论文标题
当快乐事故发生时，会激发创造力：与生成的AI一起进行协作猜测
When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI
论文作者
论文摘要
像从文本（文本到图像模型）合成图像的生成性AI技术一样，为创造性地想象新想法提供了新的可能性。我们研究了这些模型的能力，以帮助社区就其集体未来进行对话。特别是，我们设计和部署了一种便利的体验，参与者会协作猜测他们想要看到的乌托邦，然后从这些猜测中产生AI生成的图像。在一系列深入的用户访谈中，我们邀请参与者反思生成的图像并改善他们对未来的愿景。我们将发现与定制的社区杂志合成了这种经验。我们观察到，参与者经常产生想法来实施他们的愿景，并引起新的横向注意事项，从而查看了生成的图像。至关重要的是，我们发现参与者想象的输出与生成的图像之间的意外差异是为参与者提供新的见解。我们希望我们的共同创造，计算创造力和社区反思的实验模型激发了生成模型的使用，以帮助社区和组织设想更好的未来。
Generative AI techniques like those that synthesize images from text (text-to-image models) offer new possibilities for creatively imagining new ideas. We investigate the capabilities of these models to help communities engage in conversations about their collective future. In particular, we design and deploy a facilitated experience where participants collaboratively speculate on utopias they want to see, and then produce AI-generated imagery from those speculations. In a series of in-depth user interviews, we invite participants to reflect on the generated images and refine their visions for the future. We synthesize findings with a bespoke community zine on the experience. We observe that participants often generated ideas for implementing their vision and drew new lateral considerations as a result of viewing the generated images. Critically, we find that the unexpected difference between the participant's imagined output and the generated image is what facilitated new insight for the participant. We hope our experimental model for co-creation, computational creativity, and community reflection inspires the use of generative models to help communities and organizations envision better futures.
