The generation and massive proliferation of false, malicious and / or biased information today has caused the loss of confidence in the institutions that historically have had the role of producing and managing information. This phenomenon affects from scientific knowledge, to news disseminated by the media, and includes governments and organizations. This loss of confidence generates uncertainty and confusion in the citizens.
Is it possible to create systems that allow people to obtain accurate information to have a less biased and confusing view of reality? And, at the same time, can the volume of information produced by users of digital platforms be used by science to obtain a clearer picture of the uses and communication phenomena that emerge in the digital universe?
The Millennium Institute Foundational Research of Data is currently working on the study, characterization and forms of generation of what we call “robust information”, that truthful knowledge that can be extracted from non-structured sources of data. By non-structured sources this we mean all the digital content generated by the people on the web, social networks, multimedia information or online text written in natural language.
This project involves several challenges. The first is to analyze and understand the obstacles and difficulties related to the development of robust structures. Then, we have to ensure that these structures work efficiently and, finally, to be able to fight misinformation and malicious information with these systems.
In particular, we will focus on the areas most affected by the lack of robuts information systems, such as the functioning of democracy and the deficits of legitimacy, as also the segmentation and social fragmentation. These dimensions have been vulnerated by the consolidation of bubble filters that radicalize public opinion, the negative mobilization achieved by fake-news and the spreading of viral campaigns focused on homogenous and polarized publics.
Strategic lines of work
-Systems to distinguish automatically true information from false information.
-Characterization of misinformation, its contents and distribution forms.
-Active promotion of robust information structures, to encourage their use and to achieve high impact and influence.
-Detection and understanding of both organized and spontaneous activity around hate speech, discrimination and misinformation.
Juan Pablo Luna
Maria Fernanda Sepulveda