Risks of using AI to grow our food are substantial and must not be
ignored, warn researchers

Date:
February 23, 2022
Source:
University of Cambridge
Summary:
Artificial intelligence (AI) is on the cusp of driving an
agricultural revolution, and helping confront the challenge of
feeding our growing global population in a sustainable way. But
researchers warn that using new AI technologies at scale holds
huge risks that are not being considered.



FULL STORY ========================================================================== Imagine a field of wheat that extends to the horizon, being grown
for flour that will be made into bread to feed cities' worth of
people. Imagine that all authority for tilling, planting, fertilising, monitoring and harvesting this field has been delegated to artificial intelligence: algorithms that control drip-irrigation systems,
self-driving tractors and combine harvesters, clever enough to respond
to the weather and the exact needs of the crop. Then imagine a hacker
messes things up.


==========================================================================
A new risk analysis, published today in the journal Nature Machine Intelligence, warns that the future use of artificial intelligence in agriculture comes with substantial potential risks for farms, farmers
and food security that are poorly understood and under-appreciated.

"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 in the University of Cambridge's
Centre for the Study of Existential Risk (CSER), 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 huge promise of AI for improving crop management and
agricultural productivity, potential risks must be addressed responsibly
and new technologies properly tested in experimental settings to ensure
they are safe, and secure against accidental failures, unintended
consequences, and cyber- attacks, the authors say.

In their research, the authors have come up with a catalogue of risks
that must be considered in the responsible development of AI for
agriculture -- and ways to address them. In it, they raise the alarm
about cyber-attackers potentially causing disruption to commercial farms
using AI, by poisoning datasets or by shutting down sprayers, autonomous drones, and robotic harvesters. To guard against this they suggest that
'white hat hackers' help companies uncover any security failings during
the development phase, so that systems can be safeguarded against real
hackers.



==========================================================================
In a scenario associated with accidental failure, the authors suggest
that an AI system programmed only to deliver the best crop yield in the
short term might ignore the environmental consequences of achieving
this, leading to overuse of fertilisers and soil erosion in the long
term. Over-application of pesticides in pursuit of high yields could
poison ecosystems; over-application of nitrogen fertiliser would 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 the working conditions of farmers,
relieving them of manual labour. But without inclusive technology design, socioeconomic inequalities that are currently entrenched in global
agriculture -- including gender, class, and ethnic discriminations --
will remain.

"Expert AI farming systems that don't consider the complexities of
labour inputs will ignore, and potentially sustain, the exploitation of disadvantaged communities," warned Tzachor.

Various ag-bots and advanced machinery, such as drones and sensors,
are already used to gather information on crops and support farmers' decision-making: detecting diseases or insufficient irrigation, for
example. And self-driving combine harvesters can bring in a crop without
the need for a human operator.

Such automated systems aim to make farming more efficient, saving labour
costs, optimising for production, and minimising loss and waste. This
leads to increasing revenues for farmers as well as to greater reliance
on agricultural AI.

However, small-scale growers who cultivate the majority of farms
worldwide and feed large swaths of the so-called Global South are likely
to be excluded from AI-related benefits. Marginalisation, poor internet penetration rates, and the digital divide might prevent smallholders
from using advanced technologies, widening the gaps between commercial
and subsistence farmers.

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

"AI is being hailed as the way to revolutionise agriculture. As we deploy
this technology on a large scale, we should closely consider potential
risks, and aim to mitigate those early on in the technology design,"
said Dr Sea'n O' hE'igeartaigh, Executive Director of CSER and co-author
of the new research.

========================================================================== Story Source: Materials provided by University_of_Cambridge. The original
text of this story is licensed under a Creative_Commons_License. Note:
Content may be edited for style and length.


========================================================================== Journal Reference:
1. Asaf Tzachor, Medha Devare, Brian King, Shahar Avin, Sea'n O'
hE'igeartaigh. Responsible artificial intelligence in
agriculture requires systemic understanding of risks and
externalities. Nature Machine Intelligence, 2022; 4 (2): 104 DOI:
10.1038/s42256-022-00440-4 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220223111240.htm

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