Explainable Artificial Intelligence and Fairness in Asylum Law (XAIfair)

Explainable Artificial Intelligence and Fairness in Asylum Law (XAIfair)

Applying for asylum triggers a process with far-reaching consequences. Nonetheless, little is known about what exactly goes into the process. 

When a person applies for asylum national authorities have to make a legal decision with far-reaching consequences. But what exactly goes into making a decision on asylum, and why do countries reach widely different results when deciding on seemingly similar cases? The goal of this project is to develop novel inter-disciplinary approaches to answer these questions. Specifically, the project combines methods from computer vision and explainable AI to create more transparent and comprehensible data analysis of Nordic asylum decisions. The grant will finance two postdocs, one with a background in law and one with a background in data science. The two postdocs will work closely together to develop a common language and analytical framework across the disciplines.