An Interaction Framework for Studying Co-Creative AI

TL;DR

This paper introduces a general interaction framework for co-creative AI systems that supports human creativity and can guide future research in designing effective human-AI collaborative tools.

Contribution

It proposes a novel turn-based interaction framework for co-creative AI, aiding understanding and development of human-AI creative collaborations.

Findings

Framework helps compare different human-AI systems

Application to recent studies reveals design insights

Hypotheses for future co-creative AI research

Abstract

Machine learning has been applied to a number of creative, design-oriented tasks. However, it remains unclear how to best empower human users with these machine learning approaches, particularly those users without technical expertise. In this paper we propose a general framework for turn-based interaction between human users and AI agents designed to support human creativity, called {co-creative systems}. The framework can be used to better understand the space of possible designs of co-creative systems and reveal future research directions. We demonstrate how to apply this framework in conjunction with a pair of recent human subject studies, comparing between the four human-AI systems employed in these studies and generating hypotheses towards future studies.