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Automation and the changing nature of work
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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071144/ https://www.ncbi.nlm.nih.gov/pubmed/35512015 http://dx.doi.org/10.1371/journal.pone.0266326 |
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author | Josten, Cecily Lordan, Grace |
author_facet | Josten, Cecily Lordan, Grace |
author_sort | Josten, Cecily |
collection | PubMed |
description | 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’. |
format | Online Article Text |
id | pubmed-9071144 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90711442022-05-06 Automation and the changing nature of work Josten, Cecily Lordan, Grace PLoS One Research Article 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’. Public Library of Science 2022-05-05 /pmc/articles/PMC9071144/ /pubmed/35512015 http://dx.doi.org/10.1371/journal.pone.0266326 Text en © 2022 Josten, Lordan https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Josten, Cecily Lordan, Grace Automation and the changing nature of work |
title | Automation and the changing nature of work |
title_full | Automation and the changing nature of work |
title_fullStr | Automation and the changing nature of work |
title_full_unstemmed | Automation and the changing nature of work |
title_short | Automation and the changing nature of work |
title_sort | automation and the changing nature of work |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071144/ https://www.ncbi.nlm.nih.gov/pubmed/35512015 http://dx.doi.org/10.1371/journal.pone.0266326 |
work_keys_str_mv | AT jostencecily automationandthechangingnatureofwork AT lordangrace automationandthechangingnatureofwork |