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Evaluating the Impact of AI on the Labor Market: Current State of Affairsbudgetlab.yale.edu/research/evaluating-impact-ai-labor-market-current-state-affairs
382 sats \ 7 comments \ @0xbitcoiner 2 Oct AI

Key Takeaways

  • While the occupational mix is changing more quickly than it has in the past, it is not a large difference and predates the widespread introduction of AI in the workforce.
  • Currently, measures of exposure, automation, and augmentation show no sign of being related to changes in employment or unemployment.
  • Better data is needed to fully understand the impact of AI on the labor market.
  • We plan on updating this analysis regularly moving forward to see how the impact of AI on the labor market changes over time.
How has AI impacted the labor market? Since generative AI was first introduced nearly three years ago, surveys show widespread public anxiety about AI’s potential for job losses. While it is impossible to accurately predict the future, we can examine how U.S. employment has changed since ChatGPT’s release in November 2022.
Our analysis complements other recent studies that provide nascent evidence of possible AI impacts on specific occupations and sub-populations, such as early career workers. We took a broader lens, widening the aperture to the whole labor market, and asked two main questions.
[...]

Is this Time Different? Changes in the Occupational Mix

...read more at budgetlab.yale.edu
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163 sats \ 6 replies \ @optimism 2 Oct
Interesting! Especially the one buried deep down:
This basically is the reality check on #1237966
I read this as that currently, GenAI is impacting nerds and media more than expected, and nearly everything else less.
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143 sats \ 2 replies \ @SimpleStacker 2 Oct
I'm surprised legal is so small. It actually makes me question a bit the methodology of this paper, or its data sources. I'd think for legal it'd at least be used as a souped up search engine.
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100 sats \ 0 replies \ @0xbitcoiner OP 2 Oct
It actually makes me question a bit the methodology of this paper, or its data sources.
from report:
Just as the OpenAI metric has limitations, so too does Anthropic’s usage data. Figure 22 shows the occupational shares of all “conversations” with Claude (the AI chatbot), and illustrates the occupation groups that are over- and under- represented in this usage, compared to their exposure ranking and employment share.
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0 sats \ 0 replies \ @optimism 2 Oct
I think the google numbers would reflect this better?
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121 sats \ 2 replies \ @0xbitcoiner OP 2 Oct
Can’t say I agree with the nerd bit! 😂
I also thought this chart was super interesting, it gives a good idea of where AI’s doing a solid job, and more importantly, where it could be doing way better.
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33 sats \ 1 reply \ @optimism 2 Oct
it gives a good idea of where AI’s doing a solid job
I'm not convinced that this is a measure of AI doing a solid job versus where AI giants' FOMO marketing is doing a solid job, yet.
I should really go code some javascript and also be a 1337 vibecoder, because in system programming it definitely doesn't work.
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100 sats \ 0 replies \ @0xbitcoiner OP 2 Oct
Looks like I didn’t see the full picture. What you’re saying makes sense. My thinking was, if it's being used more than expected, it must be a good product. But like you said, that might not be true.
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