Telling Creative Stories Using Generative Visual Aids
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Abstract (arXiv)
Can visual artworks created using generative visual algorithms inspire human creativity in storytelling? We asked writers to write creative stories from a starting prompt, and provided them with visuals created by generative AI models from the same prompt. Compared to a control group, writers who used the visuals as story writing aid wrote significantly more creative, original, complete and visualizable stories, and found the task more fun. Of the generative algorithms used (BigGAN, VQGAN, DALL-E, CLIPDraw), VQGAN was the most preferred. The control group that did not view the visuals did significantly better in integrating the starting prompts. Findings indicate that cross modality inputs by AI can benefit divergent aspects of creativity in human-AI co-creation, but hinders convergent thinking.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 5 of its 16 references that are in the map. First posted on arXiv 27 Oct 2021.
Builds on
5 of 16 references.
References · 5
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2021Zero-Shot Text-to-Image Generationcited by 4,288
- 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
- 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,626
- 2021CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoderscited by 187
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Citing papers per year: 2022: 1; 2023: 1; 2024: 1.
3 papers.