Teaching

Fall 2023

CS 4973-05 Responsible Machine Learning

Course description:

In today’s world, machine learning (ML) models have proliferated different real-world applications, and responsibly deploying them is crucial to ensure their positive impact on society. This course is designed for senior computer science undergraduate students interested in exploring the ethical challenges and responsibilities of creating and deploying ML models. Throughout the course, students will learn about the various types of biases that can exist in ML models, methods for uncovering these biases via auditing, and algorithmic fairness techniques to mitigate them. The course will also delve into emerging ethical issues related to generative text and image models and discuss good governance of the AI landscape, covering both centralized regulatory efforts and decentralized defense mechanisms against problematic AI. Through a project component, students will have the opportunity to apply what they learn in class to a real-world scenario and gain hands-on experience in developing responsible ML models. By completing this course, students will become responsible AI practitioners who can create ethical and fair AI systems that benefit society.

Requirements:

Knowledge of Python and ML fundamentals (DS 3000 or equivalent)