Abstract
We report on a series of workshops with musicians and robotics engineers aimed to study how human and machine improvisation can be explored through interdisciplinary design research. In the first workshop, we posed two leading questions to participants. First, what can AI and robotics learn by how improvisers think about time, space, actions, and decisions? Second, how can improvisation and musical instruments be enhanced by AI and robotics? The workshop included sessions led by the musicians, which provided an overview of the theory and practice of musical improvisation. In other sessions, AI and robotics researchers introduced AI principles to the musicians. Two smaller follow-up workshops comprised of only engineering and information science students provided an opportunity to elaborate on the principles covered in the first workshop. The workshops revealed parallels and discrepancies in the conceptualization of improvisation between musicians and engineers. These thematic differences could inform considerations for future designers of improvising robots.
Highlights
This paper describes a series of workshops that were conducted with the goal of understanding what lessons researchers in AI and robotics can draw from the practice of musical improvisation in the process of designing improvising robots and AI-enabled musical instruments
As a result of all three meetings, we argue that the themes that emerged from the musicians’ human experiences of improvising both contrast and match the way that the group conceptualized machine improvisation
All workshop participants individually responded to two leading research questions: “What can AI and robotics learn by how improvisers think about time, space, actions, and decisions?” and “How can improvisation and musical instruments be enhanced by AI and robotics?” Participants were given 10 minutes to respond to the two questions
Summary
This paper describes a series of workshops that were conducted with the goal of understanding what lessons researchers in AI and robotics can draw from the practice of musical improvisation in the process of designing improvising robots and AI-enabled musical instruments. Improvisation for Musicians and Robotics Engineers tradition This opening question grounded the gathering as a joint venture between engineering and music by investigating cases for artificially intelligent improvisation agents. During this initial workshop, four improvisation themes crystallized: Improvisation as Spontaneity, Improvisation as Adaptability, Improvisation as Learning, and Improvisation as having an Inner Voice. Improvisation as Data highlights the fact that sound as data can be fed into a machine learning model While these translative themes might suggest that many workshop participants see AI improvisers in a diminished role, workshop contributors repeatedly considered AI and robotics as “superhuman,” embodying the idea of artificially intelligent agents transcending the human physical body, memory, and capacity to improvise. Our findings point to considerations that may be useful to designers of improvising robots trying to bridge the engineering and musical improvisation communities
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