This article argues that with increasingly large databases and computational power, profiling as a key part of security governance is experiencing major changes. Targeting mobile populations in order to enact security via controlling and sifting the good from the bad, profiling techniques accumulate and process personal data. However, as advanced algorithmic analytics enable authorities to make sense of unprecedented amounts of information and derive patterns in a data-driven fashion, the procedures that bring risk into being increasingly differ from those of traditional profiling. While several scholars have dealt with the consequences of black-boxed and invisible algorithmic analytics in terms of privacy and data protection, this article engages the effects of knowledge-generating algorithms on anti-discriminatory safeguards. Using the European-level efforts for the establishment of a Passenger Name Record (PNR) system as an example, and on the theoretical level connecting distinct modes of profiling with Foucauldian thought on governing, the article finds that with pattern-based categorizations in data-driven profiling, safeguards such as the Charter of Fundamental Rights of the European Union or the EU data-protection framework essentially lose their applicability, leading to a diminishing role of the tools of the anti-discrimination framework.

Patterns are the epistemological core of predictive policing. With the move towards digital prediction tools, the authority of the pattern is rearticulated and reinforced in police work. Based on empirical research about predictive policing software and practices, this article puts the authority of patterns into perspective. Introducing four ideal-typical styles of pattern identification, we illustrate that patterns are not based on a singular logic, but on varying rationalities that give form to and formalize different understandings about crime. Yet, patterns render such different modes of reasoning about crime, and the way in which they feed back into policing cultures, opaque. Ultimately, this invites a stronger reflection about the political nature of patterns.

Data matter more than ever in the regulation of borders and migration. An apt illustration of how movement is enabled or restricted by data collection and analytics was recently reported by Eyal Weizman, founding director of the London-based research agency Forensic Architecture that specialises in the production and analysis of evidence about human rights violations by state and corporate actors. Prior to a business trip to Miami where he was supposed to open Forensic Architecture's first major exhibition in the US that, among other things, displayed investigations into a CIA drone strike in Pakistan and police killings of black US citizens, Weizmann was notified that his visa waiver request had been denied and that he would not be allowed to enter the United States.Upon further inquiry at the US embassy in London, he was informed that he had been flagged as a 'security threat' by an algorithm looking for suspicious patterns in applicants' data. While officials at the embassy could not tell Weizman what exactly had triggered the unfavourable judgement by the algorithm, they suggested that "it could be something [he] was involved in, people [he] was in contact with, places to which [he] had travelled (had [he] recently been in Syria, Iran, Iraq, Yemen, or Somalia or met their nationals?), hotels at which [he] stayed, or a certain pattern of relations among these things" (Weizman 2020, n.p.). Weizman was subsequently encouraged to provide the US Department of Homeland Security with details on individuals or connections that could point in the direction of terrorism or organised crime in order to purify himself and eventually be able to travel again. Since the digital records that had prompted the algorithm to flag Weizman as a security risk concerned personal and professional networks and connections that informed investigative work into human rights violations -including those committed by US institutions and their allies -Weizman declined to provide this information.Weizman's case forcefully illustrates how the "datafication of mobility and migration management" (Broeders and Dijstelbloem 2016) reconfigures what

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