Bago, Bence, Bonnefon, Jean-François and Muller, Philippe (2025) Using generative AI to increase sceptics’ engagement with climate science. Nature Climate Change, vol. 15 (n° 11).

Abstract

Climate skepticism remains a significant barrier to public engagement with accurate climate information, because skeptics actively engage in information avoidance to escape exposure to climate facts. Here we show that generative AI can enhance engagement with climate science among skeptical audiences by subtly modifying headlines to align better with their existing perspectives, without compromising factual integrity. In a controlled experiment (N = 2000) using a stylized social media interface, headlines of climate science articles modified by an open-source large language model (Llama3 70B, version 3.0) led to more bookmarks and more upvotes, and these effects were strongest among the most skeptical participants. Skeptics who engaged with climate science as a result of this intervention showed a shift in beliefs toward the scientific consensus by the end of the study. These results show that generative AI can alter the information diet skeptics consume, with the promise that scalable, sustained engagement will promote better epistemic health. They highlight the potential of generative AI as a tool for truth, showing that while it can be misused by bad actors, it also holds promise for advancing public understanding of science when responsibly deployed by well-intentioned actors.