26.10.2025
Unai Fischer-Abaigar Featured on Executive Code
AI Prediction and Its Impact on Government Resource Allocation
MCML Junior Member Unai Fischer-Abaigar, was featured in a recent episode of Executive Code. He discussed his paper “The Value of Prediction in Identifying the Worst-Off”, exploring how governments use AI to allocate limited resources and when improving predictive models is more effective than simply expanding access to public programs. Using real data from Germany’s employment offices, his research challenges the assumption that better prediction always leads to better outcomes in public decision-making.
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Center for Digital Medicine and Health Expands
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Vincent Fortuin Receives ERC Starting Grant for Reliable Small-Data AI
MCML PI Vincent Fortuin receives an ERC Starting Grant for AutoBayes, advancing reliable AI methods for learning from small datasets.
