Food security and AI: From data collection to early warning systems

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Characterizing the socio-economic status of populations and providing reliable, up-to-date estimates of who the most vulnerable are, how many of them there are, where they reside, and why they are vulnerable, is essential for governments and humanitarian organizations to make informed and timely decisions regarding the implementation of humanitarian assistance policies and programs. Anticipatory and preventive actions have been demonstrated to yield significant benefits compared to post-disaster and post-shock aid. It is, therefore, crucial to understand the drivers of food insecurity in a context where extreme weather events play an increasingly significant role in exacerbating already critical situations. The work of WFP’s Hunger Monitoring Unit revolves around collecting reliable food security data, which is then analyzed in conjunction with climate, economic, and conflict data to support early warning systems, including the use of machine learning.

This live event includes a 15-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions, interact with the panelists and participants and build connections with the AI for Good community.

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* Register (or log in) to the AI4G Neural Network to add this session to your agenda or watch the replay
Start date
11 October 2023 at 17:00 CEST Geneva | 11:00-12:15 EDT, New York | 23:00-00:15 CST, Beijing
End date
11 October 2023 at 18:15 CEST Geneva | 11:00-12:15 EDT, New York | 23:00-00:15 CST, Beijing
Duration
75 minutes (including 15 minutes networking)
Programme stream
- Discovery - AI for Earth and Sustainability Science
Topics
- Data
  Food
UN SDGs
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Food security and AI: From data collection to early warning systems