I don’t quite understand the full extent of the AI will create jobs argument. In prior revolutions, say automation, automation created jobs because like building and maintaining robots is a whole thing. Building and maintaining AI is a whole thing, but if you’re talking about wholesale automation of intelligence, the fundamental question I have is:
What jobs will AI create that AI cannot itself do?
In the automation revolution, the bots were largely single purpose, the bots couldn’t be created by bots. There could and probably will be trillions of jobs created by AI, but they will be done by trillions of agents. How many jobs do you really create if ChatgGPT is so multi-purpose, it only takes one say 250k company to support it.
> What jobs will AI create that AI cannot itself do?
Part of the problem is the definition of "AI" is extremely nebulous. In your case, you seem to be talking about an AGI which can self-improve, while also having some physical interface letting it interact with the real world. This reality may be 6 months away, 6 years away, or 600 years away.
Given the current state of LLMs it's much more likely they will create jobs, or change workflows in existing jobs, rather than wholesale replace humans. The recent public spectacle of Microsoft's state-of-the-art Github Copilot Agent[0] shows we're quite far away from AI agents wholesale replacing even very junior positions for knowledge work.
Yeah but LLMs won't stay at the current state though. I don't understand this argument. Is there any particular reason to believe that they'll stop getting better at this point?
> What jobs will AI create that AI cannot itself do?
Good question. And one where "in the immediate..." is not relevant. In the long term then, what?
One direction: Humans are not good for semiconductor fabs. Humans bring contamination of all kinds into a space that shouldn't have any. Humans can't help themselves and tweak things they are not qualified to. Humans can't help themselves and don't report changing conditions that they should. etc, etc. So that current fabs contain mountains of automation. And yet they also have lots of humans. Full automation is really difficult. It's more that automation creates the economic conditions that make it manageable to employ the remaining humans.
> How many jobs do you really create if ChatgGPT is so multi-purpose, it only takes one say 250k company to support it.
Is this very relevant? For example the entertainment industry - I expect - relies on just a handful of data centers for digital distribution. But creating the movies and TV shows employees insane numbers of people. The question is more "What does NextGenChatOpen enables, that it cannot exploit itself"?
> What jobs will AI create that AI cannot itself do?
If we are looking long term, PART of the answer may be that asking about jobs is an insufficient question. Pending other unresolved questions, GDP is already not a good measure of standard of living anymore. Other measures such as happiness index are in their infancy but some people are thinking about alternatives.
So perhaps these non-AI jobs are non-jobs: humans living their lives instead of filling jobs. Which means whatever humans like to do: playing games (sometimes competitively), performing, hiking, collecting stamps, painting murals...
If AI is roughly where IT is in the 60's, we might see actually decreased productivity for a while until people (yes people) figure out how to use it effectively.
The question is how long? The exchange rate of information is very fast these days and there are typically less broad secrets on tool usage and management these days.
The jobs created by the need to build and maintain robots (and industrial machinery in general) are very few compared to the amount of jobs the machines replaced. The new jobs that the industrial and other technological revolutions created were mostly in other economical sectors, like services and commerce.
> What jobs will AI create that AI cannot itself do?
AI lack skin-in-the-game, they cannot bear responsibility for outcomes. They also don't experience desires or needs, so they depend on humans for that too.
To make an AI useful you need to apply it to a problem, in other words it is in a specific problem context that AI shows utility. Like Linux, you need to use it for something to get benefits. Providing this problem space for AI is our part. So you cannot separate AI usefulness from people, problems are distributed across society, non-fungible.
I am not very worried about jobs, we tend to prefer growth to efficiency. In a world of AI, humans will remain the differentiating factor between companies.
Jevons Paradox likely applies here. There could be an initial reduction in jobs, but longer term humans using AI will reduce the cost (increase the efficiency) of those jobs which will increase demand more than merely satisfy it.
Basically any job that uses a word processor, spreadsheet, drawing tool, etc will all become more efficient and if Jevons Paradox applies, demand for those things will increase beyond the reduction due to efficiency gains.
I can imagine that for many fields it will be cheaper to have humans use AI (in the near term) rather than try to make fully automated systems that require no/little supervision.
Agreed - let's say your employees cost $100/yr and your revenue is $150/yr, with a $50/yr profit. Now your employees suddenly become 2X more productive because of AI. Do you...
A) Fire half your staff, now earning $100 profit? ($50/yr to employees, $150/yr revenue)
B) Attempt to double your business, now earning $200 profit? ($100 emp, $300 rev)
C) Double your headcount and earn $400 profit?
If companies are profit-seeking, B and C should be more common than A!
You’re just making things up here. LLMs or other forms of “AI” can’t do most jobs, so it’s silly to speculate what will happen when it replaces humans in those jobs it can’t actually perform.
To the extent it can automate tasks under the direction of humans, it’s not even clear it makes those humans more productive, but it is clear that it harms those humans’ own skillsets (beyond prompt engineering).
They can't do most jobs, but they can still reduce the amount of jobs.
For example, even outsourcing giants like Infosys shrank hiring by 20% AND increased personnel utilization from 70% to 85% just by mandating employees to start using code-gen tools, and as a result were able to significantly enhance margins.
>so it’s silly to speculate what will happen when it replaces humans in those jobs it can’t actually perform
Why?
If you're waiting around for AI to do these things by the time it happens it will be getting hit like a truck. The speed of technological implementation these days is very fast, especially when compared to the speed of regulation.
Moreso we are not just seeing improvement in things like LLMs, there is broad improvements in robotics and generalized behavior in AI.
I'm surprised cashiers are listed as the job most likely to be replaced in the graphics in the article. Unattended self-checkouts have been possible for like 15 years now, and it feels like 5 years ago was peak self-checkout, with some stores drawing back from entirely self-checkout experiences and expansion slowing in others.
My understanding is that the obstacles to stores replacing the remaining cashiers with self-checkouts is not so much "we need a better machine" but (a) the shoplifting deterrence effect of staffing, (b) customers are slower at packing than cashiers, which can cause queues and other inefficiencies.
And,even if customers are slower, having 20 self checkout kiosks is still faster than 3 cashiers.
My biggest gripe with self checkout is if I make a mistake, they call it theft. I haven't been trained and certified on the register, so I can't accept the potential for getting a criminal record due to a scanning error. Example: Walmart will successfully "beep" when scanning, but will display "system busy" on the screen, and the scanned items don't show up on the receipt.
Yeah, this makes very little sense. Around me, it's pretty much just self-checkouts now, outside of peak times. There's generally one manual till open to sell cigarettes, and that's it.
Tellingly, the newest supermarket in the area (Tesco, not any sort of weird startup) only has space for one manual checkout, plus about 15 self-checkouts.
I'm so sick of this hype. My (college-aged) teenage daughter works at a grocery store. Their new "AI" enabled cash-registers are supposed to show them which scanned items go together in a bag. It suggested: 4 packs of hamburger buns should go together in a plastic bag with 2 soda can boxes. Next it suggested a dozen eggs should go together with a gallon of milk.
Every time I go to Target there are two lanes manned by staff. Everything else is self-checkout. This is every Target I go to in my state.
Every time I go to Home Depot, there is one person manning the checkout. Everything else is self-checkout.
Even fast food places have self-checkout stalls that seem to be growing in popularity. In the last few years, McDonalds has been rapidly deploying the tech.
Boba places. Self-checkout has been promoted to first-class and is the only way to order at several of them.
It's everywhere. When I was growing up, Kroger used to have every single checkout aisle staffed. Now they have one or two.
I'm honestly shocked that the perception is that self-checkout hasn't won. It's everywhere and dominates the checkout modalities.
> the shoplifting deterrence effect of staffing
This is all cost modeled. They have lots of cameras and security staff by the door. Even if the tech doesn't work, the mere threat of getting caught is enough to stop most losses. The business accepts that they won't catch everything. They're still saving money by using automated checkout.
> Even if the tech doesn't work, the mere threat of getting caught is enough to stop most losses.
This is not true. A store near me recently removed all of their self-checkout registers due to an abundance of shoplifting. When I read “Self-checkout won” I immediately thought, “Actually, shoplifting won where I’m from.” (Salt Lake City, Utah; not crime free, of course, but also not really known for crime.)
I guess my point is that it won in the past. Cashiers that could be replaced by self-checkouts... have already been replaced by self-checkouts. AI doesn't seem to change that situation.
curious how the ai experts are so wrong on truck drivers. apparent to anyone whos been on the road the US road system will be completely revamped before self driving cargo trucks are viable
The thing about that recent rollout of self-driving trucks is they picked a stretch of road connecting Houston to another shipping point in a very straight line. And they bragged about 2000 "unassisted" miles on that stretch of road which is ~250 miles in length. So they're basically championing the idea that their trucks which have driven about less than 10 trips without an on-vehicle driver in that area is competent enough to be relied upon in a real work capacity.
Whether this amount of success is proof that there won't be any issues with the tech in that area, remains to be seen. Hell, they're not even interested yet in talking about how this may pan out outside their Houston trial runs.
> Self-driving vehicles are the perfect example of how something that seems so close can be so far away.
Remember that this was before transformers, LLMs, and more recently VLM/VLAMs, though.
I'm not sure to what extent these are already integrated in self-driving hardware, but I would not be surprised if we see a big improvement in self-driving due to related technologies soon, especially with the smaller models becoming far more (efficient and) potent.
As others mentioned, self-checkout has been widespread for 30 years. They had it at most stores in the 1990s. The answer is, simply, it's cheaper for companies to hire someone at a non-living wage than it is to install and maintain these systems. Perhaps if we had some policies with teeth -- if you're going to hire a person, they must be able to afford to plausibly live and work in the area. Else, your business isn't actually a functioning business and needs reconsideration.
Self checkout is now much better than it was 30 years ago. As far as the living wage requirement, that just leads to what we’re seeing here. You get replaced by machines. If sub living wage is the best available job why should the government ban that? How is closing the business better than hiring people at shitty wages they are happy to accept?
> How is closing the business better than hiring people at shitty wages they are happy to accept?
Because it brings down the market value of said person, basically ensuring they can't make a livable wage. These companies are cheating, in a way. They're paying well below market value for the labor because of asymmetrical power. Those people are working two or three jobs to make ends meet - so, their employers aren't paying what the labor actually costs. They just get the labor at a discount because employees have zero negotiating power.
It's sort of like getting a vacuum for 15 dollars because when the vacuum salesman rang my door, I held him a gunpoint.
software is really weird as a test case for understanding AI automation on white collar work.
it seems exceptionally well-suited to AI-based automation because software engineering has already needed to figure out how to efficiently cope with humans who sometimes produce code which may have defects. most obviously automated testing and type systems. also a lot of programming tasks have verifiable solutions so it's also better for training. it seems natural that the most obviously successful AI tools are for coding.
yet the software industry has also been absorbing waves of automation for 70 years. Fortran and COBOL were referred to as "automated programming" and there was a narrative that these new tools would make it easy for non-specialists to program. this time may be different, or it may just be another wave of automation.
i think software has pretty unique properties among white collar jobs, and I would hesitate to draw conclusions about other industries based on AI progress in software engineering.
I had the opposite thought. That it was the most difficult of things to replace with AI, and that the eagerness to do so was driven by non developers who see it as an expensive cost centre that is holding them hostage. Where I work still uses very bad outsourced service desk humans, and almost computer illiterate (and sometimes actually illiterate) manual testers and wages approaching that of a senior developer. Why not them first?
I also don't really care if my job is automated. If it doesn't need doing anymore, why should I want to do it? I will do something else.
The issue is people are assuming 100% automation and job replacement by AI/ML overnight - that is NOT happening in the near future.
Realistically, we are going to see 20-30% reductions in headcount in the near-to-medium term. THIS IS STILL CATASTROPHIC.
A number of earlier stage companies I've funded have already been heavily utilizing automation to simplify code generation or scaffolding/project ops work. They use the cost savings to hire experienced SWEs at high base salaries and are able to hit the same development metrics as they would have if they had a large team of average paid SWEs. On the BDR side, they are using a massive amount of video/audio automation to scale out cold calling or first impressions, so reducing the need to hire teams of BDRs hitting the phones all the time. And finally, they are automating tier 1/2 support ticket responses and communication so reducing the need for teams of support engineers spending time basically respondng to customers with the polite equivalnet of "read the docs".
Basically, a Series A startup that would have had a staff of 50 employees 10 years ago can essentially output the exact same as a Series A startup with a headcount of 20 employees today, and with a tangible path to FCF positivity.
This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.
> A number of earlier stage companies I've funded have already been heavily utilizing automation to simplify code generation or scaffolding/project ops work. They use the cost savings to hire experienced SWEs at high base salaries and are able to hit the same development metrics as they would have if they had a large team of average paid SWEs. On the BDR side, they are using a massive amount of video/audio automation to scale out cold calling or first impressions, so reducing the need to hire teams of BDRs hitting the phones all the time. And finally, they are automating tier 1/2 support ticket responses and communication so reducing the need for teams of support engineers spending time basically respondng to customers with the polite equivalnet of "read the docs".
Impressive.
> This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.
So you lose out on people to do work? That they cannot upskill implies that there are jobs to fill. That seems like an economic void there. If the jobs cannot be filled something else must compensate.
But I see no reason to accept this narrative. In the long run we’re all upskilled out of a job. Our tiny brains can’t keep up. Certainly if something as simple-sounding as code generation and/or scaffolding can reduce headcount by this much. What will full-force AI do then?
Maybe they shouldn’t spend their time chasing that promise of bigger brain job tasks and (maybe even) higher pay (because big IQ means big pay?). Eventually the rent-seeking becomes too naked to ignore. Maybe around the time when the whole operation is maintained by the last twenty or so biggest brains of the lot (survival of the biggest). Then their tasks all get automated. Whose left standing with the spoils? Not the biggest brains.
I'm skeptical there is much AI backlash to spill out. Obviously some people don't like it, some do. Overall it's probably a positive thing or we wouldn't be investing so much in it. Unemployment levels are fairly low by historical standards (eg https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS). For each taxi driver laid off due to Waymo there are probably more people hired to make and operate the Waymos.
The Luddites were kind of unusual in the history of things. We've had all sorts of tech innovation over the last two centuries and not much has lead to riots. The luddite riots happened at time of high unemployment and inflation after the Napoleonic wars and may have been more a last straw rather than the root cause of the dissatisfaction.
The thing people forget is that the luddites were right. They were selfish assholes, but they were right. Automation cost them their jobs and made their lives worse. Of course their kids were all better off but the luddites themselves got fucked.
Lots of silly things in this article, but in re the poll data they lean on so heavily, the “AI experts” are “people who work in the AI industry”. So, in other words, people who are highly biased by the money inflow that’s chasing human job destruction.
Readit News
What jobs will AI create that AI cannot itself do?
In the automation revolution, the bots were largely single purpose, the bots couldn’t be created by bots. There could and probably will be trillions of jobs created by AI, but they will be done by trillions of agents. How many jobs do you really create if ChatgGPT is so multi-purpose, it only takes one say 250k company to support it.
Part of the problem is the definition of "AI" is extremely nebulous. In your case, you seem to be talking about an AGI which can self-improve, while also having some physical interface letting it interact with the real world. This reality may be 6 months away, 6 years away, or 600 years away.
Given the current state of LLMs it's much more likely they will create jobs, or change workflows in existing jobs, rather than wholesale replace humans. The recent public spectacle of Microsoft's state-of-the-art Github Copilot Agent[0] shows we're quite far away from AI agents wholesale replacing even very junior positions for knowledge work.
[0] https://news.ycombinator.com/item?id=44050152
Good question. And one where "in the immediate..." is not relevant. In the long term then, what?
One direction: Humans are not good for semiconductor fabs. Humans bring contamination of all kinds into a space that shouldn't have any. Humans can't help themselves and tweak things they are not qualified to. Humans can't help themselves and don't report changing conditions that they should. etc, etc. So that current fabs contain mountains of automation. And yet they also have lots of humans. Full automation is really difficult. It's more that automation creates the economic conditions that make it manageable to employ the remaining humans.
> How many jobs do you really create if ChatgGPT is so multi-purpose, it only takes one say 250k company to support it.
Is this very relevant? For example the entertainment industry - I expect - relies on just a handful of data centers for digital distribution. But creating the movies and TV shows employees insane numbers of people. The question is more "What does NextGenChatOpen enables, that it cannot exploit itself"?
If we are looking long term, PART of the answer may be that asking about jobs is an insufficient question. Pending other unresolved questions, GDP is already not a good measure of standard of living anymore. Other measures such as happiness index are in their infancy but some people are thinking about alternatives.
So perhaps these non-AI jobs are non-jobs: humans living their lives instead of filling jobs. Which means whatever humans like to do: playing games (sometimes competitively), performing, hiking, collecting stamps, painting murals...
If AI is roughly where IT is in the 60's, we might see actually decreased productivity for a while until people (yes people) figure out how to use it effectively.
AI lack skin-in-the-game, they cannot bear responsibility for outcomes. They also don't experience desires or needs, so they depend on humans for that too.
To make an AI useful you need to apply it to a problem, in other words it is in a specific problem context that AI shows utility. Like Linux, you need to use it for something to get benefits. Providing this problem space for AI is our part. So you cannot separate AI usefulness from people, problems are distributed across society, non-fungible.
I am not very worried about jobs, we tend to prefer growth to efficiency. In a world of AI, humans will remain the differentiating factor between companies.
Basically any job that uses a word processor, spreadsheet, drawing tool, etc will all become more efficient and if Jevons Paradox applies, demand for those things will increase beyond the reduction due to efficiency gains.
I can imagine that for many fields it will be cheaper to have humans use AI (in the near term) rather than try to make fully automated systems that require no/little supervision.
A) Fire half your staff, now earning $100 profit? ($50/yr to employees, $150/yr revenue)
B) Attempt to double your business, now earning $200 profit? ($100 emp, $300 rev)
C) Double your headcount and earn $400 profit?
If companies are profit-seeking, B and C should be more common than A!
To the extent it can automate tasks under the direction of humans, it’s not even clear it makes those humans more productive, but it is clear that it harms those humans’ own skillsets (beyond prompt engineering).
For example, even outsourcing giants like Infosys shrank hiring by 20% AND increased personnel utilization from 70% to 85% just by mandating employees to start using code-gen tools, and as a result were able to significantly enhance margins.
Why?
If you're waiting around for AI to do these things by the time it happens it will be getting hit like a truck. The speed of technological implementation these days is very fast, especially when compared to the speed of regulation.
Moreso we are not just seeing improvement in things like LLMs, there is broad improvements in robotics and generalized behavior in AI.
My understanding is that the obstacles to stores replacing the remaining cashiers with self-checkouts is not so much "we need a better machine" but (a) the shoplifting deterrence effect of staffing, (b) customers are slower at packing than cashiers, which can cause queues and other inefficiencies.
Where I'm from, cashiers don't pack the groceries of customers
My biggest gripe with self checkout is if I make a mistake, they call it theft. I haven't been trained and certified on the register, so I can't accept the potential for getting a criminal record due to a scanning error. Example: Walmart will successfully "beep" when scanning, but will display "system busy" on the screen, and the scanned items don't show up on the receipt.
Tellingly, the newest supermarket in the area (Tesco, not any sort of weird startup) only has space for one manual checkout, plus about 15 self-checkouts.
Every time I go to Target there are two lanes manned by staff. Everything else is self-checkout. This is every Target I go to in my state.
Every time I go to Home Depot, there is one person manning the checkout. Everything else is self-checkout.
Even fast food places have self-checkout stalls that seem to be growing in popularity. In the last few years, McDonalds has been rapidly deploying the tech.
Boba places. Self-checkout has been promoted to first-class and is the only way to order at several of them.
It's everywhere. When I was growing up, Kroger used to have every single checkout aisle staffed. Now they have one or two.
I'm honestly shocked that the perception is that self-checkout hasn't won. It's everywhere and dominates the checkout modalities.
> the shoplifting deterrence effect of staffing
This is all cost modeled. They have lots of cameras and security staff by the door. Even if the tech doesn't work, the mere threat of getting caught is enough to stop most losses. The business accepts that they won't catch everything. They're still saving money by using automated checkout.
This is not true. A store near me recently removed all of their self-checkout registers due to an abundance of shoplifting. When I read “Self-checkout won” I immediately thought, “Actually, shoplifting won where I’m from.” (Salt Lake City, Utah; not crime free, of course, but also not really known for crime.)
I guess my point is that it won in the past. Cashiers that could be replaced by self-checkouts... have already been replaced by self-checkouts. AI doesn't seem to change that situation.
Whether this amount of success is proof that there won't be any issues with the tech in that area, remains to be seen. Hell, they're not even interested yet in talking about how this may pan out outside their Houston trial runs.
April 29, 2014 - "Milken 2014: Driverless cars due in five years"[0]
Nov 24, 2015 - "Ford is 5 years away from self-driving cars"[1]
Oct 20, 2016 - "A Driverless Tesla Will Travel From L.A. to NYC by 2017"[2]
Now general consensus is level 5 autonomous self-driving is decades away, at least.
[0] https://www.usatoday.com/story/money/cars/2014/04/29/milken-...
[1] https://www.businessinsider.com/ford-is-5-years-away-from-se...
[2] https://www.nbcnews.com/business/autos/driverless-tesla-will...
Remember that this was before transformers, LLMs, and more recently VLM/VLAMs, though.
I'm not sure to what extent these are already integrated in self-driving hardware, but I would not be surprised if we see a big improvement in self-driving due to related technologies soon, especially with the smaller models becoming far more (efficient and) potent.
Deleted Comment
Because it brings down the market value of said person, basically ensuring they can't make a livable wage. These companies are cheating, in a way. They're paying well below market value for the labor because of asymmetrical power. Those people are working two or three jobs to make ends meet - so, their employers aren't paying what the labor actually costs. They just get the labor at a discount because employees have zero negotiating power.
It's sort of like getting a vacuum for 15 dollars because when the vacuum salesman rang my door, I held him a gunpoint.
it seems exceptionally well-suited to AI-based automation because software engineering has already needed to figure out how to efficiently cope with humans who sometimes produce code which may have defects. most obviously automated testing and type systems. also a lot of programming tasks have verifiable solutions so it's also better for training. it seems natural that the most obviously successful AI tools are for coding.
yet the software industry has also been absorbing waves of automation for 70 years. Fortran and COBOL were referred to as "automated programming" and there was a narrative that these new tools would make it easy for non-specialists to program. this time may be different, or it may just be another wave of automation.
i think software has pretty unique properties among white collar jobs, and I would hesitate to draw conclusions about other industries based on AI progress in software engineering.
I also don't really care if my job is automated. If it doesn't need doing anymore, why should I want to do it? I will do something else.
Realistically, we are going to see 20-30% reductions in headcount in the near-to-medium term. THIS IS STILL CATASTROPHIC.
A number of earlier stage companies I've funded have already been heavily utilizing automation to simplify code generation or scaffolding/project ops work. They use the cost savings to hire experienced SWEs at high base salaries and are able to hit the same development metrics as they would have if they had a large team of average paid SWEs. On the BDR side, they are using a massive amount of video/audio automation to scale out cold calling or first impressions, so reducing the need to hire teams of BDRs hitting the phones all the time. And finally, they are automating tier 1/2 support ticket responses and communication so reducing the need for teams of support engineers spending time basically respondng to customers with the polite equivalnet of "read the docs".
Basically, a Series A startup that would have had a staff of 50 employees 10 years ago can essentially output the exact same as a Series A startup with a headcount of 20 employees today, and with a tangible path to FCF positivity.
This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.
Impressive.
> This is a net reduction in jobs, and a significant one at that, because most people just cannot upskill - it's hard.
So you lose out on people to do work? That they cannot upskill implies that there are jobs to fill. That seems like an economic void there. If the jobs cannot be filled something else must compensate.
But I see no reason to accept this narrative. In the long run we’re all upskilled out of a job. Our tiny brains can’t keep up. Certainly if something as simple-sounding as code generation and/or scaffolding can reduce headcount by this much. What will full-force AI do then?
Maybe they shouldn’t spend their time chasing that promise of bigger brain job tasks and (maybe even) higher pay (because big IQ means big pay?). Eventually the rent-seeking becomes too naked to ignore. Maybe around the time when the whole operation is maintained by the last twenty or so biggest brains of the lot (survival of the biggest). Then their tasks all get automated. Whose left standing with the spoils? Not the biggest brains.
The Luddites were kind of unusual in the history of things. We've had all sorts of tech innovation over the last two centuries and not much has lead to riots. The luddite riots happened at time of high unemployment and inflation after the Napoleonic wars and may have been more a last straw rather than the root cause of the dissatisfaction.
https://en.wikipedia.org/wiki/Luddite
Genuine question. I'm trying to find a difference, but not succeeding.