Using Agent Based Modelling to Advance Evaluation Research in Radicalization and Recruitment to Terrorism: Prospects and Problems

Our paper argues that Agent Based Modelling (ABM) can play an important role in evaluating interventions for counter radicalization and recruitment. Its advantages are due to three realities of research and practice in this area of study. First, field research on radicalization and recruitment raises significant ethical and human subjects dilemmas beyond traditional criminological and social research that are not present to the same degree in ABM experiments. Second, given the lack of existing studies and especially existing evaluation studies, ABMs provide a mechanism for identifying which programs or practices should be focused upon in field experiments, thus allowing researchers to focus in on interventions which have most promise of success. Third, ABM allows researchers to examine very large populations of individuals, which can solve the base rate problem for evaluating interventions focused on rare events, for example on recruitment to terrorism or terrorist attacks. We illustrate these advantages of ABM studies for assessing programs and policies in the context of an ABM model developed in Proton (an Horizon 2020 project). We focus in particular on how ABMs can be developed in ways that provide valid outcome results. In this context, we emphasize the importance of a strong theoretical foundation for ABM studies, creating a realistic landscape with actual data, and testing the ABM model for its fit to outcomes in the real world.