AI and the future of African agriculture
With population and economic growth across the continent, the use of AI-based tools to increase inefficiency in Africa is of the upmost importance. In order to feed the continent, policymakers and agricultural workers in African countries will need to increase productivity by 60%, and AI- and Drone-powered precision agriculture will be a vital tool in achieving this. How can AI help increase productivity and reduce losses in food production? And what ethical implications may ensue? At the second RAIN-Africa workshop our three experts, Darlington Akogo, Christian Adumatta Gyampomah and Dr. Joyce Nakatumba-Nabende, discussed this very topic.
Darlington Akogo, founder of GUDRA and its subsidiaries, minoHealth, minoHealth AI Labs, karaAgro AI, Runmila AI Institute, and Gudra AI Studio, gave fascinating insights into how AI can help increase irrigation efficiency and detect, identify and track the spread of diseases in crops. With the help of drones and apps, farmers can ensure their crops are healthier and more fertile. AI can even help identify the most resilient crops for pollination and breeding. All of this can help increase productivity drastically and reduce waste of valuable resources and loss of food.
Christian Adumatta Gympomah, Research Associate at the Emerging Networks and Technologies Lab at Kwame Nkrumah University of Science and Technology, Ghana, on the other hand, stressed the need to improve the supply chain in order to reduce losses during transportation and unnecessary long storage in his talk. Through an AI-optimized supply chain, customers, storeowners, and the food industry would be able to easily see the produce offerings of different farmers, streamlining the information flow between suppliers and buyers.
Dr. Joyce Nakatumba-Nabende, Head of the Makerere University Artificial Intelligence lab and Lecturer at Makerere University in Uganda, described how the main focus of AI-based tools should be placed on two areas: increasing the efficiency with which (agricultural) experts can communicate with stakeholders, and enhancing the capacity of their clients (i.e. farmers) to produce. Some tools already in place include image-based disease diagnosis, which helps farmers identify plant diseases quickly and gives advice on how to control them, or chatbots and recommender systems that can help farmers make optimal decision for their crops.
Dr. Nakatumba-Nabende also stressed that AI used in agriculture needs to be founded on principles of transparency, inclusion, responsibility, impartiality, reliability, security and privacy. However, these principles require extensive legal frameworks, increased