Labor, Automation, and Sustainability in Agriculture

This week, I attended a conference at Washington State University on labor, automation, social sustainability, and resilience in U.S. agriculture. Engineers have made remarkable strides in recent years to automate routine tasks on dairies, orchards, and in strawberry harvest. Strawberries and apples will likely soon be picked by robots rather than human hands. The engineering capabilities exist, though current prototypes may not yet be as efficient as human workers. As technologies improve, adoption on commercial farms will likely be gradual. Producers can prepare now for technological advances by investing in their workforce to improve technical and data analytic skills.

Though early adopters of new technologies might be rewarded for their investment, they also bear considerable risk. Up-front costs of purchasing a robotic harvester and other tech investments are large. For example, engineering firms have been investing in the development, testing, and advancement of robotic technologies to harvest commercial strawberries for over a decade, and a robotic harvester for tabletop strawberries is now commercially available. However, most strawberries in the United States are grown in ground, not on tabletops. Investments in harvesters and retrofitting strawberry fields might prove obsolete if the technology is greatly improved after the first few seasons of field testing on commercial farms or if engineers develop a viable harvester for strawberries grown in the ground. Many producers will wait to observe and learn from those who adopt first.

Development of new agricultural technologies must be accompanied by investments in the acquisition of appropriate skills. Automated feeders and robotic milking machines have been available for commercial dairies for decades. These technologies could substantially reduce requisite labor hours. Perhaps more importantly, they also collect critical data on cow health and milking performance. When properly managed, dairy operators can use these data to improve herd health and milking efficiency. Subsequent cost-savings could be substantial for many dairies, and similar opportunities to improve efficiency are possible using precision agriculture technologies in the production of many field crops. Nevertheless, learning to analyze and interpret these data well takes time, practice, and skills that many farmers and farm workers have not yet acquired.

Farmers, ranchers, and the agricultural industry need to take a proactive role in acquiring and teaching data analytic skills. Many of these skills will likely be necessary for survival in competitive agricultural markets. The future farm workforce might include a larger share of engineers, computer programmers, and technicians as automated technologies advance. Innovative approaches to encourage acquisition of these skills in agricultural education programs, including FFA and 4-H, might have large payoffs in the future. Furthermore, as farm wages rise and producers wrestle with the challenges of procuring workers in a tight labor market, producers need to be alert to the concerns and innovations raised by farm workers. The workers who pick our crops often have some of the most transformative ideas for improving efficiency, field safety, and more comfortable working conditions.