In 2020, the European Union announced the award of the contract for the biometric part of the new database for border control, the Entry Exit System, to two companies: IDEMIA and Sopra Steria. Both companies had been previously involved in the development of databases for border and migration management. While there has been a growing amount of publicly available documents that show what kind of technologies are being implemented, for how much money, and by whom, there has been limited engagement (...) with digital methods in this field. Moreover, critical border and security scholarship has largely focused on qualitative and ethnographic methods. Building on a data feminist approach, we propose a transdisciplinary methodology that goes beyond binaries of qualitative/quantitative and opacity/transparency, examines power asymmetries and makes the labour of coding visible. Empirically, we build and analyse a dataset of the contracts awarded by two European Union agencies key to its border management policies – the European Agency for Large-Scale Information Systems (eu-LISA) and the European Border and Coast Guard Agency (Frontex). We supplement the digital analysis and visualisation of networks of companies with close reading of tender documents. In so doing, we show how a transdisciplinary methodology can be a device for making datafication ‘intelligible’ at the European Union borders. (shrink)

This paper builds off the Our Data Ourselves research project, which examined ways of understanding and reclaiming the data that young people produce on smartphone devices. Here we explore the growing usage and centrality of mobiles in the lives of young people, questioning what data-making possibilities exist if users can either uncover and/or capture what data controllers such as Facebook monetize and share about themselves with third-parties. We outline the MobileMiner, an app we created to consider how gaining access to (...) one’s own data not only augments the agency of the individual but of the collective user. Finally, we discuss the data making that transpired during our hackathon. Such interventions in the enclosed processes of datafication are meant as a preliminary investigation into the possibilities that arise when young people are given back the data which they are normally structurally precluded from accessing. (shrink)

In this article we introduce the concept of implied optical perspective in deep learning computer vision systems. Taking the BBC's experimental television programme “Made by Machine: When AI met the Archive” as a case study, we trace a conceptual and material link between the system used to automatically “watch” the television archive and a specific type of photographic practice. From a computational aesthetics perspective, we show how deep learning machine vision relies on photography, its technical regimes and epistemic advantages, and (...) we propose a novel way to identify the latent camera through which the BBC archive was seen by machine. (shrink)