The Agile Curriculum: How to Teach Agile in the Computer Science Classroom; Artificial Intelligence in the Music Industry: Artists, Labels, AI, and the Competition for Listeners

Vandre, Megan, School of Engineering and Applied Science, University of Virginia
Norton, Peter, EN-Engineering and Society, University of Virginia
Vrugtman, Rosanne, EN-Comp Science Dept, University of Virginia
Morrison, Briana, University of Virginia

How can friction between generative AI and creative industries be reduced? Generative AI applications are now widely used in creative fields. AI models can generate artwork, music and poetry. As a result, the use of copyrighted art to train AI models and the risk of devaluing human artists have become divisive controversies.

How can the University of Virginia (UVA) improve the course structure of the course Software Engineering (CS 3240) to better prepare students for an Agile work environment? With the growing adoption of Agile methodologies by workplaces, newly graduated computer science (CS) students need to have a strong understanding of the Agile framework. A review of studies on the implementation of Agile learning in university curriculum has revealed the promise of adding a “client” role and interdisciplinary collaboration in student projects to better prepare students for an Agile workplace. These suggestions are best practices that other studies have found with modifications to avoid replicating pitfalls and make it suitable for UVA’s CS curriculum. Future work would be the introduction of these suggestions in CS 3240.

How have artists and record labels in the music industry responded to the rise of AI music generation? The rapid improvement of AI music generation software has sparked concern over its effects on the music industry. AI music generation software is generally trained on large datasets of artists’ copyrighted work. Because it can mimic artists, some artists demand standards of responsible AI use. Music industry groups, including music labels and artists, have responded through litigation and by collaborating with AI developers. Copyright law and regulation have not kept pace. To protect the interests of human artists, AI software developers must secure licensing for the training sets they use.

BS (Bachelor of Science)
Artificial Intelligence, AI Music Generation, Agile

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Briana Morrison

STS Advisor: Peter Norton

Issued Date: