The risk of automation for jobs in OECD countries: a comparative analysis

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 occupati...

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Bibliographische Detailangaben
Hauptverfasser: Arntz, Melanie (VerfasserIn) , Gregory, Terry (VerfasserIn) , Zierahn-Weilage, Ulrich (VerfasserIn)
Dokumenttyp: Buch/Monographie Arbeitspapier
Sprache:Englisch
Veröffentlicht: Paris OECD Publishing 2016
Schriftenreihe:OECD social, employment and migration working papers no. 189
In: OECD social, employment and migration working papers (no. 189)

DOI:10.1787/5jlz9h56dvq7-en
Schlagworte:
Online-Zugang:Resolving-System, lizenzpflichtig: https://doi.org/10.1787/5jlz9h56dvq7-en
Resolving-System, Volltext: http://dx.doi.org/10.1787/5jlz9h56dvq7-en
Volltext
Verfasserangaben:Melanie Arntz, Terry Gregory, Ulrich Zierahn

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520 |a 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. 
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