UoN hosts Workshop on AI in Education and Science
The Faculty of Science and Technology in collaboration with the University of Linköping organized a comprehensive two-day event on March 6th and 7th focused on the theme "AI in Education and Science: Applications and Challenges." The hybrid event combined a webinar on the first day with hands-on practical sessions on the second, bringing together local experts from Kenya and international partners from Linköping University in Sweden to explore artificial intelligence's transformative potential in educational and scientific contexts.
Prof. Kerubo, Dean of the Faculty, opened the workshop by highlighting the faculty's significant presence at the university, housing all basic science departments with approximately 5,700 students and 300 staff members. She emphasized that AI is no longer just a buzzword but "a transformative force reshaping various sectors" and announced two major initiatives: the upcoming launch of the Nairobi School of AI and a new MSc in AI curriculum developed by the Department of Computing and Informatics, scheduled to begin in the 2025-2026 academic year
The first day's discussions centered on the evolving landscape of AI in Africa, with a particular focus on Kenyan applications and challenges. Prof. Miriti from UoN demonstrated Kenya's progress in developing homegrown AI solutions for crop monitoring and for cancer screening, while identifying barriers including underrepresentation of African talent and insufficient local data resources. The University of Johannesburg presentation addressed the distinction between discriminative and generative AI approaches, emphasizing the importance of selecting appropriate methods for specific problems. Linköping University's KenSwed project showcased how AI can democratize education by enabling creation of localized vocational training content for underserved populations. Key recommendations included increasing AI education investment, establishing data-sharing frameworks, and enhancing cross-institutional collaboration to develop Africa-specific AI solutions.
The heart of the workshop featured a series of research presentations, showcasing the latest advancements in conservation science: The workshop delved into cutting-edge applications of AI in conservation biology, featuring presentations from both Kenyan and Swedish researchers. The sessions showcased innovative techniques for wildlife monitoring, including advanced methods for detecting elephant movements through footstep identification and audio recognition of trumpeting calls. Researchers from Linköping University demonstrated sophisticated systems for collecting environmental sound and vibration data in savannah ecosystems, providing unprecedented insights into animal behavior patterns and habitat utilization. A particularly notable presentation featured AI-powered classification of individual leopards, highlighting the potential for non-invasive population monitoring of endangered species.
During the conservation discussions, Chair of the Department of Biology Prof. Catherine Lukhoba briefly spoke about the Ngulia Project, highlighting its significance in wildlife conservation across different parts of Kenya. She explained that the project plays a crucial role in monitoring wildlife in parks, providing valuable insights into the status of animal populations, particularly for iconic species such as lions, elephants, and rhinos that face increasing threats and are becoming endangered. Prof. Lukhoba emphasized that while conservation is fundamentally science-based, technology such as AI and advanced monitoring systems can significantly improve efforts to protect wildlife, underscoring that science and technology must work together to drive conservation initiatives forward.
The workshop further explored practical applications of smart camera technology and Bluetooth scanning systems for tracking mammals, with MSc students presenting functioning prototypes developed for field deployment. Throughout the workshop, participants engaged with actual datasets and tools, gaining hands-on experience with techniques that significantly reduce traditional data collection times while dramatically increasing accuracy. The collaborative nature of the research presented underscored the growing importance of transnational partnerships in developing conservation technologies specifically calibrated for African ecological contexts, addressing local challenges while building indigenous scientific capacity.
The two-day event highlighted both the potential and challenges of AI applications in education and science, particularly in the Kenyan context. While significant obstacles remain, including data availability and skills gaps, the collaboration between the University of Nairobi and international partners like Linköping University demonstrates a path forward for developing locally relevant AI solutions.
The collaborative event highlighted both opportunities and challenges in implementing AI solutions in Kenya and broader African contexts, with key recommendations including increased AI education investment, establishing data-sharing frameworks, and enhancing cross-institutional collaboration to develop Africa-specific AI solutions.
