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

TL;DR

This paper explores how ML-assisted image generation, specifically using GANs, can be structured to foster large-scale public dialogue and participation on complex socioscientific issues like the SDGs.

Contribution

It introduces a novel approach integrating design elements into GAN-based image generation to engage the public in socioscientific discussions and research participation.

Findings

Enhanced public engagement in socioscientific debates

Effective use of GANs for educational and participatory purposes

Potential for scaling public dialogue through visual media

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.