Building a network of excellence in artificial intelligence in Sub-Saharan Africa
Programs and partnerships
Artificial Intelligence (AI) has the potential to alter our world and to advance human development, with dramatic implications across every sector of society.Read more
Artificial Intelligence (AI) has the potential to alter our world and to advance human development, with dramatic implications across every sector of society. According to some estimates, AI could provide a 15.7 trillion-dollar boost to the world’s GDP by 2030 and is already bringing major advancements to the way we learn, conduct business, and monitor our health. For example, mobile AI health applications could deliver the kind of quality health care diagnosis usually reserved for the rich to remote locations at very low costs. It could also advance quality education with highly personalized teaching programs for all ages across the world.
At the same time, the indiscriminate dissemination of AI applications could also exacerbate inequalities. As AI applications spread rapidly across sectors and around the globe, more research is required to better understand how AI applications impact human development. To enhance the economic and social prospects of people in the global South, it is critical to support knowledge, skills development, and the institutions to responsibly implement and govern these technologies. To this end, IDRC is investing and co-designing a range of AI for development initiatives, focusing on innovations, foundations and governance. These initiatives will support relevant research, develop AI applications that are inclusive, ethical, and rights-based, and strengthen and create appropriate capacity building programs.
The main purpose of the AI for Development (AI4D) Africa project is to support the development of a network of excellence in AI in sub-Saharan Africa to strengthen and develop community scientific and technological excellence in a range of AI-related issue areas. AI4D Africa is aiming to undertake four interrelated activities, including: 1) Develop a network of institutions and individuals working on and researching AI from across sub-Saharan Africa, via workshops and consultations; 2) Deliver an AI research agenda with a focus on ethical, legal, and social aspects of AI research; 3) Generate an AI capacity building agenda via a survey of universities; and 4) Issue a call for at least ten multidisciplinary innovation projects within and outside the network, exploring local frontiers of research in AI.
AI4D Africa will run for 18 months and result in the establishment of the network, a research “roadmap”, a portfolio of innovation projects, and recommendations for capacity building for ethical and locally relevant AI research around the African continent.
The goal is to reduce mortality rates related to malaria, particularly in marginalised communities. Several Artificial Intelligence (AI) techniques have been used to solve challenges in the existing malaria diagnosis tools. The presentation summarizes the project, which has collected a dataset of 10,000 blood sample images (stained blood smear). Using the data, an open-source annotation tool was created. Working with the AI4D (Artificial Intelligence for Development) the final aim is to develop a mobile application that will assist lab technologists in malaria diagnosis.
The presentation shows the competition overview (marketing and communication; and competition engagement) for the AI4D - African Language Dataset Challenge, an effort to incentivize the creation, organization and discovery of African language datasets through a competitive challenge. Hundreds of thousands of page views for the challenge are noted.
The report provides a summary of project activities, milestones, achievements, outcomes and outputs. The project drew from the Global South ecosystem mapping, and facilitated a bottom-up network/community of researchers who investigated and provided recommendations on how future artificial intelligence for development (AI4D) networks’ research should be shaped. The project acknowledges the growing importance of funding Networks and domain-specific research relevant to African researchers and practitioners, with a focus on the ethical, legal and social aspects of AI research. One of the major results works towards addressing language barriers through machine translation.
The study explores the use of wearable devices for ambulatory blood pressure data collection, for use in blood pressure prediction/forecasting using Long Short Term Memory (LSTM) recurrent neural networks (RNN) on mobile devices. A mobile app was developed (wearable as a smart watch) during this first phase. LSTM Network is an advanced RNN, a sequential network that allows information to persist, meaning that it has the capacity to handle the vanishing gradient problem faced by RNN. [See also https://www.k4all.org/wp-content/uploads/2019/07/Early-detection-of-pre…]