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.
arXiv.org Artificial Intelligence
Oct-15-2020
- Country:
- Asia
- Japan > Honshū
- Kantō > Tokyo Metropolis Prefecture > Tokyo (0.05)
- Middle East > Saudi Arabia (0.05)
- Nepal (0.05)
- Japan > Honshū
- Europe
- Denmark > Capital Region
- Copenhagen (0.05)
- Switzerland > Geneva
- Geneva (0.05)
- United Kingdom (0.05)
- Denmark > Capital Region
- Asia
- Genre:
- Research Report (0.50)
- Technology: