Chapter 09 · Sustainability & AISustainability & AI
Computational sustainability
Definition
An interdisciplinary research field that applies computational methods — optimisation, machine learning, simulation — to environmental, economic and social sustainability problems.
References
This source provides part of the technical or institutional basis for the definition.
This source supports the explanation of how the term is applied, measured or governed in practice.
Overview
What it means
Institutionalised from 2008 around Cornell's Institute for Computational Sustainability (one of the first NSF Expeditions in Computing awards) and grown through the CompSustNet research network, the field treats sustainability challenges as computational problems: balancing conservation planning, energy systems and resource management under constraints, often at scales beyond unaided analysis.
How it is used
Research spans species-habitat optimisation, smart-grid algorithms, poverty mapping from satellite data and materials discovery. The field overlaps with climate informatics and supplies methods used across environmental AI.
Why it matters
Computational sustainability is the academic ancestor of today's 'AI for climate' wave. Its framing matters: it positions computation as one instrument among policy, economics and ecology — a tool in service of sustainability, not a substitute for it.