Toronto Metropolitan University
Artificial Intelligence for a Reduction of False Denials in Refugee Claims.pdf (672.59 kB)

Artificial Intelligence for a Reduction of False Denials in Refugee Claims

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posted on 2023-03-28, 15:34 authored by Hilary Evans CameronHilary Evans Cameron, Avi Goldfarb, Leah Morris

Deciding refugee claims is a paradigm case of an inherently uncertain judgment and prediction exercise. Yet refugee status decision-makers may underestimate the uncertainty inherent in their decisions. A feature of recent advances in artificial intelligence (AI) is the ability to make uncertainty visible. By making clear to refugee status decision-makers how uncertain their predictions are, AI and related statistical tools could help to reduce their confidence in their conclusions. Currently, this would only hurt claimants, since many countries around the world have designed their refugee status determination systems using inductive inference which distorts risk assessment. Increasing uncertainty would therefore contribute to mistaken rejections. If, however, international refugee law was to recognize an obligation under the UN Convention to resolve decision-making doubt in the claimant’s favour and use abductive inference, as Evans Cameron has advocated, then by making uncertainty visible, AI could help reduce the number of wrong denied claims.