TY - GEN
T1 - Utopian or Dystopian?: Using a ML-Assisted image generation game to empower the general public to envision the future
AU - Rafner, Janet
AU - Langsford, Steven
AU - Philipsen, Lotte
AU - Risi, Sebastian
AU - Hjorth, Arthur
AU - Simon, Joel
AU - Gajdacz, Miroslav
AU - Sherson, Jacob
N1 - Publisher Copyright: © 2021 ACM.; 13th Conference on Creativity and Cognition, C&C '21 ; Conference date: 22-06-2021 Through 23-06-2021
Doesn't seem to count as OA? (jcg: 14/02/2022)
PY - 2021/6/1
Y1 - 2021/6/1
N2 - 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.
AB - 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.
KW - Digital Technologies
KW - Machine Learning Tools
KW - Creative Expression
KW - Sustainable Development Goals
KW - GAN-based Image Generation
KW - Creativity and Cognition
KW - Public Participation in Research
KW - Socioscientific Problems
KW - User-Generated Content
KW - Dystopian and Utopian Imagery
UR - https://sebastianrisi.com/wp-content/uploads/cc_rafner2021.pdf
U2 - 10.1145/3450741.3466815
DO - 10.1145/3450741.3466815
M3 - Article in proceedings
SN - 9781450383769
T3 - ACM International Conference Proceeding Series
BT - Creativity and cognition (C&C '21)
PB - Association for Computing Machinery
CY - United States
ER -