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ChatGPT and the Labor Market: Unraveling the Effect of AI Discussions on Students' Earnings Expectations

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  • Samir Huseynov

Abstract

This paper investigates the causal impact of negatively and positively toned ChatGPT Artificial Intelligence (AI) discussions on US students' anticipated labor market outcomes. Our findings reveal students reduce their confidence regarding their future earnings prospects after exposure to AI debates, and this effect is more pronounced after reading discussion excerpts with a negative tone. Unlike STEM majors, students in Non-STEM fields show asymmetric and pessimistic belief changes, suggesting that they might feel more vulnerable to emerging AI technologies. Pessimistic belief updates regarding future earnings are also prevalent among non-male students, indicating widespread AI concerns among vulnerable student subgroups. Educators, administrators, and policymakers may regularly engage with students to address their concerns and enhance educational curricula to better prepare them for a future that AI will inevitably shape.

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  • Samir Huseynov, 2023. "ChatGPT and the Labor Market: Unraveling the Effect of AI Discussions on Students' Earnings Expectations," Papers 2305.11900, arXiv.org, revised Aug 2023.
    • Handle: RePEc:arx:papers:2305.11900
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    References listed on IDEAS

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    1. Christoph Drobner, 2022. "Motivated Beliefs and Anticipation of Uncertainty Resolution," American Economic Review: Insights, American Economic Association, vol. 4(1), pages 89-105, March.
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    5. Christoph Drobner & Sebastian J. Goerg, 2024. "Motivated Belief Updating and Rationalization of Information," Management Science, INFORMS, vol. 70(7), pages 4583-4592, July.
    6. Alexander Coutts, 2019. "Good news and bad news are still news: experimental evidence on belief updating," Experimental Economics, Springer;Economic Science Association, vol. 22(2), pages 369-395, June.
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    8. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
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    Cited by:

    1. Dong, Mengming Michael & Stratopoulos, Theophanis C. & Wang, Victor Xiaoqi, 2024. "A scoping review of ChatGPT research in accounting and finance," International Journal of Accounting Information Systems, Elsevier, vol. 55(C).

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    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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