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That is not going to happen. Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. Spreadsheets rev

That is not going to happen. Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. Spreadsheets revolutionized bookkeeping. They did not eliminate the need for accountants. Robots automated much of the manual labor in manufacturing. They did not eliminate the need for process engineers, etc. Same story for autocad, protools, avid, etc.

redox99 4y ago
AGIs should basically by definition be able to replace humans[1], so yes, when we get good enough AGIs that will happen. GPT4 won't be an AGI of course, but it still could have a massive impact on the job market. A single engineer with GPT4 could potentially do the work of 10 engineers right now. Edit: To be clear, I used GPT4 as a placeholder for "some near future LLM". I'm not making any bets on GPT4 in particular. [1] See "The employment test" https://en.wikipedia.org/wiki/Artificial_general_intelligence#Tests_for_confirming_human-level_AGI https://en.wikipedia.org/wiki/Artificial_general_intelligenc...
- ASalazarMX 4y ago
  > A single engineer with GPT4 could potentially do the work of 10 engineers right now And the potential mistakes of several engineers too, so you would need more than one engineer to double-check the output. Remember that, even if they are truly amazing, LLMs are basically incredibly powerful predictive keyboards.
- jackblemming 4y ago
  If we're going to pull random numbers from where the sun doesn't shine, why don't we say the work of a hundred engineers? How about a billion? I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive, so I'm curious how you ended up with your estimate.
  - travisjungroth 4y ago
    They said “could potentially”. They’re just making the argument (true IMO) that technology doesn’t have to replace a class of employee to have a huge effect. We still have farmers, but 1% of the population instead of >50%. Or, it could be like how assemblers didn’t get rid of software engineers but helped fuel the fire. Who knows.
    - andrepd 4y ago
      >could potentially "Potentially" we could explore the galaxy or have nanobots and Star Trek fabricators. What does it matter? ChatbotGPT is no closer to AGI than my keyboard autocomplete, and copilot is useless for any task whose answer cannot be googled in 20s.
  - redox99 4y ago
    It's just an example to make the point easier to understand A single engineer with [some near future LLM] could potentially do the work of [X] engineers right now.
  - ux-app 4y ago
    >I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive Use your imagination. Do you think that LLMs have hit their plateau? Not likely I'd say. With all the billions suddenly rushing into the space, you really think that ChatGPT v.X isn't going to replace you? Risky bet.
    - BaseballPhysics 4y ago
      > Do you think that LLMs have hit their plateau? Not likely I'd say. Mmmm, I don't know. I think LLMs are running up against fundamental limitations in the approach (hallucinations in particular) that will not be fixed unless truly new techniques are discovered. So I do actually think we're likely hitting a plateau.
      - ux-app 4y ago
        how did you reach those conclusions?
        BaseballPhysics 4y ago
        Good question! So LLMs fundamentally do not encode the nature of facts and data. They're simply (well, no, extremely sophisticated) text prediction engines. There's no embedded comprehension. And that's basic to the approach companies like OpenAI are taking. That's why it's so easy to find factual errors in the generated text from these models: they can create text that's pleasing, but that's as much as they can do. The next leap, to generate language that's also accurate, will require new techniques to bake in actual understanding. Until then, these models will always have issues with hallucinations. Or, at least, that's my expectation. Certainly nothing we've seen in GPT 3, 3.5, or Bing, which is rumoured to be based on something close to GPT 4, indicates any advances in this area.
        nadermx 4y ago
        Perhaps, but just like humans some are more adept at tasks than others. And an AGI using LLM's is completly feasable, for example on a quick thought a LLM could be trained on many LLM all specifically designed for tasks, and verfied against other LLMs, etc
  - Gigachad 4y ago
    Because ChatGPT is not self driven and has no ability to do things. I can quite easily imagine one person doing 10 peoples work with this tool. I can’t imagine them being able to type fast enough to do 100 jobs.
  - alfalfasprout 4y ago
    The problem I'm seeing is that "engineers" are not interchangeable. For some folks, the job is all straight coding. For others, it's understanding requirements, talking to stakeholders and figuring out their requirements, figuring out how to make a clean design taking lots of other factors in mind. It's not that ChatGPT is incapable... it's that it's not inherently going to make me significantly more productive.
  - evilduck 4y ago
    Where did you pull 10% from then? That also seems like you're reaching up your ass. As with all of these arguments, context matters. Both of you need to say what you're doing with these tools. I've personally found the combination to range from "utterly useless" (writing Rust for microcontrollers) to "I could see this eliminating jobs" (CRUD API work).
- matwood 4y ago
  > A single engineer with GPT4 could potentially do the work of 10 engineers right now. Big assumption, but if that's possible then businesses will fill that time. What used to take teams of people and big iron can now be done by a single person on a VPC. Did that take away jobs? Nope, requirements only expanded.
  - alfalfasprout 4y ago
    Indeed, folks making these types of conclusions seem to assume that what there is to be built will remain "constant". No, the more productive the tools the bigger the requirements. Modern high level languages didn't eliminate engineers. They suddenly meant one engineer could do what it would have taken 10 to do in COBOL or C and so software became more complex and capable.
    - matwood 4y ago
      I'm reminded of people wanting to go back to plain html. That's great if I can get the business to go back to basic html features. Same with computer speed increases. If anything, humanity has shown uncanny ability exploit any surplus resource for profit. Of course there can be industry shifts (MS was the industry for a long time and IBM before them. Google wasn't always dominant), but the pie grows to fit the available resources.
- roflyear 4y ago
  Burnout is proportional to how mch you do I think. Even if you can solve hundreds of problems a day in theory youll probably get pretty roughed up
visarga 4y ago
More importantly, everyone had access to calculators, spreadsheets, design tools, etc. And AI will be the same. The differentiating factor is still human.
VectorLock 4y ago
Secretary was the most populous job in the US before the advent of personal computers.
sebzim4500 4y ago
>Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. They did not eliminate mathematicians, but I do not believe mathematicians were ever doing arithmetic for a singificant portion of their workday. Before it was a device, "Calculator" used to be a job description. It isn't any more. Every one of those people lost their job.
- xmprt 4y ago
  I think this only becomes a problem if technology evolves faster than people change. All those "calculator" employees got better jobs. People keep making the analogy of how cars completely replaced horses (I used to as well) but horses can't fundamentally change what they are capable of. Even if the technology does evolve faster than people, governments can make sure people don't get impacted. Coal plants are more expensive to operate, worse for the environment, and less efficient but the coal industry is still kicking along for better or for worse.
  - barking_biscuit 4y ago
    >I think this only becomes a problem if technology evolves faster than people change. This is the key distinction. Bandwidth. Humans only have so much of it, and if the rate at which they need to change their careers / find a new line of work exceeds their ramp-up time to become productive in that career / line of work then we can start to expect non-linear behavior from those humans. Maybe that means some sort of mental breakdown.
- pfisherman 4y ago
  Calculation is not dead! Finding more efficient ways to do calculations was and still is an active branch of mathematics and computer science. It’s just called algorithms now. PageRank was essentially an efficient way to compute / approximate the leading eigenvector of a very large matrix.
- anticensor 4y ago
  > "Calculator" used to be a job description It was computer, not calculator.
barking_biscuit 4y ago
>That is not going to happen. Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. Spreadsheets revolutionized bookkeeping. They did not eliminate the need for accountants. Robots automated much of the manual labor in manufacturing. They did not eliminate the need for process engineers, etc. Same story for autocad, protools, avid, etc. An AGI would be a "purposeful system" the same as humans. None of the other things you mentioned are purposeful systems. In terms of their structure and function they all have limitations on their own ability to change depending on the environment they are in. The key dimensions with which to think about this problem is "can this thing be structured in only one way for all environments? Or can it be structured in only one way in any given environment, but structured differently in different environments? Or can it be structured in more than one way in any environment, and also more than one way in different environments?" and then the same for functionality "can this thing only perform one function in all environments? Or can it perform only one function in a given environment, but different functions in different environments? Or can it perform more than one function in a given environment, and more than one function in different environments?" Only things which have both properties of being "multi-multistructural" and "multi-multifunctional" meet the definition of a "purposeful system". They can change their structure to adapt to the environment, and they can change their goals within and between environments. Humans currently use computers as instruments, and when an AGI hits it will be capable of saying no.
- andrepd 4y ago
  The only snag, of course, is that GPT is no closer to AGI than my phone keyboard autocomplete.
  - barking_biscuit 4y ago
    No closer by what definition? Thinking it through, I would say that "autocomplete" would be uni-multistructural and uni-unifunctional given that autocomplete is always structured only one way for the given environment that it's in, but that structure differs between environments (e.g. a phone, or a form in a web-browser), and that regardless of what environment its in it's only function is to predict the next token of output for a given input. LLMs like ChatGPT on the other hand I would imagine to be uni-multistructural and multi-multifunctional, given that for any given environment you deploy an LLM into it's always structured the same, but there are many different structures it can take given there are lots of different LLMs. And I believe it to be multi-multifunctional because even within a single environment it can be used as an instrument to perform a wide variety of extrinsic functions, and this is true of other environments it could be deployed in. So... it's actually significantly closer.
hn_throwaway_99 4y ago
Whenever somebody makes the argument "Hey, we've had lots of technical progress in the past, but that just opened up new jobs for people to do!" I always think "Have you looked at the state of the US job market and economy over the past 40 years?" That is, we've had a huge hollowing out of all sorts of "middle" jobs in the US (e.g. someone mentioned secretaries used to be the most populous job in the US) so now we're largely (not exclusively, but largely) left with 2 categories of jobs: (a) dead-end jobs that are at present difficult to automate because they often involve manual labor: housekeepers, security guards, massage therapists, waiters, truck drivers (but, we see where that's headed...), etc. and (b) high level jobs that "manage the machines", e.g. tech jobs. It's not that hard to see where this ends up with AI being capable of more complicated tasks - I wrote about an anecdote recently where ChatGPT had essentially already obviated some positions https://news.ycombinator.com/item?id=34862450 https://news.ycombinator.com/item?id=34862450. There are a slew of very high paying jobs that AI is coming for next, e.g. there is currently a shortage of radiologists because many folks in med school see the writing on the wall and don't go into radiology residencies. While full diagnostic radiology AI may not be there yet, it certainly will be by the time folks in med school finish their career in 40 years.
- purerandomness 4y ago
  Cargo jobs that exist for bureaucratic reasons, or because of industry inertia, will be disrupted. That's the job of new inventions. Nothing to complain about, in my opinion. Those however who think that radiologists (/lawyers/secretaries) will get automated away, don't really understand what a radiologist's job really is. The boring bureaucratic part of a radiologist's job will get automated away, yes, but that's because automatable/auto-completeable tasks should get automated at some point. Think of it as a healthy organism eating away the boring part of a dream job that you, as a kid, imagined doing when you'll grow up.
  - hn_throwaway_99 4y ago
    > Those however who think that radiologists (/lawyers/secretaries) will get automated away, don't really understand what a radiologist's job really is. As someone intimately familiar with the job of a radiologist, please then tell me what "a radiologist's job really is". A diagnostic radiologist's job is to take a series of images, and output a set of findings and diagnoses. There is essentially no better task suited to modern AI. Yes, radiologists can do procedures like biopsies and potentially other interventions, but diagnostic radiologists often solely read images or at least earn the vast majority of their RVUs by reading images.

redox99 4y ago

AGIs should basically by definition be able to replace humans[1], so yes, when we get good enough AGIs that will happen. GPT4 won't be an AGI of course, but it still could have a massive impact on the job market. A single engineer with GPT4 could potentially do the work of 10 engineers right now. Edit: To be clear, I used GPT4 as a placeholder for "some near future LLM". I'm not making any bets on GPT4 in particular. [1] See "The employment test" https://en.wikipedia.org/wiki/Artificial_general_intelligence#Tests_for_confirming_human-level_AGI https://en.wikipedia.org/wiki/Artificial_general_intelligenc...

ASalazarMX 4y ago
> A single engineer with GPT4 could potentially do the work of 10 engineers right now And the potential mistakes of several engineers too, so you would need more than one engineer to double-check the output. Remember that, even if they are truly amazing, LLMs are basically incredibly powerful predictive keyboards.
jackblemming 4y ago
If we're going to pull random numbers from where the sun doesn't shine, why don't we say the work of a hundred engineers? How about a billion? I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive, so I'm curious how you ended up with your estimate.
- travisjungroth 4y ago
  They said “could potentially”. They’re just making the argument (true IMO) that technology doesn’t have to replace a class of employee to have a huge effect. We still have farmers, but 1% of the population instead of >50%. Or, it could be like how assemblers didn’t get rid of software engineers but helped fuel the fire. Who knows.
  - andrepd 4y ago
    >could potentially "Potentially" we could explore the galaxy or have nanobots and Star Trek fabricators. What does it matter? ChatbotGPT is no closer to AGI than my keyboard autocomplete, and copilot is useless for any task whose answer cannot be googled in 20s.
- redox99 4y ago
  It's just an example to make the point easier to understand A single engineer with [some near future LLM] could potentially do the work of [X] engineers right now.
- ux-app 4y ago
  >I've actually used ChatGPT and copilot and I can tell you it's not even 10% more productive Use your imagination. Do you think that LLMs have hit their plateau? Not likely I'd say. With all the billions suddenly rushing into the space, you really think that ChatGPT v.X isn't going to replace you? Risky bet.
  - BaseballPhysics 4y ago
    > Do you think that LLMs have hit their plateau? Not likely I'd say. Mmmm, I don't know. I think LLMs are running up against fundamental limitations in the approach (hallucinations in particular) that will not be fixed unless truly new techniques are discovered. So I do actually think we're likely hitting a plateau.
    - ux-app 4y ago
      how did you reach those conclusions?
      - BaseballPhysics 4y ago
        Good question! So LLMs fundamentally do not encode the nature of facts and data. They're simply (well, no, extremely sophisticated) text prediction engines. There's no embedded comprehension. And that's basic to the approach companies like OpenAI are taking. That's why it's so easy to find factual errors in the generated text from these models: they can create text that's pleasing, but that's as much as they can do. The next leap, to generate language that's also accurate, will require new techniques to bake in actual understanding. Until then, these models will always have issues with hallucinations. Or, at least, that's my expectation. Certainly nothing we've seen in GPT 3, 3.5, or Bing, which is rumoured to be based on something close to GPT 4, indicates any advances in this area.
        nadermx 4y ago
        Perhaps, but just like humans some are more adept at tasks than others. And an AGI using LLM's is completly feasable, for example on a quick thought a LLM could be trained on many LLM all specifically designed for tasks, and verfied against other LLMs, etc
- Gigachad 4y ago
  Because ChatGPT is not self driven and has no ability to do things. I can quite easily imagine one person doing 10 peoples work with this tool. I can’t imagine them being able to type fast enough to do 100 jobs.
- alfalfasprout 4y ago
  The problem I'm seeing is that "engineers" are not interchangeable. For some folks, the job is all straight coding. For others, it's understanding requirements, talking to stakeholders and figuring out their requirements, figuring out how to make a clean design taking lots of other factors in mind. It's not that ChatGPT is incapable... it's that it's not inherently going to make me significantly more productive.
- evilduck 4y ago
  Where did you pull 10% from then? That also seems like you're reaching up your ass. As with all of these arguments, context matters. Both of you need to say what you're doing with these tools. I've personally found the combination to range from "utterly useless" (writing Rust for microcontrollers) to "I could see this eliminating jobs" (CRUD API work).
matwood 4y ago
> A single engineer with GPT4 could potentially do the work of 10 engineers right now. Big assumption, but if that's possible then businesses will fill that time. What used to take teams of people and big iron can now be done by a single person on a VPC. Did that take away jobs? Nope, requirements only expanded.
- alfalfasprout 4y ago
  Indeed, folks making these types of conclusions seem to assume that what there is to be built will remain "constant". No, the more productive the tools the bigger the requirements. Modern high level languages didn't eliminate engineers. They suddenly meant one engineer could do what it would have taken 10 to do in COBOL or C and so software became more complex and capable.
  - matwood 4y ago
    I'm reminded of people wanting to go back to plain html. That's great if I can get the business to go back to basic html features. Same with computer speed increases. If anything, humanity has shown uncanny ability exploit any surplus resource for profit. Of course there can be industry shifts (MS was the industry for a long time and IBM before them. Google wasn't always dominant), but the pie grows to fit the available resources.
roflyear 4y ago
Burnout is proportional to how mch you do I think. Even if you can solve hundreds of problems a day in theory youll probably get pretty roughed up

visarga 4y ago

More importantly, everyone had access to calculators, spreadsheets, design tools, etc. And AI will be the same. The differentiating factor is still human.

VectorLock 4y ago

Secretary was the most populous job in the US before the advent of personal computers.

sebzim4500 4y ago

>Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. They did not eliminate mathematicians, but I do not believe mathematicians were ever doing arithmetic for a singificant portion of their workday. Before it was a device, "Calculator" used to be a job description. It isn't any more. Every one of those people lost their job.

xmprt 4y ago
I think this only becomes a problem if technology evolves faster than people change. All those "calculator" employees got better jobs. People keep making the analogy of how cars completely replaced horses (I used to as well) but horses can't fundamentally change what they are capable of. Even if the technology does evolve faster than people, governments can make sure people don't get impacted. Coal plants are more expensive to operate, worse for the environment, and less efficient but the coal industry is still kicking along for better or for worse.
- barking_biscuit 4y ago
  >I think this only becomes a problem if technology evolves faster than people change. This is the key distinction. Bandwidth. Humans only have so much of it, and if the rate at which they need to change their careers / find a new line of work exceeds their ramp-up time to become productive in that career / line of work then we can start to expect non-linear behavior from those humans. Maybe that means some sort of mental breakdown.
pfisherman 4y ago
Calculation is not dead! Finding more efficient ways to do calculations was and still is an active branch of mathematics and computer science. It’s just called algorithms now. PageRank was essentially an efficient way to compute / approximate the leading eigenvector of a very large matrix.
anticensor 4y ago
> "Calculator" used to be a job description It was computer, not calculator.

barking_biscuit 4y ago

>That is not going to happen. Calculators allowed us to outsource arithmetic to machines. They did not eliminate the need for mathematicians. Spreadsheets revolutionized bookkeeping. They did not eliminate the need for accountants. Robots automated much of the manual labor in manufacturing. They did not eliminate the need for process engineers, etc. Same story for autocad, protools, avid, etc. An AGI would be a "purposeful system" the same as humans. None of the other things you mentioned are purposeful systems. In terms of their structure and function they all have limitations on their own ability to change depending on the environment they are in. The key dimensions with which to think about this problem is "can this thing be structured in only one way for all environments? Or can it be structured in only one way in any given environment, but structured differently in different environments? Or can it be structured in more than one way in any environment, and also more than one way in different environments?" and then the same for functionality "can this thing only perform one function in all environments? Or can it perform only one function in a given environment, but different functions in different environments? Or can it perform more than one function in a given environment, and more than one function in different environments?" Only things which have both properties of being "multi-multistructural" and "multi-multifunctional" meet the definition of a "purposeful system". They can change their structure to adapt to the environment, and they can change their goals within and between environments. Humans currently use computers as instruments, and when an AGI hits it will be capable of saying no.

andrepd 4y ago
The only snag, of course, is that GPT is no closer to AGI than my phone keyboard autocomplete.
- barking_biscuit 4y ago
  No closer by what definition? Thinking it through, I would say that "autocomplete" would be uni-multistructural and uni-unifunctional given that autocomplete is always structured only one way for the given environment that it's in, but that structure differs between environments (e.g. a phone, or a form in a web-browser), and that regardless of what environment its in it's only function is to predict the next token of output for a given input. LLMs like ChatGPT on the other hand I would imagine to be uni-multistructural and multi-multifunctional, given that for any given environment you deploy an LLM into it's always structured the same, but there are many different structures it can take given there are lots of different LLMs. And I believe it to be multi-multifunctional because even within a single environment it can be used as an instrument to perform a wide variety of extrinsic functions, and this is true of other environments it could be deployed in. So... it's actually significantly closer.

hn_throwaway_99 4y ago

Whenever somebody makes the argument "Hey, we've had lots of technical progress in the past, but that just opened up new jobs for people to do!" I always think "Have you looked at the state of the US job market and economy over the past 40 years?" That is, we've had a huge hollowing out of all sorts of "middle" jobs in the US (e.g. someone mentioned secretaries used to be the most populous job in the US) so now we're largely (not exclusively, but largely) left with 2 categories of jobs: (a) dead-end jobs that are at present difficult to automate because they often involve manual labor: housekeepers, security guards, massage therapists, waiters, truck drivers (but, we see where that's headed...), etc. and (b) high level jobs that "manage the machines", e.g. tech jobs. It's not that hard to see where this ends up with AI being capable of more complicated tasks - I wrote about an anecdote recently where ChatGPT had essentially already obviated some positions https://news.ycombinator.com/item?id=34862450 https://news.ycombinator.com/item?id=34862450. There are a slew of very high paying jobs that AI is coming for next, e.g. there is currently a shortage of radiologists because many folks in med school see the writing on the wall and don't go into radiology residencies. While full diagnostic radiology AI may not be there yet, it certainly will be by the time folks in med school finish their career in 40 years.

purerandomness 4y ago
Cargo jobs that exist for bureaucratic reasons, or because of industry inertia, will be disrupted. That's the job of new inventions. Nothing to complain about, in my opinion. Those however who think that radiologists (/lawyers/secretaries) will get automated away, don't really understand what a radiologist's job really is. The boring bureaucratic part of a radiologist's job will get automated away, yes, but that's because automatable/auto-completeable tasks should get automated at some point. Think of it as a healthy organism eating away the boring part of a dream job that you, as a kid, imagined doing when you'll grow up.
- hn_throwaway_99 4y ago
  > Those however who think that radiologists (/lawyers/secretaries) will get automated away, don't really understand what a radiologist's job really is. As someone intimately familiar with the job of a radiologist, please then tell me what "a radiologist's job really is". A diagnostic radiologist's job is to take a series of images, and output a set of findings and diagnoses. There is essentially no better task suited to modern AI. Yes, radiologists can do procedures like biopsies and potentially other interventions, but diagnostic radiologists often solely read images or at least earn the vast majority of their RVUs by reading images.