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Environmental impact of large language models in medicine
Oliver Kleinig1,2, Shreyans Sinhal1, Rushan Khurram1
1School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.
None:
The environmental impact of large language models (LLMs) in medicine spans carbon emission, water consumption and rare mineral usage. Prior-generation LLMs, such as GPT-3, already have concerning environmental impacts. Next-generation LLMs, such as GPT-4, are more energy intensive and used frequently, posing potentially significant environmental harms. We propose a five-step pathway for clinical researchers to minimise the environmental impact of the natural language algorithms they create.
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