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.

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.

Most people don't use AI to learn new stuff. They use it to do "the job" for them and they don't even understand the result. What is the point of a person if they don't bring any value to the table other than being a "resource" to generate prompts?

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 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.

I think about it a lot in conversations like this. The story does a much better job of telling it, so I won't summarize more than: It's a discussion about how technology changes culture and how its very hard to judge if that's a good or bad thing.

It's online https://web.archive.org/web/20140222103103/http://subterrane...

As for now, autocomplete is only as good as the training data. Once humanity collectively stop being autonomous beings and generating novel ideas, it all comes to a halt. LLM suggested ideas and preferences are nothing more than some mashup/average of what came before. The ability to actually think may become a rare treasure.

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.

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.

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.

I'm seeing some incredibly dumb stuff: researchers spending months on Claude trying to do insane deduplication, unrelated to their research question, using regex; whole research methodologies YOLO'd out of ChatGPT.

The results invariably chaotic, resulting in huge amounts of stress and wasted time.

Non-technical people are treating LLMs like an oracle, making big assumptions and decisions with little regard for their implications, because their clanker told them to.

It's scary out there. The lack of critical thinking I'm seeing in some of these projects is horrific. Not unique to the post-AI era, certainly, but on a whole new level. Bad things are undoubtedly happening everywhere, right now, because someone's just like "let's ask Claude".

Knowing declarative you need to loop over elements and actually being able to write the for loop as procedural knowledge are two different shoes. I believe that this is the real danger.

Pilots have much automation in the cockpit but the pilot needs simulation hours actually flying not relying on the autopilot.

If you dont write code you will forget/loose much accuracy writing it, its just a matter of time.

I think in the software trade you will definitely use your brain less. But in other trades, it removes the time sucks and gets you back to work.

Whatever creativity/thinking/effort bandwidth that's available will now get shifted to a different place in the problem-solving effort bottleneck.

That's the hallmark of any delegation being effective. Do we see that happening with AI tools? Personally, I do see that working for me. Is it as good as the hype makes it to be or I wish it to be? maybe not, yet, for me. But that's the case with most things in life.

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.

The article takes a position that assumes hallucinations do not occur, and then posits from that stance the question as to whether we rely on AI too much. We should be taking a step back before even asking that question and focusing on the part where AI does invent answers whole-cloth.

For example I send some doc asking for a feedback and someone without reading it generate a feedback with llm with so much ambiguity that I have to get back and wait couple of more days to get a reply.

One of the most silliest thing I see is a middle manager feeding Microsoft planner to Claude to generate a report and generate future steps and sometimes it makes no sense what he present couple of weeks ago because what he present today is contradicting to the one before.

At this point I feel it’s cheaper to replace them with AI. They are just physical vessels for AI.

It’s just not that maybe they were not good enough. But now they just fully depend on AI.

I want certain answers that the docs and the code are not giving me yet. Nothing is more irritating than working through a tutorial on a new framework and then throwing all that work out because that’s not really how one should use the framework. Nothing is more frustrating than having to get through a treatise on why this framework is The Solution before I can actually see code that uses the solution. And it’s beyond annoying when this End All Be All framework has a glaring omission that’s not obvious until you’ve built large amounts of your project on top of it.

Hand the docs and the example code to the LLM, and now I can get answers. “How can I do X?” Example code. “Then I need Z” Modified code. “How is this going to handle Q?” Explanation. “That doesn’t seem quite right. Give me a reference to the doc or code showing this.” Links.

Great, in 15 min, I have learned what I need to know, I can see that this solves a problem that I have, and I have discovered that I need an implementation of S to complement this solution.

That is usefulness. And it requires experience.

Somebody asked an AI how to interpret it.

What is frightening is with something like neuralink that in a future hypothetical time would have very fast capability to keep informed and advised, you could be a zombie decision maker and nobody would really be able to tell. Even when you were pressed to why you made the decision, it's just another AI response, it's like a con artist or imposter dream scenario.

I noticed that atm, before these crazy hypotheticals potentially happen, the people that seem to take the time to understand things deeper are still way more valuable than those that just use tools more than not. Its obvious atm due to the lag in time and the way people respond in meetings, at least for now. :)

It goes like: "Here is this thing I wonder about", and the LLM is like "Yeah sure, consider these things that are super related to what you are doing, that you probably know nothing about yet (but you know... if you are interested...)".

And that goes in any direction, for any depth. Anything that is made trivial now, is just replaced by something more consequential a level or two higher. You can just get much better at things that matter more.

And just like people going to the gym to exercise their otherwise economically useless bodies, same thing will happen with the mind.

Folks, get over it.

I think partially it is because of the amount of data you can get out of an LLM and because it looks pretty good, a lot of people treat it as authoritative.

This means they send it around and then other people have to go through the work of actually validating it before being able to act on it.

So what this really means is that the person you go the information from offloaded their thinking to the AI, while cannibalizing on yours.

I think the analogy to hyper-palatable, calorific food works well:

Humans adapted for a world with too little food. Then once there was too much, obesity and overeating became a problem for the first time. Self discipline is the cost we have to pay for this kind of abundance.

We now have a general-purpose way to offload mental effort, and are discovering in real-time the negative consequences of that.

I use AI for coding, but I feel I've moved past the honey-moon period and am now learning how to use it in a way that is not a detriment. If I care about the work I'm doing I don't want the AI to do it for me, even if it could. Deciding what work I want/should be doing myself vs what can be delegated is a new skill I, and I believe we all need to learn.

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.

It makes me sad, high-level thinking is the one thing that makes humans unique. That we're willing to let that atrophy while giving our power to mega corporations for the sake of convenience is a sad state of affairs. Like, Altman's idea that intelligence will be a "metered utility" should make people terrified! That's a dystopian future. "I can't climb out of poverty because I don't have money to pay the thinking machine"

I do think there's a potential irony in this though. The people screaming loudest about how if you're not using AI you're going to get "left behind"... are probably going to get left behind. Actual skills developed by real learning, I think, are going to become more rare and valuable, not less.

Personally, I'm hoping my side project turns into a business at some point. I can tell you there's a 0% chance I'd hire a vibe coder to work on it. I just don't need that skillset. I would hire professional fiction writers (it's a tool for them), people with technical expertise I lack, etc. The one skillset I do not care about is AI usage expertise, because it's just not valuable.

AI is the current popular way (at least in these circles) and if it's too much or too little it might not matter. What will matter is if this offloading is making people unhappy and having any negative impact in civilization. I have no idea

AI makes me massively more productive as a quant, and more creative in the sense that it can often find calculations I don't know how to start, BUT the flip side of that is that I can also feel my skills atrophy and as such am trying to make sure I do maths exercises and so on. I don't worry about programming skills because programming isn't about code.

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.

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...

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

When you cognitively surrender to AI, or to another person (be it a leader/manager, or a subordinate/report), you are asking for trouble.

these are the people who are now first against the wall when the revolution comes.

why would I want to hire you to work the three hours you feel like working per day (per week?) when I can have AI with a deeper knowledge set available 24x7?

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.

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

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.

Offload your execution, not your thinking.

...huh. It's a "startup", so it's not Meta capturing their employees' inputs. I wonder what it could be.

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.

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.

Most people just wanna enjoy life and then die.

Very few actually get to a position of influence and power to actually do anything. Much of economic activity isn’t critical to life and death - it’s just stuff we have to make life more interesting than past generations.

does a bear shit in the woods?

does rust have the worst community of all time?

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.