Can Machine Learning Predict A Revolution? | Philip Schrodt | Wondros Podcast Ep 188
Originally aired on Jan 25, 2023
Jesse and Priscilla discuss using machine learning to forecast conflict and social uprisings with Philip Schrodt, mathematician and senior research political scientist of the statistical consulting firm Parus Analytical Systems. Philip explains the inherent complexity of political systems and the challenges of predicting significant events.
Can using machine learning help to predict political unrest and revolution?
- Philip Schrodt became interested in predicting significant events during his joint degree in mathematics and political science.
- The study of political systems is complex and requires input from various fields.
- Machine learning can help identify patterns and possible triggers for political unrest.
- Predicting significant events is challenging due to the dynamic nature of politics and the emergence of unexpected factors.
- The application of machine learning to predicting significant events is still in the early stages and requires further development.
- Policymakers can use machine learning techniques to better anticipate and prepare for potential crises.
- Machine learning can help inform decision-making and guide resource allocation to areas most at risk of political unrest.