1978 - ECO-REWARDS IN THE BRAIN: AI-DRIVEN MULTIMEDIA FEEDBACK FOR SUSTAINABLE CONSUMER DECISION-MAKING

Session: D04S021 - Technology & Sustainable Development
AUTHORS:
Ayoob Ayesha (Christ University ~ Delhi ~ India) , Singh Aastha (Christ University ~ Delhi ~ India)
Abstract text:
Introduction: Long-term environmental goals, such as climate action, are often undermined by human preference for immediate gratification. While sustainable choices promise benefits decades into the future, they lack the immediate reinforcement needed to shape daily habits. Advances in artificial intelligence (AI) allow for real-time, gamified feedback that may bridge this motivational gap.


Purpose: This study explores how AI-driven multimedia reward systems, including gamified eco-scores, carbon footprint dashboards, and personalized audio/video reinforcements, can promote sustainable decision-making across activities of daily life.


Method: Participants were randomly assigned to one of two groups in a two-week field trial. Both groups logged their daily activities (shopping, commuting, diet, and household practices) through a mobile application. The intervention group additionally received AI-generated reinforcements: eco-badges, celebratory audio cues, and short personalized video messages highlighting immediate ecological benefits (eg, "You saved 2 kg of CO₂ today by cycling instead of driving"). Digital phenotyping platforms (Beiwe, MindLAMP, and Ethica) were employed to passively capture mobility patterns, app usage diversity, and engagement with reinforcement content. Active ecological momentary assessments (EMAs) measured motivation, satisfaction, and willingness to repeat eco-friendly behaviors.


Results: Preliminary data indicate that the intervention group demonstrated higher engagement with sustainable practices, greater app usage diversity linked to eco-choices, and more positive affect following reinforcement. The immediacy and multi-sensory nature of AI feedback appeared to strengthen habit formation around eco-friendly activities, including food choices, transport, and resource conservation.


Conclusions: AI-driven reinforcement systems offer a novel psychological tool for bridging the gap between long-term climate goals and short-term motivation. By integrating gamified, multi-sensory feedback into everyday contexts, AI can normalize sustainable decision-making while enhancing well-being.