Responsible Artificial Intelligence

Catalog description

CS 555 / DS 555: Responsible Artificial Intelligence (3 credits) Artificial Intelligence (AI) algorithms have a significant impact on people’s lives. In this course, we discuss social responsibility around data privacy, bias in data and decision making, policies as guardrails, fairness and transparency in the context of applying AI algorithms. Case studies considering societal challenges caused by AI technologies may include AI-based hiring recommendations stemming from societal biases present in training datasets, AI-empowered selfdriving cars behaving in a dangerous manner when encountering atypical road conditions, digital health applications inadvertently revealing private patient information, or large language models like chat-GPT generating incorrect or harmful responses. This course also studies AI-based algorithmic solutions to some of these challenges. These include the design of robust machine learning algorithms with constraints to ensure fairness, privacy, and safety. Strategies for how to apply these methods to design safe and fair AI are introduced. Topics may include min-max optimization with applications to training machine learning models robust to adversarial attacks, stochastic methods for preserving privacy of sensitive data, and multi-agent machine learning models for reducing algorithmic bias and polarization in recommender systems. Recommended Background: Machine Learning at the graduate level, undergraduate level (CS 4342), or equivalent knowledge.