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crea.blender: A Neural Network-Based Image Generation Game to Assess Creativity

arXiv 2008.05914 ↗First posted 13 Aug 2020cs.HCcited by 3

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Abstract (arXiv)

We present a pilot study on crea.blender, a novel co-creative game designed for large-scale, systematic assessment of distinct constructs of human creativity. Co-creative systems are systems in which humans and computers (often with Machine Learning) collaborate on a creative task. This human-computer collaboration raises questions about the relevance and level of human creativity and involvement in the process. We expand on, and explore aspects of these questions in this pilot study. We observe participants play through three different play modes in crea.blender, each aligned with established creativity assessment methods. In these modes, players "blend" existing images into new images under varying constraints. Our study indicates that crea.blender provides a playful experience, affords players a sense of control over the interface, and elicits different types of player behavior, supporting further study of the tool for use in a scalable, playful, creativity assessment.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Aug 2020.

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3 papers.