Topics in Human-Centered Data Science: Responsible and Safe Generative AI Systems

Explore the technical, ethical, and societal dimensions of generative AI systems, gaining practical experience in building and assessing responsible AI applications.  Introduce the foundations of large language and multimodal models, emphasizing methods for evaluating their risks and governance challenges. Topics include bias and fairness, adversarial misuse and red teaming, authorship and intellectual property, data privacy and safety by design, and global AI governance. Through lectures, discussions, and hands-on projects, students will gain experience in context engineering, model evaluation, and safety analysis, developing the skills to critically assess and design responsible AI systems.