Aligning artificial intelligence with climate change mitigation
By Lynn H. Kaack, Priya Lekha Donti, Emma Strubell, George Kamiya, Felix Creutzig, D. Rolnick. 2022
Subfields: Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
- Noah A. Smith
- Yejin Choi
- Roy Schwartz
- Zeerak Talat
- Alexandra Sasha Luccioni
- Su Lin Blodgett
- Irene Solaiman
- Margaret Mitchell
Citations in the corpus
- Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “[233] and examining environmental impact across compute-related impacts, immediate impacts of applying AI, and system-level impacts [120].”
- Measuring the Carbon Intensity of AI in Cloud Instances (2022, background): “Other studies have gone beyond simply tracking the emissions from training models, aiming to quantify the emissions resulting from manufacturing computing hardware [15], the broader impacts of sustainable AI [49], and the methodologies used to assess those impacts [21, 26].”
- Taxonomy of Risks posed by Language Models (2022, background): “The wider environmental impact of operating LMs may be significant, however specific forecasts are missing and emissions will depend on some factors which are currently unknown [96], including (perhaps most importantly) what types of applications LMs will be integrated into, the anticipated scale an”