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While the application of Artificial Intelligence / Machine Learning (AI/ML) is still very nascent in the international development sector, the time is now to learn from early practical implementations, and reuse and scale what works. In this session, you'll have the opportunity to hear from two NetHope members about how they’re using AI/ML in their work, including lessons learned across all stages of the process—including how to frame a problem for AI; how to get your data in order; how to resource teams; and how to put the right processes in place.
- Catholic Relief Services: The Measurement Indicators for Resilience Analysis (MIRA) is a resilience measurement protocol that employs machine learning to gain a better understanding of resilience in rural areas in Malawi. It uses two machine learning algorithms (K Nearest Neighbor [KNN] and the Least Absolute Shrinkage and Selection Operator [LASSO]) that rely on data about shocks (e.g. natural disasters, crop destruction due to crop pests), household characteristics, and food security to predict household vulnerability. This solution is being used to improve and refine CRS' resilience programming in Malawi.
- Compassion International is exploring the use of ML to track the progress and effectiveness of their anti-poverty programs and interventions. In this webinar, Compassion will specifically discuss the algorithms to identify features in the satellite imagery that are indicative of economic activity. This method to of poverty estimation and mapping has the potential to be faster than traditional household surveys, low-cost, and offer high scalability. The solution is currently being implemented in the AWS SageMaker environment and it will be tested in South America this spring.
Please review these resources before attending this webinar:
If you are interested in learning about other practical implementations, please review past webinars:
- Lessons learned from practical implementations of AI in field programs and internal operations, featuring Plan International and The Carter Center.
- Lessons learned from practical implementations of AI in conservation contexts, featuring The Nature Conservancy and Carnegie Mellon University.
If you have a practical implementation of AI that you would like to share, please contact Leila Toplic.
Leila Toplic, Lead for Emerging Technologies Initiative, NetHope
James Campbell, Regional Technical Advisor for Monitoring, Evaluation, Accountability and Learning for Southern Africa, Catholic Relief Services
Dr. Filip Ponulak, Director of Data Science, Compassion International