OceanChat: The Effect of Virtual Conversational AI Agents on Sustainable Attitude and Behavior Change

2025-02-05

AI Summary

Traditional environmental education often fails to foster sustained pro-environmental behavior (PEB), particularly in addressing marine plastic pollution and climate change. This study proposes and empirically evaluates OceanChat, an LLM-powered virtual conversational AI agent featuring embodied, species-accurate 3D marine avatars—beluga whale, jellyfish, and seahorse—to enhance public environmental awareness and PEB through real-time dialogue. As the first experimental investigation (N = 900, between-subjects design) to validate the efficacy of conversational agents balancing anthropomorphism with taxonomic fidelity, results demonstrate that the dialogue intervention significantly increases preferences for sustainable choices and behavioral intentions. The beluga whale avatar proved most effective in eliciting empathy and perceived anthropomorphism. However, effects on policy support intention and psychological distance were negligible. Findings advance human–AI interaction research in environmental communication and inform the design of ecologically grounded, affectively resonant AI interventions.

Technology Category

Humans and AI: Emotional IntelligenceIntelligent Robots: Embodied AIData Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactionsEconomics, Online Markets and Human Computation: Humans versus LLMs for data annotation and labelingUser Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation

Abstract

Marine ecosystems face unprecedented threats from climate change and plastic pollution, yet traditional environmental education often struggles to translate awareness into sustained behavioral change. This paper presents OceanChat, an interactive system leveraging large language models to create conversational AI agents represented as animated marine creatures -- specifically a beluga whale, a jellyfish, and a seahorse -- designed to promote environmental behavior (PEB) and foster awareness through personalized dialogue. Through a between-subjects experiment (N=900), we compared three conditions: (1) Static Scientific Information, providing conventional environmental education through text and images; (2) Static Character Narrative, featuring first-person storytelling from 3D-rendered marine creatures; and (3) Conversational Character Narrative, enabling real-time dialogue with AI-powered marine characters. Our analysis revealed that the Conversational Character Narrative condition significantly increased behavioral intentions and sustainable choice preferences compared to static approaches. The beluga whale character demonstrated consistently stronger emotional engagement across multiple measures, including perceived anthropomorphism and empathy. However, impacts on deeper measures like climate policy support and psychological distance were limited, highlighting the complexity of shifting entrenched beliefs. Our work extends research on sustainability interfaces facilitating PEB and offers design principles for creating emotionally resonant, context-aware AI characters. By balancing anthropomorphism with species authenticity, OceanChat demonstrates how interactive narratives can bridge the gap between environmental knowledge and real-world behavior change.

Problem

• Promote environmental behavior through AI
• Enhance awareness via interactive marine characters
• Bridge knowledge-behavior gap in sustainability

Innovation

• AI-powered marine characters
• Personalized dialogue for engagement
• Emotionally resonant sustainability interfaces