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arXiv · 2010.12324

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

Janet Rafner·Lotte Philipsen·Sebastian Risi·Joel Simon·Jacob Sherson
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Abstract

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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Janet Rafner, Lotte Philipsen, Sebastian Risi, Joel Simon, Jacob Sherson. 2020-10-15. The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems. https://arxiv.org/abs/2010.12324

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