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.
Related
13.11.2025
Explaining AI Decisions: Shapley Values Enable Smart Exosuits
AI meets wearable robotics: MCML and Harvard researchers make exosuits smarter and safer with explainable optimization, presented at ECML-PKDD 2025.
©Gorodenkoff-stock.adobe.com
03.11.2025
Research on Human-Centred Exosuit Technology Highlighted in Börsen-Zeitung
Julian Rodemann worked with Harvard on interpretable algorithms for “Back Exosuits,” improving human–machine interaction.
02.11.2025
MCML at EMNLP 2025
MCML researchers are represented with 39 papers at EMNLP 2025 (18 Main, 13 Findings, and 8 Workshops).
