The Dynamic Creativity of Proto-artifacts in Generative Computational Co-creation

TL;DR

This paper investigates how to assess the creative merit of intermediate artifacts in human-AI collaborative creative processes, proposing a simplified two-attribute evaluation method based on value and novelty.

Contribution

It introduces a streamlined two-attribute framework for evaluating unfinished creative artifacts, reducing complexity compared to traditional three-attribute models.

Findings

A two-attribute model based on value and novelty suffices for assessing creativity.

Simplifies evaluation of numerous unfinished artifacts in computational co-creation.

Reduces the metrics needed for assessing creative merit in CCC processes.

Abstract

This paper explores the attributes necessary to determine the creative merit of intermediate artifacts produced during a computational co-creative process (CCC) in which a human and an artificial intelligence system collaborate in the generative phase of a creative project. In an active listening experiment, subjects with diverse musical training (N=43) judged unfinished pieces composed by the New Electronic Assistant (NEA). The results revealed that a two-attribute definition based on the value and novelty of an artifact (e.g., Corazza's effectiveness and novelty) suffices to assess unfinished work leading to innovative products, instead of Boden's classic three-attribute definition of creativity (value, novelty, and surprise). These findings reduce the creativity metrics needed in CCC processes and simplify the evaluation of the numerous unfinished artifacts generated by computational creative assistants.