Like all sustainable development challenges, achieving food security is a complex objective intertwined with the environment, economics, peace and security, and technology.
But, alarmingly, since 2020 global food insecurity has doubled to over 300 million people. This dramatic decline of food security, a fundamental human right, demands urgent intervention to ensure its four dimensions - availability, access, utilization and stability - do not crumble under the weight of intensifying pressure from climate change.
As weather patterns become increasingly disrupted, so too are lives and livelihoods throughout the world. Agricultural production is battling an unyielding barrage of climate change-related hazards and disasters, which disproportionately impact vulnerable populations including the smallholder farmers who produce one-third of the world's food.
Meanwhile, our global agrifood systems are also exacerbating the climate crisis through land use degradation, unsustainable farming practices and inefficient supply chains.
For Sustainable Development Goal (SDG) 2 — Zero Hunger — we know that headway is faltering across targets to double productivity of small-scale farms and to ensure sustainable food production systems. There are many reasons for this slow progress including the COVID-19 pandemic, which forced governments to divert investment away from agricultural commitments.
Our capacity to stay ahead of, and respond to, climate change disruptions increasingly depends on robust and shared data systems.
However, since the launch of the SDGs in 2015 we have witnessed astounding advances of artificial intelligence (AI) - a technology that will significantly boost our efforts towards food security and climate action.
Despite the fears of negative consequences of AI, UN Secretary-General António Guterres has rightly noted that for sustainable development “the transformative potential of AI for good is difficult even to grasp.”
If appropriately developed and governed, AI will have a profound role in our work to expand sustainable agricultural systems and to achieve food security as we strive to mitigate and limit the impacts of climate change.
First, AI will enhance the data systems that guide us to improved agricultural sustainability.
From soil health and water availability to weather trends and pest control, our capacity to stay ahead of, and respond to, climate change disruptions increasingly depends on robust and shared data systems.
Our analytical toolkits - such as remote sensing, satellite imaging and earth observation systems - are on the cusp of an AI revolution that will dramatically improve computing power, accuracy, cost efficiency, and accessibility of leading technologies to support agriculture.
Second, AI will help us achieve better agrifood systems.
Thirty per cent of human-caused greenhouse gas emissions can be traced to global agrifood systems including farms, land use changes to support agriculture, and distribution supply chains. Here, the potential for AI to improve food systems is vast across land, energy and transportation.
AI could drive a technology revolution aligned with the agricultural and climate change needs of the Global South.
Land use decisions will benefit from machine learning to more accurately determine the most suitable plots and crops based on climate modeling, ecosystem data, and disaster risk mapping. AI will also inject new efficiency into supply chains by providing rapid insights on market demand and better prepare distribution networks for impending climate shocks and disasters.
In cities, where more than half of the world population lives, AI will help us determine more efficient connections between urban consumers and surrounding producers that will reduce transportation emissions and food waste.
Third, AI could drive a technology revolution aligned with the agricultural and climate change needs of the Global South.
As an example, Africa, by some estimates, has about 45% of the world’s land suitable for sustainable agriculture and more than 65% of the labour force is engaged in the agricultural economy. But Africa faces the highest percentage of food insecurity compared to other world regions while also enduring massive impacts of climate change. In fact, 85% of the top 20 countries threatened by climate change are in Africa.
We know the causes of food insecurity are complex, and include seemingly intractable cycles of conflict, but if we truly devote our efforts to developing AI technologies for sustainable agriculture, then our clear target is the Global South. This could reframe the use of AI to ensure that Global South agrifood systems can support the livelihoods and jobs of the future.
On 1–2 July, the United Nations University Institute for Environment and Human Security and the United Nations Framework Convention on Climate Change Technology Executive Committee are co-hosting the Bonn AI and Climate Expert Meeting.
Importantly, among the meeting’s objectives is to better understand emerging solutions at the interface of AI and climate action and use this knowledge as a foundation to build strong partnerships to govern, develop and use AI for good.
The potential benefits of AI will depend on partnerships. Cooperation is the only path to fully comprehending global challenges to ensure that solutions to one problem do not amplify a different problem. Making progress at the intersection of agriculture, food security and climate change is no different.
Although there is an undercurrent of anxiety and apprehension around AI, its impacts will reflect our shared vision. It is up to us to shape that vision to support sustainable development.
This article was first published by Context. Read the original article on the Context website.
Suggested citation: Marwala Tshilidzi. "Artificial Intelligence Can Transform Global Food Security and Climate Action," United Nations University, UNU Centre, 2024-07-01, https://unu.edu/article/artificial-intelligence-can-transform-global-food-security-and-climate-action.
