I’m skeptical of the construct validity of these studies claiming to show GPT levels the playing field. Okay, so you can close a gap in some contrived game that’s played once and has low stakes; cool. In the real world, where people have skin in the game and are beholden to market forces, tools like GPT will have a multiplicative rather than additive effect.
That said, I’m skeptical the effect will be as big as some are claiming. It’s another tool, like stack overflow or syntax highlighting. It will make you faster but it won’t make you more clever.
I fear your model of why there is an outsized return for nerds is wrong and it undermines your claims about increasing equality. What's going on is mostly an effect of people enjoying doing what their good at and therefore investing more in that. Rather than increasing equality, AI helpers will be like the computer was to many boomers: a source of power for those who were good at it and dreed for those who felt they were bad at it.
But while you can power through a dislike of lifting heavy things and force yourself to get good at it for information/STEM type abilities you need to find it fun to play to gain understanding and that's nearly impossible if you hate it because it makes you feel dumb.
AI assistance will be like Photoshop. In theory everyone has the ability to learn to use the tool but some people will enjoy it more while others will come to fear it.
Though, the ability to do more self-paced learning without comparing yourself to others might help.
Also, i don't think your studies prove what you want them to prove. Rather, they seem to be just an unsurprising instance of regression to the mean.
Almost anytime you take a task and offer people a very different quicker way to do it you'll see an apparently larger benefit for those who are the worst under the current system. But that just tells us who will do best under the new system will differ not that it will be less unequal. To measure that you need to look at how much skill at the new method varies given time to master it.
If you gave a bunch of old time craftsmen a CNC machine I bet the slowest ones show the most productivity gain and it may even look like things are more equal because no one has yet had time to develop skills in the new system. Eventual power users and computer phobes look similar in day 1.
--
Formally speaking if you have a random variable of current skill that's uncorrelated with the random variable for skill in the new system then the loweat quartile in the old skill will show the most improvement because they are a random sample as far as the new skill goes.
A very narrow set of points on the study re: law exams:
1. Exam performance has very little to do with the skillsets required to be a superior lawyer in most settings.
2. AI assistance during an exam does not equate to long-term closure of significant performance gaps between average and good students. So much of what lawyers do is oral and extemporaneous.
3. But if AI can produce results superior to average students on items like legal research or document review, then elite lawyers will simply use AI instead of those average students for a variety of tasks currently done by humans, just as they began to do years ago with document review.
We've already eliminated thousands of jobs in the legal profession using AI in document reviews. It's hard to reconcile this with the broader hypothesis.
I don’t see any of this making Bezos any poorer. If anything it’s more likely to proletarianise all wages. The college premium falling relative to the poor is good, if the bottom 20% are growing wages, not if everybody is stagnating or declining but the poor less so.
We are all, relative to billionaires and the very top earners, poor.
Nice article... I would encourage you to consider the following point-of-view...
1) Technology drives productivity which leads to GDP/capita growth [well known]
2) GDP/capita growth makes individuals more powerful as compared to the collective.
3) Major shifts in technology cause major realignments in society.... we are going through one right now as profound as the industrial revolution. Major shifts in technology cause NON LINEAR changes in society. Economists almost always miss the nonlinear changes because they study backwards looking linearized models.
4) As the individual becomes more powerful, coercive (non-persuasive) mechanisms for control become increasingly difficult.
5) Countries with the greatest individual freedoms over a sustained period of time have an ability to statistically out-innovate their competitors. There is no guarantee because this is much like picking stocks... a few massive technology wins make the difference.
6) The role of government is to reflect the energy shifts from these technology shifts. It is a balancing act. Democracies tend to do a decent job at it. Much like a bucking bull... a stiff dictatorship has difficulty. They either kill the economic/technology bull or are bucked off.
The march of history is much better explained as: Technology => economy => politics vs the way history is typically taught with politics as the start.
Prior to industrial machinery, economic success was generally correlated to physical strength. The largest beneficiaries of the Industrial Revolution were physically weaker men.
Today, the economic losers are not physically but cognitively weaker. However, just like the industrial Revolution opened doors for the physically weaker, AI may well open doors for the cognitively weaker. If history really does rhyme, AI should undermine the college wage premium and make even the less intelligent more productive and economically useful.
It will also create huge fortunes of those few people who control the algorithms. But Teddy Roosevelt gave us a model to correct that as well.
This isn’t an article just about energy but I think this has to be pointed out since Noah seems to be such an advocate of solar. Either he is being dishonest or he doesn’t understand the stupidity of levelized cost of energy. Levelized cost of energy is such a stupid concept because it does not take into reliability issues with solar. This does not include the cost of keeping more reliable sources of power online (ie. Coal, natural gas, or nuclear primarily). Therefore, in reality you are just duplicating energy infrastructure, not replacing it. This perfectly explains why electricity prices have doubled in CA in the last decade.Levilized cost of energy is based on a scenario in which solar would have perfect reliability which is ridiculous. Now the counter to that would be well with battery storage we can store the electricity and make the infrastructure reliable. There are two issues with that. First, today’s commercial battery tech allows for at best hours of storage. We are a long ways away from full development of battery tech for longer timeframes of storage let alone full commercialization. Second, the cost of battery storage will be extraordinary which will have to be passed along as higher electricity costs to customers...primarily negatively impacting the same normies Noah talks about the most.
Its actually not surprising that AI improves the output of the below average performers. After all, it is trained on vast amount of human data and is engineered the generate the "most likely" next word. Substitute most likely for mean, median or mode or even p>0.5 and we land up somewhere in the middle of a standard bell curve. So AI adds value to the people on the left side of that bell curve and improves their out put. Not so much for the rest.
What this also means is that with the rapid adoption of AI, the supply of people with average skills would shoot up. This means that wages for such skills would actually drop.
The people on the right side of the bell curve would be impacted differently. The difference between their output and the average output would shrink dramatically. Many would respond to the pressure by upgrading while many would stagnate. The open question is whether there would a higher wage for them. If yes, the net effect over time would be shifting the entire bell curve to the right.
I'd advance the opposite claim and argue that we will see even greater inequality absent government intervention. The reason is because income inequality is a consequence of how hard it is to speed up a project by adding more workers and AI will only make this worse.
I mean why is it that information work has resulted in higher inequality in the first place? Why didn't it just result in more people learning to program or whatever until wages evened out? Because, while you can hire twice the construction workers and finish your building in about half the time if you double the number of programers you might eat up more time in coordinating their efforts as you gain in output. Thus, companies like Google pay a very nonlinear return for greater ability since they can't make up for quality with quantity. EDIT: you can't always halve the time for one building...I meant that if the demand for housing doubles you hire 2x the construction workers but you double the demand for searches you don't hire double the workers to improve your product since there are diminishing returns.
AI turns this process into overdrive. At google for each person with a brilliant idea you need hundreds of people to implement that code. AI will reduce that by an order of magnitude. That makes the people with the best ideas and who can beat use the AI even more relatively valuable.
The first part feels more convincing than the second part. The claims about AI equalization are interesting and novel, I haven't seen them before. It feels intuitively believable, modulo the problem with social studies being 90% flotsam. Plus I use AI, am a happy ChatGPT subscriber and have lots of ideas of what to do with it.
Green power and battery boosting isn't so convincing. I've been hearing this my whole life yet energy usage hasn't gone up, and governments are still forcing people to use drastically less based on fear generated by unreliable academic BS. The bottleneck to energy usage increasing wealth isn't technology, it's a mix of the ruling classes predilection for quasi-religious pseudoscience combined with lack of demand. If I look at my own energy usage, the only thing that'd significantly increase it would be if my country allowed powerful building-integrated air con at scale (they don't, you're only allowed portable units, for climate reasons). Again, the issue isn't how cheap solar power is, the minimization of energy usage at the cost of comfort has actually been encoded into law so people's pricing preferences don't even matter at all.
But beyond that, I'm not sure what I'd spend more energy on. I could upgrade to a bigger house but I'm not bottlenecked on energy costs for that. If energy costs halved right now my consumption would barely change, I feel like I have enough energy for what I want at the moment within the constraints of stupid regulations.
I suspect the increase in energy usage in the 20th century doesn't reflect some fundamental truth about unlimited energy demand (an implicit assumption here), but rather reflects the huge improvement in transportation technologies in that era. A car or plane just uses so much more energy than anything else it dwarfs everything else. But demand for these things is saturated now. Everyone who wants a car has one and I wouldn't do more air travel if costs fell, I already do as much as I want (I'd need more vacation time to do more travel which isn't an energy problem).
61% of Americans say they are living paycheck to paycheck even as inflation cools. Most cannot afford a $500 emergency. Central bank officials have already raised rates 11 times, pushing the Fed’s key interest rate to a target range of 5.25% to 5.5%, the highest level in more than 22 years. Now it feels to me like the Generative A.I. hype bubble is indeed more re-distribution of wealth patterns in the spirit of a Monopolistic Silicon Valley.
Furthermore there's a lot of data that's showing the U.S. is the next Japan in terms of fertility rates. Many GenZ and Alpha cohort women won't be having any kids in tomorrow's America.
A point you have wrong is on energy. Solar and wind have gotten cheap, but they lack storage which means they cannot match up with consumer demand and that is going to create big problems. Solar and wind still do well when they are burdened with storage costs. And by storage, I mean long duration, not short duration batteries.
My mental model is quite different - I think the key distinction is between who uses AI and who builds AI, not who AI helps or doesn’t help. And I think the question is who gets the spoils? The fact that ChatGPT is (currently) free is what makes it seem utopian.
Say you start with 10,000 normie-hours of work to make a product. You invest 1,000 engineer-hours of work to make the process more productive and save 5,000 normie-hours of work. You can either
a) Pay the normies the same per-hour and half as much per-output. Pay the engineers 5x what the normies make per-hour because that’s how much value they added. No extra profit for the company.
b) Pay the engineers 2x what the normies make because that’s what the labor market demands to fill roles. The company saves 30% of its labor costs as profit which it distributed to shareholders.
c) Same as (b) except you distribute the profit to workers and pay both the engineers and the normies 43% more. No profit for the company.
We have been in the land of (a) and (b) for a while. The fact that it’s difficult to monetize ChatGPT is what’s preventing all of the gains from going to shareholders and tech workers. Otherwise it becomes yet another SaaS tool that goes into the company bottom line and funnels money into Silicon Valley.
Software engineer/coder take: I've found copilot convenient to getting the general pattern i'm looking for but plugging it in correctly and the minor tweaking to fit the existing codebase is where some of the skillset is shifting to.
Alternate take, the coding tasks that copilot is solving for will reduce the need of the low performers rather than elevate them. The higher performers will shift from spending their time coding to doing code reviews and tweaking MRs from genAI. GenAI will shift to turning product tickets and bugs into code commits for the higher performers to work on.
Though all these takes are based off assumptions companies will encourage using genAI and that engineers will integrate it into their current workflow..
I'd like to offer a few observations, some of which conflict with and some of which concur with the essay.
Just to give some idea of where I've been, my first programming course in college used punch cards. Only qualified personal (not students) were allowed anywhere near the actual computer. And that big computer had only a fraction of the computing power of today's cell phones.
Anyway, one problem I have with the essay is the questionable use of the word "education". It seems to be a common misperception that education can be measured in terms of years in school. That is not so. One person can spend sixteen years going to school and end up being able to design efficient electrical grid systems. Another person will spend sixteen years, and only have learned to make mediocre art. Another person will never finish college, and end up creating Facebook or Microsoft.
And the amount of education any of us can attain outside of school is limitless. Some of us of course do learn far more than school ever taught us. Others learn little more. So, when we say "High School Diploma" or "College Degree", how much are we really saying? Add to that, that many jobs require some sort of degree, which may freeze out people who are actually quite qualified. In my experience degrees can be more like a ticket than a measure of competence.
In spite of my master's in education, I ended up spending most of my career starting and running an architectural woodworking business. Much of what was said in this essay translates to the trades, as was mentioned. A few centuries ago, nearly all work was done with hand tools. Skilled workers spent many hours doing essentially grunt work. With powered machines, the grunt work was greatly reduced, and skilled workers could spend more time utilizing their actual skills. Productivity improved massively, lesser skilled workers could feed the machines and be more productive than a skilled worker working manually. And of course, CNC production is, at this point, an older technology. Years ago, I took a course in Solidworks, which is incredible engineering design software. I think this dovetails with the essay: Solidworks improves a lesser engineer's productivity far more than it does for a higher skilled engineer.
Some (many) will disagree, but I think we're still in the Model T era of computing. The Model T is mostly notable for being affordable to the average person, not for being a great car, especially by today's standards. You could not just get in and turn a key. You had to be knowledgeable about how cars worked, so that you knew how and when to set the choke, set the spark advance, prime if necessary, turn on the ignition, and then get out front and crank. Probably almost no one today could get a Model T started, yet ten-year-olds can intuitively start and drive today's cars. I see today's consumer software computer as being very flawed and not as intuitive as presumed. In other words, you can't just get in and turn the key. Well, why not?
I've lived thru the computer revolution from the very beginning. The advancements are amazing, but not so very different from the advancements in skilled trades, farming and manufacturing. Yes, computers are part of those advancements. As of right now, I don't see AI as being that much of a game changer. It's just one more advancement, and not so very much more of an advancement than what existed a few years ago. True enough, mediocre artists can now be better artists, but great artists will not become greater. Mediocre writers will become better, but great writers will not benefit at all. And politicians, well, they've always been hopeless.
I’m skeptical of the construct validity of these studies claiming to show GPT levels the playing field. Okay, so you can close a gap in some contrived game that’s played once and has low stakes; cool. In the real world, where people have skin in the game and are beholden to market forces, tools like GPT will have a multiplicative rather than additive effect.
That said, I’m skeptical the effect will be as big as some are claiming. It’s another tool, like stack overflow or syntax highlighting. It will make you faster but it won’t make you more clever.
I fear your model of why there is an outsized return for nerds is wrong and it undermines your claims about increasing equality. What's going on is mostly an effect of people enjoying doing what their good at and therefore investing more in that. Rather than increasing equality, AI helpers will be like the computer was to many boomers: a source of power for those who were good at it and dreed for those who felt they were bad at it.
But while you can power through a dislike of lifting heavy things and force yourself to get good at it for information/STEM type abilities you need to find it fun to play to gain understanding and that's nearly impossible if you hate it because it makes you feel dumb.
AI assistance will be like Photoshop. In theory everyone has the ability to learn to use the tool but some people will enjoy it more while others will come to fear it.
Though, the ability to do more self-paced learning without comparing yourself to others might help.
Also, i don't think your studies prove what you want them to prove. Rather, they seem to be just an unsurprising instance of regression to the mean.
Almost anytime you take a task and offer people a very different quicker way to do it you'll see an apparently larger benefit for those who are the worst under the current system. But that just tells us who will do best under the new system will differ not that it will be less unequal. To measure that you need to look at how much skill at the new method varies given time to master it.
If you gave a bunch of old time craftsmen a CNC machine I bet the slowest ones show the most productivity gain and it may even look like things are more equal because no one has yet had time to develop skills in the new system. Eventual power users and computer phobes look similar in day 1.
--
Formally speaking if you have a random variable of current skill that's uncorrelated with the random variable for skill in the new system then the loweat quartile in the old skill will show the most improvement because they are a random sample as far as the new skill goes.
A very narrow set of points on the study re: law exams:
1. Exam performance has very little to do with the skillsets required to be a superior lawyer in most settings.
2. AI assistance during an exam does not equate to long-term closure of significant performance gaps between average and good students. So much of what lawyers do is oral and extemporaneous.
3. But if AI can produce results superior to average students on items like legal research or document review, then elite lawyers will simply use AI instead of those average students for a variety of tasks currently done by humans, just as they began to do years ago with document review.
We've already eliminated thousands of jobs in the legal profession using AI in document reviews. It's hard to reconcile this with the broader hypothesis.
I don’t see any of this making Bezos any poorer. If anything it’s more likely to proletarianise all wages. The college premium falling relative to the poor is good, if the bottom 20% are growing wages, not if everybody is stagnating or declining but the poor less so.
We are all, relative to billionaires and the very top earners, poor.
Nice article... I would encourage you to consider the following point-of-view...
1) Technology drives productivity which leads to GDP/capita growth [well known]
2) GDP/capita growth makes individuals more powerful as compared to the collective.
3) Major shifts in technology cause major realignments in society.... we are going through one right now as profound as the industrial revolution. Major shifts in technology cause NON LINEAR changes in society. Economists almost always miss the nonlinear changes because they study backwards looking linearized models.
4) As the individual becomes more powerful, coercive (non-persuasive) mechanisms for control become increasingly difficult.
5) Countries with the greatest individual freedoms over a sustained period of time have an ability to statistically out-innovate their competitors. There is no guarantee because this is much like picking stocks... a few massive technology wins make the difference.
6) The role of government is to reflect the energy shifts from these technology shifts. It is a balancing act. Democracies tend to do a decent job at it. Much like a bucking bull... a stiff dictatorship has difficulty. They either kill the economic/technology bull or are bucked off.
The march of history is much better explained as: Technology => economy => politics vs the way history is typically taught with politics as the start.
Prior to industrial machinery, economic success was generally correlated to physical strength. The largest beneficiaries of the Industrial Revolution were physically weaker men.
Today, the economic losers are not physically but cognitively weaker. However, just like the industrial Revolution opened doors for the physically weaker, AI may well open doors for the cognitively weaker. If history really does rhyme, AI should undermine the college wage premium and make even the less intelligent more productive and economically useful.
It will also create huge fortunes of those few people who control the algorithms. But Teddy Roosevelt gave us a model to correct that as well.
This isn’t an article just about energy but I think this has to be pointed out since Noah seems to be such an advocate of solar. Either he is being dishonest or he doesn’t understand the stupidity of levelized cost of energy. Levelized cost of energy is such a stupid concept because it does not take into reliability issues with solar. This does not include the cost of keeping more reliable sources of power online (ie. Coal, natural gas, or nuclear primarily). Therefore, in reality you are just duplicating energy infrastructure, not replacing it. This perfectly explains why electricity prices have doubled in CA in the last decade.Levilized cost of energy is based on a scenario in which solar would have perfect reliability which is ridiculous. Now the counter to that would be well with battery storage we can store the electricity and make the infrastructure reliable. There are two issues with that. First, today’s commercial battery tech allows for at best hours of storage. We are a long ways away from full development of battery tech for longer timeframes of storage let alone full commercialization. Second, the cost of battery storage will be extraordinary which will have to be passed along as higher electricity costs to customers...primarily negatively impacting the same normies Noah talks about the most.
Its actually not surprising that AI improves the output of the below average performers. After all, it is trained on vast amount of human data and is engineered the generate the "most likely" next word. Substitute most likely for mean, median or mode or even p>0.5 and we land up somewhere in the middle of a standard bell curve. So AI adds value to the people on the left side of that bell curve and improves their out put. Not so much for the rest.
What this also means is that with the rapid adoption of AI, the supply of people with average skills would shoot up. This means that wages for such skills would actually drop.
The people on the right side of the bell curve would be impacted differently. The difference between their output and the average output would shrink dramatically. Many would respond to the pressure by upgrading while many would stagnate. The open question is whether there would a higher wage for them. If yes, the net effect over time would be shifting the entire bell curve to the right.
I'd advance the opposite claim and argue that we will see even greater inequality absent government intervention. The reason is because income inequality is a consequence of how hard it is to speed up a project by adding more workers and AI will only make this worse.
I mean why is it that information work has resulted in higher inequality in the first place? Why didn't it just result in more people learning to program or whatever until wages evened out? Because, while you can hire twice the construction workers and finish your building in about half the time if you double the number of programers you might eat up more time in coordinating their efforts as you gain in output. Thus, companies like Google pay a very nonlinear return for greater ability since they can't make up for quality with quantity. EDIT: you can't always halve the time for one building...I meant that if the demand for housing doubles you hire 2x the construction workers but you double the demand for searches you don't hire double the workers to improve your product since there are diminishing returns.
AI turns this process into overdrive. At google for each person with a brilliant idea you need hundreds of people to implement that code. AI will reduce that by an order of magnitude. That makes the people with the best ideas and who can beat use the AI even more relatively valuable.
The first part feels more convincing than the second part. The claims about AI equalization are interesting and novel, I haven't seen them before. It feels intuitively believable, modulo the problem with social studies being 90% flotsam. Plus I use AI, am a happy ChatGPT subscriber and have lots of ideas of what to do with it.
Green power and battery boosting isn't so convincing. I've been hearing this my whole life yet energy usage hasn't gone up, and governments are still forcing people to use drastically less based on fear generated by unreliable academic BS. The bottleneck to energy usage increasing wealth isn't technology, it's a mix of the ruling classes predilection for quasi-religious pseudoscience combined with lack of demand. If I look at my own energy usage, the only thing that'd significantly increase it would be if my country allowed powerful building-integrated air con at scale (they don't, you're only allowed portable units, for climate reasons). Again, the issue isn't how cheap solar power is, the minimization of energy usage at the cost of comfort has actually been encoded into law so people's pricing preferences don't even matter at all.
But beyond that, I'm not sure what I'd spend more energy on. I could upgrade to a bigger house but I'm not bottlenecked on energy costs for that. If energy costs halved right now my consumption would barely change, I feel like I have enough energy for what I want at the moment within the constraints of stupid regulations.
I suspect the increase in energy usage in the 20th century doesn't reflect some fundamental truth about unlimited energy demand (an implicit assumption here), but rather reflects the huge improvement in transportation technologies in that era. A car or plane just uses so much more energy than anything else it dwarfs everything else. But demand for these things is saturated now. Everyone who wants a car has one and I wouldn't do more air travel if costs fell, I already do as much as I want (I'd need more vacation time to do more travel which isn't an energy problem).
61% of Americans say they are living paycheck to paycheck even as inflation cools. Most cannot afford a $500 emergency. Central bank officials have already raised rates 11 times, pushing the Fed’s key interest rate to a target range of 5.25% to 5.5%, the highest level in more than 22 years. Now it feels to me like the Generative A.I. hype bubble is indeed more re-distribution of wealth patterns in the spirit of a Monopolistic Silicon Valley.
Furthermore there's a lot of data that's showing the U.S. is the next Japan in terms of fertility rates. Many GenZ and Alpha cohort women won't be having any kids in tomorrow's America.
A point you have wrong is on energy. Solar and wind have gotten cheap, but they lack storage which means they cannot match up with consumer demand and that is going to create big problems. Solar and wind still do well when they are burdened with storage costs. And by storage, I mean long duration, not short duration batteries.
My mental model is quite different - I think the key distinction is between who uses AI and who builds AI, not who AI helps or doesn’t help. And I think the question is who gets the spoils? The fact that ChatGPT is (currently) free is what makes it seem utopian.
Say you start with 10,000 normie-hours of work to make a product. You invest 1,000 engineer-hours of work to make the process more productive and save 5,000 normie-hours of work. You can either
a) Pay the normies the same per-hour and half as much per-output. Pay the engineers 5x what the normies make per-hour because that’s how much value they added. No extra profit for the company.
b) Pay the engineers 2x what the normies make because that’s what the labor market demands to fill roles. The company saves 30% of its labor costs as profit which it distributed to shareholders.
c) Same as (b) except you distribute the profit to workers and pay both the engineers and the normies 43% more. No profit for the company.
We have been in the land of (a) and (b) for a while. The fact that it’s difficult to monetize ChatGPT is what’s preventing all of the gains from going to shareholders and tech workers. Otherwise it becomes yet another SaaS tool that goes into the company bottom line and funnels money into Silicon Valley.
Software engineer/coder take: I've found copilot convenient to getting the general pattern i'm looking for but plugging it in correctly and the minor tweaking to fit the existing codebase is where some of the skillset is shifting to.
Alternate take, the coding tasks that copilot is solving for will reduce the need of the low performers rather than elevate them. The higher performers will shift from spending their time coding to doing code reviews and tweaking MRs from genAI. GenAI will shift to turning product tickets and bugs into code commits for the higher performers to work on.
Though all these takes are based off assumptions companies will encourage using genAI and that engineers will integrate it into their current workflow..
I'd like to offer a few observations, some of which conflict with and some of which concur with the essay.
Just to give some idea of where I've been, my first programming course in college used punch cards. Only qualified personal (not students) were allowed anywhere near the actual computer. And that big computer had only a fraction of the computing power of today's cell phones.
Anyway, one problem I have with the essay is the questionable use of the word "education". It seems to be a common misperception that education can be measured in terms of years in school. That is not so. One person can spend sixteen years going to school and end up being able to design efficient electrical grid systems. Another person will spend sixteen years, and only have learned to make mediocre art. Another person will never finish college, and end up creating Facebook or Microsoft.
And the amount of education any of us can attain outside of school is limitless. Some of us of course do learn far more than school ever taught us. Others learn little more. So, when we say "High School Diploma" or "College Degree", how much are we really saying? Add to that, that many jobs require some sort of degree, which may freeze out people who are actually quite qualified. In my experience degrees can be more like a ticket than a measure of competence.
In spite of my master's in education, I ended up spending most of my career starting and running an architectural woodworking business. Much of what was said in this essay translates to the trades, as was mentioned. A few centuries ago, nearly all work was done with hand tools. Skilled workers spent many hours doing essentially grunt work. With powered machines, the grunt work was greatly reduced, and skilled workers could spend more time utilizing their actual skills. Productivity improved massively, lesser skilled workers could feed the machines and be more productive than a skilled worker working manually. And of course, CNC production is, at this point, an older technology. Years ago, I took a course in Solidworks, which is incredible engineering design software. I think this dovetails with the essay: Solidworks improves a lesser engineer's productivity far more than it does for a higher skilled engineer.
Some (many) will disagree, but I think we're still in the Model T era of computing. The Model T is mostly notable for being affordable to the average person, not for being a great car, especially by today's standards. You could not just get in and turn a key. You had to be knowledgeable about how cars worked, so that you knew how and when to set the choke, set the spark advance, prime if necessary, turn on the ignition, and then get out front and crank. Probably almost no one today could get a Model T started, yet ten-year-olds can intuitively start and drive today's cars. I see today's consumer software computer as being very flawed and not as intuitive as presumed. In other words, you can't just get in and turn the key. Well, why not?
I've lived thru the computer revolution from the very beginning. The advancements are amazing, but not so very different from the advancements in skilled trades, farming and manufacturing. Yes, computers are part of those advancements. As of right now, I don't see AI as being that much of a game changer. It's just one more advancement, and not so very much more of an advancement than what existed a few years ago. True enough, mediocre artists can now be better artists, but great artists will not become greater. Mediocre writers will become better, but great writers will not benefit at all. And politicians, well, they've always been hopeless.