Exposure to Artificial Intelligence and Occupational Mobility: A Cross-Country Analysis.
We document historical patterns of workers' transitions across occupations and over the life-cycle for different levels of exposure and complementarity to Artificial Intelligence (AI) in Brazil and the UK. In both countries, college-educated workers frequently move from high-exposure, low-complement...
| Publicado en: | Economía Vol. 24; no. 1; pp. 314 - 340 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
London School of Economics & Political Science
2025
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=191613869&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 191613869 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 15297470 N8H jtl: Economía issn: 15297470 maglogo: N pubinfo: dt: 2025 vid: 24 iid: 1 pid: 66142 pub: London School of Economics & Political Science artinfo: ui: 191613869 10.31389/eco.451 ppf: 314 ppct: 26 formats: fmt: – @attributes: type: T – @attributes: type: P size: 3MB tig: atl: Exposure to Artificial Intelligence and Occupational Mobility: A Cross-Country Analysis. aug: au: Cazzaniga, Mauro Pizzinelli, Carlo Rockall, Emma Tavares, Marina M. affil: MIT Sloan, United States IMF, United States Stanford University, United States su: United Kingdom Brazil Artificial intelligence Occupational mobility Income inequality Higher education Labor market Career development Countries Comparative studies sug: subj: Artificial intelligence Occupational mobility Income inequality Higher education Labor market Career development United Kingdom Brazil Professional and Management Development Training Vocational Rehabilitation Services Countries Comparative studies keyword: Artificial Intelligence Emerging Markets Employment Occupations Artificial Intelligence Emerging Markets Employment Occupations ab: We document historical patterns of workers' transitions across occupations and over the life-cycle for different levels of exposure and complementarity to Artificial Intelligence (AI) in Brazil and the UK. In both countries, college-educated workers frequently move from high-exposure, low-complementarity occupations (those more likely to be negatively affected by AI) to high-exposure, high-complementarity ones (those more likely to be positively affected by AI). This transition is especially common for young college-educated workers and is associated with an increase in average salaries. Young, highly educated workers thus represent the demographic group for which AI-driven structural change could most expand opportunities for career progression, but also highly disrupt entry into the labor market by removing stepping-stone jobs. These similar patterns of "upward" labor market transitions for college-educated workers suggest that the impact of AI adoption on the highly educated labor force could be similar across advanced economies and emerging markets. Meanwhile, non-college workers in Brazil face markedly higher chances of moving from better-paid high-exposure and low-complementarity occupations to low-exposure ones, suggesting a higher risk of income loss if AI were to reduce labor demand for the former type of jobs. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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