Learning from Foes: How Racially and Ethnically Motivated Violent Extremists Embrace and Mimic Islamic State's Use of Emerging Technologies

By Yannick Veilleux-Lepage, Chelsea Daymon and Emil Archambault

  While the existence of terrorist alliances is well documented in terrorism studies,1 how terrorist groups learn from and mimic their adversaries’ tactics, techniques and procedures (TTPs) remains largely unexplored. Building on existing terrorist innovation literature, this report introduces a framework to understand what factors can propel or hinder a terrorist group’s adoption of new TTPs. Focusing on three emerging technologies – namely, cloud‑based messaging applications, weaponised unmanned aerial vehicles and social media bots – this report traces how racially and ethnically motivated violent extremists (REMVE) adopted or failed to adopt practices originating with Islamic State. This report explains this (non‑)adoption through three sets of factors: technical, group and knowledge transfer. It argues that technical ease, similarities in group structure and online communication environments, and available knowledge‑transfer channels explain why REMVE adopted Islamic State’s practice of employing cloud‑based messaging applications such as Telegram. Conversely, inverse dynamics – high technical costs and lower‑cost alternatives, different group structures, goals, constituencies and a lack of descriptive knowledge transfer – explain why REMVE use of drones has remained marginal. Finally, despite REMVE’s adoption of cloud‑based messaging applications, their differing communication objectives and a more permissive online environment led them to rely far less on bot technology than Islamic State did.  

London:  The Global Network on Extremism and Technology (GNET) 2022. 35p.