Daten zum Projekt

Algorithmic Fairness for Asylum-Seekers and Refugees (AFAR)

Zur Projekt-Website

Initiative: Herausforderungen für Europa
Bewilligung: 01.07.2021
Laufzeit: 4 Jahre


The project team addresses two of the EU's challenges: reforming migration and asylum governance (MAG) in order to avoid another 'refugee/migration crisis', and regulating 'newtech' for fairness. 'Newtech' refers to the automation or part-automation of decisions normally made by humans, using simple closed-rule algorithms, as well as more complex machine learning and artificial intelligence systems, and related uses of digital identity mechanisms. The project builds on the collaborators' deep expertise on European MAG, drawing on legal scholarship, refugee studies and political science. The project aims to make a contribution to the understanding and institutionalisation of 'fairness'. The team conceptualises fairness three-dimensionally, encompassing: individual fairness for MAG subjects; distributive fairness across places of protection; and perceptions of fairness amongst MAG subjects. The project will answer the following research questions: 1. What are the current and emerging uses of newtech in European MAG? 2. How do European legal standards and practices foster fairness in newtech in MAG? If not, how ought these legal standards be reformed to ensure fairness? Do emergent uses of new-tech in MAG enhance or undermine fairness? 3. How does the use of newtech in MAG affect perceptions and experiences of fairness among European populations and data subjects (asylum seekers and refugees)? 4. In light of the above, how can and should newtech be employed in MAG in order to maximise fairness across its different dimensions? The team has identified newtech usages across MAG's key domains governing access to protection, responsibility-sharing for asylum processing and hosting refugees, and decision-making on asylum claims. Thus far, these practices have not been studied systematically.


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