Project presentation
Recent advances in technology have endowed governments with new repressive tools and even the ability to anticipate citizen action and engage in preemptive response. The Machine Learning for Peace Project (MLP) aims to level the playing field by equipping policymakers and civil society actors working to defend democracy with new tools to navigate increasingly sophisticated approaches to repression. MLP provides policymakers and practitioners with high-frequency, up-to-date data on the occurrence of 32 types of important political events in more than 35 countries around the world. Furthermore, these data are combined with machine learning tools to generate monthly forecasts of future changes in political conditions.
A website allows users to interact with these data and view monthly forecasts about future events that can be used to anticipate and plan for changing political conditions.
Surveying 70 NGOs in 19 countries, 80% indicated forecasts were useful to their organization.
A website allows users to interact with these data and view monthly forecasts about future events that can be used to anticipate and plan for changing political conditions.
Organization presentation
DevLab@Penn is an applied learning environment that connects academic researchers with development practitioners to design impactful programming informed by cutting-edge evidence, evaluate development projects, and produce research with actionable insights. Under the USAID-funded INSPIRES consortium, DevLab’s Machine Learning for Peace (MLP) project leverages big data and new technologies to develop research and online tools to bolster civil societies in more than 40 countries around the world.Impact
The project forecasts political events in 42 countries using data from 70M news articles in 23 languages to help policymakers and practitioners anticipate and plan for changing political conditions.Surveying 70 NGOs in 19 countries, 80% indicated forecasts were useful to their organization.
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