Artificial Intelligence, or AI, is defined as the simulation of human intelligence to perform various tasks through a computer or machine-based system. AI can speed up processes and decrease the chance of errors that would happen due to the imperfect nature of humans and human intelligence. In a continent like Africa the use of AI can aid in combating climate side effects, preventing diseases and in increasing productivity.
The beauty of artificial intelligence is the synergy it creates across different areas, for instance – if applied in agriculture it can solve the risk of diseases caused through vegetation as well as hunger. If applied in public transport it can aid the economy and create trade routes within the continent.
The different thematic areas intersect with one another, hence when one of the thematic areas is addressed it creates a sort of domino effect on the others in resolving some, but not all, prominent issues. Hence the need for AI in each thematic area is needed in the attempt to create the best and ultimate outcome. This conference has identified six thematic areas as its primary focuses:
AI in Public Services
Countless research, articles as well as past history shows us that a more connected Africa creates for a more powerful Africa. Governments may utilize AI to create better policies, make better decisions, enhance citizen participation and communication, and boost the effectiveness and efficiency of public services. Through a collaborated form of public service administration within African countries, the connection between countries can help in the elevation of trust, economy and support.
AI in Cybersecurity
The threat of cybersecurity attacks is prevalent in Africa. In a matter of seconds or minutes, AI can identify connections between risks like malware files, dubious IP addresses, or insiders. AI offers customized risk analysis, cutting down on the time security professionals need to address risks and make important judgments.
By consuming billions of data, AI’s capability for continuous learning enhances its ability to “understand” cybersecurity risks and cyber risk. AI reasoning also identifies dangers more quickly by quickly assessing connections between threats like malware files, dubious IP addresses, or insiders. Finally, AI shortens the time it takes security analysts to make crucial judgments and address risks by automating time-consuming activities and providing customized risk analyses.
Trustworthy and Ethical AI
Corruption amongst other ethical issues is an ever so present issue in Africa, for the past several decades. The use of AI could dramatically decrease corruption, abuse of power and other unethical activities that cause distrust in the public. However, it goes without saying that AI is a way to get information from the public without their knowing. This would in turn cause even more lack of trust in the system.
The problem of bias affects society and people in general, not just AI. AI systems can learn, magnify, and transmit that prejudice at digital speed and scale. A fair, consistent method must be incorporated into the design and training of any AI system. To lessen discriminatory bias, it must also have internal and external inspections. Privacy is a crucial concern for all sorts of data systems, but it is particularly crucial for AI.
AI can no longer be viewed as a “black box” that produces output without a clear knowledge of what is happening inside. Blaming technology alone for faulty judgments and calculations is just unacceptable. Data protection laws must be followed, and data must only be used for specific purposes. This is a crucial problem that will most certainly only get worse when AI is used to more and more vital tasks like sickness detection, wealth management, and autonomous driving.
AI in Geographic Information Systems
Geographic Information Systems also known as GIS empowers AI by using its geographical visualization and spatial analytic capabilities to further process and mine data. Moreover, GIS empowers AI by using its geographical visualization and spatial analytic capabilities to further process and mine data.
In-depth processing and mining of AI extraction results can enable real-time geo-fence alerts, vehicle tracking, and other applications. Retailers can use machine learning and location intelligence for site selection, customer support, price setting, supply chain optimization, location-based advertising, and personalization. Government agencies may employ georeferenced drone and satellite photos to automate fieldwork, model growth scenarios, predict crop yields, and monitor crop health in real time using machine learning algorithms. There have been some successful attempts to use GIS and AI to regulate pollution and fight disease, this in turn could help Africa immensely.
AI in Agriculture
Although a vast majority of African farmers use traditional methods of farming and crop production. With the aid of artificial intelligence, farmers in Africa may automate their operations while also switching to precise cultivation for improved crop quality and production while consuming fewer resources. With the help of artificial intelligence and machine learning models, this data is leveraged in real-time for obtaining useful insights like choosing the right time to sow seeds, determining the crop choices, hybrid seed choices to generate more yields and the like. AI systems are helping to improve the overall harvest quality and accuracy – known as precision agriculture.
These machines help improve the size of the yield and reduce waste from crops being left in the field. These machines use sensor fusion, machine vision and artificial intelligence models to identify the location of the harvestable produce and help pick the right fruits. With the help of technologies like big data, AI and machine learning, companies can detect pest and disease infestations, estimate the tomato output and yield, and forecast prices. These intelligent AI sprayers can drastically reduce the number of chemicals used in the fields and thus improve the quality of agricultural produce, and bring in cost efficiency.
AI in Public Health
Public health is one of the many industries that are still in its infancy stages in the African continent. Both patients and doctors face several challenges because of the lack of both technological and financial resources. The lack of these resources leads to the suffering and often the death of patients due to the lack of machinery for diagnosis and even when the resources are present the threat of false diagnosis is even more present.
Through the use of AI in public health various endemic and non-endemic cases in Africa can easily be identified and controlled in the early stages of the diseases. Additionally, AI tools can be used to inform public health policy. For example, predictive analytics can be used to identify risk factors for disease; and optimization frameworks (whether single stage or repeated) can be used to identify when to screen or treat disease, or which risk groups to target given limited resources. This in turn will aid in informing officials on which groups, diseases and areas should be addressed.