IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2303.01157.html
   My bibliography  Save this paper

How will Language Modelers like ChatGPT Affect Occupations and Industries?

Author

Listed:
  • Ed Felten
  • Manav Raj
  • Robert Seamans

Abstract

Recent dramatic increases in AI language modeling capabilities has led to many questions about the effect of these technologies on the economy. In this paper we present a methodology to systematically assess the extent to which occupations, industries and geographies are exposed to advances in AI language modeling capabilities. We find that the top occupations exposed to language modeling include telemarketers and a variety of post-secondary teachers such as English language and literature, foreign language and literature, and history teachers. We find the top industries exposed to advances in language modeling are legal services and securities, commodities, and investments. We also find a positive correlation between wages and exposure to AI language modeling.

Suggested Citation

  • Ed Felten & Manav Raj & Robert Seamans, 2023. "How will Language Modelers like ChatGPT Affect Occupations and Industries?," Papers 2303.01157, arXiv.org, revised Mar 2023.
  • Handle: RePEc:arx:papers:2303.01157
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2303.01157
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Genz, Sabrina & Gregory, Terry & Janser, Markus & Lehmer, Florian & Matthes, Britta, 2021. "How do workers adjust when firms adopt new technologies?," ZEW Discussion Papers 21-073, ZEW - Leibniz Centre for European Economic Research.
    2. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    3. Jason Furman & Robert Seamans, 2019. "AI and the Economy," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 161-191.
    4. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "The Economics of Artificial Intelligence: An Agenda," NBER Books, National Bureau of Economic Research, Inc, number agra-1.
    5. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    6. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    7. Morgan R. Frank & David Autor & James E. Bessen & Erik Brynjolfsson & Manuel Cebrian & David J. Deming & Maryann Feldman & Matthew Groh & José Lobo & Esteban Moro & Dashun Wang & Hyejin Youn & Iyad Ra, 2019. "Toward understanding the impact of artificial intelligence on labor," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(14), pages 6531-6539, April.
    8. Edward W. Felten & Manav Raj & Robert Seamans, 2018. "A Method to Link Advances in Artificial Intelligence to Occupational Abilities," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 54-57, May.
    9. Agrawal, Ajay & Gans, Joshua & Goldfarb, Avi (ed.), 2019. "The Economics of Artificial Intelligence," National Bureau of Economic Research Books, University of Chicago Press, number 9780226613338, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anil R. Doshi & Oliver P. Hauser, 2023. "Generative artificial intelligence enhances creativity but reduces the diversity of novel content," Papers 2312.00506, arXiv.org, revised Mar 2024.
    2. Pablo Casas & José L. Torres, 2024. "Government size and automation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 31(3), pages 780-807, June.
    3. Bohren, Noah & Hakimov, Rustamdjan & Lalive, Rafael, 2024. "Creative and Strategic Capabilities of Generative AI: Evidence from Large-Scale Experiments," IZA Discussion Papers 17302, Institute of Labor Economics (IZA).
    4. Ylenia Curci & Nathalie Greenan & Silvia Napolitano, 2024. "Innovating for the good or for the bad. An EU-wide analysis of the impact of technological transformation on job polarisation and unemployment," TEPP Working Paper 2024-02, TEPP.
    5. Pablo Casas & Concepción Román, 2024. "The impact of artificial intelligence in the early retirement decision," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(3), pages 583-618, August.
    6. Dario Guarascio & Jelena Reljic & Roman Stollinger, 2023. "Artificial Intelligence and Employment: A Look into the Crystal Ball," LEM Papers Series 2023/34, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Jin Liu & Xingchen Xu & Xi Nan & Yongjun Li & Yong Tan, 2023. ""Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets," Papers 2308.05201, arXiv.org, revised Jun 2024.
    8. Stephany, Fabian & Teutloff, Ole, 2024. "What is the price of a skill? The value of complementarity," Research Policy, Elsevier, vol. 53(1).
    9. Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," CESifo Working Paper Series 11099, CESifo.
    10. Evangelos Katsamakas & Oleg V. Pavlov & Ryan Saklad, 2024. "Artificial intelligence and the transformation of higher education institutions," Papers 2402.08143, arXiv.org.
    11. Christian Peukert & Florian Abeillon & J'er'emie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," Papers 2404.18445, arXiv.org.
    12. 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.
    13. Caleb Peppiatt, 2024. "The Future of Work: Inequality, Artificial Intelligence, and What Can Be Done About It. A Literature Review," Papers 2408.13300, arXiv.org.
    14. Ikumo Isono & Hilmy Prilliadi, 2023. "Accelerating Artificial Intelligence Discussions in ASEAN: Addressing Disparities, Challenges, and Regional Policy Imperatives," Working Papers DP-2023-16, Economic Research Institute for ASEAN and East Asia (ERIA).
    15. Fossen, Frank M. & McLemore, Trevor & Sorgner, Alina, 2024. "Artificial Intelligence and Entrepreneurship," IZA Discussion Papers 17055, Institute of Labor Economics (IZA).
    16. Mourelatos, Evangelos & Zervas, Panagiotis & Lagios, Dimitris & Tzimas, Giannis, 2024. "Can AI Bridge the Gender Gap in Competitiveness?," GLO Discussion Paper Series 1404, Global Labor Organization (GLO).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fossen, Frank M. & Sorgner, Alina, 2022. "New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    2. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    3. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2022. "Patenting in 4IR technologies and firm performance [Robots and jobs: evidence from US labor markets]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(1), pages 112-136.
    4. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    5. Mario Benassi & Elena Grinza & Francesco Rentocchini, 2020. "The rush for patents in the Fourth Industrial Revolution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(4), pages 559-588, December.
    6. Albanesi, Stefania & Dias da Silva, Antonio & Jimeno, Juan Francisco & Lamo, Ana & Wabitsch, Alena, 2023. "New Technologies and Jobs in Europe," CEPR Discussion Papers 18220, C.E.P.R. Discussion Papers.
    7. Mr. Andrew Berg & Lahcen Bounader & Nikolay Gueorguiev & Hiroaki Miyamoto & Mr. Kenji Moriyama & Ryota Nakatani & Luis-Felipe Zanna, 2021. "For the Benefit of All: Fiscal Policies and Equity-Efficiency Trade-offs in the Age of Automation," IMF Working Papers 2021/187, International Monetary Fund.
    8. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2020. "Going Revolutionary: The Impact of 4IR Technology Development on Firm Performance," SEEDS Working Papers 0720, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jul 2020.
    9. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    10. Yang, Chih-Hai, 2022. "How Artificial Intelligence Technology Affects Productivity and Employment: Firm-level Evidence from Taiwan," Research Policy, Elsevier, vol. 51(6).
    11. Parteka, Aleksandra & Wolszczak-Derlacz, Joanna & Nikulin, Dagmara, 2024. "How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    12. Carbonero, Francesco & Scicchitano, Sergio, 2021. "Labour and technology at the time of Covid-19. Can artificial intelligence mitigate the need for proximity?," GLO Discussion Paper Series 765, Global Labor Organization (GLO).
    13. Mauro Caselli & Andrea Fracasso & Arianna Marcolin & Sergio Scicchitano, 2023. "The reassuring effect of firms' technological innovations on workers' job insecurity," International Journal of Manpower, Emerald Group Publishing Limited, vol. 45(4), pages 754-778, October.
    14. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    15. Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2022. "The empirics of technology, employment and occupations: lessons learned and challenges ahead," DISCE - Quaderni del Dipartimento di Politica Economica dipe0028, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    16. Kristina McElheran & J. Frank Li & Erik Brynjolfsson & Zachary Kroff & Emin Dinlersoz & Lucia Foster & Nikolas Zolas, 2024. "AI adoption in America: Who, what, and where," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 375-415, March.
    17. Andrea Szalavetz, 2019. "Artificial Intelligence-Based Development Strategy in Dependent Market Economies - Any Room amidst Big Power Rivalry?," Central European Business Review, Prague University of Economics and Business, vol. 2019(4), pages 40-54.
    18. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    19. Seamus McGuinness & Konstantinos Pouliakas & Paul Redmond, 2023. "Skills-displacing technological change and its impact on jobs: challenging technological alarmism?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(3), pages 370-392, April.
    20. Andreas Eder & Wolfgang Koller & Bernhard Mahlberg, 2022. "Economy 4.0: employment effects by occupation, industry, and gender," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 49(4), pages 1063-1088, November.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2303.01157. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.