HYBRIDS: Hybrid Intelligence to monitor, promote and analyse transformations in good democracy practices

通过社交媒体针对弱势少数群体的虚假谣言、假新闻或仇恨言论正在成为对民主的主要威胁之一。打击虚假信息的全球战略至关重要，因为开放的民主社会依赖于能够获得可核实信息的自由公民，以便他们能够就不同的政治问题建立自己的观点。混合体的主要科学目标是为研究人员提供必要的知识，以便在对公共话语进行深入分析的基础上，设计应对虚假信息的策略和工具。在机器和深度学习的特定领域，利用自然语言处理和新的人工智能技术进行虚假信息的自动检测已经取得了有趣的进展，但这是一项非常复杂的任务，需要高度的自然语言理解、推理和推理。为了改进处理虚假信息的策略，混合体将把社会科学和人文科学提供的结构化知识整合到自然语言处理工具和深度学习算法中，从而开发新的混合型智能系统。混合智能的概念是将机器智能和人类智能结合起来，以克服现有人工智能方法的缺点。即使混合系统在不久的将来可能变得越来越决定性，但能够设计和开发这样的系统的专家很少。这主要是因为混合战略具有多学科性质，而且很难找到在计算机工程、社会科学或语言学等传统上受过独立学科培训的研究人员。我们认为，现在是启动具有必要要求的发展网络的时候了，以培训研究人员混合方法，使其在社会研究中的应用对欧洲良好民主做法的可持续性产生影响。

False rumors, fake news or hate speech against vulnerable minorities through social media are becoming one of the main threats against democracies. A global strategy against disinformation is crucial as open democratic societies rely on free citizens with the ability to access verifiable information so that they can build their own opinions on different political issues. The main scientific objective of HYBRIDS is to provide researchers with the knowledge necessary to design strategies and tools to response to disinformation on the basis of a deep analysis of public discourse. There have been interesting advances in the automatic detection of disinformation by making use of natural language processing and new artificial intelligence techniques in the specific field of machine and deep learning.However, this is a very complex task that requires a high degree of natural language understanding, inference and reasoning. To improve the strategies to deal with disinformation, HYBRIDS will integrate the structured knowledge provided by social and human sciences into natural language processing tools and deep learning algorithms, so as to develop new hybrid intelligence systems. The concept of Hybrid Intelligence consists of combining machine and human intelligence to overcome the shortcomings of existing artificial intelligence methods.Even though hybrid systems are likely to become more and more decisive in the immediate future, there are very few experts who can design and develop such systems. This is mainly due to the multidisciplinary nature of the hybrid strategy and the difficulty of finding researchers with full training in traditionally separate disciplines such as computer engineering, social sciences or linguistics. We believe it is time to launch a DN with the necessary requirements to train researchers in hybrid methodologies for their application in social studies with an impact on the sustainability of good democratic practices in Europe.