Understanding Patterns of Terrorism in India Using AI Machine Learning

Abstract

Terrorism represents an undesirable but seemingly inevitable part of the modern social landscape, and understanding terrorism dynamics can provide useful insights for developing governance structures and policies that are both more effective at reducing violence and less invasive on general society. With the tremendous increases that are happening in Artificial Intelligence capabilities in computing technology, application of AI technologies to terrorist data can yield useful insights regarding the interaction of terrorists, governance and society. Generally, there have been few applications of machine learning techniques to understanding patterns of terrorist behavior. Specifically, little work has been done to use AI to analyze terrorism patterns in India, which experiences among the world’s highest levels of terrorism. Using the Global Terrorism Database and the South Asian Terrorism Portal we apply “shallow machine learning models” that require only a modest amount of data to train themselves and can facilitate our exploration of three questions crucial to understanding the complex dynamics of terrorism, state and society: From a description of the attack can we figure out who the likely terrorist group is? Can we predict the likely location for next attack from a history of past attacks? Can we identify the principal factors that cause a city to be targeted? We believe that this project will: provide an example of socially-relevant AI research; expand our understanding of the factors that shape counterterrorism policy, and contribute to our greater recognition of the interwoven relationship of technology, knowledge and society.

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2019 Special Focus: The Social Impact of AI: Policies and New Governance Models for Social Change

KEYWORDS

Terrorism, Artificial Intelligence, India, Machine Learning, Security Policy

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