Above photo credit: Glenna Gordon
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- Presentation slides
If you are interested in learning about other practical implementations, please review past webinars:
Lessons learned from practical implementations of AI in the international development sector, featuring CRS and Compassion International.
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.
For more information about AI in the Humanitarian Sector (benefits, challenges, and the path forward), please review this blog post
AI Suitability Toolkit, including a framework with 32 questions, to help you determine suitability of AI for humanitarian and international development programs.
DRC – additional resources:
IRC white paper: https://maxkasy.github.io/home/files/papers/RefugeesWork.pdf
About this webinar
In this webinar, you will have the opportunity to learn about two practical implementations of artificial intelligence/machine learning (AI/ML) in the humanitarian sector focused on displacement and meeting the needs of refugees.
Danish Refugee Council (DRC) is using AI/ML to forecast forced displacement initially in Afghanistan, Myanmar and West Africa, and is working to expand to cover all major and potential displacement crises. The Foresight tool uses open data from sources including UNHCR, the World Bank and NGO agencies to predict forced displacement in a given country over the next one to three years. The insights are used for strategic planning and operational preparedness, both within DRC and the wider humanitarian sector.
International Rescue Committee (IRC) is using AI/ML to facilitate jobs matching and optimize service delivery for Syrian refugees in Jordan. Project Match uses an adapted Thompson’s Algorithm to target different job seekers with the most impactful interventions. The matching algorithm, combined with cash support, increased employment by 7.9%, or 143 percentage points, compared to no intervention. The algorithm itself was responsible for 6.2% or 111 percentage points, of that gain.
For more information about AI in the humanitarian sector, including some of the most promising use cases, read this blog post.
Leila Toplic, Lead for Emerging Technologies Initiative, NetHope
Alexander Kjærum, Global Advisor, Senior Analyst at the Danish Refugee Council
Grant Gordon, former Senior Director of Innovation Strategy at the International Rescue Committee