Technologies and Asylum Procedures

After the COVID-19 pandemic stopped many asylum procedures throughout Europe, fresh technologies have become reviving these types of systems. Coming from lie recognition tools examined at the border to a program for confirming documents and transcribes interviews, a wide range of systems is being employed in asylum applications. This article is exploring how these solutions have reshaped the ways asylum procedures are conducted. This reveals just how asylum seekers are transformed into compelled hindered techno-users: They are asked to conform to a series of techno-bureaucratic steps and keep up with unpredictable tiny changes in criteria and deadlines. This obstructs their particular capacity to steer these systems and to pursue their legal right for security.

It also displays how these kinds of technologies happen to be embedded in refugee governance: They facilitate the ‘circuits of financial-humanitarianism’ that function through a whirlwind of distributed technological requirements. These requirements increase asylum seekers’ socio-legal precarity simply by hindering all of them from accessing the channels of coverage. It further states that examines of securitization and victimization should be combined with an insight in to the disciplinary mechanisms for these technologies, through which migrants will be turned into data-generating subjects just who are self-disciplined by their reliance on technology.

Drawing on Foucault’s notion of power/knowledge and comarcal expertise, the article argues that these technology have an inherent obstructiveness. There is a double effect: asylum procedure advice even though they assist with expedite the asylum method, they also produce it difficult for the purpose of refugees to navigate these kinds of systems. They can be positioned in a ‘knowledge deficit’ that makes them vulnerable to bogus decisions of non-governmental celebrities, and ill-informed and unreliable narratives about their cases. Moreover, that they pose new risks of’machine mistakes’ which may result in erroneous or discriminatory outcomes.