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

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review


We present a pilot study on crea.blender, a novel co-creative game designed for large-scale, systematic assessment of distinct con- structs of human creativity. Co-creative systems are systems in which humans and computers (often with Machine Learning) col- laborate 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.
Original languageEnglish
Title of host publicationCHI PLAY 2020 - Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play
Number of pages5
Place of publicationNew York
PublisherAssociation for Computing Machinery
Publication year2 Nov 2020
ISBN (Electronic)9781450375870
Publication statusPublished - 2 Nov 2020

    Research areas

  • Co-creative systems, divergent thinking, convergent thinking, GAN

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ID: 199948516