The Game-Changing Role of Artificial Intelligence in the Agriculture Sector

.... Strategies can help promote the adoption of AI-based systems in subsistence farming, contributing to improved food security, livelihoods, and sustainable development.

Last week I was in Nairobi, Kenya, attending the AI-Connect workshop hosted by the United States Department of State and the Atlantic Council. The AI-Connect program is an initiative sponsored by the U.S. Department of State and the Atlantic Council, that encourages the responsible stewardship of ARTIFICIAL INTELLIGENCE or AI technologies in line with the Organization for Economic Cooperation and Development (OECD) AI principles.

The AI-Connect Program empowers low and middle-income countries to participate in the global, multi-stakeholder conversation more effectively on AI policy. It brings together diverse leaders from various sectors of society including government, academia, the private sector, civil society, et al, to discuss issues surrounding the responsible use of AI. Last week's event brought together AI leaders from various countries, especially the African continent, to discuss issues related to the responsible use of AI and AI policy. 

No doubt, the event was both informative and educational. The presentations, panel discussions, speeches, questions, and activities gave each participant better insight into AI policy, AI development and AI implementation.

One of the activities which I found beneficial was a group activity in which teams were required to choose a particular stakeholder and develop an AI policy applicable to the sector from which that stakeholder emanates. That activity was interesting and exciting because it allowed us to develop a policy that had contextual relevance to the realities of the African continent, keeping in mind that there are multiple African countries, diverse cultures, and diverse economies. In view of the assignment, our team selected to discuss the Agriculture Sector, with .and subsistence farmers as our key stakeholders. 

Many of my teammates (from Ghana, Cameroun, Malawi, Namibia, etc.) agreed that subsistence farming is popular, if not the most popular form of farming on the African continent, and that an AI solution could help a great multitude. After a few hours of brainstorming and ideas exchange, we concluded that AI could be used to enhance subsistence farming, benefit people, especially in rural areas, and provide food security for a nation. 

During the exercise, we explored ways in which AI could bring some unique capabilities to subsistence farming. We discussed that AI has the potential to revolutionize subsistence farming by providing a range of unique capabilities that could help farmers improve their yields, optimize resource usage, and make more informed decisions. We identified several factors including Precision farming, in which AI-based systems could provide farmers with precise information about their crops such as information on soil quality, water usage, and nutrient levels) This information can help farmers optimize their farming practices, reduce waste, and increase yields. 

We also identified Predictive Analytics as another unique capability that AI could give farmers. PA as we refer to it, uses AI algorithms to analyze substantial amounts of data to make accurate predictions about crop yields, weather patterns, and other key factors that can impact farming outcomes. This helps farmers make more informed decisions about when to plant, fertilize, and harvest their crops.

We identified other capabilities including image recognition to help farmers take proactive measures to protect their crops and prevent damage;  natural language processing which can allow the use of AI-powered chatbots and virtual assistants to provide farmers with real-time advice and support on farming practices, weather patterns, and other important information; and autonomous farming, which uses AI-powered machines and robots to  help automate various aspects of farming, such as planting, harvesting, and watering crops. All these capabilities can help farmers save time and increase efficiency while reducing the need for manual labor.

We subsequently discussed some unique benefits of using AI in subsistence farming. We listed a few of the benefits as resource optimization (help reduce costs), improved decision-making, reduced labor requirements, increased resilience (help farmers mitigate risks and build resilience in the face of unpredictable events), increased or higher crop yields, and improved food security. These benefits demonstrate the potential for AI to transform subsistence farming, improving the livelihoods of subsistence farmers and contributing to more sustainable and resilient food systems.

We also looked at the potential obstacles to subsistence farming that need to be overcome before AI can be effectively utilized in this context. Some of these obstacles include language and literacy barriers, since many subsistence farmers may not be proficient in the language or literacy required to operate AI-based systems; and limited access to technology such as computing devices and internet connectivity which are required for accessing and utilizing AI tools and applications. 

Other obstacles include limited data availability which AI systems heavily rely on to train their algorithms and make accurate predictions; the prohibitive cost of implementing AI-powered systems; the lack of technical expertise, especially in rural areas where access to technical training and education may be limited.

The other aspect of using AI in subsistence farming that we looked at was the risks. Despite the benefits of AI in this area, there are risks involved like in all other areas. A few of these risks include data privacy and security; dependence on technology, lack of transparency, cultural and linguistic barriers, and bias and discrimination.

These risks highlight the need for careful consideration and planning when implementing AI-based systems in subsistence farming. It is important to ensure these technologies are developed and deployed responsibly and ethically, with the needs and perspectives of subsistence farmers at the forefront of decision-making.

We concluded the exercise by exploring strategies that could be used to make subsistence farmers adopt AI. We acknowledged that the adoption of AI-based systems in subsistence farming will depend on a variety of factors including but not limited to, explaining the benefits of AI to the users, the proper approach to communicating the use of AI to users, the availability of technology, the cost of implementation, and the level of technical expertise among farmers.

Hence, we proposed several strategies that could help promote the adoption of AI in subsistence farming. These strategies include addressing the cultural and linguistic barriers, providing training and support, creating incentives, and fostering collaboration and knowledge-sharing. We agreed that communicating the capabilities, obstacles, risks, and benefits of AI, through channels with which they are familiar (town chiefs, radio, family members, etc.), can ensure adoption. 

Overall, these strategies can help promote the adoption of AI-based systems in subsistence farming, contributing to improved food security, livelihoods, and sustainable development.

Editor’s note: The views expressed in this commentary are solely of the author and do not necessarily represent that of the Daily Observer newspaper.