Big Data for natural hazards: lessons from and for environments with low technical capacities
A small grant from Public Policy was provided to support this work by our Ïã¸ÛÁùºÏ²ÊÖÐÌØÍø community to enhance policy engagement and impact.
4 February 2020
±Ê°ù´Ç²ú±ô±ð³¾:ÌýThere is limited understanding of how big data and new technologies can improve our ability to detect emerging natural hazards (including human, animal and plant diseases) around the world.
±Ê°ù´ÇÂá±ð³¦³Ù:ÌýExploring the rapid expansion of data-driven machine learning models in the public sector in low data, low technical capacity zones through interviews with key practitioners and policymakers. A workshop with key decisionmakers to highlight the challenges and opportunities of public sector machine learning in different contexts.Ìý
Policy audience:ÌýThe Red Cross; Department for International Development; Government Office for Science; Government of Togo.Ìý
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