Fairness in the prediction of long-term unemployment by caseworkers and machine learning
Project duration: 01.08.2024 to 31.12.2028
Abstract
The fairness of AI algorithms is much debated. In this project, we use administrative data and ML methods to compare AI and human decisions in terms of fairness. On the one hand, we use profiling data from caseworkers, where unemployed people are classified at the beginning of unemployment according to their probability of becoming long-term unemployed. On the other hand, we use ML methods to predict this probability. Both predictions are compared with respect to fairness aspects, e.g. gender or nationality.
Management
01.08.2024 - 31.12.2028
01.08.2024 - 31.12.2028
Employee
Ruben L.
Bach
01.08.2024 - 31.12.2028
Christoph
Kern
01.08.2024 - 31.12.2028