Music 356 / CS 470 | Winter 2023
Music and AI
—A Critical-Making Course—
Stanford University
Ge Wang and Yikai Li (TA)

syllabus | code | chai builds | GLOG | gallery

class: TTh 10:30am-12:20pm
location: CCRMA classroom (the Knoll)
prerequisites:1-2+ year of programming; no prior AI (or music) experience needed;
Music 256a/CS 476a or Music 220b is helpful but not necessary
supplemental text: Artful Design: Technology in Search of the Sublime (ISBN: 978-1503600522)
acknowledgements: this course is supported by Stanford HAI.

enrollment: This is an introductory course on music and AI. No prior experience with AI needed. Instructor consent is needed to enroll. If interested, please email the instructor (ge/at/ before classes begin on January 9th, 2023. Please briefly note 1) why you are interested in taking this course, and 2) which course designation you'd like to enroll in (Music356 or CS470). If accepted, you will receive a permission number to enroll in the course.

course summary:
How do we make music with artificial intelligence? What does it mean to do so (and is it even a good idea)? How might we artfully design tools and systems that balance machine automation and human interaction? More broadly, how do we want to live with our technologies? Are there—and ought there be—limits to using AI for art? (And what is Art, anyway?) In this "critical making" course, students will learn practical tools and techniques for AI-mediated music creation, engineer software systems incorporating AI, HCI and Music, and critically reflect on the aesthetic and ethical dimensions of technology.

Coursework will span the practical ("how?"), the philosophical ("why?"), and the social ("for whom?"). Topics ranges from "good-old fashioned AI" (GOFAI), machine learning, and deep artificial neural networks in the context of music and art creation. Students will use these techniques to design (and consider) automated systems as well as interactive AI tools that keep human judgment in the loop. Through these exercises, we will explore how AI might augment, not replace, human creativity.

teaching philosophy
We, the instructors, firmly believe that anyone can learn anything to which they put their earnest effort and thought. In this course, we also believe the answers to questions are secondary and sometimes even irrelevant. What truly matters here are the thoughtfulness of the questions we frame and the effort we put into the craft of designing things. Above all, our aim is for each student to acquire for themselves both “things to create with” and “things to think with” as tools that will stay and grow with them for years to come.

GDoc/Glossary Log (GLOG)


CCRMA | Music Department | Stanford University