Predicting Terrorism: Implications for Big Data in Public Safety
In the domain of counterterrorism, predictive technologies take many forms. Twitter, one of the social media platforms that has been most utilized by terrorist recruiters, has developed an algorithm to determine which of its users could be likely to join a terrorist organization.[iii] But the use of these predictive technologies do not begin and end with Internet media platforms; financial institutions have also been using artificial intelligence to better track terrorist activities by discerning abnormalities outside the range of normal bank transactions.[iv]
Predictive technologies have also assisted law enforcement to better prepare for incidences of terrorism. Most prominent among these technologies is Dfuze, a program designed by ISS Global to help identify where terrorist attacks are most likely to occur.[v] The technology aggregates data from past incidents and helps law enforcement better predict attacks and augment security at potential “hot spots.”[vi] While this technology is not foolproof, it saves law enforcement hours of wading through countless pages of data and allows for better allocation of resources.