Program Overview

This colloquium explores the safety and fairness of machine learning algorithms, delving into examples of malfunctioning systems and algorithms designed to mitigate risks. Running from February to May, the course involves weekly meetings and culminates in a project where students train a machine learning model with safety and fairness considerations. Open to juniors and seniors in Computer Science or Informatics, department consent is required.