The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems

Rafner, Janet, Philipsen, Lotte, Risi, Sebastian, Simon, Joel, Sherson, Jacob

arXiv.org Artificial Intelligence 

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.

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