The explosion of publicly available and system-integrated generative AI tools has destabilized the ways we think about language, media, art, knowledge, and imagination. In this course, we will employ generative AI to create media while critically engaging with the possibilities and limitations of AI models. Through experiments and projects, students will learn how to deploy and interpret AI processes and outputs across a variety of media practices including writing, coding, and image production. The focus will be on human-centered creative practice from chatbots to poetry and storytelling to visual art. Alongside project-based work, this course will cover the history of Artificial Intelligence as a field, consider its social impacts—including bias, ethics, and legal challenges—and reckon with its wider cultural and human implications. Students will gain a deeper understanding of what AI is and how it works. An overview of the statistical/mathematical concepts behind machine learning, neural networks, vector space, and other components will be covered but no background in mathematics is necessary. Computational methods (primarily in Python) and basic coding approaches will be introduced and employed throughout the course—prior coding experience is helpful but not required.