AI-Enhanced Climate Communication and Public Engagement: A Conceptual Framework for Responsible Environmental Messaging

Abstract

Climate change communication faces persistent challenges, including psychological distance, political polarization, misinformation, public disengagement, and difficulty translating scientific evidence into meaningful public action. Artificial intelligence offers new possibilities for climate communication by supporting audience segmentation, message personalization, climate visualization, misinformation detection, and automated public engagement. However, AI-enhanced climate communication also raises ethical concerns related to transparency, manipulation, data privacy, algorithmic bias, and unequal access to trustworthy climate information. This conceptual article examines how AI can reshape climate communication and public engagement in digital society. Drawing on climate communication research, science communication, AI ethics, algorithmic accountability, and machine learning for climate action, the article proposes a three-dimensional framework: personalized climate meaning-making, algorithmic climate visibility, and responsible public engagement. Personalized climate meaning-making refers to the use of AI to adapt climate messages to audience values, local contexts, and perceived relevance. Algorithmic climate visibility refers to the ways AI and platform algorithms shape which climate narratives become publicly visible. Responsible public engagement refers to the ethical governance of AI-supported communication practices so that persuasion does not become manipulation. The article argues that AI should not be treated as a simple solution to climate communication problems but as a socio-technical tool that must be guided by transparency, equity, trust, and democratic participation.