For California farmer Joe Del Bosque artificial intelligence was once a foreign concept. Today, he uses AI for autonomous weed control and water management.
According to McKinsey & Company analysis, AI can create economic value by improving labor and input costs as well as yield to the tune of $100 billion and by increasing sales and productivity by as much as $150 billion across the agriculture industry. However, most farmers continue to approach AI with a mixture of cautious optimism and skepticism.
“We have increasing costs all the time, we have challenges with pests and with the climate, so we’re looking for AI to help us,” says Del Bosque, who grows cantaloupe, watermelon, honeydew and Galia melons on 2,000 acres.
It’s crucial for farmers and technology companies to come together to find solutions for some of agriculture’s most pressing concerns with AI, he adds.
Building Trust Through In-Field Results
In her work as chief product officer for Avalo, Inc, a crop development company creating climate-resilient crops, Rebecca White recognizes the investment price tag for technology is a significant barrier for producers. For example, autonomous and robotic systems can cost hundreds of thousands to a million dollars per unit, she says.
That financial scope can heighten caution around new technology – a point addressed at the recent World Agri-Tech event. As industry leaders emphasize, for trust to form, the technology must first prove its reliability in the field.
Bridging the Gap Between Data and Action
AI requires data – and lots of it. The council for Agricultural Science and Technology explains data is, “commonly fragmented, distributed, heterogeneous and incompatible,” which makes it challenging to use in a way that can be readily analyzed with AI.
The real value in data lies in how it’s returned to the producer, says Ryan Gilbert, a consultant with Deep Root Strategies LLC, a company that drives innovation in agriculture through adopting new forms of technology.
“The foundation [of success] is the data being generated by the companies selling the products and how they deliver that data to farmers to be able to use” Gilbert says. “The question is: What can AI do to actually increase the quality of the information and deliver it when the farmer wants it and in the format they want to achieve the outcomes they need to remain profitable?”
Unlocking AI’s Potential Through Teamwork
The next generation could play a role in building trust. At the Center for Digital Agriculture at the University of Illinois, Jessica Wedow says students are working on several projects that connect AI and agriculture. She says having one foot in each discipline could help form a stronger sense of trust.
If you’re able to involve students who have an understanding of the problems in agriculture and the need for the end users – the farmers and the growers – when building AI-enabled tools that’s a win-win, Wedow explains.
Fredy Diaz, deputy chief data officer for USDA, also believes collaboration, sharing research and insights, will strengthen the role of AI on the farm.
“It is all about teamwork; we’re really big on a partnership between government, industry and academia. It’s something we practice almost every day in my office,” Diaz says.
For example, USDA is working with students from various universities and Amazon Web Services to create technology that solves problems in real-world agriculture.
