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 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'.
| Item Type | Article |
|---|---|
| Copyright holders | © 2022 The Authors |
| Departments | LSE > Academic Departments > Psychological and Behavioural Science |
| DOI | 10.1371/journal.pone.0266326 |
| Date Deposited | 17 May 2022 |
| Acceptance Date | 20 Mar 2022 |
| URI | https://researchonline.lse.ac.uk/id/eprint/115117 |
Explore Further
- https://www.lse.ac.uk/PBS/People/Dr-Grace-Lordan (Author)
- https://www.lse.ac.uk/PBS/People/Cecily-Josten (Author)
- https://www.scopus.com/pages/publications/85129455346 (Scopus publication)
- https://journals.plos.org/plosone/ (Official URL)
