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.

中文翻译：

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自主人工智能可能减少医疗保健碳足迹

鉴于当前的发电结构，医疗保健是全球温室气体 (GHG) 排放的一大贡献者。远程医疗可以减少医疗服务提供者和患者的出行，从而减少排放。人工智能 (AI)，尤其是自主人工智能，其医疗决策是在没有人类监督的情况下做出的，有可能进一步减少医疗保健温室气体排放，但人们也对数字技术以及人工智能训练和推理产生的温室气体排放表示担忧。在一个现实世界的例子中，我们将自主人工智能执行的接触的边际温室气体贡献与面对面的专家接触的边际温室气体贡献进行了比较。结果表明，减少 80% 是可以实现的，我们得出的结论是，自主人工智能有潜力减少医疗保健温室气体排放。