Automated Fact-Checking of Climate Change Claims with Large Language
  Models
Markus Leippold Saeid Ashraf Vaghefi Dominik Stammbach Veruska Muccione Julia Bingler Jingwei Ni Chiara Colesanti-Senni Tobias Wekhof Tobias Schimanski Glen Gostlow Tingyu Yu Juerg Luterbacher Christian Huggel
This paper presents Climinator, a novel AI-based tool designed to automate
the fact-checking of climate change claims. Utilizing an array of Large
Language Models (LLMs) informed by authoritative sources like the IPCC reports
and peer-reviewed scientific literature, Climinator employs an innovative
Mediator-Advocate framework. This design allows Climinator to effectively
synthesize varying scientific perspectives, leading to robust, evidence-based
evaluations. Our model demonstrates remarkable accuracy when testing claims
collected from Climate Feedback and Skeptical Science. Notably, when
integrating an advocate with a climate science denial perspective in our
framework, Climinator's iterative debate process reliably converges towards
scientific consensus, underscoring its adeptness at reconciling diverse
viewpoints into science-based, factual conclusions. While our research is
subject to certain limitations and necessitates careful interpretation, our
approach holds significant potential. We hope to stimulate further research and
encourage exploring its applicability in other contexts, including political
fact-checking and legal domains.