Predictive Analytics for Peace

Conflicts rarely emerge without warning—the challenge lies in detecting early signals amidst the noise. Our research pioneers data-driven approaches to conflict prevention, developing sophisticated early warning systems that integrate diverse data sources from social media sentiment to economic indicators. By identifying patterns that precede escalation, we enable peace practitioners and policymakers to intervene early with targeted, evidence-based responses that can prevent violence before it begins.

Overview

Conflicts rarely emerge without warning. Our research develops sophisticated analytical tools that can identify early indicators of rising tensions, enabling preventive action before situations escalate into violence. By integrating diverse data sources—from social media sentiment to economic indicators to satellite imagery—we create comprehensive early warning systems. Critically, we ensure these tools are developed with strong ethical frameworks, respecting privacy and avoiding surveillance overreach while still providing actionable intelligence for peace practitioners.

Research Focus Areas

Conflict Early Warning Systems

Multi-source monitoring systems that identify emerging risks before escalation.

Risk Assessment Models

Predictive models that assess vulnerability and likelihood of conflict in different contexts.

Data Integration Frameworks

Methods for combining diverse data sources while maintaining quality and ethics.

Ethical AI for Sensitive Contexts

Ensuring predictive tools respect privacy and human rights in conflict-affected areas.