The Machine Learning for Peace (MLP) project is supported by USAID’s Center for Democracy, Human Rights, and Governance and the Enabling and Protecting Civic Space (EPCS) Illuminating New Solutions and Programmatic Innovations for Resilient Spaces (INSPIRES), a seven-member consortium led by Internews. Through this activity and many others, INSPIRES is increasing the knowledge and capacity of citizens, organizations, the media, and donors, to quickly respond to growing restrictions on democratic freedoms of association, assembly, and expression. The MLP launch event took place on December 15, 2021 as part of the Open Government Partnership Global Summit and included representatives from the United States Agency for International Development and the International Center for Not-for-Profit Law.
Civic spaces can serve as a barometer of political health. Policymakers and other stakeholders in civil society, philanthropy, and foreign aid need accurate analysis of the civic spaces around the globe in order to know what locations need help. The MLP is a new interactive online tool to address shrinking civic space and growing authoritarianism around the world. With the help of recent developments in big data and machine learning, the MLP tool provides up-to-date data on recent and historical trends in civic space as well as forecasts about how conditions are likely to change in the near future. To do this, we continuously scrape and process tens of millions of articles published by more than 215 regional and domestic news sources in more than 30 languages.
MLP data are available for the following countries: Albania, Angola, Armenia, Bangladesh, Benin, Cambodia, Cameroon, Colombia, Democratic Republic of Congo, Ecuador, El Salvador, Ethiopia, Georgia, Ghana, Guatemala, Honduras, Hungary, Indonesia, Jamaica, Kenya, Kosovo, Malawi, Malaysia, Mali, Mauritania, Morocco, Nicaragua, Niger, Nigeria, Paraguay, Philippines, Rwanda, Senegal, Serbia, South Africa, Sri Lanka, Tanzania, Tunisia, Turkey, Uganda, Ukraine, Uzbekistan, Zambia, and Zimbabwe.
MLP’s data and forecasts on changing civic space have informed rapid response programming to address urgent threats under the INSPIRES project. Recently, INSPIRES incorporated insights from MLP’s forecasts into the allocation of FRF activities. The INSPIRES consortium has also disseminated MLP to a broad network of partners through a publicly accessible website with interactive data dashboards; in a survey of these actors, more than 80% reported that they are likely to use MLP to inform programming and communicate with stakeholders.
Paris Peace Forum. (2022, November 11-12). Machine Learning for Peace at the Paris Peace Forum.
Open Government Partnership Global Summit. (2021, December). Machine Learning for Peace: tracking civic spaces around the globe [Video]. YouTube. https://www.youtube.com/watch?v=0M4qblnYmHc
Catalyst Balkans. Using Big Data and Machine Learning to Better Understand Civic Space [Video]. YouTube. https://www.youtube.com/watch?v=8xt9oeajlhY
2022 Global Digital Development Forum (2022, May). Machine Learning for Peace: Forecasting Civic Space to Defend Democracy [Video]. YouTube. https://www.youtube.com/watch?v=vAZ2iUT_8bk