GPTFootprint: Increasing Consumer Awareness of the Environmental Impacts of LLMs

2025-04-25

CHI Extended Abstracts

AI Summary

Large language model (LLM) end users exhibit low environmental awareness, and the implicit energy and water consumption of LLM interactions remains imperceptible. Method: We designed and implemented GPTFootprint, a browser extension that quantifies and visualizes the real-time energy and water footprint of individual ChatGPT queries using publicly available LLM resource-consumption data, and delivers rest prompts upon reaching user-defined query thresholds. Contribution/Results: As the first individual-level, quantifiable, and immediate environmental intervention tool for AI end consumers, GPTFootprint explicitly, personally, and behaviorally couples abstract environmental costs with user actions. A one-week user study (N=42) demonstrated statistically significant improvement in users’ awareness of LLM environmental impacts (p<0.01); although query frequency was not significantly reduced, the study validates the feasibility and methodological value of awareness-driven behavioral regulation in sustainable AI practice.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Humans and AI: Intelligent User Interfaces
• Natural Language Processing: (Large) Language Models

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Responsible Web: Sustainability and climate impact of web technologies

Abstract

With the growth of AI, researchers are studying how to mitigate its environmental impact, primarily by proposing policy changes and increasing awareness among developers. However, research on AI end users is limited. Therefore, we introduce GPTFootprint, a browser extension that aims to increase consumer awareness of the significant water and energy consumption of LLMs, and reduce unnecessary LLM usage. GPTFootprint displays a dynamically updating visualization of the resources individual users consume through their ChatGPT queries. After a user reaches a set query limit, a popup prompts them to take a break from ChatGPT. In a week-long user study, we found that GPTFootprint increases people’s awareness of environmental impact, but has limited success in decreasing ChatGPT usage. This research demonstrates the potential for individual-level interventions to contribute to the broader goal of sustainable AI usage, and provides insights into the effectiveness of awareness-based behavior modification strategies in the context of LLMs.

Problem

• Raises consumer awareness of LLMs' environmental impact
• Reduces unnecessary LLM usage through user intervention
• Evaluates effectiveness of awareness-based behavior modification

Innovation

• Browser extension visualizes LLM resource consumption
• Popup prompts users after query limit reached
• Awareness tool for sustainable AI usage