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.
翻译:使用基因化视觉算法创造的视觉艺术能够激发人类在讲故事方面的创造力吗?我们要求作家从一开始即刻开始写创作性的故事,并向他们提供由同一瞬时的基因化AI模型创造的视觉。 与控制组相比,用视觉来写故事帮助写故事的作者写了更富有创造性、原创性、完整和可视觉化的故事,发现任务更有趣。 在使用的基因化算法(BigGAN、VQGAN、DALL-E、CLIPLaw)中,VQGAN是最首选的。没有观察视觉的对照组在整合起始点方面做得更好。 研究结果表明,AI的跨模式投入可以给人类-AI共同创作中的创造力的不同方面带来好处,但会阻碍共思。