How Artificial Intelligence Can Help To Solve Food Insecurity

The Global Food Shortage Crisis

Beyond the mere availability of food, food insecurity is defined as “limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable foods in socially acceptable ways.”

According to the World Summit on Food Security, there are 4 pillars essential for food security:

i. Availability: This refers to the supply of food which relies on production, distribution, and exchange.

ii. Access: Here, the available food must be affordable and within the reach of individuals and households according to their nutritional preferences.

iii. Utilization: This is a more individual pillar as it refers to whether the consumed food can meet the physiological needs of the person;

iv. Stability: This is the consistent availability of and access to food over time. 

Food insecurity in the world today is the result of failings in any or all of the 4 pillars listed above.

SDG 2 reads: "End hunger, achieve food security and improved nutrition and promote sustainable agriculture". However, the goal to achieve Zero Hunger by 2030 is in considerable peril as food insecurity data paints a grim picture. 

i. 720-811 million people faced hunger in 2020 as undernourishment rose to 9.9% in that year from 8.4% in 2019. It is projected that 660 million people will still go hungry by 2030.

ii. 1 out of every 3 people in the world (2.37 billion) lacked access to adequate food in 2020.

iii. No fewer than 3 billion people in the world cannot eat healthy food due to income inequality.

iv. Acute food insecurity “crisis” level affected 161 million people in 2021 while 227 million people were in “stressed” level of acute food insecurity – a step below “crisis”. Acute food insecurity is when there is an imminent threat to a person’s life or livelihood due to a lack of food.

Food insecurity is responsible for nutritional deficiencies that cause ill-health and affect a person's quality of life. Economically, it is estimated that $130.5 billion is spent on treating sicknesses linked to hunger and food insecurity.

How Artificial Intelligence Can Help

AI applications can be used to combat food insecurity by supporting any of the 4 pillars that guarantee food security. Markets & Markets estimates that expenditure on AI technologies and solutions will reach $4 billion by 2026.

In the area of food production, AI can be used to inform decision-making for increased productivity. AI can be used to identify nutrient deficiencies and recommend the ideal fertilizer for use to farmers. It can also perform soil analysis, which can be used to improve crop choices by monitoring soil and crop health.

Furthermore, AI can be used to drive novel methods of food production. Computer Vision and related AI algorithms have been used to push vertical indoor farming, optimize nutrient input and boost yield in real-time.

Labor shortage is also responsible for declining food production. However, AI can prove to be useful here through the use of autonomous tractors, IoT, and artificially intelligent robots. The application of these will not only help to cover for labor shortage but also improve efficiency and output as robots can work longer and make less mistakes.

Computer Vision algorithms can be used to improve food quality by aiding the sorting of harvested produce by separating the ripe fruits from unripe or overripe fruits. 

Food wastage is another important area to combat to guarantee food security. Blockchain and AI technology can be leveraged to digitize food supply chain data and help farmers and consumers to trace food better.

Machine learning and image recognition can also be used to optimize caloric consumption and improve food utilization for consumers by identifying food products and their nutritional content.

Challenges to AI Intervention

AI support for agriculture is desirable but not flawless. A possible challenge is with the adoption of the technologies as most agriculture takes place in the rural environment where literacy is limited. Farmers would need to be taught to integrate these technologies into their existing operations.

The different technologies also need to be adaptable for use in different countries as solutions without widespread usability will not do much in the fight against food insecurity.


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