SOLARIS : Strengthening democratic engagement through value based generative adversarial networks

SOLARIS：通过基于价值的生成对抗网络加强民主参与

• 批准号: 10046757
• 金额: $ 23.99万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10046757
• 关键词: SOLARIS; Strengthening; democratic; engagement; through

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 isrelated to the so-called “deepfakes”, fake images or videos simulating real events with extreme precision. If trained on a face, GANscan make it move and speak in a hyper-realistic way. This technology poses an urgent political threat since GANs could be – and havealready 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 enhancedemocratic 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, SOLARISwill establish regulatory innovations to detect and mitigate deepfake risks. On the other hand, we assess the opportunities raised by GANsfor reinvigorating the democratic engagement of citizens. We will co-create, involving citizen science, value-based GANs contents toenhance democratic engagement. SOLARIS involves three use cases: the first aims at understanding the psychological aspects of GANsperceived trustworthiness. The second simulates the circulation of threatening GANs contents on social media, to detect risks and designmitigation strategies. The third co-creates value-based GANs contents to boost awareness on key global democratic topics (e.g: climatechange, gender dimension, human migration), to ultimately enhance active and inclusive digital citizenship.

生成对抗网络（GAN）是一类能够创建类似于现实的媒体内容（音频和视频）的人工智能模型。尽管 GAN 有不同的有前景的应用领域，例如音频图形制作、人机交互、讽刺、艺术等。创意表达——它们当前和预见的误导性用途同样众多且令人担忧，主要问题与所谓的“深度伪造”、经过训练的极其精确地模拟真实事件的虚假图像或视频有关。从表面上看，GAN 可以使其以超现实的方式移动和说话，因为 GAN 可能并且已经被用来传播假新闻和虚假信息，这对民主治理和虚假信息提出了紧迫的挑战。监管：提高 GAN 的问责性、透明度和可信度 然而，GAN 也提供了增强民主意识和扩大积极和包容性公民意识的机会。 SOLARIS 通过两种方式应对这些挑战。分析与这些技术相关的政治风险，以防止对欧盟民主产生负面影响。因此，SOLARIS 将建立监管创新来检测和减轻深度造假风险。另一方面，我们评估 GAN 为重振公民民主参与带来的机会。我们将共同创建基于价值的 GAN 内容，以增强民主参与，SOLARIS 涉及三个用例：第一个旨在理解 GAN 感知的可信度的心理方面。第二个模拟威胁性 GAN 内容在社交媒体上的传播，以检测风险并设计缓解策略。第三个共同创建基于价值的 GAN 内容，以提高对全球关键民主主题（例如：气候变化、性别维度、人类移民）的认识。最终增强积极和包容的数字公民身份。