The role of Artificial Intelligence in Early Warning System for Violent Conflicts: Explores how technology can predict and prevent Violence, a cutting edge, and interdisciplinary angle

Abstract

This research paper as it is comprised of multiple tools and as the research shows AI system in multiple countries are settled down to assess and to prevent violent cases of conflict as hate speeches and other conflict oriented things. The mechanisms by which early warning systems (EWS) of violent conflict are evolving due to rising global unpredictability and digital connectivity are examined in this research. Conventional EWS, which typically uses human processing and historical data, is not working well. The present paper evaluates the potential of artificial intelligence (AI), particularly machine learning (ML), natural language processing (NLP), and geospatial intelligence (GEOINT), to improve forecasting, reduce false alarms, and facilitate prompt response. It does this by reviewing the literature in the fields of international relations, computational science, and peace studies.

By examining the cases of Kenya, Colombia, and Myanmar, the report highlights both the potential and the danger of implementing AI in politically unstable regions of the world. It offers the AI Conflict Risk Matrix (AICRM), a real-time solution that combines AI-based intelligence with dynamic and structural indicators. Digital governance, complex adaptive systems, and systems theory are the winning theoretical pillars. Despite AI's scale and adaptability, ethical concerns including data colonialism, algorithm bias, and militarism are raised. This article research paper which puts the ideas that multiple system country will have to adopt as this research refers that ethical tools of artificial intelligence guided with good and transparent governance system encircled with international security.

Keywords: Conflict Resolution, Artificial intelligence, Machine Learning, Early Warning Systems, International Security, Social and Digital Governance, Ethical Approved AI, Algorithm Biases.