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The whitepaper has three parts. The first part provides some contextual background, describing the diverse range of online services utilised by terrorists and extremists and the process by which propaganda is disseminated online. The second part details industry responses. As well as referrals from users and law enforcement, it describes the use of AI for proactive detection and collaborative, cross-platform initiatives. The third part describes four issues for discussion: transparency; definitional clarity; the impact on those targeted; and, the use of online data for predictive purposes.

Cooperation between law enforcement and tech companies is widely regarded as necessary to tackle online terrorist content. Both sectors have publicly stated their commitment to working together and there are examples of mutual cooperation. Yet there are also impediments to such collaboration, including different cultures and operating practices, and there have been high-profile instances of non-cooperation. The informality of existing collaborations has also led to concerns about censorship, mission creep and a lack of accountability and oversight.

The focus of this report is on how to resolve the impediments to closer cooperation between law enforcement and the tech sector in order to realise the benefits of mutual collaboration, while simultaneously addressing concerns about due process and accountability. The report utilises an interview-based methodology to examine the experiences and opinions of personnel from both sectors who have first-hand experience of mutual cooperation. It provides empirically grounded insights into this under-researched topic.

As efforts to identify and remove online terrorist and violent extremist content have intensified, concern has also grown about so‐called lawful but awful content. Various options have been touted for reducing the visibility of this borderline content, including removing it from search and recommendation algorithms, downranking it and redirecting those who search for it. This article contributes to this discussion by considering the moderation of such content, in terms of three sets of values. First, definitional clarity. This is necessary to provide users with fair warning of what content is liable to moderation and to place limits on the discretion of content moderators. Yet, at present, definitions of borderline content are vague and imprecise. Second, necessity and proportionality. While downranking and removal from search and recommender algorithms should be distinguished from deplatforming, tech companies’ efforts to deamplify borderline content give rise to many of the same concerns as content removal and account shutdowns. Third, transparency. While a number of platforms now publish their content moderation policies and transparency data reports, these largely focus on violative, not borderline content. Moreover, there remain questions around access to data for independent researchers and transparency at the level of the individual user.

VOX-Pol Blog Post.

Social-media companies make extensive use of artificial intelligence in their efforts to remove and block terrorist content from their platforms. This paper begins by arguing that, since such efforts amount to an attempt to channel human conduct, they should be regarded as a form of regulation that is subject to rule-of-law principles. The paper then discusses three sets of rule-of-law issues. The first set concerns enforceability. Here, the paper highlights the displacement effects that have resulted from the automated removal and blocking of terrorist content and argues that regard must be had to the whole social-media ecology, as well as to jihadist groups other than the so-called Islamic State and other forms of violent extremism. Since rule by law is only a necessary, and not a sufficient, condition for compliance with rule of values, the paper then goes on to examine two further sets of issues: the clarity with which social-media companies define terrorist content and the adequacy of the processes by which a user may appeal against an account suspension or the blocking or removal of content. The paper concludes by identifying a range of research questions that emerge from the discussion and that together form a promising and timely research agenda to which legal scholarship has much to contribute.

Social-media companies make extensive use of artificial intelligence in their efforts to remove and block terrorist content from their platforms. This paper begins by arguing that, since such efforts amount to an attempt to channel human conduct, they should be regarded as a form of regulation that is subject to rule-of-law principles. The paper then discusses three sets of rule-of-law issues. The first set concerns enforceability. Here, the paper highlights the displacement effects that have resulted from the automated removal and blocking of terrorist content and argues that regard must be had to the whole social-media ecology, as well as to jihadist groups other than the so-called Islamic State and other forms of violent extremism. Since rule by law is only a necessary, and not a sufficient, condition for compliance with rule-of-law values, the paper then goes on to examine two further sets of issues: the clarity with which social-media companies define terrorist content and the adequacy of the processes by which a user may appeal against an account suspension or the blocking or removal of content. The paper concludes by identifying a range of research questions that emerge from the discussion and that together form a promising and timely research agenda to which legal scholarship has much to contribute.