Year: 2026
Type: article
Abstract: Artificial Intelligence (AI) is increasingly framed as a key enabler of climate monitoring, modelling, adaptation, and mitigation. In this comment, I use “AI-for-climate” to refer to AI systems designed for these purposes. From optimizing energy use and improving predictive capacity to scaling adaptation planning and offering decision support, AI-for-climate holds considerable promise 1 , 2 , 3 , 4 . Yet AI is not neutral. Like humans, it is shaped by the political, economic, and epistemological systems from which it emerges, and in which it is embedded. AI-for-climate thus risks reinforcing the dominance of Western societies, economies, and knowledges and reproducing the extractive relational dynamics that are driving climate destabilization in the first place 5 . Many contemporary AI systems also rely materially on infrastructures of extraction, including global energy grids, rare earth mining, and precarious labour. At the same time, some researchers and communities are beginning to develop AI systems that are more aligned with our condition of planetary entanglement, guided by intergenerational and interspecies responsibilities, and responsive to local knowledge systems and priorities.
Source: npj Climate Action
Author: Sharon Stein
Institution: University of British Columbia
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,340
OpenAlex ID: W7154570432