With COVID-19 disrupting travel, shutting borders, and redefining what is essential work, Pandemic Borders explores what international migration will look like after the pandemic, in this series titled #MigrantFutures
In theory, under the right legal conditions, predictive technologies powered by artificial intelligence (AI) could help ensure that fewer refugees are sent home to face persecution. However, the right conditions do not exist in Canada and, under the law as it stands, AI will only hurt claimants. To understand why, it is necessary to understand the role that uncertainty plays in refugee hearings in Canada.
Under Canadian law, claimants must prove each of the assertions in their application for refugee status. If the decision maker is unsure as to whether an assertion is proven, they will reject it. If the decision maker is paralysed by doubt – "I'm not convinced that I should accept this assertion, but I'm also not convinced that I should reject it" – the law says: "Forget your second set of uncertainties. Since the claimant bears the legal burden of proof, only your first set of uncertainties matters. If you are not convinced that the assertion is proven, you should reject it. Full stop."
