The prediction isn’t based on the classification, it just conveniently captures the relevant information in a way we can expect most people to understand.
What relevant information? My point is that the sentence “The economy has three broad sectors: agriculture, manufacturing, and services” does not have any information relevant to answering “what jobs will remain after 20 years”. If economists had identified four sectors, instead of three, this would not make automation any less threatening.
”This means when a job is lost to automation, all the jobs that person could do are going away at the same time.”
This is false. A truck driver may loose his job soon, then he might move to a job in walmart, and it could take decades before that is fully automated. Of course, if you believe that all jobs will be automated soon, then the statement is true in the trivial sense.
Neither self driving cars nor robotic hands require any fundamentally new technology
Your post didn’t mention fundamentally new technology (I guess we could debate what technology is or isn’t “fundamentally new”). I understood that you were talking about large costs and delays of adoption, caused by the need to manufacture and sell physical things. Many tasks that will be automated do require physical machines. A logistics company will need huge investments to make their trucks self driving, and it might take decades before most companies are willing to make them.
If economists had identified four sectors, instead of three, this would not make automation any less threatening.
That is exactly the relevant information I need to capture. The problem is that there are no large, underserved categories of value which unskilled labor can accomplish, where automation is not imminent. The three sectors is something everyone understands, and has continuity with the rest of the automation discussion (like popular books and articles on the subject).
A truck driver may loose his job soon, then he might move to a job in walmart, and it could take decades before that is fully automated
The distinction between having their way of life destroyed vs. having their way of life destroyed but probably not starving to death is overly fine for the population at large. Further this ignores the context: there’s a lot of truck drivers, and there are already more than enough people to work for Walmart (and all similar positions). Though I see I still fail to have reinforced the intuition about the automation of skills. Sentence Mk. III:
”This means when a job is lost to automation, all the jobs that person could do **with that skill** are going away at the same time.”
I understood that you were talking about large costs and delays of adoption, caused by the need to manufacture and sell physical things.
That is true, but the focus remains on what is different this time. I may be wrong, but I strongly suspect that no one views better robots as different in kind from the sort of automation we saw in the 1980s. This is just an incremental improvement over the kinds of things we could do before. What I want people to imagine are things like call centers (unskilled, but only recently automated because talking to people was hard for machines) and accounting or the law (which implies a high level of skill is not a guarantee). Do you suppose I could make this clearer by just citing the call center example? I am not confident that ‘renting server space‘ communicates the ease to people who have no familiarity with it.
The problem is that there are no large, underserved categories of value which unskilled labor can accomplish, where automation is not imminent.
This may well be true, but that has nothing to do with the three sectors. Automation doesn’t actually happen one sector at a time. It’s not like only service jobs are going to be automated soon. There are still people working in, e.g. agriculture, whose jobs will be automated too. Talking about sectors is completely pointless, it’s a non sequitur. You’d be better off just using the sentence quoted above instead.
”This means when a job is lost to automation, all the jobs that person could do **with that skill** are going away at the same time.”
I need you to show me that this wasn’t the case in the past. The farmer who was replaced by a tractor didn’t find another job that requires plowing.
What I want people to imagine are things like call centers (unskilled, but only recently automated because talking to people was hard for machines) and accounting or the law (which implies a high level of skill is not a guarantee).
How many people are threatened by that kind of automation? Is it a significant number, compared to truck drivers, wallmart workers and all the other jobs that do require physical machines?
″ That is true, but the focus remains on what isdifferentthis time. I may be wrong, but I strongly suspect that no one views better robots as different in kind from the sort of automation we saw in the 1980s. This is just an incremental improvement over the kinds of things we could do before. ”
Here’s what I think is different about it this time. Specifically, the 1980s methods involved basically : you identify the task to be automated. You hire an automation engineering firm to do the task. This would involve custom “fixtures”, custom mechanical assemblies, and very carefully designed assembly lines. Then a team of programmers has to very carefully put together a sequence of commands to complete the task. If you binge-watch “how it’s made” videos, you will see hundreds of examples of this. Cake factories where a dipping machine is custom made for the shape of the cakes going into the chocolate dip, where it can’t make a different kinds of cake or change the chocolate ratio or make rice crispies instead or learn how to clear faults where the cake has clogged up the machine.
One big flaw with this is if you have a new kind of cake you want to make, you can’t just send a description of your new recipe to the factory and have it make it. Nor can the equipment try different strategies for cake making and self-optimize for higher speed and less errors. Nor can the equipment be given a new set of robot hardware that has slightly different performance parameters and self-adjust to make the cakes using these different robot actuators. Nor can it avoid “hurting itself” by carefully planning each motion and making sure planned motions are not going to hit anything in the environment. Some human has to set all this up. Some human has to manually adjust timings, to unclog it whenever it faults, and so on.
Today’s methods show all of the above is possible in the immediate future. Also, we can potentially build massive frameworks, where automating even small tasks is easy because the framework is stable, easy to use, easy to connect to compatible hardware. And you just go on the “app store” for the framework and rent the pieces you need to do a task. Go rent a classifier that can recognize most objects seen through a camera. A physics modeler that is both learning and already pre-trained for most ordrinary objects in a factory. Scoring software that can measure outcomes. Just grab all the pieces and put together your automation “app”.
And obviously we can go to either waldos that can do many tasks and don’t need custom mechanical fixtures, or we find a way to rapid-design fixtures and get them installed and working automatically.
And, hopefully, robots making cakes will be able to share knowledge back to the cloud, so that other robots elsewhere making transmissions get slightly better, or if an employee drops a cake on the factory floor, they know what it is.
So ultimately, while it’ll take a long time to actually build all this, ultimately we can automate all retail stores, all warehouses, all farms, and all factories. Billions of jobs. I don’t know how to automate service jobs like cutting hair with the current state of the art, but even if we can’t, if half the population of most countries are out of work and trying to re-train to cut hair or something, it crashes the labor market for barbers, etc.
What relevant information? My point is that the sentence “The economy has three broad sectors: agriculture, manufacturing, and services” does not have any information relevant to answering “what jobs will remain after 20 years”. If economists had identified four sectors, instead of three, this would not make automation any less threatening.
This is false. A truck driver may loose his job soon, then he might move to a job in walmart, and it could take decades before that is fully automated. Of course, if you believe that all jobs will be automated soon, then the statement is true in the trivial sense.
Your post didn’t mention fundamentally new technology (I guess we could debate what technology is or isn’t “fundamentally new”). I understood that you were talking about large costs and delays of adoption, caused by the need to manufacture and sell physical things. Many tasks that will be automated do require physical machines. A logistics company will need huge investments to make their trucks self driving, and it might take decades before most companies are willing to make them.
That is exactly the relevant information I need to capture. The problem is that there are no large, underserved categories of value which unskilled labor can accomplish, where automation is not imminent. The three sectors is something everyone understands, and has continuity with the rest of the automation discussion (like popular books and articles on the subject).
The distinction between having their way of life destroyed vs. having their way of life destroyed but probably not starving to death is overly fine for the population at large. Further this ignores the context: there’s a lot of truck drivers, and there are already more than enough people to work for Walmart (and all similar positions). Though I see I still fail to have reinforced the intuition about the automation of skills. Sentence Mk. III:
”This means when a job is lost to automation, all the jobs that person could do **with that skill** are going away at the same time.”
That is true, but the focus remains on what is different this time. I may be wrong, but I strongly suspect that no one views better robots as different in kind from the sort of automation we saw in the 1980s. This is just an incremental improvement over the kinds of things we could do before. What I want people to imagine are things like call centers (unskilled, but only recently automated because talking to people was hard for machines) and accounting or the law (which implies a high level of skill is not a guarantee). Do you suppose I could make this clearer by just citing the call center example? I am not confident that ‘renting server space‘ communicates the ease to people who have no familiarity with it.
This may well be true, but that has nothing to do with the three sectors. Automation doesn’t actually happen one sector at a time. It’s not like only service jobs are going to be automated soon. There are still people working in, e.g. agriculture, whose jobs will be automated too. Talking about sectors is completely pointless, it’s a non sequitur. You’d be better off just using the sentence quoted above instead.
I need you to show me that this wasn’t the case in the past. The farmer who was replaced by a tractor didn’t find another job that requires plowing.
How many people are threatened by that kind of automation? Is it a significant number, compared to truck drivers, wallmart workers and all the other jobs that do require physical machines?
″ That is true, but the focus remains on what is different this time. I may be wrong, but I strongly suspect that no one views better robots as different in kind from the sort of automation we saw in the 1980s. This is just an incremental improvement over the kinds of things we could do before. ”
Here’s what I think is different about it this time. Specifically, the 1980s methods involved basically : you identify the task to be automated. You hire an automation engineering firm to do the task. This would involve custom “fixtures”, custom mechanical assemblies, and very carefully designed assembly lines. Then a team of programmers has to very carefully put together a sequence of commands to complete the task. If you binge-watch “how it’s made” videos, you will see hundreds of examples of this. Cake factories where a dipping machine is custom made for the shape of the cakes going into the chocolate dip, where it can’t make a different kinds of cake or change the chocolate ratio or make rice crispies instead or learn how to clear faults where the cake has clogged up the machine.
One big flaw with this is if you have a new kind of cake you want to make, you can’t just send a description of your new recipe to the factory and have it make it. Nor can the equipment try different strategies for cake making and self-optimize for higher speed and less errors. Nor can the equipment be given a new set of robot hardware that has slightly different performance parameters and self-adjust to make the cakes using these different robot actuators. Nor can it avoid “hurting itself” by carefully planning each motion and making sure planned motions are not going to hit anything in the environment. Some human has to set all this up. Some human has to manually adjust timings, to unclog it whenever it faults, and so on.
Today’s methods show all of the above is possible in the immediate future. Also, we can potentially build massive frameworks, where automating even small tasks is easy because the framework is stable, easy to use, easy to connect to compatible hardware. And you just go on the “app store” for the framework and rent the pieces you need to do a task. Go rent a classifier that can recognize most objects seen through a camera. A physics modeler that is both learning and already pre-trained for most ordrinary objects in a factory. Scoring software that can measure outcomes. Just grab all the pieces and put together your automation “app”.
And obviously we can go to either waldos that can do many tasks and don’t need custom mechanical fixtures, or we find a way to rapid-design fixtures and get them installed and working automatically.
And, hopefully, robots making cakes will be able to share knowledge back to the cloud, so that other robots elsewhere making transmissions get slightly better, or if an employee drops a cake on the factory floor, they know what it is.
So ultimately, while it’ll take a long time to actually build all this, ultimately we can automate all retail stores, all warehouses, all farms, and all factories. Billions of jobs. I don’t know how to automate service jobs like cutting hair with the current state of the art, but even if we can’t, if half the population of most countries are out of work and trying to re-train to cut hair or something, it crashes the labor market for barbers, etc.