After the COVID-19 pandemic halted many asylum procedures throughout Europe, new technologies are now reviving these types of systems. By lie detection tools examined at the boundary to a system for verifying documents and transcribes selection interviews, a wide range of technology is being used in asylum applications. This article explores how these technology have reshaped the ways asylum procedures happen to be conducted. This reveals how asylum seekers happen to be transformed into obligated hindered techno-users: They are asked to comply with a series why not check here of techno-bureaucratic steps and to keep up with capricious tiny changes in criteria and deadlines. This obstructs their capacity to find the way these devices and to pursue their legal right for coverage.
It also demonstrates how these kinds of technologies will be embedded in refugee governance: They assist in the ‘circuits of financial-humanitarianism’ that function through a flutter of distributed technological requirements. These requirements increase asylum seekers’ socio-legal precarity by hindering them from getting at the stations of safeguards. It further states that studies of securitization and victimization should be coupled with an insight in to the disciplinary mechanisms of technologies, in which migrants will be turned into data-generating subjects exactly who are self-disciplined by their reliance on technology.
Drawing on Foucault’s notion of power/knowledge and comarcal knowledge, the article states that these solutions have an inherent obstructiveness. There is a double result: whilst they aid to expedite the asylum procedure, they also make it difficult designed for refugees to navigate these types of systems. They may be positioned in a ‘knowledge deficit’ that makes these people vulnerable to bogus decisions manufactured by non-governmental actors, and ill-informed and unreliable narratives about their instances. Moreover, they pose fresh risks of’machine mistakes’ which may result in incorrect or discriminatory outcomes.
