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<p>Accurate identification of true versus false climate information in the digital age is critical. Misinformation can significantly affect public understanding and policymaking. Automated fact-checking seeks to validate claims against trustworthy factual data. This study tackles the challenge of fact-checking climate claims by leveraging the currently most capable Large Language Models (LLMs). To this end, we introduce <span>Climinator</span>, an acronym for <Emphasis Type="Underline">CLI</Emphasis>mate <Emphasis Type="Underline">M</Emphasis>ediator for <Emphasis Type="Underline">IN</Emphasis>formed <Emphasis Type="Underline">A</Emphasis>nalysis and <Emphasis Type="Underline">T</Emphasis>ransparent <Emphasis Type="Underline">O</Emphasis>bjective <Emphasis Type="Underline">R</Emphasis>easoning. It significantly boosts the performance of automated fact-checking by integrating authoritative, up-to-date sources within a novel debating framework. This framework provides a trustworthy and context-aware analysis incorporating multiple scientific viewpoints. <span>Climinator</span> helps identify misinformation in real time and facilitates informed dialog on climate change, highlighting AI’s role in environmental discussions and policy with reliable data.</p>

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Automated fact-checking of climate claims with large language models

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月25日

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  • 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

摘要

Accurate identification of true versus false climate information in the digital age is critical. Misinformation can significantly affect public understanding and policymaking. Automated fact-checking seeks to validate claims against trustworthy factual data. This study tackles the challenge of fact-checking climate claims by leveraging the currently most capable Large Language Models (LLMs). To this end, we introduce Climinator, an acronym for CLImate Mediator for INformed Analysis and Transparent Objective Reasoning. It significantly boosts the performance of automated fact-checking by integrating authoritative, up-to-date sources within a novel debating framework. This framework provides a trustworthy and context-aware analysis incorporating multiple scientific viewpoints. Climinator helps identify misinformation in real time and facilitates informed dialog on climate change, highlighting AI’s role in environmental discussions and policy with reliable data.