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

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Authors Janet Rafner, Lotte Philipsen, Sebastian Risi, Joel Simon, Jacob Sherson arXiv ID 2010.12324 Category cs.HC: Human-Computer Interaction Cross-listed cs.AI Citations 1 Venue arXiv.org Last Checked 4 months ago
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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