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The Future of Agricultural Jobs in View of Robotization

Author

Listed:
  • Vasso Marinoudi

    (Lincoln Institute for Agri-Food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
    Engineers for Business S.A. (EfB), Doiranis 17, GR 54639 Thessaloniki, Greece)

  • Maria Lampridi

    (Institute for Bio-Economy and Agri-Technology (IBO), Centre of Research and Technology-Hellas (CERTH), GR 57001 Thessaloniki, Greece)

  • Dimitrios Kateris

    (Institute for Bio-Economy and Agri-Technology (IBO), Centre of Research and Technology-Hellas (CERTH), GR 57001 Thessaloniki, Greece)

  • Simon Pearson

    (Lincoln Institute for Agri-Food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK)

  • Claus Grøn Sørensen

    (Department of Electrical and Computer Engineering, Aarhus University, DK-8000 Aarhus, Denmark)

  • Dionysis Bochtis

    (Institute for Bio-Economy and Agri-Technology (IBO), Centre of Research and Technology-Hellas (CERTH), GR 57001 Thessaloniki, Greece)

Abstract

Robotics and computerization have drastically changed the agricultural production sector and thus moved it into a new automation era. Robots have historically been used for carrying out routine tasks that require physical strength, accuracy, and repeatability, whereas humans are used to engage with more value-added tasks that need reasoning and decision-making skills. On the other hand, robots are also increasingly exploited in several non-routine tasks that require cognitive skills. This technological evolution will create a fundamental and an unavoidable transformation of the agricultural occupations landscape with a high social and economic impact in terms of jobs creation and jobs destruction. To that effect, the aim of the present work is two-fold: (a) to map agricultural occupations in terms of their cognitive/manual and routine/non-routine characteristics and (b) to assess the susceptibility of each agricultural occupation to robotization. Seventeen (17) agricultural occupations were reviewed in relation to the characteristics of each individual task they entail and mapped onto a two-dimensional space representing the manual versus cognitive nature and the routine versus non-routine nature of an occupation. Subsequently, the potential for robotization was investigated, again concerning each task individually, and resulted in a weighted average potential adoption rate for each one of the agricultural occupations. It can be concluded that most of the occupations entail manual tasks that need to be performed in a standardised manner. Considering also that almost 81% of the agricultural work force is involved with these activities, it turns out that there is strong evidence for possible robotization of 70% of the agricultural domain, which, in turn, could affect 56% of the total annual budget dedicated to agricultural occupations. The presented work silhouettes the expected transformation of occupational landscape in agricultural production as an effort for a subsequent identification of social threats in terms of unemployment and job and wages polarization, among others, but also of opportunities in terms of emerged skills and training requirements for a social sustainable development of agricultural domain.

Suggested Citation

  • Vasso Marinoudi & Maria Lampridi & Dimitrios Kateris & Simon Pearson & Claus Grøn Sørensen & Dionysis Bochtis, 2021. "The Future of Agricultural Jobs in View of Robotization," Sustainability, MDPI, vol. 13(21), pages 1-15, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12109-:d:670730
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    References listed on IDEAS

    as
    1. Maria Lampridi & Dimitrios Kateris & Claus Grøn Sørensen & Dionysis Bochtis, 2020. "Energy Footprint of Mechanized Agricultural Operations," Energies, MDPI, vol. 13(3), pages 1-15, February.
    2. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    3. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    4. Dionysis Bochtis & Lefteris Benos & Maria Lampridi & Vasso Marinoudi & Simon Pearson & Claus G. Sørensen, 2020. "Agricultural Workforce Crisis in Light of the COVID-19 Pandemic," Sustainability, MDPI, vol. 12(19), pages 1-13, October.
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    2. Radosław Drozd & Radosław Wolniak & Jan Piwnik, 2023. "Systemic analysis of a manufacturing process based on a small scale bakery," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1421-1437, April.

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