A Vision for Computational Decarbonization of Societal Infrastructure

Irwin, David, Shenoy, Prashant, Hajiesmaili, Mohammad, Hanafy, Walid A., Oke, Jimi, Sitaraman, Ramesh, Agarwal, Yuvraj, Gordon, Geoffrey J., Kolter, Zico, Rajagopal, Deepak, Srivastava, Mani, Sze, Vivienne, Donti, Priya, Chien, Andrew, Birge, John, Hortacsu, Ali, Roald, Line 2025. IEEE Internet Computing 29(2):27–35.
DOI
10.1109/mic.2025.3575016

Abstract

Modern society is at a critical inflection point with rapidly accelerating demand for energy due to growth in domestic manufacturing, datacenters, artificial intelligence (AI), electric vehicles, and electric heat pumps. Sustaining this growth while also reducing society’s carbon emissions will necessitate a shift beyond our long-standing focus on improving energy efficiency to optimizing carbon efficiency. This paper lays out a vision for a new field of computational decarbonization, which focuses on optimizing and reducing the lifecycle carbon emissions of complex computing and societal infrastructure systems. We identify an important class of decarbonization problems that arise from interdependencies across multiple infrastructure domains, including computing, transportation, the built environment, and the electric power grid. As we discuss, solving these problems will require developing novel computational techniques, algorithms, systems, and AI methods that sense, optimize, and reduce the operational, embodied, and lifecycle greenhouse gas emissions of societal infrastructure over long temporal and spatial scales.