Research

Algorithmic Fairness for Asylum-Seekers and Refugees (AFAR)

This project aims to investigate the understandings and institutionalisation of ‘fairness’ in migration and asylum governance (MAG) in Europe, focusing on the actual and emerging role of newtech.

Data Science for Asylum Legal Landscaping (DATA4ALL)

Leveraging large-scale decision data in the Nordics, DATA4ALL pioneers a new research agenda combining data science and migration law to understand the significant outcome variations in asylum decisions within and across countries.

Nordic Refugee Determination: Advancing Data Science in Migration Law (NordASIL)

NordASIL will produce a novel approach to answer two questions: What factors shape the production of national asylum decisions? and Why do asylum outcomes across similar cases differ so much from one another?

Explainable Artificial Intelligence and Fairness in Asylum Law (XAIfair)

XAIfair is an interdisciplinary project where data scientists (AI/XAI researchers) and legal scholars join forces to overcome the challenge of introducing meaningful XAI into a specific legal domain, namely Nordic asylum law.

Refugee Political Participation (RPP)

Refugee Political Participation (RPP) is a project funded by the Marie Skłodowska-Curie programme of the European Union. RPP will study the political participation of refugees through cross-cutting research.