way of anti-hallucination..
You almost have to treat these models as a monkey paw, or a maliciously compliant genie. They grant you your wish, but rarely the way you intended. You must be incredibly diligent, or accept the consequences.
It’s also great for testing your own arguments. I will regularly ask Claude, “Is this factual? What are the strongest criticisms?” about something I am about to say. More often than not, I will at least tweak a comment, or sometimes even realize I am completely wrong before posting publicly.
This is my takeaway:
Authors analyzed ~300 workers doing ~1000 tasks. They collected self-reported measure of using critical thinking [yes/no], and estimate of cognitive effort of doing the task. Authors also measured workers' confidence in themselves doing the task or the AI doing the task.
They found: if someone is confident that AI can do the task, they report using critical thinking less, even though they think the task is easy. When someone is confident in doing the task and in evaluating AI responses, they use critical thinking more, even though they think the task is harder.
I think the paper is saying: low-domain expertise (read: confidence) + unrestricted AI tooling can eliminate the human from the loop. The fallout is better automation or unreliable systems. We need to resolve this ambiguity.
The question is: should low-domain expertise be coupled with more restricted AI tooling as a critical thinking forcing function? Are schools/workplaces right in restricting AI so students/new workers can reach the point of high domain expertise?
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.
I'm going to assume you're being serious.
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.
Well, I could argue that by inviting a comparison between trusting a single fact from Wikipedia and trusting arbitrary generated output, you are practicing less critical thinking than you otherwise might.
The example's not relevant; the two things are not analogous. Moreover your point only works if one accepts your conclusion that:
And this isn't especially true. All this information was self-reported to begin with. Maybe what you're describing is a pattern in the responses where participants associated verification activities with critical thinking.But they also reported assessing things about the content, like style/personality, logical soundness, relevance to a topic, or suitability for a specific purpose.
Studies don't need to justify themselves with concrete conclusions; gathering the data for future use is a fine goal.
There's often a big gap between self perception and actual performance, I wonder if this actually tracks when measured.
Regardless, confidence in oneself is hardly measured, self report is likely as good as it gets.
(2025)
and here is a direct link to the pdf without all the rigamarole:
https://www.microsoft.com/en-us/research/wp-content/uploads/...
Both added above. Thank you!
I'm beginning to think that AI is just taking Dumbo's magic feather away,
AI atrophies the brain -
https://www.rxjourney.net/how-artificial-intelligence-ai-is-...
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
Have you ever worked with a manager?
Yup. Have you ever been a manager?
AI atrophies the brain if you use it to replace your brain. There's definitely ways to it thoughtfully instead of just having it think for you.
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
Hoo, not been my experience.
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.
Have you tried asking it not to? Claude can be a harsh critic. See the other commenter
See https://arxiv.org/abs/2607.13562. AI tends to make people much more confident in their answers. I worry about this for myself, and therefore try to limit my use of AI to either "getting things done" or idle queries. For developing real thought, I think of it as a very political underling who wants you to think it's valuable.
Depends on the model. I’ve found Gemini to have the most silver tongue and Anthropic models to be the most harsh critics to the point of hilarity.
I’ve been burning spare weekly quota on fringe-adjacent physics. I often copy-paste the LaTeX format “paper” back and forth for “peer review of a friend’s work”.
Gemini: “Your friend’s insight hits the nail right on the head!”
Opus: “Tell your friend to stop wasting his time now, it’s more kind than to keep indulging him.”
Brutal.
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.
"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.
"We surveyed 319 knowledge workers who use GenAI tools (e.g., ChatGPT, Copilot) at work at least once per week, to model how they enact critical thinking when using GenAI tools, and how GenAI affects their perceived effort of thinking critically. Analysing 936 real-world GenAI tool use examples our participants shared, we find that knowledge workers engage in critical thinking primarily to ensure the quality of their work, e.g. by verifying outputs against external sources. Moreover, while GenAI can improve worker efficiency, it can inhibit critical engagement with work and can potentially lead to long-term overreliance on the tool and diminished skill for independent problem-solving. Higher confidence in GenAI’s ability to perform a task is related to less critical thinking effort. When using GenAI tools, the effort invested in critical thinking shifts from information gathering to information verification; from problem-solving to AI response integration; and from task execution to task stewardship. Knowledge workers face new challenges in critical thinking as they incorporate GenAI into their knowledge workflows. To that end, our work suggests that GenAI tools need to be designed to support knowledge workers’ critical thinking by addressing their awareness, motivation, and ability barriers."
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.
[dead]
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.
Sure. And we know that about Socrates because Plato wrote it down.
> Anecdotally, does this match anyone's actual experience?
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.
I think algebra too - it requires less understandng than geometry. You operate at a higher level, and in a sense, don't really know what you're doing.
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.
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.
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?
Who cares? Honestly, there will always be people who use things recklessly. There will always be products designed to encourage people to use things recklessly.
Thing is, it won’t be most people. Won’t even be many.
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.
Looks like the paper is from 2025?
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.
> Everyone I know who is working closely with LLMs is doing some of the most acute critical thinking of their lives these days.
According to them.
According to Claude.
Claude, please read this article for me and tell me what I should think about it.
That's what the comment section is for!
Claude's taking my job as an internet peanut gallery now too?
There goes my $100,000 salary, woe is me.
claude read the comments section and summraize. be concise.
I had ChatGPT summarize these comments and it was surprisingly good. Less personality and more thematic, coherent insight.
"using AI to perform thinking" versus "using AI to stimulate thinking"
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