Journal article
Potential reduction in healthcare carbon footprint by autonomous artificial intelligence
NPJ digital medicine, Vol.5(1), pp.1-4
05/01/2022
DOI: 10.1038/s41746-022-00605-w
PMCID: PMC9098499
PMID: 35551275
Abstract
Healthcare is a large contributor to greenhouse gas (GHG) emissions around the world, given current power generation mix. Telemedicine, with its reduced travel for providers and patients, has been proposed to reduce emissions. Artificial intelligence (AI), and especially autonomous AI, where the medical decision is made without human oversight, has the potential to further reduce healthcare GHG emissions, but concerns have also been expressed about GHG emissions from digital technology, and AI training and inference. In a real-world example, we compared the marginal GHG contribution of an encounter performed by an autonomous AI to that of an in-person specialist encounter. Results show that an 80% reduction may be achievable, and we conclude that autonomous AI has the potential to reduce healthcare GHG emissions.
Details
- Title: Subtitle
- Potential reduction in healthcare carbon footprint by autonomous artificial intelligence
- Creators
- Risa M. Wolf - Johns Hopkins University School of MedicineMichael D. Abramoff - University of IowaRoomasa Channa - University of Wisconsin–MadisonChris Tava - Digital DiagnosticsWarren Clarida - Digital DiagnosticsHarold P. Lehmann - Johns Hopkins University School of Medicine
- Resource Type
- Journal article
- Publication Details
- NPJ digital medicine, Vol.5(1), pp.1-4
- DOI
- 10.1038/s41746-022-00605-w
- PMID
- 35551275
- PMCID
- PMC9098499
- NLM abbreviation
- NPJ Digit Med
- eISSN
- 2398-6352
- Publisher
- Nature Portfolio
- Language
- English
- Date published
- 05/01/2022
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Fraternal Order of Eagles Diabetes Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984258752802771
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