Summary
"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."
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."
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101135757 |
| Start date: | 01-01-2024 |
| End date: | 31-12-2027 |
| Total budget - Public funding: | - 4 895 182,00 Euro |
Cordis data
Original description
"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."
Status
SIGNEDCall topic
HORIZON-CL4-2023-HUMAN-01-05Update Date
12-03-2024
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Organisations
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| LATVIJAS UNIVERSITATE (Coördinator)
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| BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION (BSC)
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| CONSIGLIO NAZIONALE DELLE RICERCHE (CNR)
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| CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI (CNIT)
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| DOTSOFT OLOKLIROMENES EFARMOGES DIADIKTIOY KAI VASEON DEDOMENON AE
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| F6S NETWORK IRELAND LIMITED (F6S)
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| FREE MEDIA BULGARIA
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| INTERNEWS UKRAINE
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| NATIONAL UNIVERSITY OF IRELAND GALWAY (NUI Galway)
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| PILOT4DEV
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| STICHTING INNOVATIVE POWER
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| Stichting Hogeschool Utrecht
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| UNIVERSITA DEGLI STUDI DI FIRENZE - University of Florence
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| UNIVERSITE DE MONS