I don't know if this is a good framing. "Too much" is subjective, and every heavy AI user will assert that they're just unlocking their potential, that calculators didn't make us dumber, etc.
But to latch onto the calculator argument: if you outsource adding numbers to a calculator, you're still you. On the flip side, if you use an LLM do most of your thinking, what's left? We have people here who use LLMs to raise their children, to manage relationships, to design products. So what's your unique contribution to this world - is it the prompt you once wrote? You're standing in front of a machine, pulling a lever and sometimes receiving gifts. Is that your edge, your unique experience, your purpose in life?
Many LLM maximalists say they use the tech to learn new things, but to what effect? If we're being honest, are you going to apply that knowledge of physics or computer science yourself, or will you just prompt the LLM again?
In my mind, it's pretty simple: I'm a human, LLMs are not. If a human writes a novel, it's inherently worth more. I want to support that. And I want to be a human who can write novels, the old-fashioned way. I'm not good at lifting weights or running, so my thinking is the only thing I have.
I know that the common refrain is “think of yourself as a manager now” but I’ve actually taken the opposite approach and have been telling anyone I train the same.
Diving deeper into technical understanding makes more sense to me at this point both as a way to make yourself more useful in the age of AI and also to use AI more effectively.
I regularly tell the kids to grab a text book on a subject that interests them and I do the same.
I’m willing to bet deep understanding is going to become a commodity soon.
It is easier than ever to learn difficult concepts. It is also easier than ever to produce things that used to require understanding of those concepts without them. Discipline and drive to use these powerful new tools patiently and with purpose is what is required.
I too give juniors the advice to crack open $textbook. It’s just painful to see the complex things they’ve created with horrible performance and no cohesive data model because they don’t have the requisite academic foundation to hand code the same thing given unlimited time
This is exactly the lens I use myself. I write AI software and I use it in my development process, but I try to use the AI to do things that don't remove my agency, but extend my capabilities:
- Debug things. It knows way more than I do in many areas and it sees things I will miss. If I'm struggling to find the answer, maybe it will succeed.
- Review things. It has a wealth of experience I couldn't possibly have. Ask it to critique my work and provide an alternative perspective that I can't provide myself
- Implement a design. I have already gone through the thoughtful engineering to decide what to do and how to do it. The rest amounts to translating pseudocode to the programming language. Let it type what I would have typed anyway and save me the hassle of typos, looking up function and parameter names, and other such mechanical details. Let me use that time and mental effort to better consider my design, try more alternatives, or build more things, providing more value overall.
- Suggest ideas. Even as a 20 year professional, there are things I don't know or haven't considered. Is there a newer, faster, or more maintainable way of doing this? Is what I wrote clear to anyone other than myself? Before AI, I would ask coworkers, search the web, or reference other sources. Now I can get an immediate suggestion from something with tremendous knowledge at almost no cost. It's full up to be to consider what it suggests, further explore the used and learn about them - I don't take the AI at its word and let it decide what is best for me. But I do use it to gain perspective and explore alternatives.
There are some common traits about the thighs I use AI for. They are this that I either couldn't possibly do myself (because I'm biased, or unfamiliar, or have no access to the expertise) or that I would spend a lot of time while having little agency (mechanical translation). I am not replacing learning, thinking, or deciding. I think this is the key difference.
> What are we automating? Human work or human agency? Human tasks or human thinking?
I find it's so easy to convince oneself they're doing the former when it's increasingly the latter. The thinking part is so often provided by default by the models, or is a single prompt away. The thoughts are so syntactically (though not stylistically) perfect that it's difficult to ignore them and reason greenfield.
What's the solution? Given how keen models are to short-circuit the thinking process it could be the only solution is to silo off tasks/ideas. Choosing which mental tasks to silo off is itself incredibly difficult especially when there's a pressure to deliver rapidly (and in quantity) on those tasks.
When I use a calculator, I atleast try to get with in a few digits of what I think the anwser is in my head. Mostly since when I was younger I had a very passionate teacher about how much slower everyone is now because of calculators on simple math. I just apply the same thing with LLMs, just try and think of how and what I would have said and see how close I was. Only thing I change is I don't trust the anwsers and accept some nuance in the given context. It's a double edge sword because then I crash out over it more than if I don't. When it over and under explaining the wrong sections or when it gets to an objectively terrible solution that technically anwsers the question. It feels like a student trying to get brownie points and/or give fluffed anwsers for the sake of not leaving anything blank on a test.
OT, but if we made kids learning math use log tables and slide rules for all their calculations I expect that they would engage their brains more and actually think about what they were doing, ie: form a strategy to solve a problem before they started calculating. Also I think that they would get a better "feel" for working numbers in general. I have no evidence, but I suspect that by abstracting away a lot of the "gruntwork" of calculating, we've really hampered people's development in math.
Unfortunately this adds quite a bit of overhead and would make everything take a lot more time. It might be worth it though.
We had Mental Math sessions in class. The goal was to teach you how to do math without pen/paper, calculators were not even an option. I try to teach some of this to my 6 y o.
> The goal was to teach you how to do math without pen/paper, calculators were not even an option. I try to teach some of this to my 6 y o.
It works quite well. I do the math lessons during bath-time daily with my 6 yo. He's up to the point were he can add multiply pretty much any number by 2, 3 or 4 as long as the product is under 3 digits.
Going from adding single digits to multiplication of random 2-digit numbers by 4 with lessons only during bath-time (no paper or whiteboard) gives a child a great deal of confidence with numbers.
The question presumes that most of us are "thinking" in the first place, when in actuality, most of us are just acting according to the patterns that have emerged from our encounters with the thoughts of others. We generally adopt them and/or try to hallucinate coherence when they conflict. Very few people actually "think". It's hard work and takes time. We neither have (take) the time nor are we particularly motivated to put in the work because the patterns we have learned from others are useful enough to achieve the low goals we set for ourselves.
IOW - modern AI is simply an extension of the lack of thinking that characterizes the modern life... It just does it faster and uses a hulluva lot more energy.
This is such a strange perspective to me. I wouldn't describe anybody I know in this way. Do you not engage in thoughtful conversation with the people you meet? Do you not know people who make art as a hobby? When techies propound such a dim view of humanity, I truly fear for our species. Your wealthy employer will not shed a tear when destruction visits you.
I don't think modernity caused any sort of degradation.
You said it yourself, "thinking is hard work". It's rational to save energy. This might even have incentivized the emergence of mimesis in humans, which is arguably the foundation of our ability to cooperate at large scale.
Maybe a few of us do the hard work of thinking, and, if we figure out something novel and useful, huge numbers of people ape us uncritically. It's not an inspiring picture of humanity, but it's also not a reason to disparage anyone. More of a fact of life to be dealt with strategically.
Even on Hacker News, when you see debates like 'X technology is good' or 'X technology is bad,' most of it seems to be about identity. And that identity often originates from the community they belong to.
The first identity usually starts with a community or the person who created it. Once the community forms, people under it often forget the original reasons and just accept it as their identity.
This is especially true for technology related issues, because the market share of a technology is directly tied to one's career, which makes it even more prone to becoming an identity issue.
I also do some 'thinking' in certain areas, but most of the time I don't. As my field gets deeper, it becomes harder to allocate cognitive resources to other areas. So in general, most people follow the crowd's opinion, but only maintain deep, thoughtful thinking, including 'taste,' in a few specific technical domains.
The rise of knowledge work made many people far less physically active because moving one's body was no longer a given part of one's job. This led to a lot of people (who assumed sports was exercise on top of one's work, not the only source of exercise) moving very little. This meant we needed to rediscover the importance of exercise as a pillar of health.
I think something similar will happen with knowledge work, where we have to do a lot less cognitive exercise due to AI (as well as the decline of reading and rise of short-form video), which will likely lead to eventual issues and subsequently, a rise in activities designed to replicate the cognitive exercise work used to provide.
Maybe it's a way of perspective. I adore to use AI to actually learn, so I don't feel like I offload thinking. I use AI to do all the research which earlier I did manual through google search. I still make my own decisions, I just let Claude spoon feed me all infos I want and need. Feels great man
Using AI to actually learn is indeed very helpful I've found... I just don't think most people use it for that. I recently wanted to build and train my own (albeit, small and simple 10M param model) and used AI extensively to explain concepts for me, explain lines of code, and generate in depth visuals I can use to get a visual intuitive understanding of what is happening under the hood. I think people who have a natural curiosity to understand the why and how of things benefit immensely from it, but I do admit it is very easy to just offload all thinking to it instead of asking it why something is happening. I could have just asked it to implement the entire model using PyTorch and just ran the CLI command to begin training on some auto-generated dataset, but intentionally struggled through it. Actually learning from it requires intentionality for sure.
Lol, wdym. I like to prompt it that I want evidence, so when there is any new topic where I currently don't know how to tackle it myself, I ask that it does a research and give me evidence. So i can check the sources myself. Like I said, I let it spoon feed me.
When I know upfront how to do anything, I just give all the instructions. But the OPs point was If we offload thinking too much, so that's why I was just thinking about this example when I need thinking - that's usually when I need to learn something new.
This is also now the first thing that I find it truly useful for in a non-coding role: researching how to do things in Azure, which I have not used before.
The post is illustrated by a picture of handwritten notes, like that was supposed to shock the reader or something. I find this aesthetic tiring, and it usually comes from AI-maxxers. To me its saying: look at this quaint relic of the past, bereft of day-to-day utility, replaced by superior technology. Its life is now only as a symbol of a time where people actually used their brains.
I don't think we are offloading thinking to AI. We just started to use it. AI is a tool useful to write text, for a fast searching, for the boring work. Personally I don't take the first answer, I like to challenge, to ask why, to tell it's wrong.
The reality is that most humans do very little actual thinking of their own anyway, and, if you believe that what LLMs produce constitutes a form of intelligence, it does seem "more intelligent" than most humans.
So: is outsourcing thinking a net improvement for a majority of users?
I use several models, daily, and they seem "reasonably conditioned" that they are only input to my thinking and not "my thinking". I correct them constantly; they are wrong (in reasoning/logic, in actual facts) frequently. They are demonstrably "not smarter" than I am. And yet I know many people who can "do more" with them as a "thinking" tool. I can say that "the problem" is they can't spot the errors, but they can't or won't do that in their ordinary lives, either, so, again, is it a net improvement for them?
It really depends on which angle you look at it. Is it purely to meet a business goal? Or is it also for personal growth? I think it's a mix of both, but for me it's always important that I engage mentally with the process, learn something, and solve puzzles, even if that involves letting the AI take care of the coding, which is an abstraction. You could still code and not think creatively.
I do feel like I'm offloading thinking to an AI, but I think that's a good thing. I envision a world where users and AI are aligned without corporate interference. AI lets me offload things that I don't need to know and frees up my brain to push farther than I could before. At least that's how it feels to me.
>AI lets me offload things that I don't need to know and frees up my brain to push farther than I could before.
How can you push your brain go farther than ever, when you don't use it for the basic task?
Higher Math does not work without understanding "lower" Math, running long runs does not work without starting on shorter runs. Thinking about complicated staff will probly not work, if you can't think about the easy stuff.
One can not learn a language without vocabulary and skipping learning verbs in a foreign language, because dictionaries exists does not bring one closer to being able to speak.
I don't think offloading things that you "think" you don't need to know is a realistic thing. Instead this seems like some slippery slope of intellectual degradation where slowly you'll replace more and more parts of the thought process with AI which ends in some rather sad existence.
Is a good thing depending on which ones. And our taste on what to specialize our judgment into varies a lot. One thing I do use as criteria to detect it can be a problem is in lack of understanding and lack of control of the layers that are part of verifications and diagnosing power.
The answer to this question is: Politicians, not you!
Perhaps the question to ask is: who is making all of the final decisions for the things that really matter to you in your life?
No direct democracy, just people deciding for you. You can choose once every four years. Are we surprised of how easily we delegate decisions? May be AI can do it better
I've noticed it when interviewing interns. A surprising number seem unable to think on their feet or solve problems without immediately reaching for chatgpt. I don't necessarily expect you to be able to solve a problem entirely without tools, but you should be able to give me the outline of how to go about something and why you would go that way.
After all, if you are just going to spit out AI, I will just get AI to do your job...
Decisions are special things. One of the golden rules of life is that a person (or entity) making decisions is somehow impacted or otherwise getting feedback on the repercussions of those decisions.
When you cognitively surrender to AI, or to another person (be it a leader/manager, or a subordinate/report), you are asking for trouble.
How much of the thinking is involved in asking the right question, versus coming to the correct answer? I don't have a real answer to that but it does seem to be worth considering.
Personally, I use AI to learn more about Backend Engineering actually, so it's fine for me. Beside I can also use AI to suggest and it's me verifying the idea so that's a no for me
I know people like that - the amount of inane, obsessive and just strange conversations they have with AI is concerning - there's never any actually useful result or information that they get out of these chats.
Furthermore, there are some clearly wrong questions where person asks AI to make some kind of numerical evaluation of some data. And evaluation is done entirely through inference - essentially a hallucination, instead of some one-off python script which can actually give deterministic calculated evaluation. Yet they accept the answer AI gives them.
I’ve found that when I ask AI to do something for me that I know how to do myself - but would rather not spend the time doing - there is a not insignificant chance that the AI will return a subpar result, which I can usually tell rather quickly. Either by glancing at the code, or trying to compile it and getting an error.
This happens frequently enough that it creates a real disincentive for me to use AI for anything that I already know how to do - and use it exclusively for things I don’t know how to do.
It’s deeply frustrating to realize you just wasted 20 minutes posting error messages into Claude when you could’ve just locked in and written it yourself.
Having a very dangerous AI standoff at work, where people are debating wether or not to use a particular connection pooling / threading strategy to fix a production issue, and everyone is unqualified to answer and is instead arguing what their agent said.
They are just straight up admitting they don't know anything, and advocate fiercely for their agent's recommendation.
No one cares, no one tries to stop this behavior. It's seen as good, apparently. I admitted that I don't know enough to have an opinion at the moment, I certainly don't know how to judge the contradictory opinions of multiple frontier AIs, and I fear that just made me look incompetent.
Run both. Benchmark them. Performance is notoriously difficult to predict and much easier to test. If you have a load balancer, run the new strategy on one or two servers and see how their throughput compares to the others.
Exactly! It got so easy nowadays to use AI to setup scenarios since the busy work of writing code/test harnesses and setting things up for the benchmark is done by the machine. Then throw away what does not work.
Some benchmark that would take weeks to plan, code and set up is now hours and days - the time is now spent on the benchmark itself, not on temporary code.
I don't know if this is a good framing. "Too much" is subjective, and every heavy AI user will assert that they're just unlocking their potential, that calculators didn't make us dumber, etc.
But to latch onto the calculator argument: if you outsource adding numbers to a calculator, you're still you. On the flip side, if you use an LLM do most of your thinking, what's left? We have people here who use LLMs to raise their children, to manage relationships, to design products. So what's your unique contribution to this world - is it the prompt you once wrote? You're standing in front of a machine, pulling a lever and sometimes receiving gifts. Is that your edge, your unique experience, your purpose in life?
Many LLM maximalists say they use the tech to learn new things, but to what effect? If we're being honest, are you going to apply that knowledge of physics or computer science yourself, or will you just prompt the LLM again?
In my mind, it's pretty simple: I'm a human, LLMs are not. If a human writes a novel, it's inherently worth more. I want to support that. And I want to be a human who can write novels, the old-fashioned way. I'm not good at lifting weights or running, so my thinking is the only thing I have.
I know that the common refrain is “think of yourself as a manager now” but I’ve actually taken the opposite approach and have been telling anyone I train the same.
Diving deeper into technical understanding makes more sense to me at this point both as a way to make yourself more useful in the age of AI and also to use AI more effectively.
I regularly tell the kids to grab a text book on a subject that interests them and I do the same.
I’m willing to bet deep understanding is going to become a commodity soon.
It is easier than ever to learn difficult concepts. It is also easier than ever to produce things that used to require understanding of those concepts without them. Discipline and drive to use these powerful new tools patiently and with purpose is what is required.
I too give juniors the advice to crack open $textbook. It’s just painful to see the complex things they’ve created with horrible performance and no cohesive data model because they don’t have the requisite academic foundation to hand code the same thing given unlimited time
a commodity is something of low value unless in a large aggregate.
This is exactly the lens I use myself. I write AI software and I use it in my development process, but I try to use the AI to do things that don't remove my agency, but extend my capabilities: - Debug things. It knows way more than I do in many areas and it sees things I will miss. If I'm struggling to find the answer, maybe it will succeed. - Review things. It has a wealth of experience I couldn't possibly have. Ask it to critique my work and provide an alternative perspective that I can't provide myself - Implement a design. I have already gone through the thoughtful engineering to decide what to do and how to do it. The rest amounts to translating pseudocode to the programming language. Let it type what I would have typed anyway and save me the hassle of typos, looking up function and parameter names, and other such mechanical details. Let me use that time and mental effort to better consider my design, try more alternatives, or build more things, providing more value overall. - Suggest ideas. Even as a 20 year professional, there are things I don't know or haven't considered. Is there a newer, faster, or more maintainable way of doing this? Is what I wrote clear to anyone other than myself? Before AI, I would ask coworkers, search the web, or reference other sources. Now I can get an immediate suggestion from something with tremendous knowledge at almost no cost. It's full up to be to consider what it suggests, further explore the used and learn about them - I don't take the AI at its word and let it decide what is best for me. But I do use it to gain perspective and explore alternatives.
There are some common traits about the thighs I use AI for. They are this that I either couldn't possibly do myself (because I'm biased, or unfamiliar, or have no access to the expertise) or that I would spend a lot of time while having little agency (mechanical translation). I am not replacing learning, thinking, or deciding. I think this is the key difference.
> What are we automating? Human work or human agency? Human tasks or human thinking?
I find it's so easy to convince oneself they're doing the former when it's increasingly the latter. The thinking part is so often provided by default by the models, or is a single prompt away. The thoughts are so syntactically (though not stylistically) perfect that it's difficult to ignore them and reason greenfield.
What's the solution? Given how keen models are to short-circuit the thinking process it could be the only solution is to silo off tasks/ideas. Choosing which mental tasks to silo off is itself incredibly difficult especially when there's a pressure to deliver rapidly (and in quantity) on those tasks.
When I use a calculator, I atleast try to get with in a few digits of what I think the anwser is in my head. Mostly since when I was younger I had a very passionate teacher about how much slower everyone is now because of calculators on simple math. I just apply the same thing with LLMs, just try and think of how and what I would have said and see how close I was. Only thing I change is I don't trust the anwsers and accept some nuance in the given context. It's a double edge sword because then I crash out over it more than if I don't. When it over and under explaining the wrong sections or when it gets to an objectively terrible solution that technically anwsers the question. It feels like a student trying to get brownie points and/or give fluffed anwsers for the sake of not leaving anything blank on a test.
OT, but if we made kids learning math use log tables and slide rules for all their calculations I expect that they would engage their brains more and actually think about what they were doing, ie: form a strategy to solve a problem before they started calculating. Also I think that they would get a better "feel" for working numbers in general. I have no evidence, but I suspect that by abstracting away a lot of the "gruntwork" of calculating, we've really hampered people's development in math.
Unfortunately this adds quite a bit of overhead and would make everything take a lot more time. It might be worth it though.
I'm working on this! https://magworld.pw
Looks interesting, I'll give this a listen and a read. :)
We had Mental Math sessions in class. The goal was to teach you how to do math without pen/paper, calculators were not even an option. I try to teach some of this to my 6 y o.
> The goal was to teach you how to do math without pen/paper, calculators were not even an option. I try to teach some of this to my 6 y o.
It works quite well. I do the math lessons during bath-time daily with my 6 yo. He's up to the point were he can add multiply pretty much any number by 2, 3 or 4 as long as the product is under 3 digits.
Going from adding single digits to multiplication of random 2-digit numbers by 4 with lessons only during bath-time (no paper or whiteboard) gives a child a great deal of confidence with numbers.
The question presumes that most of us are "thinking" in the first place, when in actuality, most of us are just acting according to the patterns that have emerged from our encounters with the thoughts of others. We generally adopt them and/or try to hallucinate coherence when they conflict. Very few people actually "think". It's hard work and takes time. We neither have (take) the time nor are we particularly motivated to put in the work because the patterns we have learned from others are useful enough to achieve the low goals we set for ourselves.
IOW - modern AI is simply an extension of the lack of thinking that characterizes the modern life... It just does it faster and uses a hulluva lot more energy.
This is such a strange perspective to me. I wouldn't describe anybody I know in this way. Do you not engage in thoughtful conversation with the people you meet? Do you not know people who make art as a hobby? When techies propound such a dim view of humanity, I truly fear for our species. Your wealthy employer will not shed a tear when destruction visits you.
> the modern life
I don't think modernity caused any sort of degradation.
You said it yourself, "thinking is hard work". It's rational to save energy. This might even have incentivized the emergence of mimesis in humans, which is arguably the foundation of our ability to cooperate at large scale.
https://en.wikipedia.org/wiki/Mimesis
Maybe a few of us do the hard work of thinking, and, if we figure out something novel and useful, huge numbers of people ape us uncritically. It's not an inspiring picture of humanity, but it's also not a reason to disparage anyone. More of a fact of life to be dealt with strategically.
Have you ever read Kurt Vonnegut's Timequake? I think it's very applicable to the average human experience.
I agree with many points.
Even on Hacker News, when you see debates like 'X technology is good' or 'X technology is bad,' most of it seems to be about identity. And that identity often originates from the community they belong to.
The first identity usually starts with a community or the person who created it. Once the community forms, people under it often forget the original reasons and just accept it as their identity.
This is especially true for technology related issues, because the market share of a technology is directly tied to one's career, which makes it even more prone to becoming an identity issue.
I also do some 'thinking' in certain areas, but most of the time I don't. As my field gets deeper, it becomes harder to allocate cognitive resources to other areas. So in general, most people follow the crowd's opinion, but only maintain deep, thoughtful thinking, including 'taste,' in a few specific technical domains.
Everyone is always thinking, just many of us not about what we're doing! Sorry
if we were really thinking then llm wouldn't have been able to compress all knoweldge into few gbs.
everyone is just thinking about how to recall, remix and repeat.
I'm not personally, since I don't use GenAI at all.
Especially given the comments I see here and on other tech and programming forums, I hate the direction things are going.
I still have some hope this will all fade, but the damage done will be worse the longer it goes on, I think.
I think this is absolutely an issue.
The rise of knowledge work made many people far less physically active because moving one's body was no longer a given part of one's job. This led to a lot of people (who assumed sports was exercise on top of one's work, not the only source of exercise) moving very little. This meant we needed to rediscover the importance of exercise as a pillar of health.
I think something similar will happen with knowledge work, where we have to do a lot less cognitive exercise due to AI (as well as the decline of reading and rise of short-form video), which will likely lead to eventual issues and subsequently, a rise in activities designed to replicate the cognitive exercise work used to provide.
Maybe it's a way of perspective. I adore to use AI to actually learn, so I don't feel like I offload thinking. I use AI to do all the research which earlier I did manual through google search. I still make my own decisions, I just let Claude spoon feed me all infos I want and need. Feels great man
Using AI to actually learn is indeed very helpful I've found... I just don't think most people use it for that. I recently wanted to build and train my own (albeit, small and simple 10M param model) and used AI extensively to explain concepts for me, explain lines of code, and generate in depth visuals I can use to get a visual intuitive understanding of what is happening under the hood. I think people who have a natural curiosity to understand the why and how of things benefit immensely from it, but I do admit it is very easy to just offload all thinking to it instead of asking it why something is happening. I could have just asked it to implement the entire model using PyTorch and just ran the CLI command to begin training on some auto-generated dataset, but intentionally struggled through it. Actually learning from it requires intentionality for sure.
It’s just so sycophantic though.
Lol, wdym. I like to prompt it that I want evidence, so when there is any new topic where I currently don't know how to tackle it myself, I ask that it does a research and give me evidence. So i can check the sources myself. Like I said, I let it spoon feed me.
When I know upfront how to do anything, I just give all the instructions. But the OPs point was If we offload thinking too much, so that's why I was just thinking about this example when I need thinking - that's usually when I need to learn something new.
If you build stuff with AI it's different. It's very tempting to defer many (too many?) decisions to AI.
I do daily. So far I am doing fine, not sure what exactly your point is, sorry.
This is also now the first thing that I find it truly useful for in a non-coding role: researching how to do things in Azure, which I have not used before.
The post is illustrated by a picture of handwritten notes, like that was supposed to shock the reader or something. I find this aesthetic tiring, and it usually comes from AI-maxxers. To me its saying: look at this quaint relic of the past, bereft of day-to-day utility, replaced by superior technology. Its life is now only as a symbol of a time where people actually used their brains.
Maybe, let me ask my coding agent what he thinks about this.
I don't think we are offloading thinking to AI. We just started to use it. AI is a tool useful to write text, for a fast searching, for the boring work. Personally I don't take the first answer, I like to challenge, to ask why, to tell it's wrong.
It's a well done and thought-provoking article.
The reality is that most humans do very little actual thinking of their own anyway, and, if you believe that what LLMs produce constitutes a form of intelligence, it does seem "more intelligent" than most humans.
So: is outsourcing thinking a net improvement for a majority of users?
I use several models, daily, and they seem "reasonably conditioned" that they are only input to my thinking and not "my thinking". I correct them constantly; they are wrong (in reasoning/logic, in actual facts) frequently. They are demonstrably "not smarter" than I am. And yet I know many people who can "do more" with them as a "thinking" tool. I can say that "the problem" is they can't spot the errors, but they can't or won't do that in their ordinary lives, either, so, again, is it a net improvement for them?
Interesting times and all that.
You’d lose your ability to interview at a different workplace.
It really depends on which angle you look at it. Is it purely to meet a business goal? Or is it also for personal growth? I think it's a mix of both, but for me it's always important that I engage mentally with the process, learn something, and solve puzzles, even if that involves letting the AI take care of the coding, which is an abstraction. You could still code and not think creatively.
Ironically I just caught myself offloading the thinking about this article to the comment section before I read it
I do feel like I'm offloading thinking to an AI, but I think that's a good thing. I envision a world where users and AI are aligned without corporate interference. AI lets me offload things that I don't need to know and frees up my brain to push farther than I could before. At least that's how it feels to me.
>AI lets me offload things that I don't need to know and frees up my brain to push farther than I could before.
How can you push your brain go farther than ever, when you don't use it for the basic task?
Higher Math does not work without understanding "lower" Math, running long runs does not work without starting on shorter runs. Thinking about complicated staff will probly not work, if you can't think about the easy stuff.
One can not learn a language without vocabulary and skipping learning verbs in a foreign language, because dictionaries exists does not bring one closer to being able to speak.
I don't think offloading things that you "think" you don't need to know is a realistic thing. Instead this seems like some slippery slope of intellectual degradation where slowly you'll replace more and more parts of the thought process with AI which ends in some rather sad existence.
Is a good thing depending on which ones. And our taste on what to specialize our judgment into varies a lot. One thing I do use as criteria to detect it can be a problem is in lack of understanding and lack of control of the layers that are part of verifications and diagnosing power.
The answer to this question is: Politicians, not you!
Perhaps the question to ask is: who is making all of the final decisions for the things that really matter to you in your life?
No direct democracy, just people deciding for you. You can choose once every four years. Are we surprised of how easily we delegate decisions? May be AI can do it better
Some of us are, yes.
I've noticed it when interviewing interns. A surprising number seem unable to think on their feet or solve problems without immediately reaching for chatgpt. I don't necessarily expect you to be able to solve a problem entirely without tools, but you should be able to give me the outline of how to go about something and why you would go that way.
After all, if you are just going to spit out AI, I will just get AI to do your job...
Decisions are special things. One of the golden rules of life is that a person (or entity) making decisions is somehow impacted or otherwise getting feedback on the repercussions of those decisions.
When you cognitively surrender to AI, or to another person (be it a leader/manager, or a subordinate/report), you are asking for trouble.
How much of the thinking is involved in asking the right question, versus coming to the correct answer? I don't have a real answer to that but it does seem to be worth considering.
Personally, I use AI to learn more about Backend Engineering actually, so it's fine for me. Beside I can also use AI to suggest and it's me verifying the idea so that's a no for me
imo no way
But this varies from person to person
Some of us overthink already and offloading to AI just enables us to overthink more in other directions than we would if we didn't have ai
I know people like that - the amount of inane, obsessive and just strange conversations they have with AI is concerning - there's never any actually useful result or information that they get out of these chats.
Furthermore, there are some clearly wrong questions where person asks AI to make some kind of numerical evaluation of some data. And evaluation is done entirely through inference - essentially a hallucination, instead of some one-off python script which can actually give deterministic calculated evaluation. Yet they accept the answer AI gives them.
Honestly, using AI helps me get more done in a day because I can delegate some decision making to it, usually inconsequential stuff.
I like the colonialism conversation.
I’ve found that when I ask AI to do something for me that I know how to do myself - but would rather not spend the time doing - there is a not insignificant chance that the AI will return a subpar result, which I can usually tell rather quickly. Either by glancing at the code, or trying to compile it and getting an error.
This happens frequently enough that it creates a real disincentive for me to use AI for anything that I already know how to do - and use it exclusively for things I don’t know how to do.
It’s deeply frustrating to realize you just wasted 20 minutes posting error messages into Claude when you could’ve just locked in and written it yourself.
Yes
Who is "we"? Is there a mouse in your pocket?
If you offload any of your thinking to AI, you're offloading too much of your thinking to AI.
Offload your execution, not your thinking.
Having a very dangerous AI standoff at work, where people are debating wether or not to use a particular connection pooling / threading strategy to fix a production issue, and everyone is unqualified to answer and is instead arguing what their agent said.
They are just straight up admitting they don't know anything, and advocate fiercely for their agent's recommendation.
No one cares, no one tries to stop this behavior. It's seen as good, apparently. I admitted that I don't know enough to have an opinion at the moment, I certainly don't know how to judge the contradictory opinions of multiple frontier AIs, and I fear that just made me look incompetent.
Run both. Benchmark them. Performance is notoriously difficult to predict and much easier to test. If you have a load balancer, run the new strategy on one or two servers and see how their throughput compares to the others.
Exactly! It got so easy nowadays to use AI to setup scenarios since the busy work of writing code/test harnesses and setting things up for the benchmark is done by the machine. Then throw away what does not work.
Some benchmark that would take weeks to plan, code and set up is now hours and days - the time is now spent on the benchmark itself, not on temporary code.
Seriously its easy to build prototypes with AI and benchmark...
It's not quite as easy to simulate weird behaviors that emerge across clouds and on prem data centers.
honestly sounds like you have too many unqualified employees. best case scenario though, they all come out of this having learned a little bit more.
I liked the ending well said
"we" no. just allows me to think about the stuff that matters.
and work on things that would usually be out of my element.
if you aren't thinking more than ever, you're using ai wrong.
> Side note: his startup is replacing human engineers by capturing their every input and operation, but without their explicit consent.
...huh. It's a "startup", so it's not Meta capturing their employees' inputs. I wonder what it could be.
yes