The presentation takes a closer look at the concept of outliers within the context of refugees and the asylum system. It delves into how machine learning algorithms, in conjunction with human judgment, construct the ideas of "normal" and "outlier." The objective is to explore the ethical dimensions of employing AI in high-stakes areas like this one and potential blind spots that may arise.

The presentation will be followed by a moderated conversation on AI, algorithms, bias and fairness with Melanie Ganz.

About the speaker:

Kristin Kaltenhäuser is a PhD Fellow at the Department of Computer Science at the University of Copenhagen and part of the Confronting Data Co-lab. She holds a MSc in Software Design, specialising in algorithms and data science, and an MA in Intercultural Communication and Gender Studies. Her interdisciplinary research spans the fields of data science, human-computer interaction, critical data studies and data feminism. Taking a participatory approach, her current research evolves around grounded sense-making of data in asylum decision-making in the Nordic countries, focusing on marginalized groups and outliers in data.

Kristin Kaltenhäuser

AI, Asylum, and Outliers: Understanding the Complexities of Decision-MakingLink kopieret

Kristin Kaltenhaüser