Automation and the Changing Nature of Work

Cecily Josten () and Grace Lordan
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Cecily Josten: London School of Economics

No 15180, IZA Discussion Papers from Institute of Labor Economics (IZA)

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'.

Keywords: EU Labour Force Survey; job abilities; job skills; automatability; work (search for similar items in EconPapers)
JEL-codes: J00 J21 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2022-03
New Economics Papers: this item is included in nep-cmp and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Published - published in: PLoS ONE, 2022, 17 (5), e0266326

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Related works:
Working Paper: Automation and the changing nature of work (2022)
Working Paper: Automation and the changing nature of work (2022)
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