What is needed to ensure that algorithmic decision-making tools in the asylum system support people rather than determining their fate? This question was at the heart of the international closing conference “Algorithmic Fairness for Asylum Seekers and Refugees” held at the Hertie School in Berlin.
In the panel discussion “Preference Matching and Algorithmic Tools in Practice,” Dr Devrimsel Deniz Nergiz and Sonja Reinhold, LL.M., presented the Match’In project as an example of how digital tools can be used responsibly in sensitive administrative contexts. Match’In was deliberately not discussed as a technological “solution,” but as a learning and critically monitored instrument that embeds principles of fairness, transparency, and participation—while explicitly preserving human decision-making authority.
The international exchange reinforced a core insight underlying Match’In: algorithmic systems can only unfold their benefits if they are not used predictively, autonomously, or opaquely. Match’In therefore positions itself as a case-based recommendation system that helps make individual needs, preferences, and protection requirements visible. Its purpose is to support decision-makers in administration and local authorities—without making decisions about people.
At the same time, the discussion provided important impulses for the further development of Match’In 2.0, particularly with regard to family constellations, more complex needs, and an even more reflective accompanying research framework. In this way, Match’In clearly positions itself as a project that combines digital innovation with responsibility—at the intersection of research, administration, and the lived experiences of those affected.
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