Directing the Robot: Scaffolding Creative Human-AI-Robot Interaction

TL;DR

This paper proposes a scaffolding approach to human-AI-robot interaction, emphasizing human creativity and control in open-ended, improvisational settings, moving beyond performance-focused frameworks.

Contribution

It introduces a novel scaffolding framework for AI-robot interaction that enhances human agency and creativity, supported by practical scenarios and design implications.

Findings

Humans can act as directors, guiding robotic behavior over time.

AI mediates between human intent and robotic execution.

The approach fosters creativity, agency, and flow in interactions.

Abstract

Robots are moving beyond industrial settings into creative, educational, and public environments where interaction is open-ended and improvisational. Yet much of human-AI-robot interaction remains framed around performance and efficiency, positioning humans as supervisors rather than collaborators. We propose a re-framing of AI interaction with robots as scaffolding: infrastructure that enables humans to shape robotic behaviour over time while remaining meaningfully in control. Through scenarios from creative practice, learning-by-teaching, and embodied interaction, we illustrate how humans can act as executive directors, defining intent and steering revisions, while AI mediates between human expression and robotic execution. We outline design and evaluation implications that foreground creativity, agency, and flow. Finally, we discuss open challenges in social, scalable, and mission-critical contexts. We invite the community to rethink interacting with Robots and AI not as autonomy, but as sustained support for human creativity.