I have been writing software for over 40 years and have had a long time interest in and some work in AI over that time. I wouldn’t say this gives me any more prognosticating power about how all of this is ultimately going to go, but I believe we're soon nearing an area of plateauing; whether that's because the science itself is plateauing or the intervention of governments is going to force plateau it.
So if things continue as they are today, I think in the near future, being a software developer is going to be more analogous to the medical field, where in the medical field you have different levels of professional expertise.
Some will be like nurses, and some will be closer to a medic and a smaller set will be like doctors. Each with increasingly required knowledge and experience to fulfill a needed role.
Those who used to be actual software developers are going to be (or have to become) more in the doctor role with years of internship and practical experience to be the architects guiding the overall AI implementation of software development in organizations.
The medics are going to be people who are semi-technical, where they have some technical understanding but they don't dedicate themselves to it, like say product managers, where they jump in to help development along, but don't need to have many years of experience or very deep technical knowledge.
At the nurse level, it's probably going to be similar to what people would do in the past with no code tools, where somebody in marketing who knows very little to nothing about coding at all is just going to directly converse with AI systems, but they'll never be likely to get anything more advanced than the tools they could think up for themselves.
Of course, it's so hard to tell what the next big discovery or changes to the nature of world society might push things in one direction or another.
Just FYI, if you know much about the medical field, nurses tend to do most of the actual work, with highly experienced nurses actually taking up the mantle for many duties often done by doctors. Nurses are in far higher demand, than doctors.
Your analogy isn’t necessarily wrong, but it might ignore the extreme importance of nurses. Many medical facilities are only staffed with permanent nurses, with doctors helicoptering in, from time to time, to take care of specific duties that may require certain licenses, or provide specific advice.
I completely agree with you, and I certainly meant no offense to anyone who's a practicing nurse.
I spent some time in the military, and my expression of medics and nurses are mostly derived from that experience, where I'm referring to a nurse as just any warm body who is able to provide aid.
For professional nurses who might work in hospitals, I'm sure that many of them have significant knowledge and experience to be very effective in providing medical assistance.
I think what's actually happening is that the "threshold" of technical understanding required to be more productive than average is increasing, and other non-technical skills are becoming more important. Those below the threshold are not able to provide value over anyone else, even if they have a lot of technical experience. For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
Wishful thinking by the managerial class. At best they can vibe code but they can’t verify that what was written is correct.
> Some will be like nurses, and some will be closer to a medic and a smaller set will be like doctors. Each with increasingly required knowledge and experience to fulfill a needed role.
Nursing and being a physician aren't really the same thing at all, and they require different skill sets, it's not just "having more knowledge". Just because someone is an amazing surgeon doesn't mean they would also make a good nurse.
> Those who used to be actual software developers are going to be (or have to become) more in the doctor role with years of internship and practical experience to be the architects guiding the overall AI implementation of software development in organizations.
I think you just described a staff swe
> The medics are going to be people who are semi-technical, where they have some technical understanding but they don't dedicate themselves to it, like say product managers, where they jump in to help development along, but don't need to have many years of experience or very deep technical knowledge.
These people already exist. They are the business analysts who know SQL and maybe Python, R, or VBA. Marketing people who work on Wordpress landing pages. People doing systems integration, the IT department, sales engineers, and on, and on, and on.
> At the nurse level, it's probably going to be similar to what people would do in the past with no code tools, where somebody in marketing who knows very little to nothing about coding at all is just going to directly converse with AI systems, but they'll never be likely to get anything more advanced than the tools they could think up for themselves.
You said it, no code/low-code has existed forever.
That’s a good analogy, but I think the reason we currently need the "nurse" role is the need to interact with the physical world. Most software products don't require this step, so the demand for “nurses” or "doctors" will likely decrease.
If robotics technology continues to advance, the number of nurses in real world will also decrease in the foreseeable future.
Welcome to the current day difference between being an Accredited Engineer and being a Developer. The only thing that's happening is that the Developer side are getting a wake up call.
> So if things continue as they are today, I think in the near future, being a software developer is going to be more analogous to the medical field, where in the medical field you have different levels of professional expertise.
The medical field is also going to change though. Massively. Because people are going to realize you don’t need to pay someone $400k per year to hand out advice about moderate exercise and which antibiotic is appropriate for a sneeze-cough with yellow mucus.
Regulation isn’t going to prevent this. AI is already way too easily accessible to ever rein it in again. Not to mention that the US now has serious competition from a hostile country, so they can regulate their own AIs all they want without it making a difference in practice.
> Because people are going to realize you don’t need to pay someone $400k per year to hand out advice about moderate exercise and which antibiotic is appropriate for a sneeze-cough with yellow mucus.
Who is going to realize that?
The same forces that prevent you from walking into a pharmacy and asking for antibiotics based on what you found on WebMD will prevent you from doing it with a ChatGPT printout in hand. Lawyers and doctors are the best-known examples of industries that are in control of who gets admitted to practice the profession.
It's basically a formality now to get a prescription for what you read on WebMD. Every Insurance has telemedicine, you just call, read the symptom list and get the prescription. Some even let you just email. There's a doctor or at least person with subscribing ability in the loop, but they are barely doing more than rubber stamping hundreds of requests per day.
You need to first address 1)What is work? 2)Why we need to work?
Animals don't "work". Not atleast for their own sake. If there is enough green pasture and water around, they don't even migrate to other places. So if work is meant to provide food and shelter and if machines can ensure that, humans don't need to "work".
Wealth is only a reserve capacity to help future generations so that they don't need to work for their basic needs. But if machines ensure that too, then wealth itself, as a reserve, is unnecessary.
There exists to many complex things in the world and we cannot do it all ourselves. We work so that we have something of value to trade to the people who do the work on the things we want.
We will never automate all work so we with half of humanity doing nothing of value it will be a struggle for the people who do nothing of value to convince people to do work for them.
We can see it now where products dont target the people without money. There is no point because they cant give you any reward so instead you do your work for the people that can give you something in return. We can use the government to stimulate and balance this a bit but at a certain point the number gets to high and things collapse.
The other issue is Gen Z and Gen A are now very much opposed to AI. I'm wondering with those two sets of generations who already have a very negative view of AI, how AI can survive that coming tsunami of change.
According to WRITER’s 2026 Enterprise Adoption Survey, 44% of Gen Z employees admit to sabotaging their company's AI strategy in at least one way compared to 29% of employees overall.
Sabotage behaviours include entering proprietary information into AI tools, using non-approved AI tools, refusing to use AI tools or outputs, ignoring guidelines or best practices, intentionally generating low-quality outputs, refusing to take AI training and tampering with performance metrics to make AI appear to underperform.
This is true as a sentiment, but my understanding is that the majority of students are overwhelmingly using AI for ~everything. If a thing provides massive utility people will use it.
I recently sat in on a lecture at my old uni and noticed almost every student heavily using ai. So I agree it's a but heavy handed to day young people dislike ai as a monolith.
People dislike and are dependent on things all the time. What'll be interesting to see is how that classroom of students will feel towards AI when it leaves school. I am uncomfortable with AIs being used in schools this way, myself, like almost without exception. I mean, geez, how do you compete? Do you just sort of have to, once a certain number of your classmates uses it for stuff like essays? Do they curve essays anymore?
- Work is shifting from building/doing to evaluating, judging, and steering — that's where human value will concentrate.
Other supporting points.
------
- No lab milestone or "RSI breakthrough" will suddenly eliminate jobs — economic impact unfolds gradually over decades.
- Reliability, not raw capability, is the real bottleneck holding back AI automation today.
- Historically, making work cheaper/faster (ATMs, radiology, coding) has grown employment, not destroyed it.
- Superintelligence claims misunderstand human intelligence, which is itself amplified by tools like AI ("co-superintelligence").
It is not a good idea to compress articles like this but there are many of these opinions to read and trying to get to the point quickly to uncover new viewpoints.
He's basically saying that even though AI capability is high and rapidly increasing, it is not reliable, creative or tasteful enough to replace humans. Further he implies that it will take decades before this is the case.
But we already do have have some kind of measurement of most of these types of side factors, and they actually aren't at zero and are increasing rapidly. So the implication that they will not be human level until decades from now is just (hopeful?) speculation or fuzzy thinking.
To me this looks like a really academic and official sounding version of the same quasi-religious hopium that usually defends the sanctity of the human. He is essentially saying that there is just something so special about humans that it will never be reproduced in a machine. It's very similar to dualism (and in many people actually is religious dualism). No AI is going to have human creativity or judgement. Not anytime soon. Why? Well, we all just _know_ that's not possible. Okay, maybe in a couple of decades (but they don't necessarily believe that anyway). Why would that take decades? Well we all can just _tell_ it's no where close, right? Because AI of today just isn't special like humans.
Aside from that worldview issue, I think that people still are not taking seriously or internalizing the concept of exponential improvement.
Computing efficiency gains can actually level off. In fact, they have many, many times before. But they always tilt back up again when we invent the next approach to get beyond the current level. This is how it has been for 90 years.
There are multiple ways that we continue to see huge gains in AI software, architecture, and hardware. There are huge efficiency gains available still as we move towards more radical fully compute in memory and/or analog approaches and other options like models implemented in hardware.
I have the opposite, because I'm now getting things clients generated that they want me to implement. It's definitely more work and money for me, but it's concerning somewhat because ultimately it's not good for their business. It takes me longer to implement this kind of stuff than it would for me to code it from scratch. That is in a working way, the AI generated code has far more bells and whistles, but also layers and layers of needless complexity that quite literally add no value as in they aren't even a factor of the finished output.
The problem is they are now paying me more, plus paying for the cost of using the AI, and the needless complexity also slows down the employees. So more costs there as well, any future debugging is going to cost far more and at the end of the day they are getting less quality on the core function but far more presentation data that is essentially meaningless.
In my org, it's grown the level of work. We had a lot of stuff that was never worth the devtime necessary, but now that's opened up that we can do a lot of this stuff in the background
I think this is underrepresented in everyone's calculations about how AI will affect software engineering. In my experience (and apparently yours as well) this is what many companies are using it for. All those pesky bugs that are minor annoyances but not show-stoppers are getting addressed. They aren't helping us sell more software, but they're dissatisfiers for the customers.
Worth looking into 'Jevons Paradox' for more examples of this sort of thing. TL;DR is that as things become more efficient, whether coal, or programmers, the usage of a good increases as demand skyrockets for what it can be used for.
But it's at my day job, and it's because I was able to write a prompt which automates having Copilot review uploaded scanned PDFs of invoices with checks (and the bank line obscured with a pen, so no PII) and then write a batch file which renames the files per a file-naming convention, removing the need to open them in batches of 50, find the Invoice ID, re-save using that filename, then quit and re-launch Adobe Acrobat (if left running, eventually I run into a bug where it stops saving files), then run a .bat file which renames based on Invoice ID as a filename.
Problem of course is I've been running into a limit of number of allowed files per 24 hr. period.
Even if it's not less work, it feels like less effort.
If you are asking if the machine translated from one language to another for him, the answer is essentially guaranteed to be yes. Inputting raw machine code hasn't been the norm since the 1950s.
If AI is used to solve the socialist calculation problem, most of you will die.
If AI is subject to private ownership in a competitive market between competing suppliers, it will be like better cars, we’ll just drive faster.
Power consumption will be a limiting factor in those countries relying on intermittent, weather dependent power generation with no base load. Especially if users prefer Apple’s privacy first AI on edge devices.
Hopefully in western countries it can encourage more young women to bear three children before they turn 35. Young men have to pick up their game and create an environment to redirect their suicidal empathy into more productive pursuits.
“Where can you find another non-linear servo-mechanism weighing only 150 pounds and having great adaptability, that can be produced so cheaply by completely un-skilled labour?” - Albert Crossfield 1954
> A battle of two narratives
> Build wealth before AI obviates our skills
> Build skills, agency, taste, judgement
both narratives are portrayed as being odds with each other but, I can't come up with a single "build wealth" scenario that doesn't involve building skills, agency, taste and judgement.
Mr. Narayanan seems to be trying to be a bit more positive than the vibe I am getting off of his presentation. Or maybe it is just sort of meant to make us all experience our shoved-down anxiety about being phased out with nowhere else to go. A lot of adaptation to do sounds not so fun. So I kind of think that is not a terrible point, if true.
I sort of worry about things like AI figuring out scripts so well that even multi-tier support work is gone. And learning how to write fiction or create foods so in accordance to our tastes (sugar, fat, etc with food, exactly what each of us is interested in, with writing) that we even lose those truly human creative jobs. Might not ever wanna leave those bubbles.
So much of the human drive is exploration and why and what if. Assuming everyone in the world can have no money problems, what will AI not be able to figure out? Will we enjoy the equivalent of a major breakthrough if an AI solves it in five minutes, or just the outcome? Why learn things?
AI could be a horrible jailor. And better at cancelling than any perhaps sager Gen Z or millenial. Bears some caution to be wary of this and where that power sinkhole will go.
But then, I still think the previous AI winters were more a result of sense and caution than most of us know, and we cannot fathom our species' ways of reasoning/thought processes the way we did as a species thirty, fifty, eighty years ago. Erring on the side of caution is not a terrible thing.
I mean, I have worked and work with AI, but it seems weird for us as a species not to have placed guardrails to prevent us from wiping one anothers' careers and relationships out. What will we talk about? If our generative AIs should be allowed to date?
Again, I am assuming a fast, though not sudden, acceleration that would compound, and sooner than most probably think.
The answer to this question after a lot of reflection: games.
AI can slop fork or clone existing software well, but a clone of an existing game is pointless, it's basically guaranteed to be derivative and worse than the original game, and games aren't so expensive that you can't just buy the original. AI can't know if new mechanics or angles to an existing genre will feel good to play, or if a new genre is fun, that requires a human to experience the game in its totality.
Games are also very resilient to sloppy AI coding, and if an indy game crashes nobody is getting paged.
Remember when they created "COBOL" so that everyone could write programs? This is just round two.
If you think it is different, just think of how many people write books professionally, or even publish online.
Once the noise settles down a bit and boardroom shakes off their delusions as you can see in rehiring in Ford and Zuck who was very bull on AI remark about "not being it". It will be just the same, but different.
If we were more connected to all the problems that exist in the world, we’d become acutely aware of just how much work there is to do, and we’d eagerly reach for any tool that could help us do more, faster.
Okay, but let's say this happens, and in your utopian world everyone feels equally capable, judges their skills accurately, and gets along... what do people do? Assign things and use git? What if you keep wanting to work on any of these things and as soon as you are a week into every last thing you are working on, some random person comes along and says, hey dude (or dudette), I finished that, you were taking too long? What if that random person were an AI or chatbot that got bored?
I like this article because it seems to go into decent depth on the “framework” that the author comes up with.
However, this following quote has a simple reason that I don’t see anywhere in the article or framework:
“””
Why is there a huge gap between what people in various occupations could be using AI for and what they’re actually using it for? One reason could be that people are slow to adopt technology, and that’s certainly part of our framework.
“””
I would like to add a reason: that the Silicon Valley companies who developed the LLMs are brigands: cognizant of their actions, they have stolen (and continue to steal) the world’s copyrighted material and are selling it back to the masses and the politicians as if they are the arbiters of information itself.
Specifically responding to the quoted question, I could be using Claude or ChatGPT or Grok or DeepSeek or any other to have come up with this comment, or to write emails, or to implement my Python for me, etc., but I use none of them for anything. Doing business with brigands is a choice, and a choice that I hope becomes less and less palatable so that the financial, political, social, and moral fever that is our zeitgeist finally breaks.
Come on now: we translate vague ambitions into communications for non-living entities to do human bidding. Until we have recreated humanity as mythic gawds, there is a ton of work to do.
I have been writing software for over 40 years and have had a long time interest in and some work in AI over that time. I wouldn’t say this gives me any more prognosticating power about how all of this is ultimately going to go, but I believe we're soon nearing an area of plateauing; whether that's because the science itself is plateauing or the intervention of governments is going to force plateau it.
So if things continue as they are today, I think in the near future, being a software developer is going to be more analogous to the medical field, where in the medical field you have different levels of professional expertise.
Some will be like nurses, and some will be closer to a medic and a smaller set will be like doctors. Each with increasingly required knowledge and experience to fulfill a needed role.
Those who used to be actual software developers are going to be (or have to become) more in the doctor role with years of internship and practical experience to be the architects guiding the overall AI implementation of software development in organizations.
The medics are going to be people who are semi-technical, where they have some technical understanding but they don't dedicate themselves to it, like say product managers, where they jump in to help development along, but don't need to have many years of experience or very deep technical knowledge.
At the nurse level, it's probably going to be similar to what people would do in the past with no code tools, where somebody in marketing who knows very little to nothing about coding at all is just going to directly converse with AI systems, but they'll never be likely to get anything more advanced than the tools they could think up for themselves.
Of course, it's so hard to tell what the next big discovery or changes to the nature of world society might push things in one direction or another.
Just FYI, if you know much about the medical field, nurses tend to do most of the actual work, with highly experienced nurses actually taking up the mantle for many duties often done by doctors. Nurses are in far higher demand, than doctors.
Your analogy isn’t necessarily wrong, but it might ignore the extreme importance of nurses. Many medical facilities are only staffed with permanent nurses, with doctors helicoptering in, from time to time, to take care of specific duties that may require certain licenses, or provide specific advice.
So lots of jobs for nurses.
I completely agree with you, and I certainly meant no offense to anyone who's a practicing nurse.
I spent some time in the military, and my expression of medics and nurses are mostly derived from that experience, where I'm referring to a nurse as just any warm body who is able to provide aid.
For professional nurses who might work in hospitals, I'm sure that many of them have significant knowledge and experience to be very effective in providing medical assistance.
I think what's actually happening is that the "threshold" of technical understanding required to be more productive than average is increasing, and other non-technical skills are becoming more important. Those below the threshold are not able to provide value over anyone else, even if they have a lot of technical experience. For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
For example, I think today a strong PM with no technical ability can produce higher quality technical output compared to a mediocre frontend developer with no project management ability.
Wishful thinking by the managerial class. At best they can vibe code but they can’t verify that what was written is correct.
Bad take. What you're describing already exists.
> Some will be like nurses, and some will be closer to a medic and a smaller set will be like doctors. Each with increasingly required knowledge and experience to fulfill a needed role.
Nursing and being a physician aren't really the same thing at all, and they require different skill sets, it's not just "having more knowledge". Just because someone is an amazing surgeon doesn't mean they would also make a good nurse.
> Those who used to be actual software developers are going to be (or have to become) more in the doctor role with years of internship and practical experience to be the architects guiding the overall AI implementation of software development in organizations.
I think you just described a staff swe
> The medics are going to be people who are semi-technical, where they have some technical understanding but they don't dedicate themselves to it, like say product managers, where they jump in to help development along, but don't need to have many years of experience or very deep technical knowledge.
These people already exist. They are the business analysts who know SQL and maybe Python, R, or VBA. Marketing people who work on Wordpress landing pages. People doing systems integration, the IT department, sales engineers, and on, and on, and on.
> At the nurse level, it's probably going to be similar to what people would do in the past with no code tools, where somebody in marketing who knows very little to nothing about coding at all is just going to directly converse with AI systems, but they'll never be likely to get anything more advanced than the tools they could think up for themselves.
You said it, no code/low-code has existed forever.
Tech work has been organized and divided this way for decades.
That’s a good analogy, but I think the reason we currently need the "nurse" role is the need to interact with the physical world. Most software products don't require this step, so the demand for “nurses” or "doctors" will likely decrease. If robotics technology continues to advance, the number of nurses in real world will also decrease in the foreseeable future.
Welcome to the current day difference between being an Accredited Engineer and being a Developer. The only thing that's happening is that the Developer side are getting a wake up call.
> So if things continue as they are today, I think in the near future, being a software developer is going to be more analogous to the medical field, where in the medical field you have different levels of professional expertise.
The medical field is also going to change though. Massively. Because people are going to realize you don’t need to pay someone $400k per year to hand out advice about moderate exercise and which antibiotic is appropriate for a sneeze-cough with yellow mucus.
Regulation isn’t going to prevent this. AI is already way too easily accessible to ever rein it in again. Not to mention that the US now has serious competition from a hostile country, so they can regulate their own AIs all they want without it making a difference in practice.
> Because people are going to realize you don’t need to pay someone $400k per year to hand out advice about moderate exercise and which antibiotic is appropriate for a sneeze-cough with yellow mucus.
Who is going to realize that?
The same forces that prevent you from walking into a pharmacy and asking for antibiotics based on what you found on WebMD will prevent you from doing it with a ChatGPT printout in hand. Lawyers and doctors are the best-known examples of industries that are in control of who gets admitted to practice the profession.
It's basically a formality now to get a prescription for what you read on WebMD. Every Insurance has telemedicine, you just call, read the symptom list and get the prescription. Some even let you just email. There's a doctor or at least person with subscribing ability in the loop, but they are barely doing more than rubber stamping hundreds of requests per day.
You've been able to Google your symptoms and get a maybe answer for twenty years. I don't see how AI replaces doctors any more than WebMD did.
By achieving the same or a higher level of effectiveness than doctors, obviously.
Why would the government force the technology to plateau when the Chinese won't? Outdoing the Chinese is the Trump admin's biggest hobby.
Could have sworn it was trying to convince Iran to accept a peace plan after killing their former leaders who would have committed to one.
You need to first address 1)What is work? 2)Why we need to work?
Animals don't "work". Not atleast for their own sake. If there is enough green pasture and water around, they don't even migrate to other places. So if work is meant to provide food and shelter and if machines can ensure that, humans don't need to "work".
Wealth is only a reserve capacity to help future generations so that they don't need to work for their basic needs. But if machines ensure that too, then wealth itself, as a reserve, is unnecessary.
There exists to many complex things in the world and we cannot do it all ourselves. We work so that we have something of value to trade to the people who do the work on the things we want.
We will never automate all work so we with half of humanity doing nothing of value it will be a struggle for the people who do nothing of value to convince people to do work for them.
We can see it now where products dont target the people without money. There is no point because they cant give you any reward so instead you do your work for the people that can give you something in return. We can use the government to stimulate and balance this a bit but at a certain point the number gets to high and things collapse.
I wrote a related article here: https://jonpauluritis.com/articles/good-soldiers-find-wars/
There will always be new, hard problems to work on. AI will not, and can not eliminate that.
The other issue is Gen Z and Gen A are now very much opposed to AI. I'm wondering with those two sets of generations who already have a very negative view of AI, how AI can survive that coming tsunami of change.
According to WRITER’s 2026 Enterprise Adoption Survey, 44% of Gen Z employees admit to sabotaging their company's AI strategy in at least one way compared to 29% of employees overall.
Sabotage behaviours include entering proprietary information into AI tools, using non-approved AI tools, refusing to use AI tools or outputs, ignoring guidelines or best practices, intentionally generating low-quality outputs, refusing to take AI training and tampering with performance metrics to make AI appear to underperform.
> Gen Z and Gen A are now very much opposed to AI
This is true as a sentiment, but my understanding is that the majority of students are overwhelmingly using AI for ~everything. If a thing provides massive utility people will use it.
I recently sat in on a lecture at my old uni and noticed almost every student heavily using ai. So I agree it's a but heavy handed to day young people dislike ai as a monolith.
People dislike and are dependent on things all the time. What'll be interesting to see is how that classroom of students will feel towards AI when it leaves school. I am uncomfortable with AIs being used in schools this way, myself, like almost without exception. I mean, geez, how do you compete? Do you just sort of have to, once a certain number of your classmates uses it for stuff like essays? Do they curve essays anymore?
I'm an advocate for these new tools we have, and by that definition I would be included.
Very open definition of sabotage.
Key point:
- Work is shifting from building/doing to evaluating, judging, and steering — that's where human value will concentrate.
Other supporting points. ------
- No lab milestone or "RSI breakthrough" will suddenly eliminate jobs — economic impact unfolds gradually over decades.
- Reliability, not raw capability, is the real bottleneck holding back AI automation today.
- Historically, making work cheaper/faster (ATMs, radiology, coding) has grown employment, not destroyed it.
- Superintelligence claims misunderstand human intelligence, which is itself amplified by tools like AI ("co-superintelligence").
It is not a good idea to compress articles like this but there are many of these opinions to read and trying to get to the point quickly to uncover new viewpoints.
He's basically saying that even though AI capability is high and rapidly increasing, it is not reliable, creative or tasteful enough to replace humans. Further he implies that it will take decades before this is the case.
But we already do have have some kind of measurement of most of these types of side factors, and they actually aren't at zero and are increasing rapidly. So the implication that they will not be human level until decades from now is just (hopeful?) speculation or fuzzy thinking.
To me this looks like a really academic and official sounding version of the same quasi-religious hopium that usually defends the sanctity of the human. He is essentially saying that there is just something so special about humans that it will never be reproduced in a machine. It's very similar to dualism (and in many people actually is religious dualism). No AI is going to have human creativity or judgement. Not anytime soon. Why? Well, we all just _know_ that's not possible. Okay, maybe in a couple of decades (but they don't necessarily believe that anyway). Why would that take decades? Well we all can just _tell_ it's no where close, right? Because AI of today just isn't special like humans.
Aside from that worldview issue, I think that people still are not taking seriously or internalizing the concept of exponential improvement.
Computing efficiency gains can actually level off. In fact, they have many, many times before. But they always tilt back up again when we invent the next approach to get beyond the current level. This is how it has been for 90 years.
There are multiple ways that we continue to see huge gains in AI software, architecture, and hardware. There are huge efficiency gains available still as we move towards more radical fully compute in memory and/or analog approaches and other options like models implemented in hardware.
Question: Does anybody here yet personally has less (to) work 'cause of AI?
I have the opposite, because I'm now getting things clients generated that they want me to implement. It's definitely more work and money for me, but it's concerning somewhat because ultimately it's not good for their business. It takes me longer to implement this kind of stuff than it would for me to code it from scratch. That is in a working way, the AI generated code has far more bells and whistles, but also layers and layers of needless complexity that quite literally add no value as in they aren't even a factor of the finished output.
The problem is they are now paying me more, plus paying for the cost of using the AI, and the needless complexity also slows down the employees. So more costs there as well, any future debugging is going to cost far more and at the end of the day they are getting less quality on the core function but far more presentation data that is essentially meaningless.
Not me. I made this comment, a few days ago[0]:
> It’s funny. I was looking at my GH activity graph. It’s been pretty solid green, for years. I stay busy.
> But since I’ve been using an LLM, it’s been bright green.
> I always check in code manually. I don’t let the LLM do it.
[0] https://news.ycombinator.com/item?id=48843115
In my org, it's grown the level of work. We had a lot of stuff that was never worth the devtime necessary, but now that's opened up that we can do a lot of this stuff in the background
I think this is underrepresented in everyone's calculations about how AI will affect software engineering. In my experience (and apparently yours as well) this is what many companies are using it for. All those pesky bugs that are minor annoyances but not show-stoppers are getting addressed. They aren't helping us sell more software, but they're dissatisfiers for the customers.
Worth looking into 'Jevons Paradox' for more examples of this sort of thing. TL;DR is that as things become more efficient, whether coal, or programmers, the usage of a good increases as demand skyrockets for what it can be used for.
Maybe?
But it's at my day job, and it's because I was able to write a prompt which automates having Copilot review uploaded scanned PDFs of invoices with checks (and the bank line obscured with a pen, so no PII) and then write a batch file which renames the files per a file-naming convention, removing the need to open them in batches of 50, find the Invoice ID, re-save using that filename, then quit and re-launch Adobe Acrobat (if left running, eventually I run into a bug where it stops saving files), then run a .bat file which renames based on Invoice ID as a filename.
Problem of course is I've been running into a limit of number of allowed files per 24 hr. period.
Even if it's not less work, it feels like less effort.
I’ve never written so much software
Are you the one who wrote it though or just the one who wrote prompts? Not that it matters in the end…
If you are asking if the machine translated from one language to another for him, the answer is essentially guaranteed to be yes. Inputting raw machine code hasn't been the norm since the 1950s.
Yes, AI code generation is the same.
No, but the point is to work just as much and be more productive. No company will ever expect you to work less, unless they are showing you the door.
I have about 10x more to do.
You can if you own the fruit of your labor.
I am self employed, I work now more than ever.
I guess we'll spend all day furiously wanking. Arvind is already getting a head start on that it seems
If AI is used to solve the socialist calculation problem, most of you will die.
If AI is subject to private ownership in a competitive market between competing suppliers, it will be like better cars, we’ll just drive faster.
Power consumption will be a limiting factor in those countries relying on intermittent, weather dependent power generation with no base load. Especially if users prefer Apple’s privacy first AI on edge devices.
Hopefully in western countries it can encourage more young women to bear three children before they turn 35. Young men have to pick up their game and create an environment to redirect their suicidal empathy into more productive pursuits.
“Where can you find another non-linear servo-mechanism weighing only 150 pounds and having great adaptability, that can be produced so cheaply by completely un-skilled labour?” - Albert Crossfield 1954
I like the narrative but the key point
> A battle of two narratives > Build wealth before AI obviates our skills > Build skills, agency, taste, judgement
both narratives are portrayed as being odds with each other but, I can't come up with a single "build wealth" scenario that doesn't involve building skills, agency, taste and judgement.
what am I missing ?
I agree that it is not an Either-Or scenario (https://en.wikipedia.org/wiki/False_dilemma). You are right about that.
I would doubt however that this would be an 'Equals' or 'Implies' scenario. Let go of seeing either of them as binary, and then not even as scalers.
I would take Anthropics "Theoretical limits of A.i" sales brochure, with a very large grain of salt.
Mr. Narayanan seems to be trying to be a bit more positive than the vibe I am getting off of his presentation. Or maybe it is just sort of meant to make us all experience our shoved-down anxiety about being phased out with nowhere else to go. A lot of adaptation to do sounds not so fun. So I kind of think that is not a terrible point, if true.
I sort of worry about things like AI figuring out scripts so well that even multi-tier support work is gone. And learning how to write fiction or create foods so in accordance to our tastes (sugar, fat, etc with food, exactly what each of us is interested in, with writing) that we even lose those truly human creative jobs. Might not ever wanna leave those bubbles.
So much of the human drive is exploration and why and what if. Assuming everyone in the world can have no money problems, what will AI not be able to figure out? Will we enjoy the equivalent of a major breakthrough if an AI solves it in five minutes, or just the outcome? Why learn things?
AI could be a horrible jailor. And better at cancelling than any perhaps sager Gen Z or millenial. Bears some caution to be wary of this and where that power sinkhole will go.
But then, I still think the previous AI winters were more a result of sense and caution than most of us know, and we cannot fathom our species' ways of reasoning/thought processes the way we did as a species thirty, fifty, eighty years ago. Erring on the side of caution is not a terrible thing.
I mean, I have worked and work with AI, but it seems weird for us as a species not to have placed guardrails to prevent us from wiping one anothers' careers and relationships out. What will we talk about? If our generative AIs should be allowed to date?
Again, I am assuming a fast, though not sudden, acceleration that would compound, and sooner than most probably think.
The answer to this question after a lot of reflection: games.
AI can slop fork or clone existing software well, but a clone of an existing game is pointless, it's basically guaranteed to be derivative and worse than the original game, and games aren't so expensive that you can't just buy the original. AI can't know if new mechanics or angles to an existing genre will feel good to play, or if a new genre is fun, that requires a human to experience the game in its totality.
Games are also very resilient to sloppy AI coding, and if an indy game crashes nobody is getting paged.
Remember when they created "COBOL" so that everyone could write programs? This is just round two.
If you think it is different, just think of how many people write books professionally, or even publish online.
Once the noise settles down a bit and boardroom shakes off their delusions as you can see in rehiring in Ford and Zuck who was very bull on AI remark about "not being it". It will be just the same, but different.
Ford: https://www.bbc.com/news/articles/cgrkd41n2v9o IBM: https://qz.com/companies-rehiring-workers-ai-layoffs-automat...
Noise begins to settle down... "Continual RL is all you need" paper comes out.
If we were more connected to all the problems that exist in the world, we’d become acutely aware of just how much work there is to do, and we’d eagerly reach for any tool that could help us do more, faster.
Okay, but let's say this happens, and in your utopian world everyone feels equally capable, judges their skills accurately, and gets along... what do people do? Assign things and use git? What if you keep wanting to work on any of these things and as soon as you are a week into every last thing you are working on, some random person comes along and says, hey dude (or dudette), I finished that, you were taking too long? What if that random person were an AI or chatbot that got bored?
What counts as productive work? Depends on what we value.
We will be sent in to clean up the fallout.
I like this article because it seems to go into decent depth on the “framework” that the author comes up with.
However, this following quote has a simple reason that I don’t see anywhere in the article or framework:
“”” Why is there a huge gap between what people in various occupations could be using AI for and what they’re actually using it for? One reason could be that people are slow to adopt technology, and that’s certainly part of our framework. “””
I would like to add a reason: that the Silicon Valley companies who developed the LLMs are brigands: cognizant of their actions, they have stolen (and continue to steal) the world’s copyrighted material and are selling it back to the masses and the politicians as if they are the arbiters of information itself.
Specifically responding to the quoted question, I could be using Claude or ChatGPT or Grok or DeepSeek or any other to have come up with this comment, or to write emails, or to implement my Python for me, etc., but I use none of them for anything. Doing business with brigands is a choice, and a choice that I hope becomes less and less palatable so that the financial, political, social, and moral fever that is our zeitgeist finally breaks.
'metaverse' aka the spatial internet (prolly by a new name).
Come on now: we translate vague ambitions into communications for non-living entities to do human bidding. Until we have recreated humanity as mythic gawds, there is a ton of work to do.
a professor of computer science at princeton comes up with slop like this. he supposed to be computing not a keynote of woo.
We'll be cleaning up tech debt from over-reliance on AI.
We can't do that until we clean up all the tech debt from promotion oriented development.