The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2020.
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- 2021Exploring Latent Dimensions of Crowd-sourced Creativitycited by 0
- 2021Exploring Latent Dimensions of Crowd-sourced Creativity13 Dec 2021