CAMELIA in the classroom

Project CAMELIA comes in the classroom! Students enrolled in the Ethical and Legal Framework course of the Bachelor of Science in Data Engineering and Systems at ETS de Ingenieros de Telecomunicación Universidad Politécnica de Madrid have experienced Ethical Data Science in two case studies during the 2025/26 academic year:

1. Studying Racial Bias in Predicting Risk of Recidivism in the US Criminal Justice System, based on the famous and controversial research by ProPublica. Students have applied different fairness tests to this dataset and discussed the results.

2. Using Interpretable Machine Learning to Study Bias in Credit Scoring Algorithms, based on the “German credit” dataset. Students have applied several explainability and interpretability techniques to detect bias based on nationality in the granting of credits by a bank.

In addition to inviting reflection, the case studies encourage learning by doing, which we hope will reinforce the concepts and make the subject more enjoyable. Furthermore, CAMELIA (CAsos prácticos sobre el Marco Ético y Legal de la Inteligencia Artificial, which translates to Practical Cases on the Ethical and Legal Framework for Artificial Intelligence) has generated four other case studies for learning ethical AI concepts, which, through class debates and discussions, allow ethical dilemmas arising from these technologies to be introduced into the classroom.