Exploring Anthropomorphism in Conversational Agents for Environmental Sustainability
Mathyas Giudici, Samuele Scherini, Pascal Chaussumier, Stefano Ginocchio, Franca Garzotto · 2025
The paper investigates the integration of Large Language Models (LLMs) into Conversational Agents (CAs) to encourage a shift in consumption patterns from a demand-driven to a supply-based paradigm.Specifically, the research examines the role of anthropomorphic design in delivering environmentally conscious messages by comparing two CA designs: a personified agent representing an appliance and a traditional, non-personified assistant.A lab study (N=26) assessed the impact of these designs on interaction, perceived self-efficacy, and engagement.Results indicate that LLMbased CAs significantly enhance users' self-reported eco-friendly behaviors, with participants expressing greater confidence in managing energy consumption.While the anthropomorphic design did not notably affect self-efficacy, those interacting with the personified agent reported a stronger sense of connection with the system.These findings suggest that although anthropomorphic CAs may improve user engagement, both designs hold promise for fostering sustainable behaviors in home energy management.