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AI Use Case

Track and predict risk of likely criminal activity by individuals

Predict risk of illicit activity or terrorism using historical crime data, intelligence data and other available sources (e.g. predictive policing). Largely based on tracking network traffic, most obviously social media and telecoms activity, to predict likelihood and risk of potential terror-related criminal activity. The techniques will also reveal potential suspects. Similar techniques may be used to track other "undesirables" - including pro-democracy protesters in more repressive regimes.



Risk reduction - Predictive diagnosis

Case Studies

University of Southern California~University of Southern California researchers predict risk of violent protest with a Twitter-based model ,New York Police Department (NYPD)~The NYPD searched through surveillance footage using facial recognition ,Standard Cognition~Standard Cognition aims to predict and prevent shoplifting in supermarkets using machine vision,West Midlands Police~West Midlands Police anticipates violent crime with predictive policing using machine learning,World Bank~The World Bank is exploring using machine learning to analyse and improve public spending processes and find signals indicating potential corruption with Microsoft Research

Potential Vendors

IBM,Standard Cognition,Microsoft


Public And Social Sector


Data Sets

Structured / Semi-structured,Text,Images,Audio,Video,Time series

AI Technologies

ML Task - Prediction - Regression,ML Task - Grouping - Anomaly Detection,Machine Learning (ML)

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