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.
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.
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.
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”)
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.
> 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.
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.
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.
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.
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”)
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.
" 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.
> 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.
Why surprised? The elephant is in someone else's room.
Using AI to summarize this.