Access to digital information is a driver of economic development. But although 85% of sub-Saharan Africa's population is covered by mobile broadband signal, only 37% use the internet, and those who do seldom use the web. We investigate whether AI can bridge this gap by analyzing how 469 teachers use an AI chatbot in Sierra Leone. The chatbot, accessible via a common messaging app, is compared against traditional web search. Teachers use AI more frequently than web search for teaching assistance. Data cost is the most frequently cited reason for low internet usage across Africa. The average web search result consumes 3,107 times more data than an AI response, making AI 87% less expensive than web search. Additionally, only 2% of results for corresponding web searches contain content from Sierra Leone. In blinded evaluations, an independent sample of teachers rate AI responses as more relevant, helpful, and correct than web search results. These findings suggest that AI-driven solutions can cost-effectively bridge information gaps in low-connectivity regions.

We study the problem of allocating limited supply of medical resources in developing countries, in particular, Sierra Leone. We address this problem by combining machine learning (to predict demand) with optimization (to optimize allocations). A key challenge is the need to align the loss function used to train the machine learning model with the decision loss associated with the downstream optimization problem. Traditional solutions have limited flexibility in the model architecture and scale poorly to large datasets. We propose a decision-aware learning algorithm that uses a novel Taylor expansion of the optimal decision loss to derive the machine learning loss. Importantly, our approach only requires a simple re-weighting of the training data, ensuring it is both flexible and scalable, e.g., we incorporate it into a random forest trained using a multitask learning framework. We apply our framework to optimize the distribution of essential medicines in collaboration with policymakers in Sierra Leone; highly uncertain demand and limited budgets currently result in excessive unmet demand. Out-of-sample results demonstrate that our end-to-end approach can significantly reduce unmet demand across 1040 health facilities throughout Sierra Leone.

Decades ago, a civil war in Sierra Leone left thousands as amputees. Researcher and current Education Minister David Moinina Sengeh set out to help them with a more comfortable socket for prostheses. David Moinina Sengeh is a biomechatronics engineer and the current Minister of Education and Chief Innovation Officer in his home country of Sierra Leone. He pioneered a new system for creating prosthetic sockets, which fit a prosthetic leg onto a patient's residual limb. Using multiple technologies, Sengeh created sockets that are far more comfortable than traditional ones, and can be produced cheaply and quickly.

Sierra Leone's minister of education and chief innovation officer David Moinina Sengeh is a man of many talents. He's using mobile phone technology to improve daily life, he invented a way to make a prosthetic limb with a computer-assisted technique and he's a singer and rapper and a clothing designer, too. Sierra Leone's minister of education and chief innovation officer David Moinina Sengeh is a man of many talents. He's using mobile phone technology to improve daily life, he invented a way to make a prosthetic limb with a computer-assisted technique and he's a singer and rapper and a clothing designer, too. David Moinina Sengeh is not your typical education minister.

The AI Career Fair Night will be held on the evening of December 1, 2019 in Freetown, Sierra Leone. The event will feature different job opportunities across machine learning, data engineering, data visualization, and data architects. During the event, participants could attend professional lectures on career-related topics. In the Mentor Corner, participants could seek guidance on career development issues, from developing professional competencies to job interviewing. Our mentors included HR professionals, data analysts and executives.

Landslides have caused more than 11,500 fatalities in 70 countries between 2007-2010. Over 1000 people were victims of a landslide that hit Sierra Leone in August 2017. The situation is getting worse as the volume and intensity of rainfall in West Africa is increasing. In April, Colombia's landslide left at least 254 dead and hundreds missing. Landslides are challenging across various levels, for example: social, economic, infrastructural, and environmental.

A two-person team from the UNICEF's Office of Innovation in New York recently joined DSTI in Sierra Leone to collaborate on a Machine Learning "Hackathon" As part of efforts to develop the technology and innovation ecosystem to support development of Sierra Leone, UNICEF is collaborating with the Directorate of Science, Technology and Innovation (DSTI) in the Office of the President, on a knowledge exchange partnership, around innovative Machine Learning techniques which, it is hoped, will add value to Government's work around data for decision making in the country. A two-person team from the UNICEF's Office of Innovation in New York recently joined DSTI in Sierra Leone to collaborate on a Machine Learning "Hackathon" to work on data from the education sector in support of the Government's Free Quality School Education initiative. Officials from different Government Ministries, Departments and Agencies joined the team to enhance their knowledge of Machine Learning and advanced data analysis techniques, for use in their own areas of government. Shane O'Connor, Technology for Development Specialist at UNICEF Sierra Leone, stated that the opportunity afforded by this collaboration is huge. "With the President's establishment of the DSTI and with UNICEF's collaboration, there really is great potential for a step change in how Technology and Innovation can be leveraged to deliver for Sierra Leone," he said.