论文标题

图片的力量:使用M​​L辅助图像生成使人群陷入复杂的社会科学问题

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

论文作者

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

论文摘要

使用生成的对抗网络(GAN)生成人类计算机形象,正在成为一种娱乐和开放艺术探索的良好方法。在这里,我们通过编织精心构造的设计元素来将互动进一步发展,以将ML辅助成像的生成的活动转变为大规模的大规模流行对话,就复杂的社会科学问题(例如联合国可持续发展目标(SDG))和作为公众参与研究的门户的大规模社会科学问题。

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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