IDEAS home Printed from https://ideas.repec.org/p/upf/upfgen/1890.html
   My bibliography  Save this paper

AI and digital technology: gender gaps in higher education

Author

Listed:

Abstract

This article examines gender gaps in higher education in Spain from 1985 to 2023 in the context of technological advancements, particularly digitalization and artificial intelligence (AI). We identify significant disparities, with women overrepresented in health-related fields and underrepresented in STEM disciplines. This imbalance is concerning as STEM fields offer better employment prospects and higher salaries. We analyze university degrees' exposure to technological change through Routine Task Intensity (RTI) and AI exposure indices. Our findings show that women are more enrolled in degrees with high RTI, prone to automation, and less in degrees with high AI exposure, likely to benefit from technological advancements. This suggests technological change could widen existing labor market gender gaps. To address this, we recommend policies to boost female participation in STEM fields and adapt educational curricula to reduce routine tasks and enhance AI complementarities, ensuring equitable labor market outcomes amid technological change.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • José Ignacio Conde-Ruiz & Juan José Ganuza & Manu García & Carlos Victoria, 2024. "AI and digital technology: gender gaps in higher education," Economics Working Papers 1890, Department of Economics and Business, Universitat Pompeu Fabra.
  • Handle: RePEc:upf:upfgen:1890
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Daron Acemoglu & Pascual Restrepo, 2020. "The wrong kind of AI? Artificial intelligence and the future of labour demand," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 13(1), pages 25-35.
    2. Hanushek, Eric A. & Schwerdt, Guido & Wiederhold, Simon & Woessmann, Ludger, 2015. "Returns to skills around the world: Evidence from PIAAC," European Economic Review, Elsevier, vol. 73(C), pages 103-130.
    3. David H. Autor, 2019. "Work of the Past, Work of the Future," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 1-32, May.
    4. Daron Acemoglu, 2024. "The Simple Macroeconomics of AI," NBER Working Papers 32487, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José Ignacio Conde-Ruiz & Juan José Ganuza & Manu García & Carlos Victoria, 2024. "La Demanda de Educación Superior ante el Cambio Tecnológico y la Inteligencia Artificial," Studies on the Spanish Economy eee2024-09, FEDEA.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José Ignacio Conde-Ruiz & Juan José Ganuza & Manu García & Carlos Victoria, 2024. "La Demanda de Educación Superior ante el Cambio Tecnológico y la Inteligencia Artificial," Studies on the Spanish Economy eee2024-09, FEDEA.
    2. Torrent-Sellens, Joan, 2024. "Digital transition, data-and-tasks crowd-based economy, and the shared social progress: Unveiling a new political economy from a European perspective," Technology in Society, Elsevier, vol. 79(C).
    3. Albanesi, Stefania & Dias da Silva, Antonio & Jimeno, Juan Francisco & Lamo, Ana & Wabitsch, Alena, 2023. "New Technologies and Jobs in Europe," CEPR Discussion Papers 18220, C.E.P.R. Discussion Papers.
    4. Azar, José & Alekseeva, Liudmila & Gine, Mireia & Samila, Sampsa & Taska, Bledi, 2020. "The Demand for AI Skills in the Labor Market," CEPR Discussion Papers 14320, C.E.P.R. Discussion Papers.
    5. Katya Klinova & Anton Korinek, 2021. "AI and Shared Prosperity," Papers 2105.08475, arXiv.org.
    6. Jin Liu & Kaizhe Chen & Wenjing Lyu, 2024. "Embracing artificial intelligence in the labour market: the case of statistics," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    7. Tommaso AGASISTI & Geraint JOHNES & Marco PACCAGNELLA, 2021. "Tasks, occupations and wages in OECD countries," International Labour Review, International Labour Organization, vol. 160(1), pages 85-112, March.
    8. Andrés Rodríguez-Pose & Michael Storper, 2020. "Housing, urban growth and inequalities: The limits to deregulation and upzoning in reducing economic and spatial inequality," Urban Studies, Urban Studies Journal Limited, vol. 57(2), pages 223-248, February.
    9. F. Cerina & A. Moro & M. Rendall, 2020. "A Note on Employment and Wage Polarization in the U.S," Working Paper CRENoS 202002, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    10. Clarke, Andrew & Skuterud, Mikal, 2014. "Immigrant Skill Selection and Utilization: A Comparative Analysis of Australia, Canada, and the United States," CLSSRN working papers clsrn_admin-2014-41, Vancouver School of Economics, revised 22 Sep 2014.
    11. Mengus, Eric & Davis, Donald R. & Michalski, Tomasz K., 2020. "Labor Market Polarization and The Great Divergence: Theory and Evidence," CEPR Discussion Papers 14623, C.E.P.R. Discussion Papers.
    12. Shigeru Fujita & Madison Perry, 2024. "Nonworking Parents or Hungry Children," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 9(4), pages 2-9, December.
    13. Asadullah, M. Niaz & Xiao, Saizi, 2020. "The changing pattern of wage returns to education in post-reform China," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 137-148.
    14. Wang, Jun & Liao, Chengjuan & Wan, Xuan & Song, Hui, 2021. "Skill Formation, Employment Discrimination, and Wage Inequality: Evidence from the People’s Republic of China," ADBI Working Papers 1283, Asian Development Bank Institute.
    15. Maria Rita Mancaniello & Francesco Lavanga, 2024. "Adolescence in the Italian Labour Market: In Search of an Equilibrium Among Instability, Uncertainty, and AI Challenges," Social Sciences, MDPI, vol. 13(12), pages 1-13, December.
    16. Görlitz, Katja & Penny, Merlin & Tamm, Marcus, 2022. "The long-term effect of age at school entry on cognitive competencies in adulthood," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 91-104.
    17. Barrett, Garry F. & Riddell, W. Craig, 2019. "Ageing and Skills: The Case of Literacy Skills," IZA Discussion Papers 12073, Institute of Labor Economics (IZA).
    18. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    19. Stijn Broecke & Glenda Quintini & Marieke Vandeweyer, 2018. "Wage Inequality and Cognitive Skills: Reopening the Debate," NBER Chapters, in: Education, Skills, and Technical Change: Implications for Future US GDP Growth, pages 251-286, National Bureau of Economic Research, Inc.
    20. Goel, Deepti & Barooah, Bidisha, 2018. "Drivers of Student Performance: Evidence from Higher Secondary Public Schools in Delhi," GLO Discussion Paper Series 231, Global Labor Organization (GLO).

    More about this item

    Keywords

    Gender gaps; artificial intelligence; higher education; STEM; technological change; self-actualization.;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:upf:upfgen:1890. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge The email address of this maintainer does not seem to be valid anymore. Please ask the person in charge to update the entry or send us the correct address (email available below). General contact details of provider: http://www.econ.upf.edu/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.