Generative AI as a source of information on environmental Problems: Understanding its influence on Generation Z

Generative artificial intelligence (GenAI) is rapidly emerging as a transformative tool in digital information dissemination. However, its influence on environmental communication problems remains underexplored. This research examines whether exposure to information on an environmental problem provided by GenAI (namely ChatGPT) influences individuals' pro-environmental outcomes in terms of awareness of environmental consequences, moral obligation, and attitudes toward that problem. It addresses the research gap on GenAI's effectiveness compared to traditional sources (digital newspapers) in shaping environmental perceptions, as well as the underlying mechanisms behind this effectiveness. Two experimental studies were conducted with samples of Generation Z users given this demographic's high level of engagement with AI tools. Study 1 examined changes in pro-environmental outcomes when participants were exposed to ChatGPT-generated messages about water scarcity or messages in a digital newspaper. Study 2 focused on the underlying mechanisms of ChatGPT's influence. It examined how perceived usefulness of information mediates this influence and how individual characteristics (psychological distance to the problem and technological innovativeness) moderate this process. Exposure to messages about water scarcity significantly enhanced participants' awareness of consequences, moral obligation, and attitudes toward the problem, regardless of the source. In Study 2, emphasizing problem severity enhanced perceived usefulness, a key factor in shaping pro-environmental outcomes. However, this effect varied based on individual characteristics, with moderation by psychological distance and technological innovativeness. These findings contribute to the growing discussion about the role of GenAI in environmental communication. The paper discusses the potential implications of GenAI for fostering pro-environmental attitudes and behaviors. It emphasizes the need to consider audience-specific factors to maximize the effectiveness of GenAI.