ALBERT

Description: While much time and effort in terrorism studies has gone into finding an answer to the question of why people radicalise, the question of how to rehabilitate individuals has received renewed attention with the return of many citizens who had joined the Islamic State. This has led to an increase in both programs and interventions aimed at ‘deradicalising’ or ‘disengaging’ individuals as well as studies that aim to assess the effectiveness of such efforts. This article/presentation provides an overview of the main elements of rehabilitation and reintegration programs for violent extremist offenders based on international research assessing 34 rehabilitation and reintegration programs. In the second half of the article, an evaluation of the Dutch approach to reintegrating violent extremist offenders in and after prison is presented. Finally, the main lessons learned from these programs as well as the academic literature are discussed.

Description: Many existing programs for countering violent extremism focus on either end of the radicalization spectrum. On one hand are prevention programs aimed at deterring individuals from starting down the path to violent extremism. On the other hand are disengagement/de-radicalization programs designed for assisting individuals who have been fully radicalized. Conspicuously absent are programs for those who fall in-between, into what might be referred to as the pre-criminal space: individuals who have begun to exhibit signs of radicalization, but for whom radicalization is not yet complete. The British Columbia Shift (BC Shift) initiative was created to assist individuals determined to be in this pre-criminal space; that is, those deemed to be in danger of radicalizing. The goal of BC Shift is to stop individuals from traveling further down the path of radicalization, and, ideally, to turn individuals away from the path. BC Shift operates as a navigational model, connecting at-risk individuals with services and supports in the community. BC Shift is a government initiative supported by the Canada Centre for Community Engagement and Prevention of Violence. It is a civilian organization that partners very closely with, but is separate from, law enforcement. In addition to its primary CRVE mandate, BC Shift has rapidly evolved and expanded into several other responsibilities, including coordination on national CVE standards; liaising with other CVE programs across Canada; maintaining stakeholder relationships; and helping create capacity through dialog and training. Although the program only began accepting referrals in 2019, its operation has already revealed many important lessons for CRVE programs. First, it is critically important to have the right people in the room. There has to be buy-in from the highest levels of partner agencies and stakeholders, particularly early on. Second, programs of this sort should leverage existing resources wherever possible. BC Shift has been lucky enough to coordinate with situation tables, such as the CHART program in Surrey. There are already many organizations doing excellent work in their respective communities; it is very helpful to plug into those resources. Third, even though BC Shift operates as a navigational hub, it has benefitted greatly from having a social worker as part of the team. This skill set is important in helping referred individuals feel comfortable with the process of accessing services and supports. Finally, marketing matters! CRVE programs such as BC Shift have to navigate a complex reality. The very concept of violent extremism is disconcerting to a lot of people in the community; these fears have to be addressed, and difficulties related to differences in perspective and language have to be overcome. BC Shift’s first year-and-a-half of operation has also highlighted several issues that have not yet been satisfactorily resolved. There is, for example, the “low hanging fruit” problem; agencies are typically referring less severe cases. Trying to get agencies to refer more serious cases has proved challenging. We hope that, by outlining these lessons and issues, this presentation proves to be useful to other CRVE initiatives.

Description: In this presentation, we draw a parallel between public health screening processes of asymptomatic individuals to detect a disease (i.e., cancer) and the attempt of identifying individuals who may be classified as being “at risk” of conducting a violent act. We discuss concepts related to the early detection of a condition through screening. In particular, we focus on the underlying history of the disease over time, as it moves through different stages: onset, start of asymptomatic detectability, start of symptomatic detectability, and death. Notably, such description refers to the latent (possible) insurgence of the disease and to its would-be progression if left undetected and untreated. As part of this framework, we discuss the relevant quantities that are involved when one performs a screening test. These include the probabilities of true and false positive and negative test results and the area under the curve (AUC) index. A positive test result is typically defined through the crossing of a threshold by some measured index. The behavior of the probabilities that describe the features of the test procedure as one changes the threshold that defines a positive result can be illustrated through an online application that was developed for this presentation, available at https://marcobonetti.shinyapps.io/shinyapp/. Other quantities that are discussed are the negative predictive value (NPV) and the positive predictive value (PPV). The latter quantity represents the probability that a subject is truly a case when the test result is positive. The PPV may be surprisingly low, especially if the disease has a low prevalence in the population. We then discuss some modern methods for screening through the analysis of online data streams, either through active or passive data collection, the difference being that in the first kind, the subject is active in the data collection process; in the second kind, secondary data streams are used, such as Twitter tweets, Facebook posts, or Google searches. Machine learning algorithms allow the study of phenomena at the population level (e.g., trends in a phenomenon of interest), but also the prediction of features for individual subjects. Two specific examples are discussed, both based on the use of Facebook data. The first example deals with the prediction of a depression diagnosis from Facebook language, with a comparison of the results of the automatic classification algorithm and the true (known) depression diagnoses of a set of consenting subjects. The second example is a Facebook’s suicide prevention program, which has been in place for over 10 years. The program identifies individuals that, based on their posts, comments and live videos, may be at risk of committing suicide.

Description: In recent years, there has been a proliferation of programs aimed at preventing radicalization and disengaging known violent extremists. Some programs have targeted individuals through the use of case management approaches and the development of individual intervention plans (e.g., the Desistance and Disengagement Program and the Channel program in the UK; the Australian New South Wales Corrections Proactive Integrated Support Model—PRISM—and state-based division initiatives in Australia). There is a broad consensus in the literature that the evaluation of such initiatives has been neglected. However, the evaluation of case-managed interventions to counter violent extremism (CVE) is challenging. They can have small caseloads which makes it difficult to have any comparison or control group. Client participation can vary over time, with no single intervention plan being alike. This can make it hard to untangle the relative influence of different components of the intervention on indicators of radicalization and disengagement. In this presentation, results from primary research that set out to evaluate case-managed CVE interventions in Australia and develop evaluation metrics are presented. This research involves the examination of interventions implemented by New South Wales corrections and state police. The effectiveness of these interventions was assessed against a five-point metric of client change. Client change overtime was analyzed using case note information collected by the various interventions on client participation. Results show that client change is not a linear process and that the longer an individual is engaged in a case-managed intervention, the more likely they are to demonstrate change relating to disengagement. Specific case studies are used to illustrate trajectories and turning points related to radicalization and to highlight the role of case-managed interventions in facilitating disengagement. Key elements of effective interventions include the provision of ongoing informal support. Investment in capturing case note information should be a priority of intervention providers. Different challenges confronted by case-managed CVE interventions are highlighted.

Description: On 27 March 2021, the 2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE 2021) was officially held in Nanchang, China. The Conference invited the IEEE Fellow Professor Guo Yong-xin from the National University of Singapore and the IET Fellow Professor Gao Liang from Huazhong University of Science and Technology of China, as well as other experts, to make the special speeches. The conference focused on the practical application of big data, the development of artificial intelligence and the innovation of Internet of things technology, and the conference provided a platform for academic exchanges among experts and, the experts present reported their own research progress and made prospects for the future development of big data such as application of big data in enterprise decision making, artificial intelligence such as intelligent endoscope in medicine, Internet of Things such as the Internet of Vehicles in urban transport.

Description: This presentation outlines the results of the primary programmatic evaluation efforts the Emergency Preparedness Research Evaluation and Practice (EPREP) Program has conducted since 2016. The presentation begins with an overview of the methodology of selecting outcome measures to evaluate program efficacy, as well as a description of the evaluation framework. Results of the longitudinal and quasi-experimental 2017 evaluation of the Online4Good Academy—on of the training events at the focus of the Boston CVE Pilot Program—are presented and discussed. In 2018, the EPREP Program utilized a longitudinal and quasi-experimental design to evaluate the efficacy of the Peer2Peer antihatred campaign Kombat with Kindness. Results and implications from this study are discussed. The final portion of the presentation describes the more recent activities of the EPREP Program—an evaluation of the online safety program Operation 250 (OP250). This portion of the lecture describes the psychological framework and theory of change under which OP250 implements their initiative. During the final segment we also present the preliminary results of a randomized controlled trial conducted at two different study sites in Massachusetts designed to evaluate the programs’ efficacy.

Description: In the last decade, advances in statistical modeling and computer science have boosted the production of machine-produced contents in different fields: from language to image generation, the quality of the generated outputs is remarkably high, sometimes better than those produced by a human being. Modern technological advances such as OpenAI’s GPT-2 (and recently GPT-3) permit automated systems to dramatically alter reality with synthetic outputs so that humans are not able to distinguish the real copy from its counteracts. An example is given by an article entirely written by GPT-2, but many other examples exist. In the field of computer vision, Nvidia’s Generative Adversarial Network, commonly known as StyleGAN (Karras et al. 2018), has become the de facto reference point for the production of a huge amount of fake human face portraits; additionally, recent algorithms were developed to create both musical scores and mathematical formulas. This presentation aims to stimulate participants on the state-of-the-art results in this field: we will cover both GANs and language modeling with recent applications. The novelty here is that we apply a transformer-based machine learning technique, namely RoBerta (Liu et al. 2019), to the detection of human-produced versus machine-produced text concerning fake news detection. RoBerta is a recent algorithm that is based on the well-known Bidirectional Encoder Representations from Transformers algorithm, known as BERT (Devlin et al. 2018); this is a bi-directional transformer used for natural language processing developed by Google and pre-trained over a huge amount of unlabeled textual data to learn embeddings. We will then use these representations as an input of our classifier to detect real vs. machine-produced text. The application is demonstrated in the presentation.

Description: In the Nordic countries, prevention of radicalization and violent extremism is based on an existing crime prevention collaboration. The core tenet of crime prevention approaches is that early radicalization prevention is best organized as a joint effort, where individual cases are assessed holistically and relevant information shared. This presentation is based on Nordic comparative research that provides a critical analysis of policies, perceptions, and practices regarding multiagency approaches. At the city level, we systematically explore how core components of a Nordic governance model contribute to and might be preconditions for effective multiagency collaboration and secure societies. Variations in these city-level approaches lead to an important question: do these various multiagency approaches to countering violent extremisms and radicalization constitute a unified model? The project provides an informed platform for spreading Nordic experiences and models of governance to other countries in the area of radicalization prevention and countering violent extremism. The multiagency collaboration in Nordic cities tends to be composed of a smaller number of professionals, e.g., three to eight, representing social and health services, a coordinator, and the police. Their positions vary; some represent leadership in the municipality, others are positioned at more mid-level management, and others are frontline professionals handling clients on a daily basis. The origin of these collaborative efforts is based on the School, Social and health services, and Police framework (SSP) in Denmark, Norway, and the Ankkuri group in Finland. We assert that future efforts can also be more need-based, comprising municipal/local initiatives with an element of the guiding national policies, and include the legal frameworks to guide professionals on ethical issues like confidentiality. This presentation is part of a larger project entitled “Nordic Multiagency Approaches to Handling Extremism: Policies, Perceptions, and Practices”, led by professor and center director Tore Bjørgo (University of Oslo) and is funded by NordForsk (Nordic Council of Minister), 2018–2021.

Description: Academics and policymakers recognize the absence of empirically grounded research to support the suppositions on which terrorist focused policies are based. (Sageman, Marc. 2014. “The Stagnation in Terrorism Research”. Terrorism and Political Violence 26 (4): 565–80) We developed our project, Mapping Networks and Narratives of Online Right-Wing Extremists in New South Wales, (Department of Security Studies and Criminology. 2020. Mapping Networks and Narratives of Online Right-Wing Extremists in New South Wales. https://doi.org/10.5281/zenodo.4071472) to illuminate this space. Using the analysis of large-scale online data to generate evidence-based insights into online Right-Wing Extremism (RWE) across the state, our research focused on four key questions: (1) What is the nature of the online RWE environment in New South Wales, Australia (NSW)? (2) How is this movement distributed across NSW? (3) How are themes and narratives framed in different online contexts to mobilize support? (4) What level of risk does the online right-wing environment pose? These questions were left purposely broad to facilitate an exploratory project into what was, in 2018–2019, still a relatively little studied milieu. We combined expertise from computational science, security studies, and behavioral science. We were funded by the Department of Communities and Justice, NSW. We identified two distinct—yet connected—levels of risk. The first was a creeping threat to democracy fueled by networks and content that challenged the fundamental principles of pluralistic liberal democracy. The second was a risk of violence perpetrated by individuals and/or groups that advocate and/or support the use of violence as a tactic to achieve an ideological end. The communities we examined were primarily characterized by networks of individuals as opposed to formal groups. The role played by individual influencers has important ramifications for policy communities: attention should be paid to issues of proscription and moderation. While this milieu engaged with Australian issues and events, it was notably far more obsessed with American issues: particularly those focused on populist narratives and Trumpism. Despite being hateful and extreme, online RWE communities are, firstly, spaces of sociability for users, where social networks are maintained by shared values and norms. For those involved, these spaces engender positive experiences: individuals might share an image of their dinner cooking in their kitchen interspersed with “shitposting” and virulent hate speech. While we identified a variety of narratives that focused on the delegitimization of government and dehumanization of others, the central theme was that of “white identity under threat”. We observed five distinct stages of moderation approach and echo chamber strength. A series of issues for future consideration were identified from the analysis: (1) Awareness raising for key stakeholders across different levels of government and civil society about the revolutionary and anti-social agenda of RWE communities. (2) Building awareness about the civic underpinnings of representative liberal democracy and the threat that RWE poses. (3) Expanding current Countering Violent Extremism infrastructure provided by the NSW government to individuals and communities vulnerable to right wing extremism. (4) The local government is well positioned to deliver programs in rural communities impacted by RWE. (5) Upskilling front-line workers to recognize the risks associated with RWE, and providing pathways into CVE intervention programs for individuals identified as being at-risk.

Description: The place of clinical, medical, or health professional interventions in addressing violent radicalization is a topic of ongoing debate. Although violent radicalization is primarily a social phenomenon with significant psychological dimensions, the high prevalence of mental health “issues” and past psychiatric diagnosis in lone actors suggests that it may be useful to distinguish socialized actors who have strong ties to structured extremist organizations from relatively socially isolated actors who claim, and even boast about, virtual affiliation to extremist groups. For the latter, the potential efficacy of mental health interventions should be considered. However, because of the risk of profiling, stigmatization of minorities, pathologizing social dissent, and resistance, clinical intervention may cause harm and should be carefully evaluated. Until the effectiveness of clinical interventions in reducing radical violence is improved through evaluative research, exchanges about existing clinical models can be useful to support practitioners in the field and provide initial insights about good and potentially harmful practices. The Quebec model of clinical services to mitigate violent radicalization (secondary and tertiary prevention) is structured around three pillars: multiple access points to facilitate outreach and decrease stigma; specialized teams to assess and formulate treatment plans based on existing best evidence in forensic, social, and cultural psychiatry; and collaborative involvement with primary care services, such as community mental health, education, and youth protection institutions, which are in charge of social integration and long-term management. Beyond the initial assessment, the program offers psychotherapy and/or psychiatric interventions services, including mentorship to foster clients’ social integration and life-skill development. Artistic programs offering a semi-structured, nonjudgmental environment, thus fostering self-expression and creativity, are very well received by youth. A multimedia pilot program involving young artists has been shown to provide them with alternative means of expressing their dissent. Three years on from its inception, the preliminary evaluation of the Quebec clinical model by its partners and clinicians suggests that it could be considered a promising approach to address the specific challenges of individuals who present as potential lone actors at high risk of violent radicalization. The model does not, however, appear to reach many members of extremist groups who do not present individual vulnerabilities. While initial signs are positive, a rigorous evaluation is warranted to establish the short, medium, and long-term efficacy of the model, and to eventually identify the key elements which may be transferable to other clinical settings. In 2020, a five-year evaluative research project began to examine these questions. It is important to consider that any intervention can be harmful if due attention is not paid to structural discrimination and violence stemming from associated marginalization and exclusion. Clinical care can in no way replace social justice, equity, and human rights—all key pillars in primary prevention against violent radicalization. In the meantime, however, providing empathy and care in the face of despair and rage may prove most beneficial in decreasing the risk of violent acts.