Resolute in offering a remedy for the persistent volatility in agricultural product prices, influenced by elements such as weather condition...
Resolute in offering a remedy for the persistent volatility in agricultural product prices, influenced by elements such as weather conditions, changes in demand, and intensified by speculative activities, Adedapo Alawode Emmanuel, a Nigerian agricultural economist based in the US, has proposed the efficient application of Artificial Intelligence to curb the situation.
In a detailed report provided to Arewa PUNCH, the agri-economist pointed out that fluctuations in agricultural prices lead to economic instability, which may endanger food security, discourage investment, and adversely affect both farmers and consumers, particularly in countries where agriculture is a major economic pillar.
In the article provided to our correspondent on Thursday, titled "Artificial Intelligence: The Hedge Against Extreme Weather-Driven Market Instability," Emmanuel, an expert in technology policy, rural development, and sustainable food systems, advocated for the use of AI to safeguard the safety of food and those involved in its production—covering both smallholder farmers in developing nations and consumers globally.
He stated that the worldwide agricultural economy is moving rapidly into an era of extraordinary uncertainty, noting that climate disruptions ranging from droughts and floods to irregular rainfall and extreme temperatures are now the norm.
"They are the standard. These repeated interruptions make planting and harvesting schedules uncertain, reduce the reliability of crop yields and quality, and increase the vulnerability of food supply chains," Emmanuel said.
He pointed out that the outcome leads to extreme fluctuations in food prices, sometimes reaching levels that severely impact household purchasing ability, and at other times causing significant losses for farmers' incomes. He mentioned that the effect of this instability goes beyond just producers and consumers, but also affects national budgets, trade patterns, and the overall objective of global food security.
The specialist added, “During this period of instability, technology can have a significant impact. Artificial intelligence (AI), traditionally seen as a resource for developed nations and a privilege for advanced economies, is becoming more and more vital in dealing with uncertainty. The strength of AI lies in its capacity to predict upcoming challenges, manage supply chains digitally, and assist officials in mitigating effects on farmers and consumers.”
The agricultural industry has traditionally been among the last to embrace digital innovations. However, within the farming sector, an increasing number of trials are being conducted to test AI as a strategy to combat climate change.
As an agricultural economist who has spent the past ten years examining the overlap between technology, poverty, and food systems, I am optimistic about AI's potential to reduce fluctuations, but with a key condition: if it is implemented fairly, openly, and backed by appropriate policy measures.
Climate change threatens agricultural markets through two primary channels. The first involves physical disturbances. Crop yields and production are reduced due to extreme weather events that can delay or hinder planting, watering, or fertilizing crops inconsistently or harm or destroy entire harvests.
For instance, the floods in Pakistan in 2022 submerged over 2 million hectares of agricultural land, resulting in significant damage to rice and cotton production and disrupting both local and international markets.
"East Africa has experienced consecutive maize crop failures in recent years due to drought, leading to increased food insecurity and rising regional prices. The second factor is market psychology and speculation. The fear triggered by climate shocks in the marketplace can be just as damaging as the actual loss of crops or livestock. Speculative trading on commodity exchanges, consumers' panic buying, and traders' hoarding intensify the effects of real shortages," Emmanuel emphasized.
He continued, "The outcome is unpredictable fluctuations in food prices that affect low-income and middle-income countries the most. In nations where smallholder farmers operate with minimal profit margins and consumers allocate a significant portion of their income to food staples, even a slight rise in the cost of maize, rice, or wheat can lead to millions facing food insecurity."
Artificial intelligence has the potential to enhance our predictive capabilities, strengthen the resilience of supply chains, and improve policy reactions. For instance, machine learning algorithms that analyze large datasets from remote sensing, weather predictions, soil moisture sensors, and historical crop yield data have demonstrated effectiveness in identifying early signs of crop stress. These models can predict pest outbreaks, water scarcity, or possible drops in production several months or even weeks in advance.
Emmanuel added that in India, AI-driven models have been implemented with more than 80 percent accuracy to forecast wheat production, enabling officials to modify procurement strategies ahead of abundant or poor harvests. He noted that in East Africa, early warning systems now utilize AI technologies to analyze rainfall irregularities and vegetation data, assisting in anticipating food assistance requirements before shortages occur.
"The potential extends beyond prediction. AI could also support dynamic pricing systems that modify prices instantly according to future supply and demand indicators. If models forecast a below-average maize harvest in Nigeria or Kenya, officials can adjust subsidies, lower import duties, or release stockpiles," stated the agricultural economist.
The specialist argued that this proactive modification could prevent certain extreme price fluctuations, offering greater protection to both farmers and consumers.
He pointed out that in numerous developed nations, comparable AI systems have already been implemented to stabilize dairy and cereal prices, and these lessons can be adapted and applied to situations in the developing world.
Adedapo Alawode Emmanuel said, "Artificial intelligence can also enhance logistics, allowing food supply chains to be flexible and quickly redirect food from areas with excess to those in need, ensuring every market has sufficient stock. The reduction in food waste, which currently accounts for one-third of all globally produced food, along with more streamlined and efficient supply networks, can help reduce erratic price fluctuations."
The fleeting freshness of items like fruits and vegetables adds extra strain on their pricing.
Cold-chain management enhanced by AI, which employs sensors and data analysis to track and improve temperature-controlled storage, transportation, and delivery, can help these products remain fresh for longer and suffer fewer losses after harvest, thereby supporting more stable pricing. Governments and humanitarian organizations can apply AI simulations to assess the effects of various policy strategies across different climate-related stress situations.
Algorithms might go through a series of policy options, including export restrictions, increasing food aid, fertilizer subsidies, and tax breaks, to deliver almost real-time evaluations of their effects. These AI-powered insights could help leaders move past impulsive reactions and implement thoughtful, strategic measures.
Artificial intelligence is not a cure-all. The gap between individuals with digital access and those without poses a growing risk.
He stated that in Sub-Saharan Africa and South Asia, numerous small-scale farmers lack access to smartphones, the internet, or the digital skills required to utilize AI-driven platforms. If left solely to market dynamics, AI is likely to increase current disparities between commercial farms that can adopt AI and family-run farms that require it the most.
Emmanuel added that another issue regarding digital access is that numerous AI models are developed and evaluated using data from major commercial farms in North America or Europe, which may differ significantly from the circumstances and structures found in smallholder farming across rural areas in Africa, Asia, or Latin America.
"Without data that reflect actual conditions in the field, AI forecasts might be incorrect or not useful for farmers in rural areas," the agricultural expert cautioned.
Nevertheless, he stated, "A separate group of issues involves matters of corporate governance and monopolization. Agricultural data and the AI systems that analyze it are becoming more centralized within a few major companies. The algorithms driving significant decisions impacting entire food systems should be open and transparent, and when AI is linked to profit-driven objectives and closed platforms, these ethical and governance standards may be at risk."
Ultimately, deploying AI is costly. Low-income nations might be excluded unless they receive funding from international aid, public-private collaborations, or open-source AI groups. AI has the potential to significantly enhance agricultural resilience and stabilize prices, but only if specific conditions are fulfilled. The first requirement is data. Governments, academic institutions, and international organizations need to work together to invest in local data sources that reflect the complete range of farming systems, environments, and seasons.
The second aspect is inclusivity. Farmers, traders, and local communities should be involved in the process of designing, testing, and applying these tools to ensure that AI platforms are user-friendly, reliable, and culturally suitable.
Third, organizations focused on development should look for open-source or at least understandable models to prevent control by a single entity and ensure clarity.
"Fourth, it is essential to establish suitable governance structures to oversee the application of AI and ensure that the implementation of AI technologies benefits the public rather than just private interests," he emphasized once more.
Ultimately, enhancing capabilities will be crucial for making AI accessible to all. Farmers, agricultural advisors, and policymakers must receive training and education in digital skills to effectively utilize these technologies. AI is not a universal solution, but it serves as a tool that can be used to address challenges caused by climate-related fluctuations in agricultural prices.
The resources are available, but they need to be used carefully and within strong policy structures, along with the participation of all involved parties.
This issue does not solely fall upon farmers or governments to address. Private companies and civil society will also have to collaborate closely.
"With increasing climate instability becoming the standard, the issue is no longer if AI should be involved in agriculture and food systems. The focus now is on how to incorporate it effectively and fairly to safeguard food security and those who grow it—both for small-scale farmers in developing nations and consumers globally," concluded Adedapo Alawode Emmanuel.
Provided by SyndiGate Media Inc. (Syndigate.info).
COMMENTS