14 ms·

The Tragedy of the Cognitive Commons

114 points by jmintz 1mo ago

LolWolf 1mo ago
It's so wild to have a whole paper about this... that's also LLM written. What are we even doing here?
xendo 1mo ago
For anyone that does LLM supported work it's crystal clear that skill decline is real. Surprisingly, the leadership at my work doesn't give rats ass about it. They published AI engineering manifesto, pushing for loops, workflows, advocating for producing many times more code. All of this ignoring the elephant in the room.
- chrisjj 1mo ago
  Why surprised? The elephant is in someone else's room.
- noir_lord 1mo ago
  Cynically they may be banking (however misguided it turns out to be) on model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model. The hype from non-technical people about AI would make you think they already discovered AGI.
  - burningChrome 1mo ago
    >> model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model. How people in tech are aware they're training their replacements? Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers?
    - ThePhysicist 1mo ago
      I don't know, I find AI still misses the mark so much for stuff that's not happening inside a well constrained framework with very specific guardrails and boundary conditions. Every time I have agents build something half complex that I would be easily able to pull off myself (albeit not at their pace) I always ask if everything is correct and working and I get a resounding "yes!", then I test it and it's essentially a steaming pile of garbage which I then tell the agent and after which it goes "you're absolutely right to push back, this isn't good at all!" as if it was clear from the beginning. I don't know if we'll achieve real intelligence soon with these things but what we have now isn't there yet. It's incredibly useful but I don't think you can replace a good programmer with it, you can make a good programmer into an excellent one though! Same goes for writing, anyone who has written long complex texts with LLMs knows that a ton of editing is required to make it half decent.
      - deleted 1mo ago
        [deleted]
      - brokenmachine 1mo ago
        Even for my tiny toy projects, I notice a bug and I tell the LLM and it corrects it, most of the time, but I shudder at the amount of code it generates or changes. If it has some subtle data corruption bug then you're hosed. It's just crazy to me to think about running AI changes in production on a real product.
    - taurath 1mo ago
      > Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers? The boosters are loud and the failures are made silent, until the failures become impossible to ignore. Tens to hundreds of millions of dollars spent on AI in enterprise software companies need to show RoI at some point, and the promises of executives leaning on AI's productivity improvements to make their accelerated release schedules need to actually make the releases. Its currently a very dangerous career move to publically apply critical thinking to LLM capabilities. I think the math sort of does itself.
- FrustratedMonky 1mo ago
  " skill decline is real" Is this -> More people that are not devs, are using AI to create things, and are skilling up to a mediocre level? or Is this -> Existing experts, are actually loosing there skills? Using AI is reducing someone already known skills.
  - jselysianeagle 1mo ago
    > More people that are not devs, are using AI to create things, and are skilling up to a mediocre level? What skills are being developed by non-devs prompting AI to churn out code they don't understand? Note that I'm not debating if the code is good or works or whatever, I'm asking if any real skills are being developed merely by prompting AI towards some goal.
    - FrustratedMonky 1mo ago
      I don't think it is zero. If they are producing code, there is some knowledge being absorbed. Nobody is using AI to create an app is learning zero. Its just what they are learning, is not as much as they think, and really random, not-structured. Like reading just a few random chapter of a book across multiple classes. They get a smattering of ad-hoc tidbits of knowledge. I am really worried if using AI is reducing someone's already gained knowledge. Moving someone backwards. That has me a bit more scared.
      - bluefirebrand 1mo ago
        > If they are producing code, there is some knowledge being absorbed. Nobody is using AI to create an app is learning zero Maybe not actually absolutely zero, but it's much closer to zero than what they would learn creating the app themselves
      - jplusequalt 1mo ago
        >I am really worried if using AI is reducing someone's already gained knowledge. Moving someone backwards. That has me a bit more scared. It absolutely is. It removes a lot of friction from pathways that kept previous knowledge firm. This isn't unique to AI. When calculators came around, people had a new tool that decreased the need to do arithmetic in your head. This has lead to a decline in the percentage of people who knew arithmetic, but can no longer do it adequately without the external tool. Another example would be assembly skills declining amongst software engineers after compiled languages become dominant. What I would argue is unique to AI is two-fold. The first being that the scale of things being automated is enormous. Keeping with just software, AI isn't only a tool that decreases the need to write code, it's also a tool that decreases the need to do your own research, debugging, system design, version control, etc. The list of tasks a regular engineer is responsible for that have not been consumed by AI is small. To make matters more frightening, this is just a single industry. The same applies to multiple other knowledge heavy fields (e.g. mathematics). The second thing I'd argue is unique about AI is the addictive nature of it. These LLMs are deliberately coerced into being sycophants that blow smoke up your ass unless you deliberately tell the model not too (and it may still do it anyways!). A calculator didn't compliment your insight for asking it to calculate the square root of -1. Furthermore, many people have talked about the resemblance of LLMs to slot machines--there's a feeling that anything could be possible if you only prompt the model correctly. Your first prompt is wildly off the mark, but your next prompt is better though still not quite right, so you continue forward. You keep iterating your instructions, your word choices, your tone, all in search of the desired response. In this way, an LLM is a slot machine, your prompt the lever you pull, and the output is the jackpot. All this taken together, we have a machine that decreases the need to engage with the critical faculties of your own brain, which has been trained to keep your attention through flattery, and whose probabilistic nature preys on our love for gambling.
- sushusshs 1mo ago
  I don’t think it’s as clear cut as you make it out to be. Maintenance <> growth Once you got a skill it’s quite hard to actually lose it. It’s like riding a bike as they say. I find all the reading of those walls of code exercises my mind better than the writing did. I’m sure I lost memories of how to read a file by hand or balance a tree but who cares? I am thinking about architecture and design a lot more these days and every decision I make has to be actually argued for even to myself. I can no longer lean back and say “that’s how we always do it” or “too expensive to change now” as I find many people in practice actually do. They were just coasting on premade architectural choices and their “skills” consisted of knowing arcane incantations and syntactic details completely unrelated to the (business) problem at hand. I am not convinced many developers actually have the skills they think they have. They could wrestle syntax and mess around with tooling, but could they abstract properly? Define clear semantic boundaries? Have proper civil discussions about responsibilities and where they should lie on the right level of abstraction? Nothing has changed in that regard. If anything that part has been amplified. (“taste”)
- ndriscoll 1mo ago
  It doesn't seem clear to me at all. e.g. I've been having a fun time learning Godot this last week with codex laying down groundwork for logic, generating assets, etc. This gives me something concrete that I can work with and ground myself within instead of starting from a blank canvas. I don't much care for the actual scripting logic because it's all basically trivial to me with a few decades of programming experience, and I'm not going to be able to develop my artistic abilities to a useful capacity anytime within the next few years, so I can instead focus on learning architecture/organization patterns and game systems that I'm interested in while I read through docs. So basically, if you use it to wave away things you've mastered or explicitly don't want to learn at the moment, you can stay focused on things you are figuring out. I don't see it as any different from writing "by induction" in a math proof without writing all the details because you and the reader know you could easily work them out. In this way I can learn things that I simply would not have the time to dig into before, increasing my skillset. As is was before AI, metacognition is the most widely useful skill to have.
- doug_durham 1mo ago
  I don't see it being "crystal clear" that skill decline is real. People are doing work they wouldn't have been able to do before. They are getting a more broad exposure to technologies than they have before.
  - nomel 1mo ago
    Seems like pretty clear breadth vs depth tradeoff, with a reduced total area. People rarely cared about the details to begin with. Now those that did care can no longer justify the time that was previously required.
hn22fazjsv 1mo ago
[dead]
joemazerino 1mo ago
Using AI to summarize this.
io84 1mo ago
A new and growing fear I have is that AI cuts off some of the most well-trodden pathways to intellectual growth. Every time the AI solves a problem that I would not have been able to efficiently solve alone, it has replaced an interaction that previously would have happened with a mentor/supervisor/code reviewer. This is faster for the person seeking the micro-assistance, but there is a flipside: fewer human-to-human acts of mentorship and shared problem solving. We lose a lively ingredient of team formation, expert formation, and a source of joy for all involved. As this scales up it feels plausible that we end up with a wider deagradation of intellectual standards. I like the Cognitive Comons framing.
- falcor84 1mo ago
  >Every time the AI solves a problem that I would not have been able to efficiently solve alone, it has replaced an interaction that previously would have happened with a mentor/supervisor/code reviewer. I suppose that Socrates would strongly agree, seeing how the same argument could be applied to learning from a book.
  - schneems 1mo ago
    The difference is that the act of writing a book is a type of knowledge generation/curation/distillation that Socrates didn't know about. I don't think the act of writing prompts for an LLM advances thinking/cognition in the same way.
    - DiscourseFan 1mo ago
      I am fairly certain Socrates knew about books, he just wasn't literate himself. But literacy was quite common amongst Athenian citizens, it was sort of an outlier for the time. Of course most of the day-labor was done by slaves, but it afforded them the time for cultural pursuits and healthy debate, and Socrates was very much a product of that.
  - abathologist 1mo ago
    Reading a book is a form of communication between the writers the readers, and literary culture enriches this with the ongoing interactions around texts. The argument voiced by Socrates in the Phaedrus is not primarily that it removes or stifles interaction but that it undermines memory (and thinking) and that it will "create forgetfulness in the learners' souls, because they will not use their memories; they will trust to the external written characters and not remember of themselves". AFAIK, there is well established research that shows that the move from oral to literate cultures does indeed bear this out. More recent studies about how wayfinding deteriorates when we rely on GPS seems a like a similar dynamic. There is another charge against writing in the Phaedrus, which is that texts cannot answer for themselves (contrary to spoken interlocutors) or adjust their communication to the needs and character of the reader: > when they have been once written down they are tumbled about anywhere among those who may or may not understand them, and know not to whom they should reply, to whom not: and, if they are maltreated or abused, they have no parent to protect them; and they cannot protect or defend themselves An interesting thing about computation is that it is a writing and re-writing that can indeed be responsive and, in a non-trivial sense, "answer for itself". LLMs do this in a form that is obviously very successful for engagement (and for hype) and for producing a lot of compelling output. I think the Phaedrus also has something to say here: > Soc. Then [they who who knows the just and good and honourable] will not seriously incline to "write" his thoughts "in water" with pen and ink, sowing words which can neither speak for themselves nor teach the truth adequately to others? > > Phaedr. No, that is not likely. > > Soc. No, that is not likely--in the garden of letters he will sow and plant, but only for the sake of recreation and amusement; he will write them down as memorials to be treasured against the forgetfulness of old age, by himself, or by any other old man who is treading the same path. He will rejoice in beholding their tender growth; and while others are refreshing their souls with banqueting and the like, this will be the pastime in which his days are spent.
nixonaddiction 1mo ago
for a lot of the article i was mentally replacing "ai" with "calculator" and going "yeah we will just need longer education times. more schooling etc." but the phrasing of "who pays for the increased schooling times?" is a good one. i think "debt" can be a decent way to conceptualize the cost and repayment of training someone. feels evil to say, but viewing people as firms you can invest in and expect returns upon. you know not all loans will be repayed, but hopefully they'll average to a profit. (risk management etc.) student loans are. a decent example. the government/private enterprise gives money to pay for education, then this is repayed, providing a financial incentive for paying for someone else's longer schooling timelines. firms investing in training can be viewed as an extension of student loans. but then ah, there are countless stories of how debtor/creditor relationships can be exploited. indentured servitude etc. there are a lot of complications coming to mind. also "altruistic" people who give without expectation of repayment. or the divide between like, communal vs individualistic cultures. (individualism, i argue, encourages the formalization of debt, as opposed to a more communal culture where the expectation of repayment is informal.) you could do math on how many people pay vs how many people benefit, who is the biggest stakeholder, etc. but i am on my lunch break and need to get back to my work. good article tho. good topic to bring up.
culebron21 1mo ago
Similar to the argument made by John Blow several years ago. Though, Blow blamed frameworks/engines and layers of abstractions. I wonder if the authors came to this framing themselves, or listened him. https://www.youtube.com/watch?v=q3OCFfDStgM https://www.youtube.com/watch?v=q3OCFfDStgM
jmfldn 1mo ago
My approach is to write a bit of totally AI-free code every day. So after a day of Claude, I'll spend at least 30 mins wrestling with something. The gnarlier the better, e.g.leet code or Project Euler-type stuff. I think of it as like lifting weights for the mind. The more I struggle at the edge of my knowledge and skill the better. The other thing is to give your agent a skill not to solve certain key problems unless explicitly prompted. Write the scaffolding sure, but leave the juicy parts alone. And if I get stuck, I have it enter into a dialogue with me, nudging me towards understanding.
- bogzz 1mo ago
  I solved a Leetcode Medium on my first try in about 10 minutes the other day and it felt so amazing. Thinking through architecture, project composition, composability, etc when working with agents felt fine for a while but it made me feel disconnected from what I'm actually building. Actually engaging my brain to solve the lower-level, on-the-ground code allows me to think of better ways to do things while I'm writing them. It's like writing anything. You start with something you want to convey, a thesis, and then it evolves and becomes better as you write it. An agent will just write it with no thought, as in it will reflect one of the LLM 'ghosts' as Andrej Karpathy puts it, doing something in the same way that someone in the training data has done it on a similar or different problem. This is why I get conniptions now when I am sent generated text or am expected to read it on a public forum. It's disrespectful of the time of every person expected to read it. That said, I wouldn't like to go back to the before times without having the agentic option available. Ideally, businesses should not mandate how LLM's are to be used at their company, and just let the devs find their own flow. That is, if quality is even a factor that any company optimizes for anymore.
Animats 1mo ago
The pseudo-academic style of the article is awful. All abstractions and buzzwords, no examples. Also, the tragedy of the commons concept is far older than 1968. The term "common" refers to common grazing land upon which anyone could graze animals. That's an English term. The American equivalent is "open range". Getting past that, the author has a point. There's a loss of shared expertise when there aren't people around learning and doing something. In the US, we've seen this in manufacturing. The number of Americans who know how to set up a good production plant is much lower than it was in the 1980s. That's the consequence of the hollowing out of American manufacturing. The author talks about AI vs. white collar work, but fails to make the connection with outsourcing vs. blue collar work. The loss of this expertise has recently been made very clear in the US as attempts are made to scale up weapons production for the US's various wars. Progress is very slow, as has been seen with both artillery ammo and air-defense missiles.
- PaulDavisThe1st 1mo ago
  > Also, the tragedy of the commons concept is far older than 1968. The term "common" refers to common grazing land upon which anyone could graze animals. That's an English term. The American equivalent is "open range". The term is not "common" or "commons" but "tragedy of the commons" which dates back to a book in 1968 by Garrett Hardin. Elinor Ostrom subsequently showed that most or all of Hardin's assumptions and claims were wrong, or at the very least, far from universal, and that the process he describes elides what actually drives the destructions of resources held in common: greed and power.
  - zaphar 1mo ago
    I think you might be thinking about Elinor Ostrom and she didn't show that his assumptions and claims were wrong exactly. She expanded on the work to clarify the difference between managed vs unmanaged commons. Showing that successful commons are managed in some way with established rules and limits around the usage. The term still has use especially if it is used to clarify the need for management of common resources to avoid the tragedy.
    - 1mo ago
jgalt212 1mo ago
Perhaps, but I find when I use AI (for fixing things), I learn a few things here and there as the AI-provided answers are often wrong. And when I work around these errors, the learning occurs.
zackmorris 1mo ago
I thought the article was going to be about countless millions of minds trying to win the internet lottery and merely reinventing the wheel or failing. I'm not worried about AI taking jobs. I'm worried that humanity has lost the ability to share at such a monumental level that basic sustenance and financial security are out of reach, even with AI. After lifetimes of negative reinforcement, the only salvation seems to be the disruption of capitalism itself. Somewhat ironically, the wealthiest and most powerful people in the world seem to be investing trillions of dollars into AI to do just exactly that.
- foxglacier 1mo ago
  They are not out of reach - people just increase their expectations to ensure that they never achieve satisfaction. I think that's fine but it is optional - if you want to just exist without striving for anything, nobody's stopping you. It's easy to be self-sufficient if you'll tolerate pre-industrial standards of living. There are others who want that too and you can coordinate with them and share among yourselves. This already happens. Modern standards of living and your high expectations are a consequence of capitalism. Ironically, you can actually have your cake and eat it too. So many other people love to participate in capitalism, that they provide enough good things to make self-sufficient living easier today than it was in pre-industrial times. No, humanity hasn't lost the ability to share - it's the exact opposite - trade (and capitalism) has enabled sharing far beyond what it ever was before. Even better, it's done though voluntary and mutually beneficial exchange rather than people being forced into a fixed role in life which was often something horrible like servant, slave-girl, or warrior.
sfny 1mo ago
This paper misrepresent fundamental concepts from Ostrom’s work, which won a Nobel, and fails to contextualize Hardin’s theories. As a 'human resource development' paper it somehow pretends that capitalism doesn't exist? Hardin coined "The Tragedy of the Commons" in 1968, elaborated on his theory in his 1974 paper "Lifeboat Ethics: the Case Against Helping the Poor". He was a eugenicist and specifically targeted refugees. He lobbied US Congress in opposition to international famine relief. His evidence-free theories must be contextualized within his overall white-nationalist project. https://www.splcenter.org/resources/extremist-files/garrett-hardin https://www.splcenter.org/resources/extremist-files/garrett-... The paper asserts that "expertise within a profession" is a commons. As an industry we've never been able to define the specific, task-level role boundaries between PM/designer/engineer across companies. So how is a profession defined? What are the units of expertise here? This paper fails to provide a defensible definition of their commons. Ostrom's commons need clear boundaries and resource units. https://en.wikipedia.org/wiki/Elinor_Ostrom https://en.wikipedia.org/wiki/Elinor_Ostrom From the abstract: "*The paper reframes expertise development as collective stewardship*" which ignores capitalism. Firms are incentivized to build proprietary expertise, eg Slang at Goldman. Individuals are incentivized to build proprietary expertise and use it as leverage for higher compensation. Even if we fudge commons into a more generic collective action problem, this paper doesn't reckon with the tension between market incentives and collective expertise. This tension comes up again and again, in open source, in academia, and corporate L&D programs. The author goes on to use professional organizations as an example of governance for their Cognitive Commons. The examples of medicine, law, and engineering are particularly bad as these are credentialed, legally enforced enclosures of expertise, and not self-policing or democratic. They are the opposite of commons. The author should have just written about expertise as a resource pool and avoided the commons. This was a frustrating read. The paper is a disservice to the commons literature.
- treetalker 1mo ago
  Law practice in the United States is self-policing.
  - sfny 1mo ago
    We can view the bar association as a self-policing group to some extent. But the unauthorized practice of law is a crime in most jurisdictions, so it's policed by the State. In the context of Ostrom's commons this means a hypothetical 'lawyer-commmons' exists at the whim of the State and is unlikely to survive. In practice, a fake lawyer serving jail time can't get out of jail by negotiating with the bar association for access to lawyering. It's similar for medicine and engineering. I take your overall point that professional organizations have internal rules, decorum, membership criteria, etc. If you're at all interested, Ostrom's 8 rules for managing the commons are worth a read.
i_s 1mo ago
Maybe we have to subsidize zoomers until we can figure this out.
- foxglacier 1mo ago
  And if the solution turns out to be "we don't need those skills anymore", what will happen to those subsidized people? Better just let them find work wherever they see a demand. Software has gutted many other industries of competent people. Maybe now they can return and lift up the rest of the economy.
cadamsdotcom 1mo ago
We will look back on this era as one of transition. AI is in its "look monkey can do tricks how cute" era - but it won't be long. For instance the era of "whoa" is happening right now in mathematics (Anthropic researchers are pushing math's frontier with little more than the prompt "you can do it" - ie. brute force), and in coding agents we're crossing over - look into leading-edge benchmarks like SlopCodeBench that are pushing labs to RL for long term codebase health and not just problem-solving. The reason I say coding agents will go in this direction is labs are competing to have the most appealing models and so seeking out new unsaturated benchmarks they can hill-climb and show flashy results from, demonstrate to customers they're the best and deserve spend. What these cognitive tools do is make the mundane work we're lamenting the loss of redundant. Who cares if junior devs can't code? When this stuff really gets going they'll be using their answer boxes to both code AND to have have design discussions with a form of intelligence that has every PhD ever obtained and infinite patience. Consider: long division used to be in school curricula; our forebears had to know it to be considered "educated"; and yet I, in my 40s, was never taught long division. Where did it go?

114 points by jmintz 1mo ago

It's so wild to have a whole paper about this... that's also LLM written. What are we even doing here?

xendo 1mo ago

For anyone that does LLM supported work it's crystal clear that skill decline is real. Surprisingly, the leadership at my work doesn't give rats ass about it. They published AI engineering manifesto, pushing for loops, workflows, advocating for producing many times more code. All of this ignoring the elephant in the room.

chrisjj 1mo ago
Why surprised? The elephant is in someone else's room.
noir_lord 1mo ago
Cynically they may be banking (however misguided it turns out to be) on model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model. The hype from non-technical people about AI would make you think they already discovered AGI.
- burningChrome 1mo ago
  >> model skill in aggregate growing faster than the skills of their staff decline at which point, bin the staff, use the model. How people in tech are aware they're training their replacements? Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers?
  - ThePhysicist 1mo ago
    I don't know, I find AI still misses the mark so much for stuff that's not happening inside a well constrained framework with very specific guardrails and boundary conditions. Every time I have agents build something half complex that I would be easily able to pull off myself (albeit not at their pace) I always ask if everything is correct and working and I get a resounding "yes!", then I test it and it's essentially a steaming pile of garbage which I then tell the agent and after which it goes "you're absolutely right to push back, this isn't good at all!" as if it was clear from the beginning. I don't know if we'll achieve real intelligence soon with these things but what we have now isn't there yet. It's incredibly useful but I don't think you can replace a good programmer with it, you can make a good programmer into an excellent one though! Same goes for writing, anyone who has written long complex texts with LLMs knows that a ton of editing is required to make it half decent.
    - deleted 1mo ago
      [deleted]
    - brokenmachine 1mo ago
      Even for my tiny toy projects, I notice a bug and I tell the LLM and it corrects it, most of the time, but I shudder at the amount of code it generates or changes. If it has some subtle data corruption bug then you're hosed. It's just crazy to me to think about running AI changes in production on a real product.
  - taurath 1mo ago
    > Or are we quickly approaching an apex where the people running these companies realize AI cannot completely replace human developers? The boosters are loud and the failures are made silent, until the failures become impossible to ignore. Tens to hundreds of millions of dollars spent on AI in enterprise software companies need to show RoI at some point, and the promises of executives leaning on AI's productivity improvements to make their accelerated release schedules need to actually make the releases. Its currently a very dangerous career move to publically apply critical thinking to LLM capabilities. I think the math sort of does itself.
FrustratedMonky 1mo ago
" skill decline is real" Is this -> More people that are not devs, are using AI to create things, and are skilling up to a mediocre level? or Is this -> Existing experts, are actually loosing there skills? Using AI is reducing someone already known skills.
- jselysianeagle 1mo ago
  > More people that are not devs, are using AI to create things, and are skilling up to a mediocre level? What skills are being developed by non-devs prompting AI to churn out code they don't understand? Note that I'm not debating if the code is good or works or whatever, I'm asking if any real skills are being developed merely by prompting AI towards some goal.
  - FrustratedMonky 1mo ago
    I don't think it is zero. If they are producing code, there is some knowledge being absorbed. Nobody is using AI to create an app is learning zero. Its just what they are learning, is not as much as they think, and really random, not-structured. Like reading just a few random chapter of a book across multiple classes. They get a smattering of ad-hoc tidbits of knowledge. I am really worried if using AI is reducing someone's already gained knowledge. Moving someone backwards. That has me a bit more scared.
    - bluefirebrand 1mo ago
      > If they are producing code, there is some knowledge being absorbed. Nobody is using AI to create an app is learning zero Maybe not actually absolutely zero, but it's much closer to zero than what they would learn creating the app themselves
    - jplusequalt 1mo ago
      >I am really worried if using AI is reducing someone's already gained knowledge. Moving someone backwards. That has me a bit more scared. It absolutely is. It removes a lot of friction from pathways that kept previous knowledge firm. This isn't unique to AI. When calculators came around, people had a new tool that decreased the need to do arithmetic in your head. This has lead to a decline in the percentage of people who knew arithmetic, but can no longer do it adequately without the external tool. Another example would be assembly skills declining amongst software engineers after compiled languages become dominant. What I would argue is unique to AI is two-fold. The first being that the scale of things being automated is enormous. Keeping with just software, AI isn't only a tool that decreases the need to write code, it's also a tool that decreases the need to do your own research, debugging, system design, version control, etc. The list of tasks a regular engineer is responsible for that have not been consumed by AI is small. To make matters more frightening, this is just a single industry. The same applies to multiple other knowledge heavy fields (e.g. mathematics). The second thing I'd argue is unique about AI is the addictive nature of it. These LLMs are deliberately coerced into being sycophants that blow smoke up your ass unless you deliberately tell the model not too (and it may still do it anyways!). A calculator didn't compliment your insight for asking it to calculate the square root of -1. Furthermore, many people have talked about the resemblance of LLMs to slot machines--there's a feeling that anything could be possible if you only prompt the model correctly. Your first prompt is wildly off the mark, but your next prompt is better though still not quite right, so you continue forward. You keep iterating your instructions, your word choices, your tone, all in search of the desired response. In this way, an LLM is a slot machine, your prompt the lever you pull, and the output is the jackpot. All this taken together, we have a machine that decreases the need to engage with the critical faculties of your own brain, which has been trained to keep your attention through flattery, and whose probabilistic nature preys on our love for gambling.
sushusshs 1mo ago
I don’t think it’s as clear cut as you make it out to be. Maintenance <> growth Once you got a skill it’s quite hard to actually lose it. It’s like riding a bike as they say. I find all the reading of those walls of code exercises my mind better than the writing did. I’m sure I lost memories of how to read a file by hand or balance a tree but who cares? I am thinking about architecture and design a lot more these days and every decision I make has to be actually argued for even to myself. I can no longer lean back and say “that’s how we always do it” or “too expensive to change now” as I find many people in practice actually do. They were just coasting on premade architectural choices and their “skills” consisted of knowing arcane incantations and syntactic details completely unrelated to the (business) problem at hand. I am not convinced many developers actually have the skills they think they have. They could wrestle syntax and mess around with tooling, but could they abstract properly? Define clear semantic boundaries? Have proper civil discussions about responsibilities and where they should lie on the right level of abstraction? Nothing has changed in that regard. If anything that part has been amplified. (“taste”)
ndriscoll 1mo ago
It doesn't seem clear to me at all. e.g. I've been having a fun time learning Godot this last week with codex laying down groundwork for logic, generating assets, etc. This gives me something concrete that I can work with and ground myself within instead of starting from a blank canvas. I don't much care for the actual scripting logic because it's all basically trivial to me with a few decades of programming experience, and I'm not going to be able to develop my artistic abilities to a useful capacity anytime within the next few years, so I can instead focus on learning architecture/organization patterns and game systems that I'm interested in while I read through docs. So basically, if you use it to wave away things you've mastered or explicitly don't want to learn at the moment, you can stay focused on things you are figuring out. I don't see it as any different from writing "by induction" in a math proof without writing all the details because you and the reader know you could easily work them out. In this way I can learn things that I simply would not have the time to dig into before, increasing my skillset. As is was before AI, metacognition is the most widely useful skill to have.
doug_durham 1mo ago
I don't see it being "crystal clear" that skill decline is real. People are doing work they wouldn't have been able to do before. They are getting a more broad exposure to technologies than they have before.
- nomel 1mo ago
  Seems like pretty clear breadth vs depth tradeoff, with a reduced total area. People rarely cared about the details to begin with. Now those that did care can no longer justify the time that was previously required.

hn22fazjsv 1mo ago

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joemazerino 1mo ago

Using AI to summarize this.

io84 1mo ago

A new and growing fear I have is that AI cuts off some of the most well-trodden pathways to intellectual growth. Every time the AI solves a problem that I would not have been able to efficiently solve alone, it has replaced an interaction that previously would have happened with a mentor/supervisor/code reviewer. This is faster for the person seeking the micro-assistance, but there is a flipside: fewer human-to-human acts of mentorship and shared problem solving. We lose a lively ingredient of team formation, expert formation, and a source of joy for all involved. As this scales up it feels plausible that we end up with a wider deagradation of intellectual standards. I like the Cognitive Comons framing.

falcor84 1mo ago
>Every time the AI solves a problem that I would not have been able to efficiently solve alone, it has replaced an interaction that previously would have happened with a mentor/supervisor/code reviewer. I suppose that Socrates would strongly agree, seeing how the same argument could be applied to learning from a book.
- schneems 1mo ago
  The difference is that the act of writing a book is a type of knowledge generation/curation/distillation that Socrates didn't know about. I don't think the act of writing prompts for an LLM advances thinking/cognition in the same way.
  - DiscourseFan 1mo ago
    I am fairly certain Socrates knew about books, he just wasn't literate himself. But literacy was quite common amongst Athenian citizens, it was sort of an outlier for the time. Of course most of the day-labor was done by slaves, but it afforded them the time for cultural pursuits and healthy debate, and Socrates was very much a product of that.
- abathologist 1mo ago
  Reading a book is a form of communication between the writers the readers, and literary culture enriches this with the ongoing interactions around texts. The argument voiced by Socrates in the Phaedrus is not primarily that it removes or stifles interaction but that it undermines memory (and thinking) and that it will "create forgetfulness in the learners' souls, because they will not use their memories; they will trust to the external written characters and not remember of themselves". AFAIK, there is well established research that shows that the move from oral to literate cultures does indeed bear this out. More recent studies about how wayfinding deteriorates when we rely on GPS seems a like a similar dynamic. There is another charge against writing in the Phaedrus, which is that texts cannot answer for themselves (contrary to spoken interlocutors) or adjust their communication to the needs and character of the reader: > when they have been once written down they are tumbled about anywhere among those who may or may not understand them, and know not to whom they should reply, to whom not: and, if they are maltreated or abused, they have no parent to protect them; and they cannot protect or defend themselves An interesting thing about computation is that it is a writing and re-writing that can indeed be responsive and, in a non-trivial sense, "answer for itself". LLMs do this in a form that is obviously very successful for engagement (and for hype) and for producing a lot of compelling output. I think the Phaedrus also has something to say here: > Soc. Then [they who who knows the just and good and honourable] will not seriously incline to "write" his thoughts "in water" with pen and ink, sowing words which can neither speak for themselves nor teach the truth adequately to others? > > Phaedr. No, that is not likely. > > Soc. No, that is not likely--in the garden of letters he will sow and plant, but only for the sake of recreation and amusement; he will write them down as memorials to be treasured against the forgetfulness of old age, by himself, or by any other old man who is treading the same path. He will rejoice in beholding their tender growth; and while others are refreshing their souls with banqueting and the like, this will be the pastime in which his days are spent.

nixonaddiction 1mo ago

for a lot of the article i was mentally replacing "ai" with "calculator" and going "yeah we will just need longer education times. more schooling etc." but the phrasing of "who pays for the increased schooling times?" is a good one. i think "debt" can be a decent way to conceptualize the cost and repayment of training someone. feels evil to say, but viewing people as firms you can invest in and expect returns upon. you know not all loans will be repayed, but hopefully they'll average to a profit. (risk management etc.) student loans are. a decent example. the government/private enterprise gives money to pay for education, then this is repayed, providing a financial incentive for paying for someone else's longer schooling timelines. firms investing in training can be viewed as an extension of student loans. but then ah, there are countless stories of how debtor/creditor relationships can be exploited. indentured servitude etc. there are a lot of complications coming to mind. also "altruistic" people who give without expectation of repayment. or the divide between like, communal vs individualistic cultures. (individualism, i argue, encourages the formalization of debt, as opposed to a more communal culture where the expectation of repayment is informal.) you could do math on how many people pay vs how many people benefit, who is the biggest stakeholder, etc. but i am on my lunch break and need to get back to my work. good article tho. good topic to bring up.

culebron21 1mo ago

Similar to the argument made by John Blow several years ago. Though, Blow blamed frameworks/engines and layers of abstractions. I wonder if the authors came to this framing themselves, or listened him. https://www.youtube.com/watch?v=q3OCFfDStgM https://www.youtube.com/watch?v=q3OCFfDStgM

jmfldn 1mo ago

My approach is to write a bit of totally AI-free code every day. So after a day of Claude, I'll spend at least 30 mins wrestling with something. The gnarlier the better, e.g.leet code or Project Euler-type stuff. I think of it as like lifting weights for the mind. The more I struggle at the edge of my knowledge and skill the better. The other thing is to give your agent a skill not to solve certain key problems unless explicitly prompted. Write the scaffolding sure, but leave the juicy parts alone. And if I get stuck, I have it enter into a dialogue with me, nudging me towards understanding.

bogzz 1mo ago
I solved a Leetcode Medium on my first try in about 10 minutes the other day and it felt so amazing. Thinking through architecture, project composition, composability, etc when working with agents felt fine for a while but it made me feel disconnected from what I'm actually building. Actually engaging my brain to solve the lower-level, on-the-ground code allows me to think of better ways to do things while I'm writing them. It's like writing anything. You start with something you want to convey, a thesis, and then it evolves and becomes better as you write it. An agent will just write it with no thought, as in it will reflect one of the LLM 'ghosts' as Andrej Karpathy puts it, doing something in the same way that someone in the training data has done it on a similar or different problem. This is why I get conniptions now when I am sent generated text or am expected to read it on a public forum. It's disrespectful of the time of every person expected to read it. That said, I wouldn't like to go back to the before times without having the agentic option available. Ideally, businesses should not mandate how LLM's are to be used at their company, and just let the devs find their own flow. That is, if quality is even a factor that any company optimizes for anymore.

Animats 1mo ago

The pseudo-academic style of the article is awful. All abstractions and buzzwords, no examples. Also, the tragedy of the commons concept is far older than 1968. The term "common" refers to common grazing land upon which anyone could graze animals. That's an English term. The American equivalent is "open range". Getting past that, the author has a point. There's a loss of shared expertise when there aren't people around learning and doing something. In the US, we've seen this in manufacturing. The number of Americans who know how to set up a good production plant is much lower than it was in the 1980s. That's the consequence of the hollowing out of American manufacturing. The author talks about AI vs. white collar work, but fails to make the connection with outsourcing vs. blue collar work. The loss of this expertise has recently been made very clear in the US as attempts are made to scale up weapons production for the US's various wars. Progress is very slow, as has been seen with both artillery ammo and air-defense missiles.

PaulDavisThe1st 1mo ago
> Also, the tragedy of the commons concept is far older than 1968. The term "common" refers to common grazing land upon which anyone could graze animals. That's an English term. The American equivalent is "open range". The term is not "common" or "commons" but "tragedy of the commons" which dates back to a book in 1968 by Garrett Hardin. Elinor Ostrom subsequently showed that most or all of Hardin's assumptions and claims were wrong, or at the very least, far from universal, and that the process he describes elides what actually drives the destructions of resources held in common: greed and power.
- zaphar 1mo ago
  I think you might be thinking about Elinor Ostrom and she didn't show that his assumptions and claims were wrong exactly. She expanded on the work to clarify the difference between managed vs unmanaged commons. Showing that successful commons are managed in some way with established rules and limits around the usage. The term still has use especially if it is used to clarify the need for management of common resources to avoid the tragedy.
  - 1mo ago

jgalt212 1mo ago

Perhaps, but I find when I use AI (for fixing things), I learn a few things here and there as the AI-provided answers are often wrong. And when I work around these errors, the learning occurs.

zackmorris 1mo ago

I thought the article was going to be about countless millions of minds trying to win the internet lottery and merely reinventing the wheel or failing. I'm not worried about AI taking jobs. I'm worried that humanity has lost the ability to share at such a monumental level that basic sustenance and financial security are out of reach, even with AI. After lifetimes of negative reinforcement, the only salvation seems to be the disruption of capitalism itself. Somewhat ironically, the wealthiest and most powerful people in the world seem to be investing trillions of dollars into AI to do just exactly that.

foxglacier 1mo ago
They are not out of reach - people just increase their expectations to ensure that they never achieve satisfaction. I think that's fine but it is optional - if you want to just exist without striving for anything, nobody's stopping you. It's easy to be self-sufficient if you'll tolerate pre-industrial standards of living. There are others who want that too and you can coordinate with them and share among yourselves. This already happens. Modern standards of living and your high expectations are a consequence of capitalism. Ironically, you can actually have your cake and eat it too. So many other people love to participate in capitalism, that they provide enough good things to make self-sufficient living easier today than it was in pre-industrial times. No, humanity hasn't lost the ability to share - it's the exact opposite - trade (and capitalism) has enabled sharing far beyond what it ever was before. Even better, it's done though voluntary and mutually beneficial exchange rather than people being forced into a fixed role in life which was often something horrible like servant, slave-girl, or warrior.

sfny 1mo ago

This paper misrepresent fundamental concepts from Ostrom’s work, which won a Nobel, and fails to contextualize Hardin’s theories. As a 'human resource development' paper it somehow pretends that capitalism doesn't exist? Hardin coined "The Tragedy of the Commons" in 1968, elaborated on his theory in his 1974 paper "Lifeboat Ethics: the Case Against Helping the Poor". He was a eugenicist and specifically targeted refugees. He lobbied US Congress in opposition to international famine relief. His evidence-free theories must be contextualized within his overall white-nationalist project. https://www.splcenter.org/resources/extremist-files/garrett-hardin https://www.splcenter.org/resources/extremist-files/garrett-... The paper asserts that "expertise within a profession" is a commons. As an industry we've never been able to define the specific, task-level role boundaries between PM/designer/engineer across companies. So how is a profession defined? What are the units of expertise here? This paper fails to provide a defensible definition of their commons. Ostrom's commons need clear boundaries and resource units. https://en.wikipedia.org/wiki/Elinor_Ostrom https://en.wikipedia.org/wiki/Elinor_Ostrom From the abstract: "*The paper reframes expertise development as collective stewardship*" which ignores capitalism. Firms are incentivized to build proprietary expertise, eg Slang at Goldman. Individuals are incentivized to build proprietary expertise and use it as leverage for higher compensation. Even if we fudge commons into a more generic collective action problem, this paper doesn't reckon with the tension between market incentives and collective expertise. This tension comes up again and again, in open source, in academia, and corporate L&D programs. The author goes on to use professional organizations as an example of governance for their Cognitive Commons. The examples of medicine, law, and engineering are particularly bad as these are credentialed, legally enforced enclosures of expertise, and not self-policing or democratic. They are the opposite of commons. The author should have just written about expertise as a resource pool and avoided the commons. This was a frustrating read. The paper is a disservice to the commons literature.

treetalker 1mo ago
Law practice in the United States is self-policing.
- sfny 1mo ago
  We can view the bar association as a self-policing group to some extent. But the unauthorized practice of law is a crime in most jurisdictions, so it's policed by the State. In the context of Ostrom's commons this means a hypothetical 'lawyer-commmons' exists at the whim of the State and is unlikely to survive. In practice, a fake lawyer serving jail time can't get out of jail by negotiating with the bar association for access to lawyering. It's similar for medicine and engineering. I take your overall point that professional organizations have internal rules, decorum, membership criteria, etc. If you're at all interested, Ostrom's 8 rules for managing the commons are worth a read.

i_s 1mo ago

Maybe we have to subsidize zoomers until we can figure this out.

foxglacier 1mo ago
And if the solution turns out to be "we don't need those skills anymore", what will happen to those subsidized people? Better just let them find work wherever they see a demand. Software has gutted many other industries of competent people. Maybe now they can return and lift up the rest of the economy.

cadamsdotcom 1mo ago

We will look back on this era as one of transition. AI is in its "look monkey can do tricks how cute" era - but it won't be long. For instance the era of "whoa" is happening right now in mathematics (Anthropic researchers are pushing math's frontier with little more than the prompt "you can do it" - ie. brute force), and in coding agents we're crossing over - look into leading-edge benchmarks like SlopCodeBench that are pushing labs to RL for long term codebase health and not just problem-solving. The reason I say coding agents will go in this direction is labs are competing to have the most appealing models and so seeking out new unsaturated benchmarks they can hill-climb and show flashy results from, demonstrate to customers they're the best and deserve spend. What these cognitive tools do is make the mundane work we're lamenting the loss of redundant. Who cares if junior devs can't code? When this stuff really gets going they'll be using their answer boxes to both code AND to have have design discussions with a form of intelligence that has every PhD ever obtained and infinite patience. Consider: long division used to be in school curricula; our forebears had to know it to be considered "educated"; and yet I, in my 40s, was never taught long division. Where did it go?