The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems
This work addresses the challenge of public engagement in socioscientific problems, though it appears incremental by building on existing GAN-based image generation methods.
The paper tackled the problem of engaging the public in complex socioscientific issues by using ML-assisted image generation, resulting in a method that transforms this activity into a catalyst for large-scale dialogue and public participation in research related to the UN Sustainable Development Goals.
Human-computer image generation using Generative Adversarial Networks (GANs) is becoming a well-established methodology for casual entertainment and open artistic exploration. Here, we take the interaction a step further by weaving in carefully structured design elements to transform the activity of ML-assisted imaged generation into a catalyst for large-scale popular dialogue on complex socioscientific problems such as the United Nations Sustainable Development Goals (SDGs) and as a gateway for public participation in research.