Human-in-the-loop Artificial Intelligence for Fighting Online Misinformation: Challenges and Opportunities

Abstract

The rise of online misinformation is posing a threat to the functioning of democratic processes. The ability to algorithmically spread false information through online social networks together with the data-driven ability to profile and micro-target individual users has made it possible to create customized false content that has the potential to influence decision making processes. Fortunately, similar data-driven and algorithmic methods can also be used to detect misinformation and to control its spread. Automatically estimating the reliability and trustworthiness of information is, however, a complex problem and it is today addressed by heavily relying on human experts known as fact-checkers. In this paper, we present the challenges and opportunities of combining automatic and manual fact-checking approaches to combat the spread on online misinformation also highlighting open research questions that the data engineering community should address.

Publication
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering

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