How the risk of job automation in the UK has changed over time

Matthew James Darke
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Matthew James Darke: University of Warwick

Warwick-Monash Economics Student Papers from Warwick Monash Economics Student Papers

Abstract: Developments in Artificial Intelligence and Machine Learning technologies have had massive implications for labour automation. This paper builds on the task-based methodology first adopted by Frey and Osborne (2013) to predict how the risk of automation evolved in the UK labour between 2012 and 2017 using data from the UK Skills and Employment Survey. The analysis accounts for technological progress, making use of two sets of experts’ assessments for 70 occupations. The probability of automation is predicted for each individual using a set of self-reported job skills. It finds that the proportion of jobs at high-risk from automation has risen from 10.6% to 23.4%, and that this is largely due to better technology rather than changing job skill requirements. It also identifies sectors experiencing the greatest increase in automation risk between the two periods and, in contrast, those which appear complementary to technology, drawing on occupational case studies as evidence.

Keywords: Employment; Skills Demand; Technology JEL Classification: J01; J21; J24; J62; O33 (search for similar items in EconPapers)
Date: 2022
New Economics Papers: this item is included in nep-big, nep-his, nep-lab, nep-pay, nep-rmg and nep-tid
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Persistent link: https://EconPapers.repec.org/RePEc:wrk:wrkesp:41

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