The early warning/early action (EWEA) community has been working for decades on analytics to help prevent conflict. The field has evolved significantly since its inception in the 1970s and 80s. The systems have served with variable success to predict conflict trends, alert communities to risk, inform decision makers, provide inputs to action strategies, and initiate a response to violent conflict. Present systems must now address the increasingly complex and protracted nature of conflicts in which factors previously considered peripheral have become core elements in conflict dynamics.
Topic:
Science and Technology, Conflict, Risk, and Early Warning
The complex crises in our world—from rising instability linked to pandemic effects and climate change, to ongoing challenges of civil war, urban violence, violent extremism—require complex analysis and insights. Emerging technologies, data, and data science methods have been recognized as potential tools to help tackle some of these “wicked” problems across the humanitarian-development-peace nexus. Artificial intelligence (AI) and machine learning (ML) potentially open a range of new opportunities for early warning and humanitarian preparedness, assessment and monitoring, service delivery, and operational and organizational efficiency. Advanced data analysis is the core of these efforts, and its success often depends on timely access, as well as the right quality and quantity of data.
Topic:
Science and Technology, Artificial Intelligence, Data, Machine Learning, and Peacebuilding