There are more people in need to operate it or added it to reduce workload. It is more likely automates tasks more often than entire jobs and increases productivity before reducing jobs. However, there will be the day when the ulitmate utopian goal will be to remove the word 'work' out of the dictorary for sure.
From personal experience, corporations conduct layoffs such that they can't be shown on official unemployment numbers. Many of their former employees face legal harassment and denial of benefits in order to reduce corporate liability.
The idea that AI isn't increasing unemployment is an illusion created by statistical modeling. Usually, statisticians are good at convincing others of their modeling choices. For example, even if programmers get laid off and janitorial jobs increase, the overall employment rate might not show any damage.
When stakeholders cite statistics, they can always shape the modeling to fit their narrative. I'm not sure if this is a general trait of statisticians, but they tend to interpret overall indicators in ways that favor their own school or affiliation.
One possible interpretation of why the overall job market looks stable, despite AI eroding employment, is that macroeconomic forces are strong enough to keep unemployment from rising. But that interpretation might have been excluded precisely because the speaker is affiliated with Anthropic.
Predictive statistics are also subjective. Surveys can be manipulated depending on how you select the sample group. This is really a mix of hope and bias, framed as objective prediction. The public tends to think of technological change as a single 'event,' while technologists experience it gradually in real time. But the public only notices it when it suddenly appears. Nokia employees probably felt safe too, right up until Steve Jobs walked out with the iPhone.
Curious about this, I looked into the US BLS survey. I found that working just one hour counts as being employed. So I wonder if they've looked into whether quality jobs are disappearing while bad jobs are increasing.
And the real impact of AI will likely show up not as layoffs, but as a freeze on new hires. That is, existing employees, because of company-specific tacit knowledge, might be kept, but the hiring rate for new workers, especially younger ones, will drop in roles highly exposed to AI. So instead of looking at total unemployment, we should look at youth employment as a leading indicator.
Of course, this could just be the limit of my knowledge. I'm self-taught with no formal degree. I could be wrong. But honestly, it doesn't take much digging to see that what this person is saying doesn't hold up.
One of the skills I've developed most while reading HN is learning how to present statistical truths in a polished way, even when the content isn't actually true.
One day, AI will be able to provide midwit analyses like this.
Until that day, we can just say what we all know: 1) AI will absolutely decimate white-collar office jobs in the future, 2) composition of the workplace will change (more women will elect not to participate), and 3) we're in a capital boom where both successful and incompetent spending on AI occurred.
I suspect the reason people are hesitant to admit the obviousness of the future reality of white collar job loss (or replacement at the very least) is ego.
And I suspect that will be the last thing to finally implode, with interesting and positive social consequences.
"Based on this grid, what is the most Democratic voting group in America? It’s voters with postgraduate degrees but lower-to-middle household incomes of $30K to $60K per year."
simple, the trillions of dollars bieng spent at some ridiculous rate of whatever number of milliins per hour is bubbling the whole worlds economy
that and while indivual productivity isn't great, the ever increasing scale of industrial production of everything is reducing real unit costs and providing more profit froth to the foam based economy
and lastly is the simple fact that AI does not actualy do anything except burn money and the vast majority of what AI gets credited for still needs human support and monitoring and the real situation is one of
REDUCED efficiency , the rest is just a shell game needing people to do the shuffling, speaking of which!, hey! time to write a quote!
also not to be rude to anyone who still uses it but i dont know anyone under the age of 40 that uses twitter still -- unless they do porn -- and a lot of people i know have begun to joke that it's the new facebook because it's like 99% racist old people and bots.
not saying this to be mean but more just to inform people that hey; careful about admitting you're still using it since at best you're convincing the room you're a porn addict and at worst you're an alt-right fascist.
This is from Peter McCrory, Head of Economics at Anthropic. Calling that out since it wasn't obvious to me at first.
In most cases, it's actually (much) worse. For example, the infamous Ford rehiring.
There are more people in need to operate it or added it to reduce workload. It is more likely automates tasks more often than entire jobs and increases productivity before reducing jobs. However, there will be the day when the ulitmate utopian goal will be to remove the word 'work' out of the dictorary for sure.
From personal experience, corporations conduct layoffs such that they can't be shown on official unemployment numbers. Many of their former employees face legal harassment and denial of benefits in order to reduce corporate liability.
The idea that AI isn't increasing unemployment is an illusion created by statistical modeling. Usually, statisticians are good at convincing others of their modeling choices. For example, even if programmers get laid off and janitorial jobs increase, the overall employment rate might not show any damage.
When stakeholders cite statistics, they can always shape the modeling to fit their narrative. I'm not sure if this is a general trait of statisticians, but they tend to interpret overall indicators in ways that favor their own school or affiliation.
One possible interpretation of why the overall job market looks stable, despite AI eroding employment, is that macroeconomic forces are strong enough to keep unemployment from rising. But that interpretation might have been excluded precisely because the speaker is affiliated with Anthropic.
Predictive statistics are also subjective. Surveys can be manipulated depending on how you select the sample group. This is really a mix of hope and bias, framed as objective prediction. The public tends to think of technological change as a single 'event,' while technologists experience it gradually in real time. But the public only notices it when it suddenly appears. Nokia employees probably felt safe too, right up until Steve Jobs walked out with the iPhone.
Curious about this, I looked into the US BLS survey. I found that working just one hour counts as being employed. So I wonder if they've looked into whether quality jobs are disappearing while bad jobs are increasing.
And the real impact of AI will likely show up not as layoffs, but as a freeze on new hires. That is, existing employees, because of company-specific tacit knowledge, might be kept, but the hiring rate for new workers, especially younger ones, will drop in roles highly exposed to AI. So instead of looking at total unemployment, we should look at youth employment as a leading indicator.
Of course, this could just be the limit of my knowledge. I'm self-taught with no formal degree. I could be wrong. But honestly, it doesn't take much digging to see that what this person is saying doesn't hold up.
One of the skills I've developed most while reading HN is learning how to present statistical truths in a polished way, even when the content isn't actually true.
The guy with his back to the volcano says "what problem?"
One day, AI will be able to provide midwit analyses like this.
Until that day, we can just say what we all know: 1) AI will absolutely decimate white-collar office jobs in the future, 2) composition of the workplace will change (more women will elect not to participate), and 3) we're in a capital boom where both successful and incompetent spending on AI occurred.
I suspect the reason people are hesitant to admit the obviousness of the future reality of white collar job loss (or replacement at the very least) is ego.
And I suspect that will be the last thing to finally implode, with interesting and positive social consequences.
> 2) composition of the workplace will change (more women will elect not to participate)
What? Why on earth would it specifically hit women?
Have you not been present in our recent two-decade credentialed make-believe economy?
The one that puts government in the place of a father?
https://www.forbes.com/sites/michelletravis/2026/01/29/women...
Edit:
"Based on this grid, what is the most Democratic voting group in America? It’s voters with postgraduate degrees but lower-to-middle household incomes of $30K to $60K per year."
https://www.natesilver.net/p/the-dsa-sweet-spot-highly-educa...
The task list only gets bigger
simple, the trillions of dollars bieng spent at some ridiculous rate of whatever number of milliins per hour is bubbling the whole worlds economy that and while indivual productivity isn't great, the ever increasing scale of industrial production of everything is reducing real unit costs and providing more profit froth to the foam based economy and lastly is the simple fact that AI does not actualy do anything except burn money and the vast majority of what AI gets credited for still needs human support and monitoring and the real situation is one of REDUCED efficiency , the rest is just a shell game needing people to do the shuffling, speaking of which!, hey! time to write a quote!
I’ve seen layoffs tied-to and to make up for AI spending. So the headline at least is inaccurate.
That said, the savvier firms are looking to eliminate the army of low-quality, and “cheaper” contractors and consultants.
The idiotic ones are doubling-down on the cheaper labor while shoring up on spending.
Gross; twitter.
Here: https://xcancel.com/PeterMcCrory/status/2079979321607745905
also not to be rude to anyone who still uses it but i dont know anyone under the age of 40 that uses twitter still -- unless they do porn -- and a lot of people i know have begun to joke that it's the new facebook because it's like 99% racist old people and bots.
not saying this to be mean but more just to inform people that hey; careful about admitting you're still using it since at best you're convincing the room you're a porn addict and at worst you're an alt-right fascist.