Strengthening demOcratic engagement through vaLue-bAsed geneRative adversarIal networkS

Generative adversarial networks (GANs) are a class of AI models able to create media contents audio and video resembling reality. Although there are different promising areas of application of GANs e.g. audio-graphic productions, human-computer interactions, satire, artistic creative expression their current and foreseen misleading uses are just as numerous and worrying. The main concern is related to the so-called deepfakes, fake images or videos simulating real events with extreme precision. If trained on a face, GANs can make it move and speak in a hyper-realistic way. This technology poses an urgent political threat since GANs could be and have already been used to spread fake news and disinformation.This raises an urgent challenge to democratic governance and regulation: to improve GANs accountability, transparency, and trustworthiness. Nevertheless, GANs also constitute an opportunity to enhance democratic awareness and expand active and inclusive citizenship.SOLARIS reacts to these challenges in two ways. On the one hand, we analyse political risks associated with these technologies, to prevent negative implications for EU democracies. As a result, SOLARIS will establish regulatory innovations to detect and mitigate deepfake risks. On the other hand, we assess the opportunities raised by GANs for reinvigorating the democratic engagement of citizens. We will co-create, involving citizen science, value-based GANs contents to enhance democratic engagement. SOLARIS involves three use cases: the first aims at understanding the psychological aspects of GANs perceived trustworthiness. The second simulates the circulation of threatening GANs contents on social media, to detect risks and design mitigation strategies. The third co-creates value-based GANs contents to boost awareness on key global democratic topics (e.g: climate change, gender dimension, human migration), to ultimately enhance active and inclusive digital citizenship.