Disinformation, produced and spread on the Web via social media platforms, websites, and forums is not a new phenomenon, but it has taken on an unprecedented scale since 2016 with the campaign for the presidential election in the US, the Brexit campaign, and in 2017 with the French presidential campaign. These days the acute health crisis associated with Covid-19 has exacerbated this problem considerably. Online social media platforms try to limit the virality of disinformation spread for example through content moderation. Whilst these measures show some kind of effectiveness in limiting the diffusion of misleading or fake information, this issue still persists: identifying disinformation and reporting its status to the users is not enough to counter it. Indeed, there is a need to design intelligent solutions to fight the spread of disinformation in a pedagogical way, to persuade the user to stop the viral spreading of false information by providing verified counter-arguments.
In the ATTENTION project, we propose to address that urgent need by designing intelligent ways to identify disinformation online and generate counter-arguments to fight the spread of such information online. The idea is to avoid the undesired effects that come with content moderation when dealing with online disinformation, such as overblocking, and to directly intervene in the discussion, (e.g., Twitter threads) by engaging with people spreading incorrect information, through textual arguments that are meant to counter the fake content as soon as possible, and prevent it from further spreading. The project tackles this issue from a multidisciplinary perspective including law, sociology and Artificial Intelligence in order to ensure as a result AI solutions compliant with the ethical and sociological challenges connected to online disinformation.
Madame Villata Serena (Laboratoire informatique, signaux systèmes de Sophia Antipolis)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
I3S Laboratoire informatique, signaux systèmes de Sophia Antipolis
EA4150 INSTITUT DE RECHERCHES JURIDIQUES DE LA SORBONNE
Buster.AI BusterAI / Julien Mardas
CMH Centre Maurice Halbwachs
Help of the ANR 521,989 euros
Beginning and duration of the scientific project: December 2021 - 36 Months