The author says it's too long. So let's tighten it up.<p><i>A criticism of the use of large language models (LLMs) is that it can deprive us of cognitive skills.
Are some kinds of use are better than others? Andy Masley's blog says "thinking often leads to more things to think about", so we shouldn't worry about letting machines do the thinking for us — we will be able to think about other things.</i><p><i>My aim is not to refute all his arguments, but to highlight issues with "outsourcing thinking".</i><p><i>Masley writes that it's "bad to outsource your cognition when it:"</i><p>- <i>Builds tacit knowledge you'll need in future.</i><p>- <i>Is an expression of care for someone else.</i><p>- <i>Is a valuable experience on its own.</i><p>- <i>Is deceptive to fake.</i><p>- <i>Is focused in a problem that is deathly important to get right, and where you don't totally trust who you're outsourcing it to.</i><p><i>How we choose to use chatbots is about how we want our lives and society to be.</i><p>That's what he has to say. Plus some examples, which help make the message concrete. It's a useful article if edited properly.
I think that this summary is oversimplifying: The rest of the blog post elaborates on how the author and Masley has a completely different interpretation of that bullet point list. The rest of the text is not only examples; it provides elaborations of what thought processes led him to his conclusions. I found the nuancing of the two opposing interpretations, not the conclusion, the most enjoyable part of the post.<p>(This comment could also be shortened to “that’s oversimplifying”. I think my longer version is both more convincing and enjoyable.)
I feel like your comment is in itself a great analogy for the "beware of using LLMs in human communication" argument. LLMs are in the end statistical models that regress to the mean, so they by design flatten out our communication, much like a reductionist summary does. I care about the nuance that we lose when communicating through "LLM filters", but others dont apparently.<p>That makes for a tough discussion unfortunately. I see a lot of value lost by having LLMs in email clients, and I dont observe the benefit; LLMs are a net time sink because I have to rewrite its output myself anyway. Proponents seem to not see any value loss, and they do observe an efficiency gain.<p>I am curious to see how the free market will value LLM communication. Will the lower quality, higher quantity be a net positive for job seekers sending applications or sales teams nursing leads? The way I see it either we end up in a world where eg job matching is almost completely automated, or we find an effective enough AI spam filter and we will be effectively back to square one. I hope it will be the latter, because agents negotiating job positions is bound to create more inequality, with all jobs getting filled by applicants hiring the most expensive agent.<p>Either way, so much compute and human capital will go wasted.
> Proponents seem to not see any value loss, and they do observe an efficiency gain.<p>You get to start by dumping your raw unfiltered emotions into the text box and have the AI clean it up for you.<p>If you're in customer support, and have to deal with dumbasses all day long who are too stupid to read the fucking instructions. I imagine being able to type that out, and then have the AI remove profanity and not insult customers to be rather cathartic. Then, substitute "read the manual" for an actually complicated to explain thing.
I don’t understand this summary - isn’t this a summary of the authors recitation of Masleys position? It’s missing the part that actually matters, the authors position and how it differs from Masley?
This here is why I always read the comments /first/ on HN
Ever since Google experimented LLM in Gmail it bothers me alot. I firmly believe every word and the way you put them together portrays who you are. Using LLM for direct communication is harmful to human connections.
It can be. It can also not be. A friend of mine had a PITA boss. Thanks to ChatGPT he salvaged his relationship with him even though he hated working with him.<p>He went on to something else but his stress levels went way down.<p>All this is to say: I agree with you if the human connection is in good faith. If it isn’t then LLMs are helpful sometimes.
<a href="https://en.wikipedia.org/wiki/NPC_(meme)" rel="nofollow">https://en.wikipedia.org/wiki/NPC_(meme)</a>
This comment has made me glad for LLM in Gmail. If someone is going to over analyze my every word because he firmly believes it portrays who I am, I'd appreciate the layer obfuscation between me and this creepazoid.
If your words don’t portray who you are, what does?
People make mistakes in the words they use, I often think “oops, I shouldn’t have said it like that”.
Actions? I generally judge people by what they do, not what they say - though of course I have to admit that saying things does fall under "doing something", if it's impactful.
Assuming you did not use an LLM to craft your comment, I’d say “case in point”.
What I am worried about (and it's something about regular internet search that has worried me for the past ~10 years or so) is that, after they've trained a generation of folks to rely on this tech, they're going to start inserting things into the training data (or whatever the method would be) to bias it towards favoring certain agendas wrt the information it presents to the users in response to their queries.
> after they've trained a generation of folks to rely on this tech ... bias it towards favoring certain agendas<p>previously, this happened with print media. Then it happened with the airwaves. It only makes logical sense that the trend continues with LLMs.<p>Basically, the fundamental issue is that the source of information is under someone else's control, and that someone will always have an agenda.<p>But with LLMs, it's crucial to try change the trend. IMHO, it should be possible for a regular person to own their computing - this should include the LLM capability/hardware, as well as the model(s). Without such capabilities, the exact same will happen as has in the past with new technologies.
I worried about this a lot more at the tail end of 2003, when OpenAI's GPT-4 (since March) was still very clearly ahead of every other model. It briefly looked like control of the most useful model would stay with a single organization, giving them outsized influence in how LLMs shape human society.<p>I don't worry about that any more because there's so much competition: dozens of organizations now produce usable LLMs and the "best" is no longer static. We have frontier models from the USA, France (Mistral) and China now.<p>The risk of a model monopoly centralizing cultural power feels a lot lower now then it did a couple of years ago.
Model competition does nothing to address monopoly consolidation of compute. If you have control over compute, you can exert control over the masses. It doesn't matter how good my open source model is if I can't acquire the resources to run it. And I have no doubt that the big players will happily buy legislation to both entrench their compute monopoly/cartel and control what can be done using their compute (e.g. making it a criminal offence to build a competitor).
> to bias it towards favoring certain agendas wrt the information it presents to the users in response to their queries.<p>Do you mean like Grok is already doing in such a ham-fisted way?
Absolutely. Like most things on the Internet, it will get enshittified. I think it is very likely that at some point there will be "ads" in the form of the chat bot giving recommendations that favor certain products and services.
This is already happening. People are conditioned to embrace capitalism, where a small percentage of the population are born into the owning class, and a majority who labour.
Being told how my grandma had problems and was eventually told to shut down her knitting production (done in free time in addition to regular work) by police in the Communist Poland, I believe that it's better to have somehow upgraded capitalism then try to build a good communism just one more time.<p>It still got her enough extra buck to build a house in the city after moving out from the village.
This is something I noticed myself. I let AI handle some of my project and later realized I didn't even understand my own project well enough to make decisions about it :)
One bothersome aspect of generative assistance for personal and public communication not mentioned is that it introduces a lazy hedge, where a person can always claim that "Oh, but that was not really what I meant" or "Oh, but I would not express myself in that way" - and use it as a tool to later modify or undo their positions - effectively reducing honesty instead of increasing it.
> where a person can always claim that "Oh, but that was not really what I meant"<p>that already happens today - they claim autocorrect or spell checks instead of ai previously.<p>I don't accept these as excuses as valid (even if it was real). It does not give them a valid out to change their mind regardless of the source of the text.
Yep! However the problem will increase by many orders of magnitude as the volume of generated content far surpasses the content created by autocorrect mechanisms, in addition to autocorrect being a far more local modification that does not generate entire paragraphs or segments of content, making it harder to excuse large changes in meaning.<p>I agree that they make for poor excuses - but as generative content seeps into everything I fear it will become more commonly invoked.
> I fear it will become more commonly invoked.<p>yep, but invoking it doesnt force you to accept it. The only thing you get to control is your own personal choices. That's why i am telling you not to accept it, and i hope that people reading this will consider this their default stance.
Never in my life would I accept that as a valid excuse. If you sent the mail, committed the code or whatever, you take responsibility for it. Anything else is just pathetic.
Are you embracing the fundamental attribution error?
Good question. I certainly commit that error sometimes, like everyone else. But the issue here is people using LLMs to write eg emails and then not taking responsibility for what they write. That has nothing to do with attribution, only accountability.<p>"I was having a bad day, my mother had just died" is a very valid explanation for a poorly worded email. "It was AI" is not.
You must be a delightful person to work with.<p>> If you sent the mail, committed the code or whatever, you take responsibility for it. Anything else is just pathetic.<p>Have you discussed this with your therapist?
I guess you got hung up on the word "pathetic". See my comment below, I used it not as "despicable" but rather "something to feel sorry for". Indeed, people writing emails using LLMs and then blame the AI for consequences, that is something that makes me feel sorry for them.<p>Implying mental health issues? That makes me think you were triggered by my comment.
I mean he mentioned it in IMO too harsh of a way (e.g. “pathetic”) but I do think it raises the point: if you don’t own up to your actions then how can you be held accountable to anything?<p>Unless we want to live in a world where accountability is optional, I think taking responsibility for your actions is the only choice.<p>And to be honest, today I don’t know where we stand on this. It seems a lot of people don’t care enough about accountability but then again a lot of people do. That’s just my take.
Yes, thank you. I used "pathetic" in the meaning of something which makes feel sorry for them, not something despicable. I fully expect people to stand by what they write and not blame AI etc, but my comment came across as too aggressive.
I mean we're only human. We all make mistakes. Sure, some mistakes are worse than others but in the abstract, even before AI, who hasn't sent an email that they later regretted?
Therapists are also supposed to take responsibility for their work.
This list of things not to use AI for is so quaint. There's a story on the front page right now from The Atlantic: "Film students who can no longer sit through films". But why? Aren't they using social media, YouTube, Netflix, etc responsibly? Surely they know the risks, and surely people will be just as responsible with AI, even given the enormous economic and professional pressures to be irresponsible.
<p><pre><code> > Surely they know the risks, and surely people will be just as responsible with AI
</code></pre>
I can't imagine even half of students can understand the short and long term risk of using social media and AI intensively.
At least I couldn't when I was a student.
What is the lesson in the anecdote about film students? To me, it’s that people like <i>the idea</i> of studying film more than they like actually studying film. I fail to see the connection to social media or AI.
AI performs strictly in the Platonic world, as is the social media experience. As is the film student.
Social media's rotted their attention span
> Film students who can no longer sit through films<p>Everyone loves watching films until they get a curriculum with 100 of them along with a massive reading list, essays, and exams coming up.
> surely people will be just as responsible with AI<p><i>That's exactly what worries us.</i>
We lose something when we give up horses for cars.<p>Have too many of us outsourced our ability to raise horses for transport?<p>Surely you're capable of walking all day without break?
I am actually, we haven't owned car for years. We also rarely watch TV and eschew social media, so I can still pay attention and analyze things.<p>But this makes me super weird! This is the whole point of social media bans for kids: if you make it optional, it'll still be prevalent and people making healthy choices will be social weirdos. Healthy paths need to be free and accessible, and things need to be built around them (eg don't assume everyone has a smartphone, etc)
It's a funnily relevant parallel you're making, because <i>designing everything around the car</i> has absolutely been one of the biggest catastrophes of 2nd half of the 20th century. Much like "AI" in the past couple years, the personal automobile is a useful tool but making anything and everything subservient towards its use has had catastrophic consequences.
It is political. Designing everything around cars benefits the class of people called "Car Owners". Not so much people who don't have the money or desire to buy a car.<p>Although, congestion pricing is a good counter-example. On the surface it looks like it is designed to benefit users of public transportation. But turns out it also benefits car-owners, because it reduces traffic jams and lets you get to your destination with your own car faster.
But having a car is kind of bad. Maybe you remember when everyone smoked, and there was stuff for smokers everywhere. Sure that made it easier for smokers, but ultimately that wasn't good for them (nor anyone around them).
>Designing everything around cars benefits the class of people called "Car Owners".<p>Designing everything around cars hurts everyone including car owners. Having no option but to drive everywhere just sucks.
No, it benefits car manufacturers and sellers, and mechanics and gas stations.<p>Network/snowball effects are not all good. If local businesses close because everybody drives to WalMart to save a buck, now other people around those local businesses also have to buy a car.<p>I remember a couple of decades ago when some bus companies in the UK were privatized, and they cut out the "unprofitable" feeder routes.<p>Guess what? More people in cars, and those people didn't just park and take the bus when they got to the main route, either.
>No, it benefits car manufacturers and sellers, and mechanics and gas stations.<p>Everybody thinks they're customers when they buy a car, but they're really the product. These industries, and others, are the real customers
Perhaps the films were weren't worth sitting through?
Recently a side discussion came up - people in the Western world are "rediscovering" fermented, and pickled, foods that are still in heavy use in Asian cultures.<p>Fermentation was a great way to /preserve/ food, but it can be a bit hit and miss. Pickling can be outright dangerous if not done correctly - botulism is a constant risk.<p>When canning of foods came along it was a massive game changer, many foods became shelf stable for months or years.<p>Fermentation and pickling was dropped almost universally (in the West).
The “lump of cognition” framing misses something important. it’s not about how much thinking we do, but which thinking we stop doing. A lot of judgment, ownership, and intuition comes from boring or repetitive work, and outsourcing that isn’t free. Lowering the cost of producing words clearly isn’t the same as increasing the amount of actual thought.
I'm grateful that I spent a significant part of my life forced to solve problems and forced to struggle to produce the right words. In hindsight I know that that's where all the learning was. If I'd had a shortcut machine when I was young I'd have used it all the time, learned much less, and grown up dependent on it.
I'd argue that <i>choosing</i> words is a key skill because language is one of our tools for examining ideas and linking together parts of our brains in new ways.<p>Even just writing notes you'll never refer to again, you're making yourself codify vaguer ideas or impressions, test assumptions, and then compress the concept for later. It's an new <i>external</i> information channel between different regions of your head which seems to provide value.
Looking at the words that get produced at this lowered cost, and observing how satisfactory they apparently are to most people (and observing the simplicity of the heuristics people use to try to root out "cheap" words), has been quite instructive (and depressing).
I actually wrote up quite a few thoughts related to this a few days ago but my take is far more pessimistic: <a href="https://www.neilwithdata.com/outsourced-thinking" rel="nofollow">https://www.neilwithdata.com/outsourced-thinking</a><p>My fundamental argument: The way the average person is using AI today is as "Thinking as a Service" and this is going to have absolutely devastating long term consequences, training an entire generation not to think for themselves.
There's an Isaac Asimov story where people are "educated" by programming knowledge into their brains, Matrix style.<p>A certain group of people have something wrong with their brain where they can't be "educated" and are forced to learn by studying and such. The protagonist of the story is one of these people and feels ashamed at his disability and how everyone around him effortlessly knows things he has to struggle to learn.<p>He finds out (SPOILER) that he was actually selected for a "priesthood" of creative/problem solvers, because the education process gives knowledge without the ability to apply it creatively. It allows people to rapidly and easily be trained on some process but not the ability to reason it out.
I think you hit the nail on the head. Without years of learning by doing, experience in the saddle as you put it, who would be equipped to judge or edit the output of AI? And as knowledge workers with hands-on experience age out of the workforce, who will replace us?<p>The critical difference between AI and a tool like a calculator, to me, is that a calculator's output is accurate, deterministic and provably true. We don't usually need to worry that a calculator might be giving us the wrong result, or an inferior result. It simply gives us an objective fact. Whereas the output of LLMs can be subjectively considered good or bad - even when it is accurate.<p>So imagine teaching an architecture student to draw plans for a house, with a calculator that spit out incorrect values 20% of the time, or silently developed an opinion about the height of countertops. You'd not just have a structurally unsound plan, you'd also have a student who'd failed to learn anything useful.
<p><pre><code> > The critical difference between AI and a tool like a calculator, to me, is that a calculator's output is accurate, deterministic and provably true.
</code></pre>
This really resonates with me.
If calculators returned even 99.9% correct answers, it would be impossible to reliably build even small buildings with them.
We are using AI for a lot of small tasks inside big systems, or even for designing the entire architecture, and we still need to validate the answers by ourselves, at least for the foreseeable future.
But outsourcing thinking reduces a lot of brain powers to do that, because it often requires understanding problems' detailed structure and internal thinking path.<p>In current situation, by vibing and YOLOing most problems, we are losing the very ability we still need and can't replace with AI or other tools.
If you don't have building codes, you can totally yolo build a small house, no calculator needed. It may not be a great house, just like vibeware may not be great, but also, you have something.<p>I'm not saying this is ideal, but maybe there's another perspective to consider as well, which is lowering barriers to entry and increased ownership.<p>Many people can't/won't/don't do what it takes to build things, be it a house or an app, if they're starting from zero knowledge. But if you provide a simple guide they can follow, they might end actually building something. They'll learn a little along the way, make it theirs, and end up with ownership of their thing. As an owner, change comes from you, and so you learn a bit more about your thing.<p>Obviously whatever gets built by a noob isn't likely to be of the same caliber as a professional who spent half their life in school and job training, but that might be ok. DIY is a great teacher and motivator to continue learning.<p>Contrast to high barriers to entry, where nothing gets built and nothing gets learned, and the user is left dependent on the powers that be to get what he wants, probably overpriced, and with features he never wanted.<p>If you're a rocket surgeon and suddenly outsource all your thinking to a new and unpredictable machine, while you get fat and lazy watching tv, that's on you. But for a lot of people who were never going to put in years of preparation just to do a thing, vibing their idea may be a catalyst for positive change.
> If calculators returned even 99.9% correct answers, it would be impossible to reliably build even small buildings with them.<p>I think past successes have led to a category error in the thinking of a lot of people.<p>For example, the internet, and many constituent parts of the internet, are built on a base of fallible hardware.<p>But mitigated hardware errors, whether equipment failures, alpha particles, or other, are uncorrelated.<p>If you had three uncorrelated calculators that each worked 99.99% of the time, and you used them to check each other, you'd be fine.<p>But three seemingly uncorrelated LLMs? No fucking way.
There's another category error compounding this issue: People think that because past revolutions in technology eventually led to higher living standards after periods of disruption, this one will too. I think this one is the exception for the reasons enumerated by the parent's blog post.
Agreed.<p>In point of fact, most technological revolutions have fairly immediately benefited a significant number of people in addition to those in the top 1% -- either by increasing demand for labor, or reducing the price of goods, or both.<p>The promise of LLMs is that they benefit people in the top 1% (investors and highly paid specialists) by reducing the demand for labor to produce the same stuff that was already being produced. There is an incidental initial increase in (or perhaps just reallocation of) labor to build out infrastructure, but that is possibly quite short-lived, and simultaneously drives a huge increase in the cost of electricity, buildings, and computer-related goods.<p>But the benefits of new technologies are never spread evenly.<p>When the technology of travel made remote destinations more accessible, it created tourist traps. Some well placed individuals and companies do well out of this, but typically, most people living near tourist traps suffer from the crowds and increased prices.<p>When power plants are built, neighbors suffer noise and pollution, but other people can turn their lights on.<p>We haven't yet begun to be able to calculate all the negative externalities of LLMs.<p>I would not be surpised if the best negative externality comparisons were to the work of Thomas Midgley, who gifted the world both leaded gasoline and CFC refrigerants.
The LLMs are not uncorrelated, though, they're all trained on the same dataset (the Internet) and subject to most of the same biases
It's funny, I'm working on trying to get LLMs to place electrical devices, and it silently developed opinions that my switches above countertops should be at 4 feet and not the 3'10 I'm asking for (the top cannot be above 4')
That's quite funny, and almost astonishing, because I'm not an architect, and that scenario just came out of my head randomly as I wrote it. It seemed like something an architect friend of mine who passed away recently, and was a big fan of Douglas Adams, would have joked about. Maybe I just channeled him from the afterlife, and maybe he's also laughing about it.
On the other hand the incorrect values may drive architects to think more critically about what their tools are producing.
On the whole, not trusting one's own tools is a regression, not an advancement. The cognitive load it imposes on even the most capable and careful person can lead to all sorts of downstream effects.
I think the comparison to giving change is a good one, especially given how frequently the LLM hype crowd uses the fictitious "calculator in your pocket" story. I've been in the exact situation you've described, long before LLMs came out and cashiers have had calculators in front of them for longer than we've had smartphones.<p>I'll add another analogy. I tell people when I tip I "round off to the nearest dollar, move the decimal place (10%), and multiply by 2" (generating a tip that will be in the ballpark of 18%), and am always told "that's too complicated". It's a 3 step process where the hardest thing is multiplying a number by 2 (and usually a 2 digit number...). It's always struck me as odd that the response is that this is too complicated rather than a nice tip (pun intended) for figuring out how much to tip quickly and with essentially zero thinking. If any of those three steps appear difficult to you then your math skills are <i>below that of elementary school.</i><p>I also see a problem with how we look at math and coding. I hear so often "abstraction is bad" yet, that is all coding (and math) is. It is fundamentally abstraction. <i>The ability to abstract is what makes humans human.</i> All creatures abstract, it is a necessary component of intelligence, but humans certainly have a unique capacity for it. Abstraction is no doubt hard, but when in life was anything worth doing easy? I think we unfortunately are willing to put significantly more effort into justifying our laziness than we will to be not lazy. My fear is that we will abdicate doing worthwhile things because they are hard. It's a thing people do every day. So many people love to outsource their thinking. Be it to a calculator, Google, "the algorithm", their favorite political pundit, religion, or anything else. Anything to abdicate responsibility. Anything to abdicate effort.<p>So I think AI is going to be no different from calculators, as you suggest. They can be great tools to help people do so much. But it will be far more commonly used to outsource thinking, even by many people considered intelligent. Skills atrophy. It's as simple as that.
I briefly taught a beginner CS course over a decade ago, and at the time it was already surprising and disappointing how many of my students would reach for a calculator to do <i>single-digit</i> arithmetic; something that was a requirement to be committed to memory when I was still in school. Not surprisingly, teaching them binary and hex was extremely frustrating.<p><i>I tell people when I tip I "round off to the nearest dollar, move the decimal place (10%), and multiply by 2" (generating a tip that will be in the ballpark of 18%), and am always told "that's too complicated".</i><p>I would tell others to "shift right once, then divide by 2 and add" for 15%, and get the same response.<p>However, I'm not so sure what you mean by a problem with thinking that abstraction is bad. Yes, abstraction is bad --- because it is a way to hide and obscure the actual details, and one could argue that such dependence on opaque things, just like a calculator or AI, is the actual problem.
That would have devastating consequences in the pre-LLM era, yes. What is less obvious is whether it'll be an advantage or disadvantage going forward. It is like observing that cars will make people fat and lazy and have devastating consequences on health outcomes - that is exactly what happened but the net impact was still positive because cars boost wealth, lifestyles and access to healthcare so much that the net impact is probably positive even if people get less exercise.<p>It is unclear that a human thinking about things is going to be an advantage in 10, 20 years. Might be, might not be. In 50 years people will probably be outraged if a human makes an important decision without deferring to an LLM's opinion. I'm quite excited that we seem to be building scaleable superintelligences that can patiently and empathetically explain why people are making stupid political choices and what policy prescriptions would actually get a good outcome based on reading all the available statistical and theoretical literature. Screw people primarily thinking for themselves on that topic, the public has no idea.
I believe that collectively we passed that point long before the onset of LLMs. I have a feeling that throughout the human history vast amounts of people ware happy to outsource their thinking and even pay to do so. We just used to call those arrangements religions.
Religions may outsource opinions on morality, but no one went to their spiritual leader to ask about the Pythagorean theorem or the population of Zimbabwe.
Well, now, that's not actually true:<p>[1] <a href="https://plato.stanford.edu/entries/pythagoreanism/" rel="nofollow">https://plato.stanford.edu/entries/pythagoreanism/</a>
[2] <a href="https://en.wikipedia.org/wiki/Pythia" rel="nofollow">https://en.wikipedia.org/wiki/Pythia</a>
That’s a bit cynical. Religion is more like a technology. It was continuously invented to solve problems and increase capacity. Newer religions superseded older and survived based on productive and coercive supremacy.
> Can you audit/review/identify issues in a codebase if you've never written code?<p>Actual knowledge about systems work much better more often than not, LLMs are not sentient and still need to be driven to get decent results.
I'll say that I'm still kinda on the fence here, but I will point out that your argument is <i>exactly</i> the same as the argument against calculators back in the 70s/80s, computers and the internet in the 90s, etc.
You could argue that a lot of the people who few up with calculators have lost any kind of mathematical intuition. I am always horrified how bad a lot of people are with simple math, interest rates and other things. This definitely opened up a lot of opportunities for companies to exploit this ignorance.
The difference is a calculator always returns 2+2=4. And even then if you ended up with 6 instead of 4, the fact you know how to do addition already leads you to believe you fat fingered the last entry and that 2+2 does not equal 6.<p>Can’t say the same for LLM. Our teachers were right with the internet of course as well. If you remember those early internet wild west school days, no one was using the internet to actually look up a good source. No one even knew what that meant. Teachers had to say “cite from these works or references we discussed in class” or they’d get junk back.
To some extent, the argument against calculators is perfectly valid.<p>The cash register says you owe $16.23, you give the cashier $21.28, and all hell breaks loose.
Too late. Outsourcing has already accomplished this.<p>No one is making cool shit for themselves. Everyone is held hostage ensuring Wall Street growth.<p>The "cross our fingers and hope for the best" position we find ourselves in politically is entirely due to labor capture.<p>The US benefited from a social network topology of small businesses. No single business being a lynch pin that would implode everything.<p>Now the economy is a handful of too big to fails eroding links between human nodes by capturing our agency.<p>I argued as hard as I could against shipping electronics manufacturing overseas so the next generation would learn real engineering skills. But 20 something me had no idea how far up the political tree the decision was made back then. I helped train a bunch of people's replacements before the telecom focused network hardware manufacturer I worked for then shut down.<p>American tech workers are now primarily cloud configurators and that's being automated away.<p>This is a decades long play on the part of aging leadership to ensure Americans feel their only choice is capitulate.<p>What are we going to do, start our own manufacturing business? Muricans are fish in a barrel.<p>And some pretty well connected people are hinting at similar sense of what's wrong: <a href="https://www.barchart.com/story/news/36862423/weve-done-our-country-a-great-disservice-by-offshoring-nvidias-jensen-huang-says-we-have-to-create-prosperity-for-all-not-just-phds" rel="nofollow">https://www.barchart.com/story/news/36862423/weve-done-our-c...</a>
The interesting axis here isn’t how much cognition we outsource, it’s how reversible the outsourcing is. Using an LLM as a scratchpad (like a smarter calculator or search engine) is very different from letting it quietly shape your writing, decisions, and taste over years. That’s the layer where tacit knowledge and identity live, and it’s hard to get back once the habit forms.<p>We already saw a softer version of this with web search and GPS: people didn’t suddenly forget how to read maps, but schools and orgs stopped teaching it, and now almost nobody plans a route without a blue dot. I suspect we’ll see the same with writing and judgment: the danger isn’t that nobody thinks, it’s that fewer people remember how.
Yet it does feel different with LLMs compared to your examples. Yes, people can’t navigate without Apple/Google maps, but that’s still very different from losing critical thinking skills.<p>That said, LLMs are perhaps accelerating that but aren’t the only cause (lack of reading, more short form content, etc)
> it’s hard to get back once the habit forms.<p>Humans are highly adaptable. It's hard to go back while the thing we're used to still exists, but if it vanished from the world we'd adapt within a few weeks.
Outsourcing to thinking is exactly what I tell our developers. They are hired to do the kind of thinking I’d rather not do.
Not to nitpick but I find his point on automating vacation planning on AI so silly.<p>Apparently he think of planning a vacation as some artistic expression.
I really enjoyed and agree with the majority of the article, but this was my nit as well. My hatred of vacation planning is often the reason I don't go on more vacations. It seems like automating a task that is experienced by the individual as completely monotonous ( and only affects that individual) would be a great example of something worth handing off to a text generator.
Some of humanity’s most significant inventions are
language (symbolic communication), writing, the scientific method, electricity, the computer.<p>Notice something subtle.<p>Early inventions extend coordination. Middle inventions extend memory. Later inventions extend reasoning. The latest inventions extend agency.<p>This suggests that human history is less about tools and more about outsourcing parts of the mind into the world.
The main difference is that the computer you use for writing is not requiring you to pay for every word. And that's the difference in the business models being pushed right now all around the world.
I like this imaginary world you propose that gives free computers, free electricity, a free place to store it, and is free from danger from other tribes.<p>Sign me up for this utopia.
If an AI thinks for you, you're no longer "outsourcing" parts of your mind. What we call "AI" now is technically impressive but is not the end point for where AI is likely to end up. For example, imagine an AI that is smart enough to emotionally manipulate you, at what point in this interaction do you lose your agency to "outsource" yourself instead of acting as a conduit to "outsource" the thoughts of an artificial entity? It speaks to our collective hubris that we seek to create an intellectually superior entity and yet still think we'll maintain control over it instead of the other way around.
> we seek to create an intellectually superior entity and yet still think we'll maintain control over it instead of the other way around.<p>Intellect is not the same thing as volition.
> Intellect is not the same thing as volition.<p>Two questions...<p>1. Do you think it's impossible for AI to have it's own volition?<p>2. We don't have full control over the design of AI. Current AI models are grown rather than fully designed, the outcomes of which are not predictable. Would you want to see limits placed on AI until we had a better grasp of how to design AI with predictable behaviour?
There's a parallel there to drugs. They are most definitely not "intelligent", yet they can still destroy our agency or free-will.
We are going to be able to think plenty about other things than what we are doing, yes. That is called anxiety.
Great blog post, and I fully agree. The human touch in communication and reflection can not be emphasized enough.
I still read the LLMs output quite critically and I cringe whenever I do. LLMs are just plain wrong a lot of the time. They’re just not very intelligent. They’re great at pretending to be intelligent. They imitate intelligence. That is all they do. And I can see it every single time I interact with them. And it terrifies me that others aren’t quite as objective.
I usually feed my articles to it and ask for insight into whats working. I usually wait to initiate any sort of AI insight until my rough draft is totally done...<p>Working in this manner, it is so painfully clear it doesnt really follow the flow of the article even. It misses on so many critical details and just sorta fills in its own blanks wrong... When you tell it that its missing a critical detail, it treats you like some genius, every single time.<p>It is hard for me to try to imagine growing up with it, and using it to write my own words for me. The only time i copy paste words to a fellow human that is ai generated, is for totally generic customer service style replies, for questions i dont totally consider worthy of any real time.<p>AI has kinda taken away my flow state for coding, rare as it was... I still get it when writing stuff I am passionate about, and I can't imagine I'll ever wanna outsource that.
> When you tell it that its missing a critical detail, it treats you like some genius, every single time.<p>Yeah, or as I say, Uriah Heep.<p>To be fair, telling everybody they are geniuses is the obvious next step after participation awards.<p>Because people have figured out that participation awards are worthless, so let's give them all first place.
> And it terrifies me that others aren’t quite as objective.<p>I have been reminded constantly throughout this that a very large fraction of people are easily impressed by such prose. Skill at detecting AI output (in any given endeavour), I think, correlates with skill at valuing the same kind of work generally.<p>Put more bluntly: slop is slop, and it has been with us for far longer than AI.
How many of you know how to do home improvement? Fix your own clothes? Grow your own food? <i>Cook</i> your own food? How about making a fire or shelter? People used to know all of those things. Now they don't, but we seem to be getting along in life fine anyway. Sure we're all frightened by the media at the dangers lurking from not knowing more, but actually our lives are fine.<p>The things that are actually dangerous in our lives? Not informing ourselves enough about science, politics, economics, history, and letting angry people lead us astray. Nobody writes about that. Instead they write about spooky things that can't be predicted and shudder. It's easier to wonder about future uncertainty than deal with current certainty.
Executive function is not the same as weaving or carpentry. The scary problem comes from people who are trying to abdicate their entire understand-and-decide phase to an outside entity.<p>What's more, that's not fundamentally a new thing, it's always been <i>possible</i> for someone to helplessly cling to another <i>human</i> as their brain... but we've typically considered that to be a mental-disorder and/or abuse.
> <i>How many of you know how to [...] cook your own food?</i><p>That's a very low bar. I expect most people know how to cook, at least simple dishes.
I know how to cook! You open the freezer, grab a Hot Pocket, Unwrap it, put it in the microwave, hit 2, and wait 3 minutes (it has to cool). That's what you meant, right?<p>Some people really don't.
Systems used to be robust, now they’re fragile due to extreme outsourcing and specialization. I challenge the belief that we’re getting along fine. I argue systems are headed to failure, because of over optimization that prioritized output over resilience.
Interesting read..<p>To his point: personally, I find it shifts 'where and when' I have to deal with the 'cognitive load'. I've noticed (at times) feeling more impatient, that I tend to skim the results more often, and that it takes a bit more mental energy to maintain my attention..
One perspective I’m circling right now about this topic is that maybe we’re coming to realize as a society that what we considered intelligence (or symbolic intelligence whatever you wanna call that thing that we measure with traditional IQ tests, verbal fluency, etc) is actually a far less essential cognitive aspect to us as humans then we had previously assumed and is in fact, far more mechanical in nature than we had formerly believed.<p>This ties with how I sometimes describe current generation AI as a form of mechanized intelligence: like Babbage’s calculating machine, but scaled up to be able to represent all kinds of classes of things.<p>And in this perspective that I’m circling these days where I’m currently coming down on it is maybe the effect of this realization will be something like the dichotomy outlined in the Dune series: namely, that between mechanized intelligence embodied by mentats and the more intuitive and prescient aspects of cognition embodied by the Benni Jessarit and Paul’s lineage.<p>A simple but direct way to describe this transition in perspective may be that we come to see what we formally thought of as intelligence in the West/reductive tradition as a form of mechanized calculation that it’s possible to outsource to automatic non-biological processes, and we start to lean in more deeply to the more intuitive and prescient aspects of cognition.<p>One thing I’m reminded of is how Indian yogic texts describe various aspects of mind.<p>I’m not sure if it’s a one-to-one mapping because I’m not across that material but merely the idea of distinguishing between different aspects of mind is something with precedent; and central to that is the idea of removing association between self identity and the aspects of mind.<p>And so maybe one of the effects for us as a society will be something akin to that.
A lot of this stuff depends on how a person chooses to engage, but my contrarian take is that actually throughout history whenever anyone said X technology will lead to the downfall of humanity for y reasons, that take was usually correct.<p>The article he references gives this example:<p>“Is it lazy to watch a movie instead of making up a story in your head?”<p>Yes, yes it is, this was a worry when we transitioned from oral culture to written culture, and I think it was probably prescient.<p>For many if not most people cultural or technological expectations around what skills you _have_ to learn probably have an impact on total capability. We probably lost something when Google Maps came out and the average person didn’t have to learn to read a map.<p>When we transitioned from paper and evening news to 24 hour partisan cable news, I think more people outsourced their political opinions to those channels.
> We probably lost something when Google Maps came out and the average person didn’t have to learn to read a map.<p>Even in my mid 30s I see this issue with people around my age. Even for local areas, it seems like no one really understands what direction they are heading, they just kinda toggle on the GPS and listen for what to do... forever?<p>On pretty much every modern GPS, there is a button to show the full route instead of the current step the user is on(as well as keeping it in a static orientation). I feel like just that being the default most of the time, would help a ton of people.
Distributed verification. 8 billions of us can divide up the topics and subjects and pool together our opinions and best conclusions.
See Scott Alexander’s The Whispering Earring (2012):<p><a href="https://gwern.net/doc/fiction/science-fiction/2012-10-03-yvain-thewhisperingearring.html" rel="nofollow">https://gwern.net/doc/fiction/science-fiction/2012-10-03-yva...</a>
Social media has given me a rather dim view of the quality of people's thinking, long before AI. Outsourcing it could well be an improvement.
> Social media has given me a rather dim view of the quality of people's thinking, long before AI. Outsourcing it could well be an improvement.<p><i>Cogito, ergo sum</i><p>The corollary is: <i>absence of thinking equals non-existence</i>. I don't see how that can be an improvement. Improvement can happen only when it's applied to the quality of people's thinking.
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Thinking developed naturally as a tool that helps our species to stay dominant on the planet, at least on land. (Not by biomass but by the ability to control.)<p>If outsourcing thought is beneficial, those who practice it will thrive; if not, they will eventually cease to practice it, one way or another.<p>Thought, as any other tool, is useful when it solves more problems than it creates. For instance, an ability to move very fast may be beneficial if it gets you where you want to be, and detrimental, if it misses the destination often enough, and badly enough. Similarly, if outsourced intellectual activities miss the mark often enough, and badly enough, the increased speed is not very helpful.<p>I suspect that the best results would be achieved by outsourcing relatively small intellectual acts in a way that guarantees very rare, very small errors. That is, AI will become useful when AI becomes <i>dependable</i>, comparable to our other tools.
> If outsourcing thought is beneficial, those who practice it will thrive<p>It makes them prey to and dependent on those who are building and selling them the thinking.<p>> I suspect that the best results would be achieved by outsourcing relatively small intellectual acts in a way that guarantees very rare, very small errors. That is, AI will become useful when AI becomes dependable, comparable to our other tools.<p>That's like saying ultra processed foods provide the best results when eaten sparingly, so it will become useful when people adopt overall responsible diets. Okay, sure, but what does that matter in practice since it isn't happening?
Outsourcing thinking is not a skill. It is the same as skipping gym. Nothing to practice here
A lot of people practice not going to a gym! I bet it reflects e.g. on their dating outcomes, at least statistically.<p>I suspect that outsourcing thinking may reflect on quite some outcomes, too. We just need time to gather the statistics.