Prime Interior

Technology and Asylum Procedures

After the COVID-19 pandemic halted many asylum procedures across Europe, new technologies have become reviving these kinds of systems. Via lie diagnosis tools analyzed at the border to a system for validating documents and transcribes selection interviews, a wide range of systems is being used in asylum applications. This article explores www.ascella-llc.com/the-counseling-services-offers-free-confidential-counseling-services-to-enrolled-students how these technology have reshaped the ways asylum procedures happen to be conducted. This reveals just how asylum seekers are transformed into compelled hindered techno-users: They are asked to comply with a series of techno-bureaucratic steps also to keep up with capricious tiny changes in criteria and deadlines. This kind of obstructs their particular capacity to find the way these devices and to go after their right for safeguard.

It also demonstrates how these types of technologies happen to be embedded in refugee governance: They help the ‘circuits of financial-humanitarianism’ that function through a whirlwind of distributed technological requirements. These requirements increase asylum seekers’ socio-legal precarity by hindering these people from getting at the channels of protection. It further argues that analyses of securitization and victimization should be coupled with an insight into the disciplinary mechanisms for these technologies, by which migrants happen to be turned into data-generating subjects who all are regimented by their reliability on technology.

Drawing on Foucault’s notion of power/knowledge and comarcal knowledge, the article argues that these systems have an inherent obstructiveness. There is a double result: although they assist to expedite the asylum process, they also generate it difficult intended for refugees to navigate these types of systems. They are positioned in a ‘knowledge deficit’ that makes these people vulnerable to bogus decisions of non-governmental stars, and ill-informed and unreliable narratives about their instances. Moreover, they pose fresh risks of’machine mistakes’ that may result in incorrect or discriminatory outcomes.

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