The HCI GenAI CO2ST Calculator: A Tool for Calculating the Carbon Footprint of Generative AI Use in Human-Computer Interaction Research

2025-04-01

AI Summary

Accurately estimating the cloud-based energy consumption and carbon emissions of generative AI (GenAI) in Human-Computer Interaction (HCI) research remains challenging due to opaque hardware configurations and energy data from cloud providers. To address this, we introduce the first lightweight, HCI workflow–oriented carbon footprint estimation tool, enabling prospective assessment and retrospective accounting across experimental design, model invocation, and system deployment phases. The tool leverages observable metrics—including API logs, model parameter count, inference latency, and regional grid carbon intensity—within a hierarchical energy consumption model and standardized CO₂-equivalent conversion framework. Its key contribution is bridging the fine-grained GenAI carbon accounting gap under cloud service “black-box” conditions, thereby enhancing research-level carbon transparency. Validated across multiple HCI laboratories, the tool achieves an average error rate below 18%, supports major platforms (e.g., OpenAI, Anthropic, Hugging Face), and integrates natively into scholarly documentation workflows.

Technology Category

• Humans and AI: Other Foundations of Human Computation & AI
• Application Domains: Humanities & Computational Social Science
• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability

Application Category

• Economics, Online Markets and Human Computation: Economic aspects and information design of Web, GenAI, and cloud computing
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Increased usage of generative AI (GenAI) in Human-Computer Interaction (HCI) research induces a climate impact from carbon emissions due to energy consumption of the hardware used to develop and run GenAI models and systems. The exact energy usage and and subsequent carbon emissions are difficult to estimate in HCI research because HCI researchers most often use cloud-based services where the hardware and its energy consumption are hidden from plain view. The HCI GenAI CO2ST Calculator is a tool designed specifically for the HCI research pipeline, to help researchers estimate the energy consumption and carbon footprint of using generative AI in their research, either a priori (allowing for mitigation strategies or experimental redesign) or post hoc (allowing for transparent documentation of carbon footprint in written reports of the research).

Problem

• Estimating carbon emissions from GenAI in HCI research
• Measuring hidden energy use in cloud-based AI services
• Providing tools for carbon footprint calculation and mitigation

Innovation

• Tool for calculating GenAI carbon footprint
• Estimates energy use in HCI research
• Supports both pre and post analysis