Artificial Intelligence as Im/Mobility: Pre-Limirary Thoughts on Understanding the Use of Ai in Immigration Systems

Abstract

Technology, including artificial intelligence in im/migration service delivery and migration management have been widely deployed in EuroAmerica (Mongia, 2018; Walia, 2021). In Canada, Immigration Refugee Citizenship Canada (IRCC) has, in the past few years, secretly piloted an in-house built AI system for triaging im/migrant applications from China, India and the Philippines (Molnar & Gill, 2018). The 2 million immigration applications backlog in part caused by the COVID-19 pandemic has been used as a justification to accelerate the push for the adoption of AI in im/migration affairs stating the need to modernize, optimize and expedite immigration affairs. Building on AoIR 2022’s theme, I take a decolonial approach to the study of AI and im/migration issues. I follow the claim made by decolonial scholars (El-Nany, 2020) that it is necessary to go back in history in order to better understand current power relations, systemic racism and patriarchy, the ongoing dispossession and forced im/mobility of racialized populations located in the global South. I conceptualize the use of AI as immobility to show how populations become testing grounds to decide who is worthy of im/mobility. Methodologically, this conference paper is informed by access to information requests made to the government of Canada to shed light on the use of AI systems within the IRCC. In addition, this paper relies on desk research including newspaper articles, blog posts and podcasts by and with immigration lawyers, and parliamentary hearings.