Automated Fact-Checking of Climate Change Claims with Large Language Models

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Hauptverfasser: Leippold, Markus, Vaghefi, Saeid Ashraf, Stammbach, Dominik, Muccione, Veruska, Bingler, Julia, Ni, Jingwei, Colesanti-Senni, Chiara, Wekhof, Tobias, Schimanski, Tobias, Gostlow, Glen, Yu, Tingyu, Luterbacher, Juerg, Huggel, Christian
Format: Preprint
Veröffentlicht: 2024
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author Leippold, Markus
Vaghefi, Saeid Ashraf
Stammbach, Dominik
Muccione, Veruska
Bingler, Julia
Ni, Jingwei
Colesanti-Senni, Chiara
Wekhof, Tobias
Schimanski, Tobias
Gostlow, Glen
Yu, Tingyu
Luterbacher, Juerg
Huggel, Christian
author_facet Leippold, Markus
Vaghefi, Saeid Ashraf
Stammbach, Dominik
Muccione, Veruska
Bingler, Julia
Ni, Jingwei
Colesanti-Senni, Chiara
Wekhof, Tobias
Schimanski, Tobias
Gostlow, Glen
Yu, Tingyu
Luterbacher, Juerg
Huggel, Christian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_12566
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Automated Fact-Checking of Climate Change Claims with Large Language Models
Leippold, Markus
Vaghefi, Saeid Ashraf
Stammbach, Dominik
Muccione, Veruska
Bingler, Julia
Ni, Jingwei
Colesanti-Senni, Chiara
Wekhof, Tobias
Schimanski, Tobias
Gostlow, Glen
Yu, Tingyu
Luterbacher, Juerg
Huggel, Christian
Computation and Language
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.
title Automated Fact-Checking of Climate Change Claims with Large Language Models
topic Computation and Language
url https://arxiv.org/abs/2401.12566