This paper reports the findings of a scoping review on the environmental harms of AI. We reviewed 198 publications to consider the specific environmental harms explored in the literature, the life stages of AI development that are commonly discussed, and the potential solutions that are being researched in the field of AI development. The findings point to a dominant focus on the energy use and greenhouse gas emissions of AI in existing literature, at the expense of other environmental harms, such as water usage, mining, and waste. The literature also predominantly focused on the time during which AI is being used, with less focus on the production and aftermath of AI technology, and the environmental harms associated with these stages of use. The solutions proposed in the literature were wide-ranging, from reducing the carbon emissions of AI models, to producing alternatives to mainstream LLMs. Overall, there was little focus to date on the environmental harms of AI used in education settings in the literature, pointing to a significant gap in research. Drawing on the findings of this review, we suggest future directions for AI research in order to be more critically engaged with the environmental impacts in education policy and practice.
Quadros et al. (Wed,) studied this question.