Well we had people being "let go" (how I hate this term...as if they were trying to flee but couldn't before) at our Call Center. Replaced by AI. The women were older. Didn't have long until retirement. Seems to be still worth it to kick them.
While it's likely due to other factors (i.e. like maybe the stock indices have just completely de-coupled from reality or are just being helped by AI-hype?), the fact that US job openings seemingly de-coupled from S&P 500 in Nov/Dec 2022 when ChatGPT was publicly released (as a web app) is pretty interesting.
I saw a great shift in our data science job offers: we removed the old offers and now only search machine learning experts. We do not know if they would have any problem to work on. But we surely are looking for one.
I'm not surprised, is saving tens of thousands (if not hundreds of thousands) of dollars per employee worth screwing up by betting on AI and losing millions? Notice that the headlines of companies wanting AI are wanting their employees to use AI to be more productive, and that's fine, but they still need their employees to be fully aware of the output so they're not just churning out slop.
Job numbers? Pretty sure you could make the case that this claim isn't true, but the data might be too nebulous.
But it's definitely had an effect on jobs.
It's made so many underqualified people think they have a new superpower, and made so many people miserable with the implied belittling of their actual skills. It's really damaging work culture.
Of course studies like this are aimed at people who think jobs are interchangeable neutral little black boxes that can be scaled up and scaled down, and who don't like to think about what they involve.
> Overall, our metrics indicate that the broader labor market has not experienced a discernible disruption since ChatGPT’s release
I am a small anecdote where developers who just use chatgpt/cursor are in higher positions than me who learned to code back in 2010. Use as in "chatgpt told me..." about whatever topic. Still they are accomplishing the task (getting code out there that works).
I also had a vibe coded prototype get handed to me to fix it
A great and relevant quote from a recent Noah Smith article discussing this same subject:
> The debate over whether AI is taking people’s jobs may or may not last forever. If AI takes a lot of people’s jobs, the debate will end because one side will have clearly won. But if AI doesn’t take a lot of people’s jobs, then the debate will never be resolved, because there will be a bunch of people who will still go around saying that it’s about to take everyone’s job. Sometimes those people will find some subset of workers whose employment prospects are looking weaker than others, and claim that this is the beginning of the great AI job destruction wave. And who will be able to prove them wrong?
Zero effects on jobs overall, i.e. for every person displaced by AI, another has been hired? Or zero effects on any individual person's job, i.e. not one single person has lost their job due to their boss wanting to replace them with AI?
>> "Since amortization took effect [ in 2022 thanks to a time-triggered portion of the Trump-era Tax Cuts and Jobs Act ("TCJA" 2017) ], the growth rate of R&D spending has slowed dramatically from 6.6 percent on average over the previous five years to less than one-half of 1 percent over the last 12 months," Estes said. "The [R&D] sector is down by more than 14,000 jobs"
> Hopefully R&D spending at an average of 6.6% will again translate to real growth
>> In 2017 Trump made businesses have to amortize these [R&D] expenses over 5 years instead of deducting them, starting in 2022 (it is common for an administration to write laws that will only have a negative effect after they're gone). This move wrecked the R&D tax credit. Many US businesses stopped claiming R&D tax credits entirely as a result. Others had surprise tax bills
> People just want the same R&D tax incentives back:
>And major companies conducting layoffs like IBM and Salesforce have held themselves up as examples of that narrative, though their employee culls may be more focused on outsourcing than automation.
Automation seems to be a better excuse than outsourcing
Every year, large companies secretly rank employees and then yank the 10% or so they consider low performing. This is called rank and yank [1]. If your company has performance reviews and is ran by MBAs it almost certainly uses it.
The most important aspect of rank and yank is that it has to be done in secrecy. Your company will not tell you it is using it. Even your manager might not know this.
When rank and yank is not done in secrecy, employees react to it by hiring the most mediocre people they can, sabotaging/isolating strong performers, hiring to fire, forming peer review/code review mafias, avoiding helping others as much as possible, etc. Anything they can do to not land in the bottom 10%. This cannibalizes the company and an example is what Ballmer did to Microsoft.
Any person with a ChatGPT account can now ask it to analyze the "game" of rank and yank from the perspective of game theory and realize how dumb the whole idea is. The rational strategy for the employee is to destroy the company from within. But MBAs love it because it involves a made up statistical distribution.
The only truth about rank and yank is that it's a stupid idea that has impacted the careers of millions of hard working people around the world, while also impacting many families and their future. It has converted thousands of companies into horrible places to work filled with workplace psychopaths at the top.
MBAs are people who believe in the work of the person that kickstarted the decline of American manufacturing, Jack Welch. Jack Welch extracted record profits from GE for 20 years, but left it a hollowed-out "pile of shit" according to his successor. The worse part is that MBAs aspire to be like him and in the process have ruined the whole manufacturing industry.
So to pull off a rank and yank every year you need a scapegoat, and this year the scapegoat is AI. In previous years it has been the economy, or some other excuse. AI will naturally become the scapegoat for everything.
Have you ever wondered why your company is laying off people while having job postings for the same positions? Does it happen every year? Does it happen after performance reviews? Is it always around 10% of the workforce? Oof... that's a tough guess, I wonder what it might be!
AI is the perfect scapegoat because the company can claim they're using AI and boost their value somehow. But if AI could reduce your headcount by so much then your company, your business model, your processes, your intellectual property, etc. have no intrinsic value anyways and the correct interpretation of the situation is that everyone should divest and make the share price go to zero.
Not surprised. There’s some good applications but the hype bubble is on the verge of bursting. Many companies are boated and inefficient but it’s highly unlikely that “AI” is the fix.
Ironically the thing broken in most cases is poor quality management that let things get so bloated and messy in the first place… the same folks that are cluelessly boasting about the potential of AI in their company.
My personal experience lines up with this. From what I've seen all the AI hype is coming from:
- Companies building AI models & tools - this one is obvious.
- Executives using AI to justify layoffs - there have been constant rounds of layoffs across corporate America since ~2021, but recent ones have been rebranded as "AI taking the jobs" so no one points to the obvious corporate mismanagement, offshoring and greed.
- Bosses using AI to push employees to work harder - I have personally seen this at my own company. AI is an excuse to increase forced attrition. "You aren't good enough" is harder to justify, so now it is "you aren't using AI well enough".
Real-world use cases of AI meanwhile haven't really moved beyond the prototype stage.
As someone who attended this school and has a degree from their economics department: this finding very consistent from what I learned in classes covering the economics of innovation. Historically, technological revolutions have increased productivity and labor force participation, despite many pundits at the time worried about loss of jobs.
The core intuition for this phenomenon is that human society overall takes the tech productivity gains to do more things overall, creating new goods and services. The broader range of goods and services overall also enables more people to find work.
Put another way, "“One thing I love about customers is that they are divinely discontent. Their expectations are never static – they go up. It’s human nature. You cannot rest on your laurels in this world. Customers won’t have it.” -- one of Bezos's Amazon shareholder letters.
One of my favorite counterintuitive examples: The biggest economic gains from the 1800s Industrial Revolution actually came from the humble washer/dryer. By making routine homeware 100x more efficient, this (along with other home appliances) allowed more women to enter the labor force, nearly doubling labor force participation within a couple generations. Though, at the beginning, lots of people were opining about homemakers losing a sense of purpose or relaxing all the time.
It's certainly possible that this study is just reinforcing the researcher's biases from their previous understanding of the economics of innovation, and also possible that this study is accurate today but conditions will change in the future. That said, I believe the burden of proof is on the pundits claiming cataclysmic job loss, which is counter to economic historians' models of innovation.
You can't take these things in a vacuum. Labor has gotten weaker over time. AI just gives more power to employers.
Take Klarna. They laid off 700 people, realized it was a mistake, but they are hiring people back as gig workers [0]. Not proper employees with a salary and benefits. The thing about the US in particular is that a job is not just a job. It's your social safety net, as too many welfare programs have onerous work requirements. Employers know this. They have way too much power, probably more than ever before in our lifetimes. AI gives them that much more power.
36 comments
[ 2.7 ms ] story [ 44.7 ms ] thread>As previously noted, the metrics from OpenAI and Anthropic are imperfect proxies for AI risk and usage, while still being the best available.
Seems they're just coming out and admitting they refuse to measure it themselves. Not a good sign.
But it's definitely had an effect on jobs.
It's made so many underqualified people think they have a new superpower, and made so many people miserable with the implied belittling of their actual skills. It's really damaging work culture.
Of course studies like this are aimed at people who think jobs are interchangeable neutral little black boxes that can be scaled up and scaled down, and who don't like to think about what they involve.
> Overall, our metrics indicate that the broader labor market has not experienced a discernible disruption since ChatGPT’s release
Because metrics don't tell the story.
Title implies all things AI, when they were actually looking at GenAI. I know it's what everyone thinks of, but I hate how everything gets muddled.
I suspect AI is currently fashionable as a smokescreen to justify deep cost cutting (See MSFT example.)
I also had a vibe coded prototype get handed to me to fix it
> The debate over whether AI is taking people’s jobs may or may not last forever. If AI takes a lot of people’s jobs, the debate will end because one side will have clearly won. But if AI doesn’t take a lot of people’s jobs, then the debate will never be resolved, because there will be a bunch of people who will still go around saying that it’s about to take everyone’s job. Sometimes those people will find some subset of workers whose employment prospects are looking weaker than others, and claim that this is the beginning of the great AI job destruction wave. And who will be able to prove them wrong?
Source: https://www.noahpinion.blog/p/ai-and-jobs-again
From "House restores immediate R&D deduction in new tax bill" (2024) https://news.ycombinator.com/item?id=39213002 .. https://news.ycombinator.com/context?id=38988189 :
>> "Since amortization took effect [ in 2022 thanks to a time-triggered portion of the Trump-era Tax Cuts and Jobs Act ("TCJA" 2017) ], the growth rate of R&D spending has slowed dramatically from 6.6 percent on average over the previous five years to less than one-half of 1 percent over the last 12 months," Estes said. "The [R&D] sector is down by more than 14,000 jobs"
> Hopefully R&D spending at an average of 6.6% will again translate to real growth
From "Generative AI as Seniority-Biased Technological Change" https://news.ycombinator.com/item?id=45275202 :
> Did tech reduce hiring after Section 174 R&D tax policy changes?
[...]
> From https://news.ycombinator.com/item?id=45131866 :
>> In 2017 Trump made businesses have to amortize these [R&D] expenses over 5 years instead of deducting them, starting in 2022 (it is common for an administration to write laws that will only have a negative effect after they're gone). This move wrecked the R&D tax credit. Many US businesses stopped claiming R&D tax credits entirely as a result. Others had surprise tax bills
> People just want the same R&D tax incentives back:
> "Tell HN: Help restore the tax deduction for software dev in the US (Section 174)" (2025 (2439 points)) https://news.ycombinator.com/item?id=44226145
It is suspected that hiring levels correlate with the cancelling of the R&D Tax credit.
The TCJA (2017 Trump) cancelled the R&D tax credit.
The OBBA (2025 Trump) restored the R&D tax credit for tax year 2025.
Automation seems to be a better excuse than outsourcing
Every year, large companies secretly rank employees and then yank the 10% or so they consider low performing. This is called rank and yank [1]. If your company has performance reviews and is ran by MBAs it almost certainly uses it.
[1] https://en.wikipedia.org/wiki/Vitality_curve
The most important aspect of rank and yank is that it has to be done in secrecy. Your company will not tell you it is using it. Even your manager might not know this.
When rank and yank is not done in secrecy, employees react to it by hiring the most mediocre people they can, sabotaging/isolating strong performers, hiring to fire, forming peer review/code review mafias, avoiding helping others as much as possible, etc. Anything they can do to not land in the bottom 10%. This cannibalizes the company and an example is what Ballmer did to Microsoft.
Any person with a ChatGPT account can now ask it to analyze the "game" of rank and yank from the perspective of game theory and realize how dumb the whole idea is. The rational strategy for the employee is to destroy the company from within. But MBAs love it because it involves a made up statistical distribution.
The only truth about rank and yank is that it's a stupid idea that has impacted the careers of millions of hard working people around the world, while also impacting many families and their future. It has converted thousands of companies into horrible places to work filled with workplace psychopaths at the top.
MBAs are people who believe in the work of the person that kickstarted the decline of American manufacturing, Jack Welch. Jack Welch extracted record profits from GE for 20 years, but left it a hollowed-out "pile of shit" according to his successor. The worse part is that MBAs aspire to be like him and in the process have ruined the whole manufacturing industry.
So to pull off a rank and yank every year you need a scapegoat, and this year the scapegoat is AI. In previous years it has been the economy, or some other excuse. AI will naturally become the scapegoat for everything.
Have you ever wondered why your company is laying off people while having job postings for the same positions? Does it happen every year? Does it happen after performance reviews? Is it always around 10% of the workforce? Oof... that's a tough guess, I wonder what it might be!
AI is the perfect scapegoat because the company can claim they're using AI and boost their value somehow. But if AI could reduce your headcount by so much then your company, your business model, your processes, your intellectual property, etc. have no intrinsic value anyways and the correct interpretation of the situation is that everyone should divest and make the share price go to zero.
Ironically the thing broken in most cases is poor quality management that let things get so bloated and messy in the first place… the same folks that are cluelessly boasting about the potential of AI in their company.
- Companies building AI models & tools - this one is obvious.
- Executives using AI to justify layoffs - there have been constant rounds of layoffs across corporate America since ~2021, but recent ones have been rebranded as "AI taking the jobs" so no one points to the obvious corporate mismanagement, offshoring and greed.
- Bosses using AI to push employees to work harder - I have personally seen this at my own company. AI is an excuse to increase forced attrition. "You aren't good enough" is harder to justify, so now it is "you aren't using AI well enough".
Real-world use cases of AI meanwhile haven't really moved beyond the prototype stage.
The core intuition for this phenomenon is that human society overall takes the tech productivity gains to do more things overall, creating new goods and services. The broader range of goods and services overall also enables more people to find work.
Put another way, "“One thing I love about customers is that they are divinely discontent. Their expectations are never static – they go up. It’s human nature. You cannot rest on your laurels in this world. Customers won’t have it.” -- one of Bezos's Amazon shareholder letters.
One of my favorite counterintuitive examples: The biggest economic gains from the 1800s Industrial Revolution actually came from the humble washer/dryer. By making routine homeware 100x more efficient, this (along with other home appliances) allowed more women to enter the labor force, nearly doubling labor force participation within a couple generations. Though, at the beginning, lots of people were opining about homemakers losing a sense of purpose or relaxing all the time.
It's certainly possible that this study is just reinforcing the researcher's biases from their previous understanding of the economics of innovation, and also possible that this study is accurate today but conditions will change in the future. That said, I believe the burden of proof is on the pundits claiming cataclysmic job loss, which is counter to economic historians' models of innovation.
Take Klarna. They laid off 700 people, realized it was a mistake, but they are hiring people back as gig workers [0]. Not proper employees with a salary and benefits. The thing about the US in particular is that a job is not just a job. It's your social safety net, as too many welfare programs have onerous work requirements. Employers know this. They have way too much power, probably more than ever before in our lifetimes. AI gives them that much more power.
0 - https://www.livemint.com/companies/news/klarnas-ai-replaced-...