The risk of automation for jobs in OECD countries

• Verfasst von: Arntz, Melanie [VerfasserIn]
• Verfasst von: Gregory, Terry [VerfasserIn]
• Verfasst von: Zierahn-Weilage, Ulrich [VerfasserIn]
• Titel: The risk of automation for jobs in OECD countries
• Titelzusatz: a comparative analysis
• Verf.angabe: Melanie Arntz, Terry Gregory, Ulrich Zierahn
• Verlagsort: Paris
• Verlag: OECD Publishing
• Jahr: 2016
• Umfang: 1 Online-Ressource (circa 35 Seiten)
• Illustrationen: Illustrationen
• Gesamttitel/Reihe: OECD social, employment and migration working papers ; no. 189
• Fussnoten: Gesehen am 11.12.2023
• Schrift/Sprache: Zusammenfassung in französischer Sprache
• DOI: doi:10.1787/5jlz9h56dvq7-en
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Employment
• Sach-SW: Social Issues/Migration/Health
• Form-SW: Amtsdruckschrift
• Form-SW: Arbeitspapier
• Form-SW: Graue Literatur
• K10plus-PPN: 876380739
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

In recent years, there has been a revival of concerns that automation and digitalisation might after all result in a jobless future. The debate has been fuelled by studies for the US and Europe arguing that a substantial share of jobs is at “risk of computerisation”. These studies follow an occupation-based approach proposed by Frey and Osborne (2013), i.e. they assume that whole occupations rather than single job-tasks are automated by technology. As we argue, this might lead to an overestimation of job automatibility, as occupations labelled as high-risk occupations often still contain a substantial share of tasks that are hard to automate. Our paper serves two purposes. Firstly, we estimate the job automatibility of jobs for 21 OECD countries based on a task-based approach. In contrast to other studies, we take into account the heterogeneity of workers’ tasks within occupations. Overall, we find that, on average across the 21 OECD countries, 9 % of jobs are automatable. The threat from technological advances thus seems much less pronounced compared to the occupation-based approach. We further find heterogeneities across OECD countries. For instance, while the share of automatable jobs is 6 % in Korea, the corresponding share is 12 % in Austria. Differences between countries may reflect general differences in workplace organisation, differences in previous investments into automation technologies as well as differences in the education of workers across countries.