Work

Slower is Greener: Acceptance of Eco-feedback Interventions on Carbon Heavy Internet Services

Year: 2025

Type: article

Abstract: The carbon emissions of modern information and communication technologies (ICT) present a significant environmental challenge, accounting for approximately 4% of global greenhouse gases, and are on par with the aviation industry. Modern internet services levy high carbon emissions due to the significant infrastructure resources required to operate them, owing to strict service requirements expected by users. One opportunity to reduce emissions is relaxing strict service requirements by leveraging eco-feedback. In this study, we explore the effect of the carbon reduction impact of allowing longer internet service response time based on user preferences and feedback. Across four services (i.e., Amazon, Google, ChatGPT, Social Media) our study reveals opportunities to relax latency requirements of services based on user feedback; this feedback is application-specific, with ChatGPT having the most favorable eco-feedback tradeoff. Further system studies suggest leveraging the reduced latency can bring down the carbon footprint of an average service request by 93.1%.

Source: ACM Journal on Computing and Sustainable Societies

DOI: 10.1145/3723038

Authors: Hyeonwook Kim, Sydney Young, Xuesi Chen, Udit Gupta, Josiah Hester

Institutions: Georgia Institute of Technology, Carnegie Mellon University, Cornell University, Cornell Tech

Language: English

Topic: Green IT and Sustainability

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Climate action, Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: hybrid

Funder: National Science Foundation