The Creativity of Text-to-Image Generation
By Jonas Oppenlaender. International Conference on Entertainment and Media in the Ubiquitous Era, 2022
300 citations recorded by the source corpus.
Text-guided synthesis of images has made a giant leap towards becoming a mainstream phenomenon. With text-to-image generation systems, anybody can create digital images and artworks. This provokes the question of whether text-to-image generation is creative. This paper expounds on the nature of human creativity involved in text-to-image art (so-called “AI art”) with a specific focus on the practice of prompt engineering. The paper argues that the current product-centered view of creativity falls short in the context of text-to-image generation. A case exemplifying this shortcoming is provided and the importance of online communities for the creative ecosystem of text-to-image art is highlighted. The paper provides a high-level summary of this online ecosystem drawing on Rhodes’ conceptual four P model of creativity. Challenges for evaluating the creativity of text-to-image generation and opportunities for research on text-to-image generation in the field of Human-Computer Interaction (HCI) are discussed.
Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Mechanical Engineering
View Paper: https://www.semanticscholar.org/paper/b66c1c7617b42f3814d516faf7d2ca3b771a0c9e
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In Cognitive Neuroscience
In Experimental and Cognitive Psychology
In Mechanical Engineering
Citations in the corpus
- Generative artificial intelligence (2023, background): “…a text-to-image creation process, image editing capabilities are possible, e.g., via image-to-image systems that manipulate and extend images according to the user’s prompting (Oppenlaender, 2022) Video X-to-video applications deal with the creation of synthetic videos, i.e., dynamic motion images.”