Artificial Intelligence (AI) In Agriculture in Africa - Part 2
E. Etta April 2024
Artificial Intelligence (AI) can be used in Africa. According to a report by The Guardian, AI can play an important role in exploiting the potential of countries’ fast-growing populations. AI can be used in various sectors such as healthcare, agriculture, education, finance, and governance. For instance, in South Africa, drones are used to monitor weeds, while in Mauritius, computers are used to crunch health data for better outcomes for patients; In Rwanda, AI efficiently schedules the delivery of medicine to patients in remote areas by using drones; In Cape Town, a startup is digitizing African languages to allow them to be translated by AI-powered software such as Google Translate and so boost connectivity.
Artificial Intelligence (AI) holds great promise for boosting Africa’s food security, as it intersects with precision agriculture, supply chain management, and access to food. AI in agriculture across Africa has been gaining traction and is being applied in various ways to address challenges and enhance productivity. It's important to note that the adoption of AI in agriculture varies across different regions of Africa, and challenges such as infrastructure limitations, access to technology, and education levels can impact its widespread implementation. However, Africa is lagging behind the rest of the world in AI, and there is a need to integrate AI into the lives of 1.4 billion people. Despite the challenges, many experts believe that AI can help tackle the economic problems that Africa faces.
The challenges of AI in Africa
Despite its vast potential, the adoption and implementation of AI in Africa faces several challenges, including a lack of relevant technical skills, inadequate basic and digital infrastructure, insufficient investment in research and development, and a need for more flexible and dynamic regulatory systems.
The skills gap
Though there is a perception that people in Africa, especially the young ones, lack the necessary technical skills. This is a perception that is a bit misguided for several reasons:
1. Young people even without formal training are leading the charge in adopting a lot of these new technologies and using them in creative ways.
2. Recognizing the talent of these young people, a number of international firms have established training programs in several countries in Africa and are training young people in the current technologies and creating a pipeline for those that complete their training to get jobs with their companies.
3. Innovative forms of trans-continental collaboration such as Deep Learning Indaba (a Zulu word for gathering), which is fostering a community of AI researchers in Africa, and Zindi, a platform that challenges African data scientists to solve the continent’s toughest challenges, are gaining ground, buoyed by the recent “homecoming“ of several globally-trained African experts in AI.
Data limitations
The success of AI applications depends on the availability of high-quality and diverse data. In Africa, there is a significant challenge in ensuring that AI systems are trained on data that accurately reflects the local population and addresses the unique challenges faced by the continent.
Solution: One solution to this problem would be to have AI applications that are developed in Africa for the prevailing conditions in Africa.
Research and development
Investment in research and development is critical for driving innovation and fostering the growth of AI technologies in Africa. However, the continent lags behind in this area, with limited funding available for AI-related projects. To overcome this challenge, Africa must develop innovative financial instruments to fund human capital development.
Solutions: One possible solution is to reach out to the African diaspora living and working in other continents to provide the initial investment particularly with guarantee of returns. Another solution is to set up grassroots funding resources to gather financing for AI related projects.
Displacement of jobs
There is a fear that the growth of AI and automation will lead to a displacement of jobs. That is a fear that is felt globally and yes there may be loss of jobs in some areas but the technology is expected to create jobs in other areas. The challenge in Africa and globally is pivoting and creating jobs and opportunities that are enhanced and supported by AI not overtaken by AI.
Other Challenges of AI in Africa
Africa’s biggest companies – are not adopting or deploying AI applications widely, causing them to trail behind global rivals. The few that have invested in AI have incurred above-average costs because they have imported talent and technology. Whereas they should be following some of the examples of multinational companies and making use of homegrown talent and innovations which would cut down on their costs.
What are the advantages and challenges of AI use in Africa for Agriculture
AI presents multifaceted advantages. Technological advancements have facilitated the development of diverse AI applications in agriculture, spanning areas such as weather forecasting, pest analysis, weed detection, and precision farming practices. These advancements significantly contribute to optimizing agricultural processes and output, driving the growth of the AI in the agriculture market. Ongoing efforts by governments, NGOs, and private organizations aim to address these challenges and promote the use of AI for sustainable agriculture in the continent.
Challenges
Addressing the challenges requires a collaborative effort involving governments, NGOs, the private sector, and local communities to ensure that AI in agriculture is deployed responsibly and inclusively in Africa. Limited Infrastructure: Many regions in Africa lack the necessary infrastructure, including power supply, which are crucial for implementing and sustaining AI technologies in Agriculture.
Data Accessibility and Quality: Access to high-quality, diverse, and representative data is a challenge. Limited data on local farming practices, crop varieties, and weather patterns can hinder the development and effectiveness of AI applications. Systems need to be developed that will make it easy to collect, store and disseminate useful data.
Affordability: The cost of implementing AI technologies, including sensors, drones, and computing infrastructure, can be prohibitive for small-scale farmers who make up a significant portion of the agricultural workforce in Africa.
Solutions: There needs to be partnerships developed possibly between private organizations and the African governments to provide at a low cost some of these AI technologies. Another solution would be to look at ways to develop lower cost technologies that can be more affordable for the farmers in Africa. There could also be investment by private entities or individuals in these farms to manage the use and implementation of these technologies with built in payoff in the crops yielded and/or profits generated on these farms.
Skills Gap: There is a shortage of skilled professionals who can develop, implement, and maintain AI solutions. Training programs and educational initiatives are needed to bridge this gap.
Regulatory Framework: Clear and supportive regulatory frameworks are essential for the responsible adoption of AI in agriculture. The lack of such frameworks can lead to uncertainties and potential misuse.
Cultural and Linguistic Diversity: Africa is linguistically and culturally diverse. Developing AI
systems that can cater to this diversity, considering different languages and local contexts, is a challenge.
Solutions: This challenge underscores the need for some AI technologies to be developed locally or rather within Africa because it would possibly need less adaptation. Researchers from across the continent are collaborating on an open source AI project to develop machine translation for African languages - facilitating communication, increasing accessibility and opening doors to the world’s youngest continent to play a stronger role in shaping the digital world.
Opportunities: AI is important to agriculture in Africa for several reasons, as it offers solutions to address various challenges faced by farmers on the continent. Here are some key reasons why AI is crucial in the context of African agriculture: Climate Resilience: Africa is susceptible to climate variability and extreme weather events. It is AI-powered tools, including weather prediction models and climate monitoring systems, that assist farmers in adapting to changing weather conditions, managing risks, and making timely decisions to mitigate the impact of climate-related challenges. For example Nigeria, as one of the top six greenhouse gas emitters in Africa will be one of the countries in Africa most affected by global warming in the near future.
Precision Agriculture: AI can enable precision farming techniques, optimizing resource use, and increasing crop yield. This is particularly beneficial in regions where resources like water and fertilizer are scarce. This advantage becomes even more important with the continued onset of global warming.
Crop Disease Prediction and Monitoring: AI can analyze data to predict and monitor crop diseases, enabling timely interventions and reducing the risk of crop loss.
Financial Inclusion: AI-powered tools can support financial inclusion by providing credit scoring and risk assessment for smallholder farmers, enabling them to access financial services.
Supply Chain Optimization: AI can enhance the efficiency of agricultural supply chains, reducing post-harvest losses and ensuring timely delivery of products to markets.
Monitoring and Management of Livestock: AI applications can help monitor the health and behavior of livestock, enabling early disease detection and improving overall herd management. This is especially important with managing livestock on the pasture.
Job Creation and Economic Growth: The development and deployment of AI technologies in agriculture can stimulate economic growth and create job opportunities in research, development, and implementation.
Conclusion
While the potential benefits of AI in African agriculture are significant, it's important to address challenges related to infrastructure, access to technology, and the need for proper education and training to ensure widespread adoption and maximize the positive impact of these technologies. There are solutions for some of the issues in this article but more solutions need to be addressed and implemented in the near future.
Resources
1. A goldmine at our fingertips: The promise and perils of AI in Africa
2. Advances in Food Security and Sustainability
3. AI In Agriculture Market size worth $ 1610 Million, Globally, by 2030 at 9.52% CAGR:
Verified Market Research
4. AI in Agriculture — The Future of Farming
5. AI Is Here to Stay! How Artificial Intelligence Can Contribute to Economic Growth in Africa
6. Deep Learning Indaba
7. How Artificial Intelligence Can Be Used in Agriculture (jiva.ag)
8. Masakhane: Using AI to Bring African Languages Into the Global Conversation
9. Nigeria must lead on climate change
10. Sizing the Prize
11. The future is intelligent: Harnessing the potential of artificial intelligence in Africa
12. What is artificial intelligence (AI)?
13. What Is Artificial Intelligence? Definition, Uses, and Types
