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Robots in agriculture: prospects, impacts, ethics, and policy

Abstract

Agriculture is both the site of development of important new technologies and a key area of application of technologies developed elsewhere. It is little wonder, then, that many thinkers believe that progress in the science and engineering of robotics may soon change the face of farming. This paper surveys the prospects for agricultural robotics, discusses its likely impacts, and examines the ethical and policy questions it may raise. Along with the environmental and economic impacts of robots, political, social, cultural, and security implications of the introduction of robots that have received little attention in the larger literature on agricultural robotics are considered. Key policy choices necessary to meet the ethical challenges likely to arise as agricultural robots start to become used more widely, and to maximise the social, environmental, and economic benefits of robotics in agriculture, are highlighted.

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References

  • Autor, D. (2014). Skills, education, and the rise of earnings inequality among the ‘other 99 percent.’ Science,344(6186), 843–851.

    CAS  PubMed  Google Scholar 

  • Bac, C. W., van Henten, E. J., Hemming, J., & Edan, Y. (2014). Harvesting robots for high-value crops: State‐of‐the‐art review and challenges ahead. Journal of Field Robotics,31(6), 888–911.

    Google Scholar 

  • Barbut, S. (2014). Automation and meat quality-global challenges. Meat Science,96(1), 335–345.

    PubMed  Google Scholar 

  • Basu, S., Omotubora, A., Beeson, M., & Fox, C. (2020). Legal framework for small autonomous agricultural robots. AI & Society,35(1), 113–134.

    Google Scholar 

  • Bechar, A., & Vigneault, C. (2016). Agricultural robots for field operations: Concepts and components. Biosystems Engineering,149, 94–111.

    Google Scholar 

  • Belforte, G., Deboli, R., Gay, P., Piccarolo, P., & Aimonino, D. R. (2006). Robot design and testing for greenhouse applications. Biosystems Engineering,95(3), 309–321.

    Google Scholar 

  • Bell, S. E., Hullinger, A., & Brislen, L. (2015). Manipulated masculinities: Agribusiness, deskilling, and the rise of the businessman-farmer in the United States. Rural Sociology,80(3), 285–313.

    Google Scholar 

  • Bergerman, M., Billingsley, J., Reid, J., & van Henten, E. (2016). Robotics in agriculture and forestry. In B. Siciliano, & O. Khatib (Eds.), Springer handbook of robotics (pp. 1463–1492). Cham, Switzerland: Springer.

  • Bergman, K., & Rabinowicz, E. (2013). Adoption of the automatic milking system by Swedish milk producers. Working paper. AgriFood Economics Center. Retrieved 23 June, 2019, from https://www.agrifood.se/Files/AgriFood_WP20137.pdf

  • Bock, B., & Shortall, S. (2006). Rural gender relations: Issues and case studies (1st ed.). Cambridge, MA: CABI Publishing.

    Google Scholar 

  • Brom, F. W. A. (2000). Food, consumer concerns, and trust: Food ethics for a globalizing market. Journal of Agricultural and Environmental Ethics,12(2), 127–139.

    Google Scholar 

  • Butler, D., & Holloway, L. (2015). Technology and restructuring the social field of dairy farming: Hybrid capitals, ‘stockmanship’ and automatic milking systems. Sociologia Ruralis,56(4), 513–530.

    Google Scholar 

  • Byard, R. W. (2017). Farming deaths – An ongoing problem. Forensic Science, Medicine, and Pathology,13(1), 1–3.

    PubMed  Google Scholar 

  • Caldwell, D. G. (Ed.). (2012). Robotics and automation in the food industry: Current and future technologies. Cambridge, MA: Elsevier.

    Google Scholar 

  • Carbonell, I. (2016). The ethics of big data in big agriculture. Internet Policy Review,5(1), 1–13. https://doi.org/10.14763/2016.1.405

    Article  Google Scholar 

  • Carr, N. (2015). The glass cage: How our computers are changing us. London, UK: Vintage.

    Google Scholar 

  • Chappell, M. J., & LaValle, L. A. (2011). Food security and biodiversity: Can we have both? An agroecological analysis. Agriculture and Human Values,28(1), 3–26.

    Google Scholar 

  • Cheein, F. A. A., & Carelli, R. (2013). Agricultural robotics: Unmanned robotic service units in agricultural tasks. IEEE Industrial Electronics Magazine,7(3), 48–58.

    Google Scholar 

  • Clarke, A. (2017). Robotics set to increase farm productivity. Farmers Weekly,1160(May 12th), 72–73.

    Google Scholar 

  • Clarke, R. A., & Knake, R. K. (2010). Cyber war: The next threat to national security and what to do about it. New York, NY: Ecco.

    Google Scholar 

  • Dai, J. S., & Caldwell, G. D. (2010). Origami-based robotic paper-and-board packaging for food industry. Trends in Food Science and Technology,21(3), 153–157.

    CAS  Google Scholar 

  • Davis, J. L., & Chouinard, J. B. (2016). Theorizing affordances: From request to refuse. Bulletin of Science, Technology & Society,36(4), 241–248.

    Google Scholar 

  • De George, R. T. (2003). The ethics of information technology and business. Malden: Blackwell Publishing.

    Google Scholar 

  • De Stefano, V. (2018). ‘Negotiating the algorithm’: Automation, artificial intelligence and labour protection. Working paper. International Labor Office. Retrieved 17 August, 2020, from https://www.ilo.org/wcmsp5/groups/public/---ed_emp/---emp_policy/documents/publication/wcms_634157.pdf

  • De-An, Z., Jidong, L., Wei, J., Ying, Z., & Yu, C. (2011). Design and control of an apple harvesting robot. Biosystems Engineering,110(2), 112–122.

    Google Scholar 

  • Díaz, S., Fargione, J., Chapin, F. S., III., & Tilman, D. (2006). Biodiversity loss threatens human well-being. PLoS Biology,4(8), 277.

    Google Scholar 

  • Eastwood, C., Klerkx, L., Ayre, M., & Dela Rue, B. (2019). Managing socio-ethical challenges in the development of smart farming: From a fragmented to a comprehensive approach for responsible research and innovation. Journal of Agricultural and Environmental Ethics,32(5–6), 741–768.

    Google Scholar 

  • Fantoni, G., Santochi, M., Dini, G., Tracht, K., Scholz-Reiter, B., Fleischer, J., et al. (2014). Grasping devices and methods in automated production processes. CIRP Annals – Manufacturing Technology,63(2), 679–701.

    Google Scholar 

  • Fineman, S. (1987). Unemployment: Personal and social consequences. London, UK: Tavistock.

    Google Scholar 

  • Fleming, A., Jakku, E., Lim-Camacho, L., Taylor, B., & Thorburn, P. (2018). Is big data for big farming or for everyone? Perceptions in the Australian grains industry. Agronomy for Sustainable Development,38(24), 1–10.

    Google Scholar 

  • Foley, J. A., Ramankutty, N., Brauman, K. A., Cassidy, E. S., Gerber, J. S., Johnston, M., et al. (2011). Solutions for a cultivated planet. Nature,478(7369), 337–342.

    CAS  PubMed  Google Scholar 

  • Food and Agriculture Organisation of the United Nations (FAO), International Fund for Agricultural Development (IFAD), & World Food Programme (WFP). (2015). The state of food insecurity in the world 2015. Meeting the 2015 international hunger targets: Taking stock of uneven progress. Rome: FAO.

  • Francione, G. L. (2010). The abolition of animal exploitation. In G. L. Francione & R. Garner (Eds.), The animal rights debate: Abolition or regulation? (pp. 1–102). New York, NY: Columbia University Press.

    Google Scholar 

  • Franklin, A. (1999). Animals and modern cultures: A sociology of human–animal relations in modernity. London, UK: Sage.

    Google Scholar 

  • Greenberg, A. (2018). The untold story of NotPetya, the most devastating cyberattack in history. Wired, Retrieved from August 22, https://www.wired.com/story/notpetya-cyberattack-ukraine-russia-code-crashed-the-world/.

  • Hair, J. (2016). Drone mustering tested by central Queensland farmers. ABC News Online, December 18th. Retrieved August 17, 2020, from https://www.abc.net.au/news/2016-12-18/drone-mustering-rockhampton-cattle-experiment/8085320

  • Hansen, B. G. (2015). Robotic milking-farmer experiences and adoption rate in Jæren, Norway. Journal of Rural Studies,41, 109–117.

    Google Scholar 

  • Holloway, L., Bear, C., & Wilkinson, K. (2013). Re-capturing bovine life: Robot–cow relationships, freedom and control in dairy farming. Journal of Rural Studies,33, 131–140.

    Google Scholar 

  • Holloway, L., Bear, C., & Wilkinson, K. (2014). Robotic milking technologies and renegotiating situated ethical relationships on UK dairy farms. Agriculture and Human Values,31(2), 185–199.

    Google Scholar 

  • Horrigan, L., Lawrence, R. S., & Walker, P. (2002). How sustainable agriculture can address the environmental and human health harms of industrial agriculture. Environmental Health Perspectives,110(5), 445–456.

    PubMed  PubMed Central  Google Scholar 

  • Howard, M. (2017). Trump cannot stop the advance of the machines: Reshoring and the social relations of globalisation and technological innovation. The Critique, January/February. Retrieved August 17, 2020, from http://www.thecritique.com/articles/trumpcannotstopmachines/.

  • Jacobs, J. A., & Siegford, J. M. (2012). Invited review: The impact of automatic milking systems on dairy cow management, behavior, health, and welfare. Journal of Dairy Science, 95(5), 2227–2247.

  • Jakku, E., Taylor, B., Fleming, A., Mason, C., Fielke, S., Sounness, C., et al. (2019). “If they don’t tell us what they do with it, why should we trust them with it?” Trust, transparency, and benefit-sharing in Smart Farming. NJAS – Wageningen Journal of Life Sciences,90–91, 100285.

    Google Scholar 

  • Johnson, D. G. (2015). Technology with no human responsibility? Journal of Business Ethics,127(4), 707–715.

    Google Scholar 

  • Jukan, A., Masip-Bruin, X., & Amla, N. (2017). Smart computing and sensing technologies for animal welfare: A systematic review. ACM Computing Surveys,50(1), 1–27.

    Google Scholar 

  • Kates, N., Greiff, B. S., & Hagen, D. Q. (1990). The psychosocial impact of job loss. Arlington, VA: American Psychiatric Press.

    Google Scholar 

  • Kayacan, E., Kayacan, E., Raymon, H., & Saeys, W. (2015). Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor. Computers and Electronics in Agriculture,115, 78–87.

    Google Scholar 

  • Keogh, M., & Henry, M. (2016). The implications of digital agriculture and Big Data for Australian agriculture. Sydney, NSW: Australian Farm Institute.

    Google Scholar 

  • Key, N. (2019). Farm size and productivity growth in the United States Corn Belt. Food Policy,84, 186–195.

    Google Scholar 

  • King, A. (2017). Technology: The future of agriculture. Nature,544, S21–S23.

    CAS  PubMed  Google Scholar 

  • Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and Agriculture 4.0: New contributions and a future research agenda. NJAS-Wageningen Journal of Life Sciences,90–91, 1–16.

    Google Scholar 

  • Liepins, R. (2009). Making men: The construction and representation of agriculture-based masculinities in Australia and New Zealand. Rural Sociology,65(4), 605–620.

    Google Scholar 

  • Lowenberg-DeBoer, J., Behrendt, K., Godwin, R., & Franklin, K. (2019). The impact of swarm robotics on arable farm size and structure in the UK. In 93rd agricultural economics society annual conference 2019. Coventry, UK.

  • Lowenberg-DeBoer, J., Huang, I. Y., Grigoriadis, V., & Blackmore, S. (2020). Economics of robots and automation in field crop production. Precision Agriculture,21, 278–299.

    Google Scholar 

  • Marx, L., & Smith, M. (Eds.). (1994). Does technology drive history? The dilemma of technological determinism. Cambridge, MA: MIT Press.

    Google Scholar 

  • Mathijs, E. (2004). Socio-economic aspects of automatic milking. In A. Meijering, H. Hogeveen, & C. J. A. M. De Koning (Eds.), Automatic milking, a better understanding (pp. 46–55). Wageningen: Academic Publishers.

    Google Scholar 

  • Meech, J., & Parreira, J. (2011). An interactive simulation model of human drivers to study autonomous haulage trucks. Procedia Computer Science,6, 111–123.

    Google Scholar 

  • Millar, J., & Roots, J. (2012). Changes in Australian agriculture and land use: Implications for future food security. International Journal of Agricultural Sustainability,10(1), 25–39.

    Google Scholar 

  • Nayak, R., & Padhye, R. (2018). Introduction to automation in garment manufacturing. In R. Nayak & R. Padhye (Eds.), Automation in garment manufacturing (pp. 1–27). Cambridge: Woodhead Publishing.

    Google Scholar 

  • Nielsen, J. U., Madsen, N. T., Clarke, R., Oliveira, R., Georgieva, P., Feyo de Azevedo, S., et al. (2014). Automation in the meat industry: Slaughter line operation. In M. Dikeman & C. Devine (Eds.), Encyclopedia of meat sciences (2nd ed., pp. 43–52). Oxford: Academic Press.

    Google Scholar 

  • Norman, D. A. (1988). The psychology of everyday things. New York, NY: Basic Books.

    Google Scholar 

  • Pala, M., Mizenko, L., Mach, M., & Reed, T. (2014). Aeroponic greenhouse as an autonomous system using intelligent space for agriculture robots. In J. H. Kim, E. Matson, H. Myung, P. Xu, & F. Karray (Eds.), Robot intelligence technology and applications 2. Advances in intelligent systems and computing, Vol. 274 (pp. 83–93). Cham, Switzerland: Springer.

    Google Scholar 

  • Pedersen, S. M., Fountas, S., Have, H., & Blackmore, B. S. (2006). Agricultural robots – System analysis and economic feasibility. Precision Agriculture,7(4), 295–308.

    Google Scholar 

  • Pini, B. (2017). Masculinities and management in agricultural organizations worldwide. New York, NY: Routledge.

    Google Scholar 

  • Puri, V., Nayyar, A., & Raja, L. (2017). Agriculture drones: A modern breakthrough in precision agriculture. Journal of Statistics and Management Systems,20(4), 507–518.

    Google Scholar 

  • Reid, J., Moorehead, S., Foessel, A., & Sanchez, J. (2016). Autonomous driving in agriculture leading to autonomous worksite solutions. SAE Technical Paper 2016-01-8006. https://doi.org/10.4271/2016-01-8006.

  • Rollin, B. E. (1990). Animal welfare, animal rights and agriculture. Journal of Animal Science,68(10), 3456–3461.

    CAS  PubMed  Google Scholar 

  • Rose, D. C., & Chilvers, J. (2018). Agriculture 4.0: Broadening responsible innovation in an era of smart farming. Frontiers in Sustainable Food Systems,2, 87.

    Google Scholar 

  • Rotz, S., Gravely, E., Mosby, I., Duncan, E., Finnis, E., Horgan, M., et al. (2019). Automated pastures and the digital divide: How agricultural technologies are shaping labour and rural communities. Journal of Rural Studies,68, 112–122.

    Google Scholar 

  • Sachs, C. (1996). Gendered fields: Rural women, agriculture, and environment. Boulder: Westview Press.

    Google Scholar 

  • Saggiomo, M., Wischnowski, M., Simonis, K., & Gries, T. (2018). Automation in production of yarns, woven, and knitted fabric. In R. Nayak & R. Padhye (Eds.), Automation in garment manufacturing (pp. 49–74). Cambridge: Woodhead Publishing.

    Google Scholar 

  • Satz, D. (2012). Why some things should not be for sale: The moral limits of markets. Oxford: Oxford University Press.

    Google Scholar 

  • Schewe, R. L., & Stuart, D. (2015). Diversity in agricultural technology adoption: How are automatic milking systems used and to what end? Agriculture and Human Values,32, 199–213.

    Google Scholar 

  • Schimmelpfennig, D. (2016). Farm profits and adoption of precision agriculture. Washington, D.C.: U.S. Department of Agriculture, Economic Research Service.

    Google Scholar 

  • Schmitz, A., & Moss, C. B. (2015). Mechanized agriculture: Machine adoption, farm size, and labor displacement. AgBioForum,18(3), 278–296.

    Google Scholar 

  • Shah, A. (2018). Can you repair what you own? Mechanical Engineering,140(9), 37–41.

    Google Scholar 

  • Sheng, Y., & Chancellor, W. (2019). Exploring the relationship between farm size and productivity: Evidence from the Australian grains industry. Food Policy,84, 196–204.

    Google Scholar 

  • Sheng, Y., Zhao, S., Nossal, K., & Zhang, D. (2015). Productivity and farm size in Australian agriculture: Reinvestigating the returns to scale. Australian Journal of Agricultural and Resource Economics,59(1), 16–38.

    Google Scholar 

  • Slaughter, D. C., Giles, D. K., & Downey, D. (2008). Autonomous robotic weed control systems: A review. Computers and Electronics in Agriculture, 61(1), 63–78.

    Google Scholar 

  • Smith, E. (2011). Women into science and engineering? Gendered participation in higher education STEM subjects. British Education Research Journal,37(6), 993–1014.

    Google Scholar 

  • Sparrow, R. (2020). Robotics. In H. LaFollette (Ed.), International encyclopedia of ethics. Malden, MA: John Wiley & Sons.

    Google Scholar 

  • Sparrow, R., & Howard, M. (2017). When human beings are like drunk robots: Driverless vehicles, ethics, and the future of transport. Transportation Research Part C,80, 206–215.

    Google Scholar 

  • Srnicek, N., & Williams, A. (2015). Inventing the future: Postcapitalism and a world without work. London: Verso.

    Google Scholar 

  • Stock, P. V., & Forney, J. (2014). Farmer autonomy and the farming self. Journal of Rural Studies,36, 160–171.

    Google Scholar 

  • Straete, E. P., Vik, J., & Hansen, B. G. (2017). The social robot: A study of the social and political aspects of automatic milking systems. Proceedings in System Dynamics and Innovation in Food Networks 2017, https://doi.org/10.18461/pfsd.2017.1722.

  • Tse, C., Barkema, H. W., DeVries, T. J., Rushen, J., & Pajor, E. A. (2018). Impact of automatic milking systems on dairy cattle producers’ reports of milking labour management, milk production and milk quality. Animal, 12(12), 2649–2656.

  • Thompson, P. B. (2017). The spirit of the soil: Agriculture and environmental ethics. New York: Routledge.

    Google Scholar 

  • Thrupp, L. A. (2000). Linking agricultural biodiversity and food security: The valuable role of agrobiodiversity for sustainable agriculture. International Affairs,76(2), 265–281.

    CAS  PubMed  Google Scholar 

  • Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R., & Polasky, S. (2002). Agricultural sustainability and intensive production practices. Nature,418(6898), 671–677.

    CAS  PubMed  Google Scholar 

  • Twine, R. (2010). Animals as biotechnology: Ethics, sustainability, and critical animal studies. London: Routledge.

    Google Scholar 

  • UK Robotics and Autonomous Systems (UK-RAS) Network. (2018). Agricultural robotics: The future of robotic agriculture. London, UK: UK-RAS Network.

    Google Scholar 

  • United States Department of Agriculture. (2020). Ag and food statistics: Charting the essentials, February 2020. Washington, DC: U.S. Department of Agriculture, Economic Research Service.

    Google Scholar 

  • Weichselbaum, J., Zinner, C., Gebauer, O., & Pree, W. (2013). Accurate 3D-vision-based obstacle detection for an autonomous train. Computers in Industry,64(9), 1209–1220.

    Google Scholar 

  • Weilbach, F., & van Renen, C. (2017). Managing growth: Africa Agribusiness Insights Survey 2017/2018. Research document. Price Waterhouse Coopers. Retrieved August 17, 202, from https://www.pwc.co.za/en/assets/pdf/africa-agribusiness-insights-survey-2017-2018.pdf.

  • Werkheiser, I. (2018). Precision livestock farming and farmers’ duties to livestock. Journal of Agricultural and Environmental Ethics,31(2), 181–195.

    Google Scholar 

  • Winner, L. (1980). Do artifacts have politics? Daedalus,109(1), 121–136.

    Google Scholar 

  • Wolfert, S. L. G., Verdouw, C., & Bogaardt, M.-J. (2017). Big data in smart farming – A review. Agricultural Systems,153, 69–80.

    Google Scholar 

  • Woods, A. (2012). Rethinking the history of modern agriculture: British pig production, c. 1910–65. Twentieth Century British History,23(2), 165–191.

    PubMed  Google Scholar 

  • Yahya, N. (2018). Green urea: Green energy and technology. Singapore: Springer.

    Google Scholar 

  • Yue, C., Alfnes, F., & Jensen, H. H. (2009). Discounting spotted apples: Investigating consumers’ willingness to accept cosmetic damage in an organic product. Journal of Agricultural and Applied Economics,41(1), 29–46.

    Google Scholar 

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Acknowledgements

Some of the research for this manuscript was conducted in the course of writing a working paper for the Australian Council of Learned Academies Horizon Scanning report on the Future of Agriculture Technology. This manuscript represents a heavily revised version of that working paper. Thanks are due to Joshua Hatherley for his assistance with bibliographic research for this paper.

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Sparrow, R., Howard, M. Robots in agriculture: prospects, impacts, ethics, and policy. Precision Agric 22, 818–833 (2021). https://doi.org/10.1007/s11119-020-09757-9

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Keywords

  • Agricultural robotics
  • Precision farming
  • Ethics
  • Automation/autonomy
  • Sustainability