Automated Fact Checking System For Climate Change Claims

Bonisiwe Shabane

-Dec 6, 2025, 11:35 PM

automated fact checking system for climate change claims

npj Climate Action volume 4, Article number: 17 (2025) Cite this article 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. In the era of digital information abundance, the endeavor to counter climate misinformation has found a promising ally in artificial intelligence (AI). Research shows that engaging with an AI chatbot on climate change can significantly align public perception with scientific consensus1, highlighting the importance of ensuring that the large language models (LLMs) underpinning these systems are... Therefore, we ask how well we can embed scientific consensus into automated fact-checking.

To this end, we developed Climinator—an acronym for CLImate Mediator for INformed Analysis and Transparent Objective Reasoning. Climinator evaluates the veracity of climate statements and improves its verdicts with evidence-based and scientifically credible reasoning and references to relevant literature. Our vision is to use AI to catalyze a well-informed global climate dialog, enrich public discourse with scientific insights, and foster a more informed society ready to engage with climate challenges. Climinator serves as a first step in this direction. Platforms like Climate Feedback and Skeptical Science have made commendable efforts to involve climate scientists in volunteering their expertise and providing an essential service in addressing climate misinformation. These scientists voluntarily dedicate their time to giving concise science-based evaluations, including references, and delivering a final verdict on disputed claims.

Despite their valuable contributions, these efforts face significant challenges, including scalability and actuality. Hence, their impact is limited by the sheer volume of misinformation and skepticism in digital media, worsened by misinformation spreading more rapidly and widely than factual information2. As a response, automated fact-checking3,4 aims to debunk misinformation at scale using natural language processing methods. While automated fact-checking tools have improved, they struggle with complex claims due to a lack of detailed reasoning5,6,7, particularly in the domain of climate change8. To address this problem, we introduce an advanced framework that overcomes these limitations by integrating LLMs within a Mediator-Advocate model. Although recent work has explored the aggregation of different viewpoints using LLMs to build a general consensus9, we address real-world claim complexities and evidence controversies in a novel way10,11,12.

In particular, we introduce separate “Advocates,” each drawing on a distinct text corpus to represent a specific viewpoint, while a “Mediator” either asks follow-up questions or synthesizes these perspectives into a cohesive and balanced... Climate+Tech launches an open source AI fact-checking system that combines multiple AI models to evaluate climate claims against scientific sources, achieving 85% agreement with expert consensus. The spread of climate misinformation poses a significant challenge in our digital age. Recent research highlights the scale of this problem: To address this challenge, we’re excited to announce the launch of Climate+Tech FactChecker, an open source AI-powered system designed to fact-check climate claims at scale while maintaining scientific rigor and transparency. Related Solution: This tool is part of our broader initiative on AI tools for society.

Learn more about our complete ecosystem of fact-checking and democratic discourse tools in “AI Tools for Society: Fact-Checking, Democracy & Climate Communication”. Our system’s unique approach mirrors how expert panels evaluate scientific claims. Multiple AI “advocates” examine evidence independently from different scientific sources, provide structured reasoning with citations, and a “mediator” AI reconciles their findings into a final verdict. 2024 S1 COMP90042 Natural Language Processing Group Project Fork with 2024 COMP90042 Project Description. Overleaf Report: https://www.overleaf.com/read/sgchwdbmvjbq#c47aff

The impact of climate change or humanity is a significant cocern. However, the increase is unverified statements regarding climate science has led to a distortion of public opinion, underscoring the importance of conducting on claims related to climate science. Consider the following claim and related evidence: Claim: The Earth's climate sensitivity is so low that a doubling of atmoshperic CO2 will result in a surface temperature change on the order of 1 cellus degree or less. arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.

arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. 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. Keywords: Climate sciences; Communication; Education; Environmental social sciences.

Competing interestsThe authors declare no competing interests. Fig. 1. Performance in terms of accuracy… Fig. 1.

Performance in terms of accuracy (averaged micro-F1) of various models in classifying Climate… Climate change is an important issue that affects everyone. People often make Claims about it, but not all statements are true. This paper talks about a new tool designed to help check if these claims are accurate. The tool uses advanced computer models that can understand and analyze large amounts of information quickly. In today's world, people are surrounded by information, some of which may not be true.

This is especially true with climate change, where various individuals and groups make conflicting statements that can confuse the public. The recent claims made by notable figures can spark debate about what is accurate and what is not. For example, a recent claim stated that there is no scientific Evidence supporting the need to phase out fossil fuels to limit global warming. This claim shows how critical it is to have a reliable system that can verify such statements. The tool discussed in this paper is designed to automatically check facts related to climate change. It uses a method called the Mediator-Advocate framework.

This framework helps the tool to collect and evaluate different scientific opinions effectively, leading to accurate outcomes based on evidence. Gathering Claims: The tool starts by gathering statements related to climate change from various sources. Analyzing Claims: It breaks down these claims into smaller parts to understand them better. Climate+Tech FactChecker takes a major step toward democratizing climate fact-checking by integrating Ollama, enabling deployment of powerful open source language models for transparent and customizable verification of climate claims. We’re excited to announce that Climate+Tech FactChecker now fully integrates with Ollama, enabling deployment of powerful open source language models for climate fact-checking. This integration marks a significant step toward more transparent, customizable, and accessible climate information verification.

The transition to open source AI models for fact-checking addresses several critical challenges in the fight against climate misinformation: Transparency and Trust: Recent studies show that 68% of people are concerned about the “black box” nature of AI systems1. Open source models allow complete visibility into the decision-making process, crucial for building trust in automated fact-checking. Independence: With 73% of experts emphasizing the importance of independent verification systems2, open source models ensure fact-checking isn’t dependent on any single commercial entity or authority.

Automated Fact Checking System For Climate Change Claims

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Npj Climate Action Volume 4, Article Number: 17 (2025) Cite

It Significantly Boosts The Performance Of Automated Fact-checking By Integrating

To This End, We Developed Climinator—an Acronym For CLImate Mediator

Despite Their Valuable Contributions, These Efforts Face Significant Challenges, Including

In Particular, We Introduce Separate “Advocates,” Each Drawing On A