Relating cognitive models of design creativity to the similarity of sketches generated by an AI partner

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Abstract

This paper presents and evaluates a new method for inspiring creativity in a co-creative design system. The method uses a computational model of aconceptual shift based on clustering of deep features from a database of sketches. The co-creative sketching tool maps a user's sketch to a sketch of a distinct category that has high, medium, or low visual and semantic similarity. We hypothesize that the degree of similarity between the user's and the system's sketches is associated with a range of cognitive models of creativity in a design context. We report on the findings of an empirical study that analyzes different design scenarios in which the user sketches in response to a proposed conceptual shift. The findings show that how similar the computational agent's sketch is to the user's original sketch is related to the presence of three types of design creativity in the user's response: combinatorial, exploratory, and transformational.

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Karimi, P., Davis, N., Maher, M. L., Grace, K., & Lee, L. (2019). Relating cognitive models of design creativity to the similarity of sketches generated by an AI partner. In C and C 2019 - Proceedings of the 2019 Creativity and Cognition (pp. 259–270). Association for Computing Machinery, Inc. https://doi.org/10.1145/3325480.3325488

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