Utopian or Dystopian?: Using a ML-Assisted image generation game to empower the general public to envision the future

Janet Rafner, Steven Langsford, Lotte Philipsen, Sebastian Risi, Arthur Hjorth, Joel Simon, Miroslav Gajdacz, Jacob Sherson

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


The rise of digital technologies and Machine Learning (ML)-Tools for creative expression brings about novel opportunities for studying creativity and cognition at scale. In this paper, we present a pilot study of crea.blender SDG-an online GAN based image generation game. We designed crea.blender SDG with two goals in mind: The first, to let people create images relating to the United Nations Sustainable Development Goals (SDGs) and through them, engage in large-scale conversations on complex socioscientific problems. The second, as a fun and inspiring gateway for public participation in research, generating data for the creativity and cognition research and design community. Specifically in this pilot, we study and affirm that the design of crea.blender SDG is flexible enough to allow users to create images that express both anxiety and hope for the future; affirm that user generated images express these ideas in ways that are meaningful to people other than the original creator; and begin to investigate which specific features of images are more closely related to dystopian or utopian ideas of the future. Finally, we discuss implications for future design and research with ML-based creativity tools.
Original languageEnglish
Title of host publicationCreativity and cognition (C&C '21)
Place of PublicationUnited States
PublisherAssociation for Computing Machinery
Publication date1 Jun 2021
ISBN (Print)9781450383769
Publication statusPublished - 1 Jun 2021
SeriesACM International Conference Proceeding Series


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