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Measuring the impact of AI on jobs at the organization level : lessons from a survey of UK business leaders
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Hunt, William, Sarkar, Sudipa and Warhurst, Christopher (2022) Measuring the impact of AI on jobs at the organization level : lessons from a survey of UK business leaders. Research Policy, 51 (2). 104425. doi:10.1016/j.respol.2021.104425
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Official URL: https://doi.org/10.1016/j.respol.2021.104425
Abstract
Advances in artificial intelligence (AI) have reignited debates about the impact of technology on the future of work, raising concerns about massive job losses. However, extant evidence is beset by methodological limitations. The majority of studies are either (1) based on modelling predictions, underpinned by subjective judgements or (2) measure the effect of automation technologies more broadly using proxies for AI effects. Analysis of what actually happens in organisations introducing AI-enabled technologies is lacking. This Research Note proposes a third methodology based on the use of bespoke employer surveys. Drawing on a new and unique survey of UK business leaders, it illustrates the utility of this approach through the presentation of descriptive findings on the association between introduction of AI and job creation and destruction within organisations. Directions for future research using this approach are suggested.
| Item Type: | Journal Article | |||||||||
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| Subjects: | H Social Sciences > HC Economic History and Conditions H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HF Commerce Q Science > Q Science (General) T Technology > T Technology (General) |
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| Divisions: | Faculty of Social Sciences > Institute for Employment Research | |||||||||
| Library of Congress Subject Headings (LCSH): | Artificial intelligence , Artificial intelligence -- Economic aspects, Artificial intelligence -- Industrial applications, Automation, Employees -- Effect of automation on, Automation -- Economic aspects, Job creation , Employees -- Dismissal of | |||||||||
| Journal or Publication Title: | Research Policy | |||||||||
| Publisher: | Elsevier BV | |||||||||
| ISSN: | 0048-7333 | |||||||||
| Official Date: | March 2022 | |||||||||
| Dates: |
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| Volume: | 51 | |||||||||
| Number: | 2 | |||||||||
| Article Number: | 104425 | |||||||||
| DOI: | 10.1016/j.respol.2021.104425 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| RIOXX Funder/Project Grant: |
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