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Carlos Castillo | Universitat Pompeu Fabra

Distinguished Research Professor

Carlos Castillo | Universitat Pompeu Fabra

Distinguished Research Professor

Biography

Carlos Castillo is a Distinguished Research Professor at Universitat Pompeu Fabra in Barcelona, where he leads the Web Science and Social Computing research group. He is a web miner with a background on information retrieval, and has been influential in the areas of crisis informatics, web content quality and credibility, and adversarial web search. He is a prolific, highly cited researcher who has co-authored over 80 publications in top-tier international conferences and journals, receiving a test-of-time award, four best paper awards, and two best student paper awards. His works include a book on Big Crisis Data, as well as monographs on Information and Influence Propagation, and Adversarial Web Search.

PRESENTATION: ALGORITHMIC FAIRNESS AND JUSTICE

This talk describes some limitations of Machine Learning (ML) algorithms for predicting juvenile recidivism. Particularly, we are interested in analyzing the trade-off between predictive performance and fairness. To that extent, we evaluate fairness of ML models in conjunction with SAVRY, a structured professional risk assessment framework, on a novel dataset originated in Catalonia. In terms of accuracy on the prediction of recidivism, the ML models slightly outperform SAVRY. However, across three fairness metrics used in other studies, we find that SAVRY is in general fair, while the ML models tend to discriminate against male defendants, foreigners, or people of specific national groups.

All session by Carlos Castillo | Universitat Pompeu Fabra