Telling Creative Stories Using Generative Visual Aids
This addresses how AI can boost divergent creativity in human-AI co-creation for writers and artists, though it is incremental in exploring cross-modality inputs.
The study investigated whether generative AI visuals enhance human creativity in storytelling, finding that writers using AI-generated images produced more creative, original, and complete stories, with VQGAN being the most preferred model, though the control group better integrated prompts.
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.