Machine learning (ML) threatens or promises to upend many industries. The goal of this seminar is to have students develop a sense of literacy around ML—its promises, pitfalls, and possibilities. This seminar investigates how ML intersects with art and design processes, emphasizing the role of decision-making between human and machine. Applications of ML in art and architecture are explored through a series of case studies with an emphasis on the potential of ML as collaborator. During these case studies, students also consider the second-order impacts and ethical ramifications. Students eventually isolate a moment from their own design process and expand on it by developing a machine-learning algorithm of their own accompanied by a five-page paper.