Automated Motivational Agent Framework for a Greener Lifestyle Behavior Change

Abstract

Every person is aware of ecological issues. Hence, consciously, ecological issues are already objects of the mind. What is lacking is the behavioral preference for activities and practices that would lead to an ecologically-sustainable behavior. Hence, intervention may be needed to stir things up with a drop of behavioral insights – to really turn the tide. This study aims to develop a framework that can be used in designing chatbots as a tool and a space for discussion for the diffusion and generation of practical ideas and knowledge for a greener lifestyle behavior change. We utilized a theory-based behavior change agent framework and motivation techniques to guide our structured intervention. To validate the technical feasibility of the framework's design principles, theoretical underpinnings, and procedures, a functionality review of chatbot development platforms was conducted. The features provided by Artificial Intelligence Markup Language (AIML) language proved that it is possible to develop a chatbot as a tool to bring about behavioral change. We contribute a valuable framework that can be adopted in the design of conversational agents equipped and trained with behavioral science perspectives to help effectively address the challenges presented by climate change and declining natural resource availability.