Construct Validity in Automated Counter-Terrorism Analysis

Abstract

Abstract Governments and social scientists are increasingly developing machine learning methods to automate the process of identifying terrorists in real-time and predict future attacks. However, current operationalizations of ‘terrorist’ in artificial intelligence are difficult to justify given three issues that remain neglected: insufficient construct legitimacy, insufficient criterion validity, and insufficient construct validity. I conclude that machine learning methods should be at most used for the identification of singular individuals deemed terrorists and not for identifying possible terrorists from some more general class, nor to predict terrorist attacks more broadly, given intolerably high risks that result from such approaches.