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Over the past decade, two major phenomena have developed in the digital realm. On the one hand, extremism has grown massively on the Internet, with sprawling online ecosystems hosting a wide range of radical subcultures and communities associated with both ‘stochastic terrorism’ and the ‘mainstreaming of extremism’. On the other hand, Artificial Intelligence (AI) has undergone exponential improvement: from ChatGPT to video deepfakes, from autonomous vehicles to face-recognition CCTV systems, an array of AI technologies has abruptly entered our everyday lives. This report examines ‘AI extremism’, the toxic encounter of these two evolutions – each worrying in its own right. Like past technological progress, AI will indeed be – in fact already is – used in various ways to bolster extremist agendas. Identifying the many opportunities for action that come with a range of AI models, and linking them with different types of extremist actors, we offer a clear overview of the numerous facets of AI extremism. Building on the nascent academic and government literature on the issue as well as on our own empirical and theoretical work, we provide new typologies and concepts to help us organize our understanding of AI extremism, systematically chart its instantiations, and highlight thinking points for stakeholders in countering violent extremism.

The report begins by outlining some of the broad knowledge around the idea of mass persuasion, before focusing specifically on lessons that have been learned in the field of P/CVE. This is followed by a synthesis of existing “How To” guides for the creation of strategic communications from a range of policy and practitioner stakeholders. Then, we discuss specific knowledge of audiovisual content, particularly considerations for short-form video content. The report concludes by outlining how stakeholders, including social media platforms, can monitor, measure, and evaluate the impact of this type of content.

Exposure to radicalizing information has been associated with support for violent extremism. It is, however, unclear whether specific information use behavior, namely, a distinct pattern of incidental exposure (IE) to and active selection (AS) of radicalizing content, indicates stronger violent extremist attitudes and radical action intentions. Drawing on a representative general population sample (N = 1509) and applying latent class analysis, we addressed this gap in the literature. Results highlighted six types of information use behavior. The largest group of participants reported a near to zero probability of both IE to and AS of radicalizing material. Two groups of participants were characterized by high or moderate probabilities of incidental exposure as well as a low probability of active selection of radicalizing content. The remaining groups displayed either low, moderate, or high probabilities of both IE and AS. Importantly, we showed between-group differences regarding violent extremist attitudes and radical behavioral intentions. Individuals reporting near zero or high probabilities for both IE to and AS of radicalizing information expressed the lowest and strongest violent extremist attitudes and willingness to use violence respectively. Groups defined by even moderate probabilities of AS endorsed violent extremism more strongly than those for which the probability for incidental exposure was moderate or high but AS of radicalizing content was unlikely.

VOX-Pol’s new report presents findings from the REASSURE (Researcher, Security, Safety, and Resilience) project’s in-depth interviews with 39 online extremism and terrorism researchers. Based at universities, research institutes, and think tanks in Europe and North America, the interviewees studied mainly, albeit not exclusively, far-right and violent jihadist online activity. The report catalogues for the first time the range of harms they have experienced, the lack of formalised systems of care or training, and their reliance therefore on informal support networks to mitigate those harms.

Much qualitative research has drawn an association between social media and domestic terrorism, with the studies reaching different conclusions. However, few empirical studies have evaluated whether the surge in social media participation affects domestic terrorist events. Controlling for common explanations in the literature, we conduct a cross-national, time-series analysis of up to 151 countries from 2000 to 2019 to assess the impact of social media penetration on domestic terrorism. We find that greater social media penetration increases the likelihood of domestic terrorism in countries as it supports extremists’ ability to recruit, mobilize, and train terrorists. Using mediation analysis, we also find that greater social media penetration amplifies online and political polarization, increasing the likelihood of domestic terrorism events. Our work indicates the possible mechanisms linking social media and domestic terrorism and the need to develop and apply appropriate counterterrorism strategies to mitigate terrorist operations.

Due to recent rises in extremism across the globe (Dean et al. in J Polic Intell Count Terror 11:121–142, 2016; Le Roux in Responding to the rise in violent extremism in the Sahel. Africa Center For Strategic Studies, 2019, p. 26) and (Jones in Int Secur 32:7–40, 2008), governments and law enforcement organisations, such as the police, have looked to new strategies to counter violent extremism (Russell and Theodosiou in Counter-extremism: a decade on from 7/7. Quilliam Foundation, 2015). Specifically, there has been an expanse of the field now widely known as Countering Violent Extremism (CVE). CVE is a highly contested area; however, upon conducting a literature review, Inserra (Revisiting efforts to counter violent extremism: leadership needed. The Heritage Foundation, 2015, p. 2) helpfully reduced the term CVE down to descriptions of interventions intended to “stop individuals from radicalizing”. LaFree and Freilich (Annu Rev Criminol 2:383–404, 2019) distinguish counter-terrorism from CVE, they describe counter-terrorism as military responses (‘hard’) as opposed to non-military responses (‘soft’), referred to as countering violent extremism strategies. This chapter contends that, although counter narratives tend to lack academic standing, there does appear to be a widespread acceptance that narratives influence individuals’ beliefs. Therefore, in the absence of other more effective methods of CVE online, it is argued that counter-narratives (CN) should be used in informed ways by organisations such as the police (Monaghan in Crime Media Cult 18(1):21–39, 2020). This chapter will compare academic understandings of narrative and communication alongside examples of counter narratives issued against them. It will then assess the impact of such strategies and potential alternatives for CN.