Veracity: An Open-Source AI Fact-Checking System
Veracity: An Open-Source AI Fact-Checking System
Taylor Lynn Curtis, Maximilian Puelma Touzel, William Garneau, Manon Gruaz, Mike Pinder, Li Wei Wang, Sukanya Krishna, Luda Cohen, Jean-François Godbout, Reihaneh Rabbany, Kellin Pelrine
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Demo Track. Pages 11021-11024.
https://doi.org/10.24963/ijcai.2025/1254
The proliferation of misinformation poses a significant threat to society, exacerbated by the capabilities of generative AI.
This demo paper introduces Veracity, an open-source AI system designed to empower individuals to combat misinformation through transparent and accessible fact-checking. Veracity leverages the synergy between Large Language Models (LLMs) and web retrieval agents to analyze user-submitted claims and provide grounded veracity assessments with intuitive explanations. Key features include multilingual support, numerical scoring of claim veracity, and an interactive interface inspired by familiar messaging applications. This paper will showcase Veracity's ability to not only detect misinformation but also explain its reasoning, fostering media literacy and promoting a more informed society.
Keywords:
Multidisciplinary Topics and Applications: MTA: Software engineering
AI Ethics, Trust, Fairness: ETF: Trustworthy AI
Humans and AI: HAI: Human-computer interaction
Multidisciplinary Topics and Applications: MTA: News and media
