Artificial system

Using artificial intelligence in agriculture carries substantial risks, warn researchers

Imagine a field of wheat stretching out to the horizon, cultivated for flour that will be made into bread to feed the population of the cities. Imagine if all the authority to plow, plant, fertilize, monitor and harvest that field had been delegated to artificial intelligence: algorithms that control drip irrigation systems, autonomous tractors and combine harvesters, sufficiently intelligent to respond to the weather and specific needs. of the harvest. Then imagine that a hacker ruins everything.

A new risk analysis, published today in the journal artificial intelligence of nature, warns that the future use of artificial intelligence in agriculture carries substantial potential risks to farms, farmers and food security that are poorly understood and underestimated.

The idea of ​​intelligent machines running farms is not science fiction. Large companies are already pioneering the next generation of autonomous ag-bots and decision support systems that will replace humans in the field,said Dr Asaf Tzachor of the Center for the Study of Existential Risk (CSER) at the University of Cambridge, first author of the paper.

“But so far no one seems to have asked the question ‘are there any risks associated with a rapid deployment of agricultural AI?'” he added.

Despite the enormous promise of AI to improve crop management and agricultural productivity, potential risks need to be responsibly addressed and new technologies properly tested in experimental settings to ensure they are safe and protected. against accidental failures, unintended consequences and cyber-attacks, the authors say.

In their research, the authors compiled a catalog of risks that need to be considered in the responsible development of AI for agriculture – and ways to address them. In it, they sound the alarm about cyber attackers who could disrupt commercial farms using AI, by poisoning datasets or shutting down sprayers, autonomous drones and robotic harvesters. To guard against this, they suggest that “white hat hackers” help companies discover any security flaws during the development phase, so that systems can be protected against real hackers.

In a scenario associated with an accidental failure, the authors suggest that an AI system programmed only to deliver the best short-term crop yield could ignore the environmental consequences of that achievement, leading to overuse of fertilizers and soil erosion. long-term. Excessive application of pesticides in search of high yields could poison ecosystems; excessive application of nitrogen fertilizers will pollute the soil and surrounding waterways. The authors suggest involving applied ecologists in the technology design process to ensure these scenarios are avoided.

Autonomous machines could improve working conditions for farmers by relieving them of manual labor. But without an inclusive technology design, the socio-economic inequalities that are currently entrenched in global agriculture – including gender, class and ethnic discrimination – will persist.

“AI expert farming systems that do not consider the complexity of labor inputs will ignore and potentially support the exploitation of disadvantaged communities,” warns Tzachor.

Various advanced ag-bots and machines, such as drones and sensors, are already being used to gather crop information and support farmers’ decision-making: detecting diseases or insufficient irrigation, for example. And autonomous combines can bring in a harvest without the need for a human operator. These automated systems aim to make farming more efficient, reduce labor costs, optimize production and minimize losses and waste. This leads to increased income for farmers as well as greater reliance on agricultural AI.

However, the small producers who cultivate the majority of farms worldwide and power large swathes of the so-called Global South are likely to be excluded from AI-related benefits. Marginalization, low internet penetration rates and the digital divide could prevent smallholders from using advanced technologies, thus widening the gaps between commercial and subsistence farmers.

With an estimated two billion people suffering from food insecurity, including some 690 million people suffering from malnutrition and 340 million children suffering from micronutrient deficiencies, artificial intelligence technologies and precision agriculture promise substantial benefits for food and nutrition security in the face of climate change and a growing world population.

“AI is being hailed as the way to revolutionize agriculture. As we deploy this technology at scale, we need to take a close look at the potential risks and aim to mitigate them early in the design of the technology,” said Dr. Seán Ó hÉigeartaigh, executive director of CSER and co-author of the new research.