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 UCL community to enhance policy engagement and impact.
4 February 2020
Problem: There 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.
Project: Exploring 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.
Policy audience: The Red Cross; Department for International Development; Government Office for Science; Government of Togo.