IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0266326.html
   My bibliography  Save this article

Automation and the changing nature of work

Author

Listed:
  • Cecily Josten
  • Grace Lordan

Abstract

This study identifies the job attributes, and in particular skills and abilities, which predict the likelihood a job is recently automatable drawing on the Josten and Lordan (2020) classification of automatability, EU labour force survey data and a machine learning regression approach. We find that skills and abilities which relate to non-linear abstract thinking are those that are the safest from automation. We also find that jobs that require ‘people’ engagement interacted with ‘brains’ are also less likely to be automated. The skills that are required for these jobs include soft skills. Finally, we find that jobs that require physically making objects or physicality more generally are most likely to be automated unless they involve interaction with ‘brains’ and/or ‘people’.

Suggested Citation

  • Cecily Josten & Grace Lordan, 2022. "Automation and the changing nature of work," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-15, May.
  • Handle: RePEc:plo:pone00:0266326
    DOI: 10.1371/journal.pone.0266326
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0266326
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0266326&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0266326?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David Deming & Lisa B. Kahn, 2018. "Skill Requirements across Firms and Labor Markets: Evidence from Job Postings for Professionals," Journal of Labor Economics, University of Chicago Press, vol. 36(S1), pages 337-369.
    2. Marco Vivarelli, 2014. "Innovation, Employment and Skills in Advanced and Developing Countries: A Survey of Economic Literature," Journal of Economic Issues, Taylor & Francis Journals, vol. 48(1), pages 123-154.
    3. Lordan, Grace & McGuire, Alistair, 2019. "Widening the High School Curriculum to Include Soft Skill Training: Impacts on Health, Behaviour, Emotional Wellbeing and Occupational Aspirations," IZA Discussion Papers 12439, Institute of Labor Economics (IZA).
    4. Lordan, Grace & Neumark, David, 2018. "People versus machines: The impact of minimum wages on automatable jobs," Labour Economics, Elsevier, vol. 52(C), pages 40-53.
    5. Daron Acemoglu & Pascual Restrepo, 2022. "Tasks, Automation, and the Rise in U.S. Wage Inequality," Econometrica, Econometric Society, vol. 90(5), pages 1973-2016, September.
    6. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    7. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    8. Grace Lordan & Jörn‐Steffen Pischke, 2022. "Does Rosie Like Riveting? Male and Female Occupational Choices," Economica, London School of Economics and Political Science, vol. 89(353), pages 110-130, January.
    9. James Heckman & Tim Kautz, 2013. "Fostering and Measuring Skills: Interventions That Improve Character and Cognition," Working Papers 2013-019, Human Capital and Economic Opportunity Working Group.
    10. Kautz, Tim & Heckman, James J. & Diris, Ron & ter Weel, Bas & Borghans, Lex, 2014. "Fostering and Measuring Skills: Improving Cognitive and Non-Cognitive Skills to Promote Lifetime Success," IZA Discussion Papers 8696, Institute of Labor Economics (IZA).
    11. Jyldyz Djumalieva & Antonio Lima & Cath Sleeman, 2018. "Classifying Occupations According to Their Skill Requirements in Job Advertisements," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-04, Economic Statistics Centre of Excellence (ESCoE).
    12. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    13. David H. Autor & David Dorn & Gordon H. Hanson, 2015. "Untangling Trade and Technology: Evidence from Local Labour Markets," Economic Journal, Royal Economic Society, vol. 0(584), pages 621-646, May.
    14. Catherine J. Weinberger, 2014. "The Increasing Complementarity between Cognitive and Social Skills," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 849-861, December.
    15. Cecily Josten & Grace Lordan, 2022. "Automation and the changing nature of work," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-15, May.
    16. Piotr Lewandowski & Albert Park & Wojciech Hardy & Yang Du & Saier Wu, 2022. "Technology, Skills, and Globalization: Explaining International Differences in Routine and Nonroutine Work Using Survey Data," The World Bank Economic Review, World Bank, vol. 36(3), pages 687-708.
    17. 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.
    18. Lordan, Grace, 2018. "Robots at work: a report on automatable and non-automatable employment shares in Europe," LSE Research Online Documents on Economics 90500, London School of Economics and Political Science, LSE Library.
    19. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2017. "Revisiting the risk of automation," Economics Letters, Elsevier, vol. 159(C), pages 157-160.
    20. Ljubica Nedelkoska & Glenda Quintini, 2018. "Automation, skills use and training," OECD Social, Employment and Migration Working Papers 202, OECD Publishing.
    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. Cecily Josten & Grace Lordan, 2022. "Automation and the changing nature of work," PLOS ONE, Public Library of Science, vol. 17(5), pages 1-15, May.
    2. Weller, Jürgen, 2022. "Tendencias mundiales, pandemia de COVID-19 y desafíos de la inclusión laboral en América Latina y el Caribe," Documentos de Proyectos 48610, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    3. Wen Zhang & Kee-Hung Lai & Qiguo Gong, 2024. "The future of the labor force: higher cognition and more skills," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    4. Vili Lehdonvirta & Lulu P Shi & Ekaterina Hertog & Nobuko Nagase & Yuji Ohta, 2023. "The future(s) of unpaid work: How susceptible do experts from different backgrounds think the domestic sphere is to automation?," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-16, February.

    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. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the employment and skill impact of new technologies: A survey and some methodological issues," MERIT Working Papers 2019-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    2. Belloc, Filippo & Burdin, Gabriel & Cattani, Luca & Ellis, William & Landini, Fabio, 2022. "Coevolution of job automation risk and workplace governance," Research Policy, Elsevier, vol. 51(3).
    3. Consoli, Davide & Marin, Giovanni & Rentocchini, Francesco & Vona, Francesco, 2023. "Routinization, within-occupation task changes and long-run employment dynamics," Research Policy, Elsevier, vol. 52(1).
    4. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    5. Lordan, Grace & Stringer, Eliza-Jane, 2022. "People versus machines: The impact of being in an automatable job on Australian worker’s mental health and life satisfaction," Economics & Human Biology, Elsevier, vol. 46(C).
    6. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    7. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    8. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).
    9. Damioli, G. & Van Roy, V. & Vertesy, D. & Vivarelli, M., 2021. "May AI revolution be labour-friendly? Some micro evidence from the supply side," GLO Discussion Paper Series 823, Global Labor Organization (GLO).
    10. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    11. Arntz, Melanie & Gregory, Terry & Zierahn-Weilage, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    12. Ghodsi, Mahdi & Stehrer, Robert & Barišić, Antea, 2024. "Assessing the impact of new technologies on wages and labour income shares," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
    13. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    14. Nikolova, Milena & Cnossen, Femke & Nikolaev, Boris, 2024. "Robots, meaning, and self-determination," Research Policy, Elsevier, vol. 53(5).
    15. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    16. Verónica Escudero & Hannah Liepmann & Ana Podjanin, 2024. "Using Online Vacancy and Job Applicants' Data to Study Skills Dynamics," Research in Labor Economics, in: Big Data Applications in Labor Economics, Part B, volume 52, pages 35-99, Emerald Group Publishing Limited.
    17. 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).
    18. Maria-Chiara Morandini & Anna Thum-Thysen & Anneleen Vandeplas, 2020. "Facing the Digital Transformation: Are Digital Skills Enough?," European Economy - Economic Briefs 054, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    19. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the digital divide: Workers' exposure to digitalization and its consequences for individual employment," Discussion Papers 118, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    20. Damioli, Giacomo & Van Roy, Vincent & Vertesy, Daniel & Vivarelli, Marco, 2021. "Will the AI revolution be labour-friendly? Some micro evidence from the supply side," MERIT Working Papers 2021-016, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).

    More about this item

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J00 - Labor and Demographic Economics - - General - - - General

    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:plo:pone00:0266326. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.