This paper presents a prototypical computational framework for music computing appropriation. Putting Human-Computer Interaction at the center of the issue, it proposes to use Artificial Intelligence (AI) to assist humans in their first uses of music computing systems—namely, their exploration. We first review how interaction design may be central to exploration and appropriation of music computing systems, highlighting guidelines and potential directions to improve it. We then present our framework proposal , centered on exploration, detailing both its interactive workflow and the AI model at stake. We finally illustrate the pedagogical potential of our framework in two musical applications that we implemented, and discuss future research toward understanding how AI could be used by humans as collaborators for self-expression and appropriation of music computing practices.