Send message to Authors

Short abstract

With Music AI as the case study, our critical interdisciplinary AI course invited computing students to move beyond techno-solutionist framings. Drawing on teaching and student experiences, we reflect on the challenges and what they mean for developing critical interdisciplinary pedagogies.

Long abstract

Calls to educate computing students “in the public interest” have often taken the form of incorporating Ethics and Responsibility courses across computer science degrees, with particular attention to AI. While welcome, these efforts can remain framed within assumptions inherited from technical disciplines, in which interventions are limited to technical fixes, overlooking the need to interrogate AI systems as sociotechnical assemblages resulting from the mutual mediations between society, culture and technology.

In this paper we reflect on our approach to developing and teaching a critical interdisciplinary AI course focused on the cultural ramifications of Music AI. The eight-week course was taught by researchers from anthropology, science and technology studies, music studies, creative practice and computing (among other disciplines) who are themselves researching critical approaches to Music AI. The course introduces students to a range of perspectives on Music AI and encourages them to develop greater reflexivity about their technical work, its promise and its limits. The aim is to teach them how to articulate complex sociotechnical problems, broadening their scope beyond technical concerns, and on this basis, empowering them to eventually build different and better systems.

We reflect on how the course has worked in practice, drawing both on our experience delivering it and the students’ we interviewed. We discuss what was challenging, focusing on communication across disciplines and on navigating tensions between the pedagogical methods of the social sciences and humanities and those of STEM. We conclude by presenting provocations to induce a critical interdisciplinary transformation in higher education.