PRESENTATION AT COLLEGE MUSIC SOCIETY NATIONAL CONFERENCE

Reimagining Music in the Age of AI: Potential, Pitfalls, and Transformative Practice in Music Learning & Creativity Panel Discussion with Tina Tallon, Scott Lipscomb, Bill Bauer, Peter Webster, and Jim Frankel More details about the conference can be found here. Abstract: Artificial intelligence is rapidly reshaping music learning and teaching, placing faculty in the position of responding in real time to tools evolving faster than established pedagogies. This Table Talk brings together five perspectives—spanning research, classroom practice, and industry—to examine how AI is already influencing musical creativity, instruction, and evaluation, and how educators might respond with intention rather than reaction. The session is organized as a sequence of concise, complementary presentations. Contributors will address distinct facets of AI in music: its role as a creative and scholarly collaborator; frameworks for ethical and pedagogically sound integration; patterns of adoption (and resistance) among K–12 and university educators; and the expanding role of generative AI within commercial music technologies. One presentation will offer a case study from a large-enrollment university course, demonstrating how a specially trained AI chatbot enabled individualized, high-quality feedback at scale, along with survey data regarding student perceptions of the AI evaluation process. Across these perspectives, several shared questions emerge: Where does AI meaningfully enhance musical learning, and where might it diminish essential skills? What constitutes responsible and ethical AI use in creative and academic contexts? How should faculty rethink assessment practices in light of increasingly sophisticated generative tools? This session addresses the CMS conference goal of exploring “emergent technologies that pose both opportunities and potential challenges to music-makers and educators.” A moderated Q&A will conclude the session, allowing attendees to compare experiences across institutional contexts and identify practical strategies for integrating AI into music teaching and creative work.