AI, agriculture and the future of food

“So far, no one seems to have asked the question, ‘Are there any risks associated with rapid deployment of agricultural AI?'” said Asaf Tzachor, a researcher at the Center for Risk Studies. existential from the University of Cambridge, in a press release.
The potential benefits are huge. Increasing agricultural productivity could help feed the estimated 2.4 billion people worldwide who suffer from food insecurity and malnutrition and revolutionize the way farmers use their land.
It could have a cost. The analysis highlights potential flaws in the agricultural data that powers AI-powered systems and the possibility that autonomous systems put productivity above the environment. This could lead to unintended errors resulting in over-fertilization, unsafe pesticide use, improper irrigation or erosion, jeopardizing crop yields, water supply and soil. And large-scale crop failures could exacerbate food insecurity.
Cybersecurity is another potential point of failure. The researchers said cyberattacks could disrupt entire food systems. The more agricultural systems depend on smart machines, the more disruption could be created if it malfunctions or is destroyed.
Then there are the people – and without inclusive technology, the researchers warn, AI could simply increase the inequalities that already exist in agriculture. While big farmers benefit, small farmers in southern countries, for example, could be completely excluded from agricultural gains.
Potential solutions mentioned by researchers include data sharing, citizen input, and digital “sandboxes” where developers can predict potential points of failure in agricultural AI.
“The technological modernization of agriculture has done a lot,” write the researchers. But irresponsible developers could “ignore and thereby perpetuate the drivers of nutritional insecurity, labor exploitation and environmental resource depletion.”
Responsible artificial intelligence in agriculture requires a systemic understanding of risks and externalities
Intelligence of natural machines