Defining and Quantifying Creative Behavior in Popular Image Generators
This work addresses the need for objective criteria to evaluate AI creativity, which is incremental as it builds on existing debates without proposing a new paradigm.
The paper tackled the problem of quantifying creativity in generative AI models by introducing practical measures to help users select appropriate image-to-image generation models, with results showing that these measures align with human intuition.
Creativity of generative AI models has been a subject of scientific debate in the last years, without a conclusive answer. In this paper, we study creativity from a practical perspective and introduce quantitative measures that help the user to choose a suitable AI model for a given task. We evaluated our measures on a number of popular image-to-image generation models, and the results of this suggest that our measures conform to human intuition.