Red Cards for Climate Myths: introducing ClimaVAR, an AI-based Tool for Climate Disinformation Detection - Oliveira Jr., Marcos A. de; Whiteman, Gail; Nugroho, Nectarios K.; Siwach, Ashish; Cavalheiro, Gerson G. H. (Anais do Seminário Integrado de Software e Hardware (SEMISH), 2026)
Climate disinformation undermines public understanding, erodes trust in science, and delays effective climate action. This paper introduces ClimaVAR, an AI-based tool that uses a football referee metaphor to evaluate climate-related statements. ClimaVAR proposes a pipeline which, from a user textual input, combines: (i) climate disinformation detection using Computer-assisted recognition of (climate change) denial and skepticism (CARDS) model, (ii) Retrieval-Augmented Generation (RAG) from curated scientific documents to find correct statements when disinformation is detected, and (iii) a large language model layer to generate accessible answers translating climate science into football metaphors. The system analyzes user-submitted climate statements and issues football-related messages (offside, yellow/red card, goal) indicating alignment or not with truth, accompanied by explanations and scientific references. Deployed at high-profile events including COP30 and side events at Davos, during the World Economic Forum 2026, ClimaVAR has demonstrated the potential of culturally adapted interfaces to increase engagement with climate science. Initial results demonstrated that 66% of user inputs were tagged as misinformation. Complementary analyses enabled also grouping inputs by topic, with themes such as: Climate Denial & Skepticism, Human Causation & Consensus, Physical Impacts & Extreme Events, Energy & Policy, and Other/Emerging Topics.