- AI encompasses various techniques and approaches such as machine learning, deep learning, natural language processing, computer vision, and robotics, among others.
- The ultimate goal of AI is to create machines that can think, learn, and act like humans, potentially revolutionising industries, improving efficiency, and solving complex problems.
Image: HANDOUT
Image: HANDOUT
In keeping with the tradition of being a leader in the adoption of new technologies, Kenya is set to lead the adoption of Artificial Intelligence (AI) in the region.
AI is the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, understanding natural language, and even creativity.
AI encompasses various techniques and approaches such as machine learning, deep learning, natural language processing, computer vision, and robotics, among others.
AI systems can range from simple rule-based systems to highly complex neural networks capable of autonomous decision-making and adaptation.
The ultimate goal of AI is to create machines that can think, learn, and act like humans, potentially revolutionising industries, improving efficiency, and solving complex problems.
AI in Kenya has been steadily growing in recent years, with various initiatives and developments aimed at harnessing the potential of artificial intelligence to address local challenges and drive innovation. The healthcare sector is taking the lead in the adoption of this new technology.
From improving efficiency in diagnosis to predicting diseases and enhancing screening for non-communicable diseases like cancer, AI is slowly taking root in the sector. If well implemented, these actions will help increase access to care and ensure that diseases are caught early for timely interventions.
The adoption of electronic health records (EHR) at Aga Khan University Hospital, Nairobi has for example enabled it to start exploring various use cases of AI to optimise healthcare service delivery.
AI automation is being launched in areas such as medical imaging, clinical decision support systems, predictive analytics, and healthcare operations/administration.
For instance, AI tools are being used to analyze radiology images and suggest the level of treatment required to optimise clinical outcomes. Clinical decision support systems analyse data to assist healthcare providers in making evidence-based treatment decisions, while predictive analytics can predict patient outcomes and recommend personalised treatment plans.
Additionally, AI tools are being explored in automating repetitive tasks such as insurance claims processing and supply chain management.
Early detection of diseases via AI
In coming years, it is predicted that AI will play a critical role in the early diagnosis of non-communicable diseases like cancer, a major win in reducing related deaths. Collaborators from the University of Michigan and Aga Khan University, in a new paper in the journal Gut, propose that AI and machine learning could be deployed to address the continent’s emerging colorectal cancer (CRC) problem.
The team believes that Computer algorithms could examine population-level data to determine which patients are at the highest risk and should be prioritized for screening. Once screened, other algorithms designed for pattern recognition can quickly scan the images to identify abnormalities that warrant a closer inspection by trained pathologists.
The two universities were last October awarded a research grant of Sh112 million from the National Institutes of Health (NIH) to explore the transformative potential of Artificial Intelligence (AI) and machine learning technologies in the realm of colorectal cancer diagnosis.
Such tools are already being tested and have shown promise in the US and other high-income countries. But advancements in cloud computing, decreasing costs, the penetration of mobile phones, and other factors have primed parts of Africa for AI health applications—assuming, the authors caution, that a host of other challenges can be overcome.
AI in other key sectors
In Agriculture AI is being applied to improve crop yields, optimize resource usage, and provide farmers with valuable insights.
For example, AI-powered drones for precision application of fertilizer and pesticides in farms, detection of crop diseases, etc. On the other hand, AI is being integrated into financial systems to enhance fraud detection, credit scoring, and customer service.
It is refreshing to see the impact of AI in Education and Skills Development. Efforts are underway to explore the integration of AI into the education curriculum at various levels.
This is aimed at preparing the workforce for the AI-driven future and fostering innovation from a young age.
What more AI can do
At a time when we need to increase our efforts towards environmental conservation, AI can play a significant role in monitoring and preserving the environment by analysing satellite imagery to track deforestation, monitor wildlife populations, and detect illegal activities such as poaching and logging.
AI technologies such as image recognition and natural language processing can also be used to digitise and preserve cultural artifacts, historical documents, and indigenous languages.
In addition, AI can support rapid urbanization through smart city solutions to improve infrastructure, transportation, energy efficiency, and public safety. It can also enhance the tourist experience by personalizing travel recommendations, optimizing itinerary planning, and providing real-time language translation services.
AI can also offer great support to disaster Management and Response: AI-powered predictive modelling and risk analysis can improve disaster preparedness and response efforts by forecasting potential disasters and enabling proactive mitigation strategies.
Challenges to navigate
While AI in Kenya is still in its early stages compared to other developed economies, there is significant potential for growth and impact driven by a combination of government support, entrepreneurial activity, and a young tech-savvy population.
By fostering an enabling environment for AI innovation, Kenya can position itself as a leader in technology and drive economic growth and development for the benefit of its citizens.
However, as AI adoption grows, there is increasing awareness about the ethical implications of AI technologies.
One of the challenges facing AI adoption in Kenya is the availability and quality of data. Efforts are underway to improve data collection, management, and accessibility, including initiatives to digitise government records and promote open data policies.
Additionally, investments in broadband infrastructure are crucial to ensure reliable internet connectivity, which is essential for AI applications.
Discussions around data privacy, bias in algorithms, and ensuring AI benefits are inclusive and accessible to all segments of society are gaining traction.
Government legislation is also key in providing a regulatory framework for the adoption of Artificial Intelligence (AI).
On 17-18th April, the Aga Khan University is hosting a Digital Transformation in East Africa Conference in Nairobi, where Artificial Intelligence is one of the themes for the speakers to talk about in the context of Kenya and East Africa.
For registration, visit the event page (https://www.aku.edu/events/dtea/Pages/home.aspx).
Mr Khan and Mr Shikuku are the Global Chief Information Officer and the Regional ICT Director at the Aga Khan University, respectively.