Automated Fact-Checking for Assisting Human Fact-Checkers

TL;DR

This paper surveys intelligent technologies that assist human fact-checkers by automating claim identification, evidence retrieval, and verification, aiming to improve the efficiency and accuracy of fact-checking in the digital age.

Contribution

It provides a comprehensive overview of current AI tools supporting fact-checking processes, highlighting challenges and future directions for integrating automation with human expertise.

Findings

Identifies key AI tasks in fact-checking workflow

Discusses challenges in claim detection and evidence retrieval

Outlines potential impact on real-world fact-checking

Abstract

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism. Nowadays, politicians and other key players enjoy direct access to their audiences through social media, bypassing the filters of official cables or traditional media. However, the multiple advantages of free speech and direct communication are dimmed by the misuse of media to spread inaccurate or misleading claims. These phenomena have led to the modern incarnation of the fact-checker -- a professional whose main aim is to examine claims using available evidence and to assess their veracity. As in other text forensics tasks, the amount of information available makes the work of the fact-checker more difficult. With this in mind, starting from the perspective of the professional fact-checker, we survey the available intelligent technologies that can support the human expert in the different steps of her fact-checking endeavor. These include identifying claims worth fact-checking, detecting relevant previously fact-checked claims, retrieving relevant evidence to fact-check a claim, and actually verifying a claim. In each case, we pay attention to the challenges in future work and the potential impact on real-world fact-checking.