Lessons From Joint Improvisation Workshops for Musicians and Robotics Engineers

Area of Science:

• Human-Computer Interaction
• Robotics
• Music Cognition
• Artificial Intelligence

Background:

• Interdisciplinary design research offers novel approaches to understanding complex human behaviors like improvisation.
• Exploring the intersection of human improvisation and artificial intelligence (AI) / robotics is crucial for developing advanced interactive systems.

Purpose of the Study:

• To investigate how musicians' and robotics engineers' conceptualizations of improvisation align and diverge.
• To identify potential areas where AI and robotics can learn from human improvisers.
• To explore how AI and robotics can enhance musical improvisation and instruments.

Main Methods:

• Conducted a series of interdisciplinary workshops involving musicians and robotics engineers.
• Included educational sessions on musical improvisation theory and practice, and AI principles.
• Organized follow-up workshops with engineering and information science students for deeper elaboration.

Main Results:

• Identified parallels and discrepancies in the conceptualization of improvisation between musicians and engineers.
• Highlighted differing perspectives on time, space, actions, and decision-making in improvisation.
• Revealed insights into how AI and robotics might be designed to better support or emulate improvisational processes.

Conclusions:

• The identified thematic differences between musicians and engineers are critical for informing the design of future improvising robots.
• This research provides a foundation for developing AI and robotic systems that can engage in more nuanced and human-like improvisation.
• Further research can leverage these insights to create more sophisticated human-robot collaborative improvisation systems.