  Open AI's language model, GPT-3, has shown great potential for many NLP
tasks, with applications in many different domains. In this work we carry out a
first study on GPT-3's capability to communicate musical decisions through
textual explanations when prompted with a textual representation of a piece of
music. Enabling a dialogue in human-AI music partnerships is an important step
towards more engaging and creative human-AI interactions. Our results show that
GPT-3 lacks the necessary intelligence to really understand musical decisions.
A major barrier to reach a better performance is the lack of data that includes
explanations of the creative process carried out by artists for musical pieces.
We believe such a resource would aid the understanding and collaboration with
AI music systems.
