HackerPapers

arXiv:2303.10130econ.GN

GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models

Tyna Eloundou, Sam Manning, Pamela Mishkin, Daniel Rock

Abstract

We investigate the potential implications of large language models (LLMs), such as Generative Pre-trained Transformers (GPTs), on the U.S. labor market, focusing on the increased capabilities arising from LLM-powered software compared to LLMs on their own. Using a new rubric, we assess occupations based on their alignment with LLM capabilities, integrating both human expertise and GPT-4 classifications. Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted. We do not make predictions about the development or adoption timeline of such LLMs. The projected effects span all wage levels, with higher-income jobs potentially facing greater exposure to LLM capabilities and LLM-powered software. Significantly, these impacts are not restricted to industries with higher recent productivity growth. Our analysis suggests that, with access to an LLM, about 15% of all worker tasks in the US could be completed significantly faster at the same level of quality. When incorporating software and tooling built on top of LLMs, this share increases to between 47 and 56% of all tasks. This finding implies that LLM-powered software will have a substantial effect on scaling the economic impacts of the underlying models. We conclude that LLMs such as GPTs exhibit traits of general-purpose technologies, indicating that they could have considerable economic, social, and policy implications.

arXiv comments
Journal reference
DOI
Subjects
econ.GNGeneral Economics cs.AIArtificial Intelligence cs.CYComputers and Society

On Hacker News

Linked by 10 identifiable commenters in 11 comments across 10 threads, from Mar 2023 to Nov 2025. Found in 2 HN submissions from Mar 2023 to Mar 2026. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments10 threads

  1. MIT study finds AI can replace 11.7% of U.S. workforce 1 comment

    • Yes, agree. There should be range. Similar precision appears in other exposure studies also. E.g. This one was trending from OpenAI and Wharton a short while back: arxiv.org/pdf/2303.10130

      sciencegeek123View on HNParent context

  2. John Carmack talk at Upper Bound 2025 1 comment

    • That is what open ai’s non-profit economic research arm has claimed. LLMs will fundamentally change how we interact with the world like the Internet did. It will take time like the Internet and a couple of hype cycle pops but it will change the way we do things. It will help a…

      orochimaaruView on HNParent context

  3. OpenAI not expecting to break into profitability until 2029 1 comment

    • Penn and OpenAI claimed: "Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19% of workers may see at least 50% of their tasks impacted." https://arxiv.org/abs/2303.10130

      anarticleView on HNParent context

  4. AutoDev: Automated AI-driven development by Microsoft 1 comment

    • See Appendix D in https://arxiv.org/pdf/2303.10130.pdf OpenAI’s “GPTs are GPTs: An early look at the labor market impact potential of large language models” It’s not just construction workers. Still safe to be a pro athlete and a short order cook, too!

      bluebooView on HNParent context

  5. Google AI chief says there's a 50% chance we'll hit AGI in just 5 years 1 comment

    • 1. "I think GPT-3 is artificial general intelligence, AGI. I think GPT-3 is as intelligent as a human. And I think that it is probably more intelligent than a human in a restricted way… in many ways it is more purely intelligent than humans are. I think humans are approximating…

      famouswafflesView on HNParent context

  6. The future of AI according to thousands of forecasters 1 comment

    • Yes you'll find that any testable definition of AGI that has not been passed yet would be unpassable for a big chunk of the human population. In other words, General, Artificial and Intelligent have been passed. That's why a few papers/researchers opt to call these models…

      famouswafflesView on HNParent context

  7. Anthropic’s $5B, 4-year plan to take on OpenAI 1 comment

    • You don't need to just take one source. OpenAI authored their own paper [1] on the economic impacts of just LLMs: "Our findings reveal that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by the introduction of LLMs, while approximately 19%…

      lhlView on HNParent context

  8. AI could replace equivalent of 300M jobs – report 2 comments

    • GPTs are GPTs: An Early Look at the Labor Market Impact - Potential of Large Language Models Tyna Eloundou1, Sam Manning, Pamela Mishkin, and Daniel Rock OpenAI, OpenResearch, University of Pennsylvania March 27, 2023 https://arxiv.org/pdf/2303.10130.pdf

      achowView on HNParent context

    • A human will unfortunately need do it, because Agricultural Equipment Operators have no exposed tasks to LLMs [0]. We'll need other AI advancements. [0]: https://arxiv.org/pdf/2303.10130v4.pdf

      wolpoliView on HNParent context

  9. OpenAI Research Says 80% of U.S. Workers' Jobs Will Be Impacted by GPT 1 comment

    • The study didn't say they will all simply lose their job? Did you just read the headline and assume "80% of jobs will be impacted by GPT" means they lose their jobs? Impacted doesn't mean completely automate either, it can just be assisting, improving efficiency, better quality…

      dmixView on HNParent context

  10. ChatGPT is down 1 comment

    • Hmm... Perhaps "high income workers" take serious this paper: "OpenAI publishes paper on the economic impact of GPT-4: Higher income workers most exposed" https://www.reddit.com/r/Futurology/comments/11whznb/openai_... https://arxiv.org/abs/2303.10130

      brutusurpView on HNParent context

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.