For complementary research guides relating to AI see the following USC Libraries Research guides:
AI and Teaching and Learning by Danielle Mihram. This guide is a detailed overview of AI literacy research and scholarship in the broad field of teaching and learning in Colleges and Universities. It addresses technical, ethical, critical, and societal dimensions of AI in education in our current AI-embedded world.
AI and the Digital Humanities by Danielle Mihram. This Guide focuses on the digital transformation and innovation in Digital Humanities (DH) research and scholarship together with Artificial Intelligence (AI) as a catalyst for scalable advancements.
AI@USC in Benjamin Hall's Research Guide, Artificial Intelligence for Business. "This guide was created as an attempt to organize the influx of AI trends, tools, and ethical incidents that are material to the business world. The pages herein are not perfect, they are not an endorsement of AI or any AI tool, and the guide is a continual work-in-progress."
Using Generative AI in Research, by Michaela Ullmann in collaboration with Benjamin Hall, Mike Jones, and Clarissa Moreno. This Research Guide provides information on the use of Generative AI in academic papers and research, and provides guidance on the ethical use of Generative AI in an academic setting."
SEE ALSO:
Music - Information resources for the field of music by Andrew Justice.
Music Education, by Andrew Justice. “Here you will find all the basic resources for research in Music Education. “
About this Guide
This Guide (prepared for our USC Community - Faculty, Students, and Staff) focuses on the many facets of Artificial Intelligence (AI) research and scholarship in the broad field of music teaching and learning. The rapid evolution of this field necessitates frequent updates as well as information emendations in order for us to remain fully aware of its many facets. Consequently, this guide will regularly monitor and include recent trends in this field so that we may successfully and productively network and collaborate with the AI and teaching/learning communities and scholars both at USC and nationwide.
For a listing of Centers and Units working on AI at USC see: AI@USC in Benjamin Hall's Research Guide, Artificial Intelligence for Business.
I invite you to communicate with me, Danielle Mihram, if you would like to find information on AI within the fields of music teaching and learning that would help you in your teaching and research.
Additional pages that further reveal the scope of AI in music are currently under development.
AI's many Forms and Types of Assistance
The integration of AI in music education at the college and university level is a rapidly evolving area with a broad scope of potential applications and benefits, alongside important challenges.
AI technology has reached the point where it can generate, compose, and enhance musical content that has previously been performed by humans. AI music can take many forms and types of assistance, from generating an entire song from start to finish, to writing specific aspects of a composition, to mixing and mastering a production, to voice cloning, and more. AI tools are now being used to generate music, analyze music for recommendations, assist with mixing and mastering, and even predict music trends.
The integration of AI with other emerging technologies
The integration of AI with other emerging technologies, such as virtual reality (VR) and augmented reality (AR), could create immersive learning environments. These technologies can simulate concert halls, orchestras, and other performance settings, providing students with realistic practice experiences that enhance their skills and confidence.
The Need for AI Literacy
Students can now effortlessly compose using simple text prompts with AI music generators, a situation which encourages innovative pedagogical approaches and democratizes creativity in the music classroom.
Consequently, enhancing AI literacy among students and teachers, developing assessment frameworks that reflect the collaborative nature of AI-assisted music creation, defining acceptable boundaries in terms of ensuring equitable access to AI tools, and providing professional development opportunities for music teachers have all become major focal points in the context of AI literacy.
In addition, cultural bias, originality, equity, and the ethical use of generative AI in school music education require careful attention and, in some cases, regulation.
Balancing the use of AI With The Need for Human interaction
Another important challenge is balancing the use of AI with the need for human interaction. While AI can enhance music education, the emotional and expressive aspects of music require human insight and connection. Finding the right balance between AI tools and personal (human) interaction is essential . Teachers are now working to balance between leveraging AI tools and maintaining personal interaction with their students, thus ensuring that the human element remains central to the learning experience.
In addition, focus on collaboration and reflection is equally necessary. Encouraging a collaborative approach between humans and AI, and emphasizing reflective learning experiences where students evaluate and critically assess AI-generated content, can foster creativity and responsible AI use.
Need for Assessment Methods
As AI technology matures and its capabilities in music education expand, a deeper focus is expected on researching the long-term impact on student creativity and learning, designing effective assessment methods that reflect the collaborative nature of AI-assisted music creation, and establishing robust ethical frameworks for its use.
This Guide provides an overview of these many aspects of the role role of AI in music and addresses issues such as curriculum development, continuing education, as well as policy and regulatory frameworks.
Attribution:
(a) Initial bibliographic searches conducted for the compilation of this Guide were conducted using Google's AI assistant, Gemini. That information was rigorously checked and verified.
(b) The information gathered for this Guide is based and is the result of searches in a multitude of bibliographic sources which are listed in our RESOURCES page.
Opportunities for Educators:
Automated assistance and feedback: AI-driven tutoring systems can provide one-on-one support for music theory or instrument techniques, offer instant feedback, and automate assessment, freeing up educators' time for more complex instructional duties.
Streamlined administration: AI can automate tasks like grading and managing course materials, potentially freeing up instructor time for more personalized mentorship and interaction with students.
Ethical implications: Crucial considerations are: intellectual property, ownership of AI-generated music, potential devaluation of human-created work, potential biases in AI training data sets, use of copyrighted materials in training AI, and the risk of overreliance on AI in creative fields.
Importance of human interaction: While AI offers valuable tools, it shouldn't replace the unique guidance, mentorship, and emotional connection that skilled human teachers provide in music education.
Bibiiographic searches in our USC Databases and using Advanced Search with the key words - Artificial Intelligence AND music - yield a few records. Since the research on AI and music is evolving at a rapid pace it is not unreasonable to expect the appearance of a much greater number of additional publications in the near future.
However, a search in Google Scholar, which does appear in our USC Databases listings, does yield a significant number of records. when the key words - Artificial Intelligence music education - are used (See this Guide's page RESOURCES).
The readings appearing below are merely examples of results obtained using just Google as a search engine: