Abstract
Abstract
With the rise of Generative Adversarial Networks (GANs), AI has increasingly become a partner to human designers in
co-creating cultural artifacts. While generative models have been applied in various creative tasks across disciplines, a
theoretical foundation for understanding human-GAN collaboration is yet to be developed. Drawing from the mixed-initiative
co-creation community, we propose a preliminary framework to analyze co-creative GAN applications. We identify four
primary interaction patterns: Curating, Exploring, Evolving, and Conditioning. The suggested framework enables us to discuss
the affordances and limitations of the different kind of interactions underlying co-creative GAN applications
With the rise of Generative Adversarial Networks (GANs), AI has increasingly become a partner to human designers in
co-creating cultural artifacts. While generative models have been applied in various creative tasks across disciplines, a
theoretical foundation for understanding human-GAN collaboration is yet to be developed. Drawing from the mixed-initiative
co-creation community, we propose a preliminary framework to analyze co-creative GAN applications. We identify four
primary interaction patterns: Curating, Exploring, Evolving, and Conditioning. The suggested framework enables us to discuss
the affordances and limitations of the different kind of interactions underlying co-creative GAN applications
| Original language | English |
|---|---|
| Title of host publication | Proceeding of the 3rd Workshop on Human-AI Co-Creation with Generative Models (HAI-GEN ‘22)at ACM IUI Workshops |
| Publication date | 2022 |
| Publication status | Published - 2022 |
Keywords
- Generative Adversarial Networks
- Co-creation
- Human-AI Collaboration
- Mixed-Initiative Interaction
- Interaction Patterns
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Towards a Framework for Human-AI Interaction Patterns in Co-Creative GAN Applications
09/08/2023
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