After the COVID-19 pandemic stopped many asylum procedures across Europe, fresh technologies are reviving these systems. Coming from lie recognition tools examined at the border to a program for confirming documents and transcribes interviews, a wide range of technology is being made use of in asylum applications. This article explores how these technologies have reshaped the ways asylum procedures are conducted. It reveals just how asylum seekers will be transformed into required hindered techno-users: They are asked to comply with a series of techno-bureaucratic steps and keep up with unforeseen tiny changes in criteria and deadlines. This kind of obstructs their particular capacity to navigate these devices and to pursue their right for security.

It also displays how these kinds of technologies will be embedded in refugee governance: They aid the ‘circuits of financial-humanitarianism’ that function through a whirlwind of distributed technological requirements. These requirements increase asylum seekers’ socio-legal precarity by hindering all of them from getting at the channels of security. It further argues that examines of securitization and victimization should be coupled with an insight in the disciplinary mechanisms of such technologies, in which migrants are turned into data-generating subjects so, who are regimented by their dependence on technology.

Drawing on Foucault’s notion of power/knowledge and comarcal knowledge, the article states that these technologies have an inherent obstructiveness. They have a double impact: www.ascella-llc.com/the-counseling-services-offers-free-confidential-counseling-services-to-enrolled-students/ while they aid to expedite the asylum method, they also help to make it difficult designed for refugees to navigate these systems. They are really positioned in a ‘knowledge deficit’ that makes all of them vulnerable to illegitimate decisions created by non-governmental actors, and ill-informed and unreliable narratives about their cases. Moreover, they will pose fresh risks of’machine mistakes’ that may result in erroneous or discriminatory outcomes.