If anything, I think most here outsource too little thinking to AI.
What am I supposed to be afraid of? Losing skills I no longer need to get the job done?
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.
Unfortunately this adds quite a bit of overhead and would make everything take a lot more time. It might be worth it though.
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.
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.
The issue being, gratification is rarely a good guideline. It just means collapsing the gap between doing the thing and the idea of having done the thing. But that gap is where you actually learn things
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.
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
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.
...huh. It's a "startup", so it's not Meta capturing their employees' inputs. I wonder what it could be.
Offload your execution, not your thinking.
When you cognitively surrender to AI, or to another person (be it a leader/manager, or a subordinate/report), you are asking for trouble.
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...
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.
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.
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.
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.
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 token-generating machine, pulling a lever, 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? 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 because it's hard-earned and anchored to experiences we share. 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.
You can treat AI as a whispering earring - "What should we do now? How do we fix this? What do you think?" Or you can treat it like an exoskelton - "Implement kd-tree with metric space xyz for this problem, mapping this to that blah blah".
That's pre-thought execution automation that makes review much simpler - you already know the shape of the desired output. The whispering earring is atrophy.
While I appreciate you laying it out so plainly, I disagree. A novel is a bunch of words and I don't care if they were written by one person, five, an AI, or infinite monkeys on typewriters. What's valuable in a novel (or a poem) is in the words.
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.
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
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.
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.
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.
Somebody asked an AI how to interpret it.
In fact, when I use AI, I don't really use it for the things I actually enjoy doing. For example, I like making UI animations, and I don't use AI for that. I also don't use AI when I'm playing games I enjoy. But when I have to make something tedious like a login screen, I use AI. And after I write the code, I just throw the entire codebase at AI to write the documentation.
The problem is that this only lets me think about things I have a taste for.
Having taste and diving deep into it is good. Immersion is great. But on the flip side, you also need to do things that aren't your taste. That's more cognitively healthy. AI prevents that.
In that sense, I think AI's strength is that it creates an environment where you can dive deeper into the areas you like.
But the real question becomes how you use the cognitive surplus that's left after offloading tasks to AI.
I visit Korean, Chinese, Japanese, and USA sites, and honestly, most people, including myself, only have deep thinking about certain topics. Outside of those, we just follow the prevailing opinion.
So I'm not really sure. I don't think using AI makes me stop thinking. I just think it creates a bias that makes my thinking only focus on the parts I want to focus on.
I find I'm not thinking less per say, just thinking about different things. Maybe you could argue there are CEOs who get too far out of touch with the reality on the ground and should get more directly involved in the work. However, I don't know how well one could argue that the CEO should do all of the work.
I see at least the current iteration LLMs and harnesses as me managing and coordinating them and thinking differently, not less.
does a bear shit in the woods?
does rust have the worst community of all time?
Perhaps the only way forward will be if we figure out how to merge with the AIs so we can keep up. Otherwise, a soma-filled world likely awaits. And unlike Brave New World, I think it might actually be a lot more pleasant, but still one with a different set of tradeoffs.
Annoyed, you go find a popular programming chatbot, and ask the question. The chatbot will give you answer, no matter how poorly worded or nonsensical your question, and it will do it cheerfully and confidently. It may even tell you how great your question or idea is. Granted, the answer will be worthless, both because the question was poorly worded and because the chatbot is simply spewing statistically probable text, but you won't know. You're a beginner, without experience to know correct from bullshit. You try to use the answer the chatbot gave you, and when it doesn't work, you go back to the chatbot. It will continue to cheerfully answer your questions as long as you have tokens to spend. The chatbot will never give up on trying to help you, it will never be rude, it won't complain.
And people wonder why chatbots are so popular.
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.
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.
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 just thinking about how to recall, remix and repeat.
It’s bad enough for rational reasoned discourse that we anthropomorphise LLMs, let’s please not then feed those words back into human discourse, further diluting their meaning. No one “hallucinates coherence”, hallucinations are by definition a perception which does not match reality.
> AI is simply an extension of
It may be an extension, but not “simply” as it also creates the problem where it didn’t exist. I’ve seen several reports (both on and offline) of people who used to engage in deep thinking (I’m talking scientists, postgrads, PhDs working at the edge of what we know) now worrying they are losing their ability to properly think due to their LLM use.
> It just does it faster and uses a hulluva lot more energy.
I hope we can agree that’s bad and that we should try to stop and even reverse it, not simply shrug our shoulders and go “ah well, we were already going to shit anyway, might as well fuck everything up faster”.
It's possible to set that latter value to be nonzero. You can't use free markets to set it because they necessarily cannot see what price to set, so you kinda have to guess, but IMO, it isn't zero, and I'd hazard to say it's positive.
ofjcihen•1h ago
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.
allthetime•56m ago
georgeburdell•40m ago
bryanrasmussen•33m ago
therobots927•23m ago
Which means as a human your only added value is on the edge of the distribution. Which means you need to be learning and doing more complex, deep topics.
nurettin•23m ago
demosthanos•23m ago
For myself, I have found that I am better able to learn new topics than ever before because being able to have a conversation with a moderately competent but sometimes catastrophically wrong AI about any new subject is actually the perfect mix of helpful and unhelpful for learning.
I use a loop along these lines:
* Ask a question * Get an answer * Be skeptical of the answer * Investigate/reason about the answer * Critique the answer * Rinse and repeat
This kind of loop is far more useful to me than any textbook ever has been, because a textbook just drips information into my head. It's more likely to be accurate, but not guaranteed, and it doesn't encourage me to actually engage with the material in the way that a wrong AI answer does.
ofjcihen•18m ago
dspillett•8m ago
One of the many reasons I'm determined to remain a luddite wrt AI. I hate the idea of being a manager and have refused promotions to avoid it in the past. I don't want to manage automatons any more than I want to manage people. I want to do stuff, not manage.
geraneum•5m ago
How does the text generated by LLM make “our” understanding deeper compared to text written in the books?