Leveraging advances in artificial intelligence could revolutionize the Earth and environmental sciences. We must ensure that our research funding and training choices give the next generation of geoscientists the capacity to realize this potential.
In Earth and environmental science (EES), quantitative prediction models gauge the state of scientific knowledge and help put it to practical use. With the emergence of big data, exponential growth in computational speed and increasing awareness of the practical limits of classical physics-based and statistical models, a new modelling approach has appeared: artificial intelligence (AI) (for a short glossary of machine learning-related jargon, see Table 1). A major component of the broader data-science tidal wave, which has been deemed the fourth industrial revolution1 and fourth paradigm of science2, AI can accelerate discovery and prediction thanks to its scalability, capacity to determine patterns within large datasets and wide applicability.
https://www.nature.com/articles/s41561-021-00865-3
