Nethope Logo

Start:

March 31, 2020 11:00am
U.S. Eastern Time

End:

March 31, 2020 12:00pm
U.S. Eastern Time

Provided by:

NetHope's Emerging Technologies Initiative

Lessons Learned From Practical Implementations of AI/ML in the International Development Sector

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.


View the Recording

Presentation Materials Shared

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:

If you have a practical implementation of AI that you would like to share, please contact Leila Toplic.

Host

Leila Toplic

Lead for Emerging Technologies Initiative
NetHope

Speakers

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

Twitter @NetHope_orgFacebook NetHopeorgYouTube iconLinkedIn Company NetHopeInstagram nethope_org
crossmenu