Algorithmic Fairness for Asylum-Seekers and Refugees (AFAR)
AFAR (‘Algorithmic Fairness for Asylum Seekers and Refugees’) investigates the usages of new technologies in migration and asylum governance, in particular the automation or part-automation of decisions normally taken by humans, as well as more complex machine learning and artificial intelligence systems, and related uses of digital identity mechanisms. At its heart, AFAR is an exploration of the concept of ‘fairness’ as a legal, normative and political concept. The project explores fairness as a multidimensional concept, and considers whether existing legal standards appropriately institutionalise fairness, in particular when decision-making in these fields is increasingly automated. The project includes work packages to map the use of new technologies in migration and asylum in Europe; explore the evolving overlapping legal standards in this domain; analyse public attitudes and perceptions of fairness in the use of new technologies in migration and asylum governance; and develop proposals to reform practices for fairness.
Led by Cathryn Costello at the Hertie School’s Centre for Fundamental Rights, AFAR is an international collaborative project that also involves researchers at the University of Copenhagen, University of Zagreb, University of Oxford, and at the EUI/MPC. The project is funded by the Volkswagen Foundation in the frame of its “Challenges for Europe” programme.
The MPC’s contributions to AFAR will include (i) analysis of public perceptions of the use of new technologies in migration and asylum governance, and (ii) the development of an executive training programme for policy makers and practitioners.
AFAR outputs will include Working Papers, academic journal articles, policy briefs, and training programmes.