Skip to main content
European Commission logo print header

Participative Assistive AI-powered Tools for Supporting Trustworthy Online Activity of Citizens and Debunking Disinformation

Project description

Innovative platform to debunk disinformation content

Disinformation poses a significant threat to modern democracies. Thus, new solutions are needed to debunk its contents successfully. The EU-funded AI4Debunk project aims to create four AI-powered interfaces centred around humans. These interfaces include a web plug-in, a collaborative platform, a smartphone app and an augmented reality (AR) interface, which will all be built using a debunking application programming interface, or API. The project will focus on disinformation on the war in Ukraine and climate change, and map disinformation content onto knowledge graphs and compare it to existing databases. The platform, named Disinfopedia, is designed to instantly detect fake content. The app verifies content in everyday life, and the AR interface provides insight into fake news and social media.


"AI4Deunk aims to develop 4 human-centered AI-powered interfaces: a web plug-in, a collaborative platform, a smartphone app, and an AR interface. All these solutions will be built upon a ""debunking"" API.

To develop such an API, AI4Debunk will focus on 2 peculiar disinformation topics: the war in Ukraine and disinformation related to climate change. By deeply analysing these case studies thanks to sociological experts (targets groups, sources, way of diffusion...) we will map disinformation contents on knowledge graphs, and compare them to existing databases thanks to AI methods such as NLP. These knowledge graphs will be the skeleton of our technical work: one will be multimodal meaning that all types of modalities (written content, image, video) will be directly embedded, while the monomodal will be only about written content (the different modalities will be previously embedded into written content).

Then debunking modules will be developed, for each type of modality, based on AI and ML methods that could detect and examine questionable content, by comparing it to the context extracted from the knowledge graphs. RNN, CNN, multi-modal language interpretation, and transformers methods will be used to that extent. The goal of such modules is to give a score of fakeness, which we will call Disinofscore, for content given as input.

The API will then integrate this method and will be the bases of the 4 interfaces abovementioned. The plugin will allow people to be instantly noticed when a content they are considering is fake or true, the collaborative platform - also called Disinfopedia, will allow more proactive online users to report questionable content, that will be checked by a debunking committee chaired by a senior analyst, the app interface will allow people to check content in their everyday life, while the AR interface will allow citizens to have hindsight on the incoming generation of fake news and social media."


Net EU contribution
€ 511 968,13
1586 RIGA

See on map

Latvija Latvija Rīga
Activity type
Higher or Secondary Education Establishments
Total cost
No data

Participants (13)