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Machine learning in Earth and environmental science requires education and research policy reforms

Nature Geoscience volume 14, pages 878–880 (2021)Cite this article

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A Publisher Correction to this article was published on 24 December 2021

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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.

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References

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Authors and Affiliations

  1. National Water and Climate Center, Natural Resources Conservation Service, US Department of Agriculture, Portland, OR, USA

    Sean W. Fleming

  2. College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA

    Sean W. Fleming, James R. Watson & Ashley Ellenson

  3. Water Resources Graduate Program, Oregon State University, Corvallis, OR, USA

    Sean W. Fleming

  4. Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Vancouver, British Columbia, Canada

    Sean W. Fleming & Alex J. Cannon

  5. Department of Civil and Construction Engineering, Oregon State University, Corvallis, OR, USA

    Ashley Ellenson

  6. Climate Research Division, Environment and Climate Change Canada, Vancouver, British Columbia, Canada

    Alex J. Cannon

  7. Computational Earth Sciences Group, Environmental and Earth Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    Velimir C. Vesselinov

Authors
  1. Sean W. Fleming
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  2. James R. Watson
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  3. Ashley Ellenson
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  4. Alex J. Cannon
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  5. Velimir C. Vesselinov
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Corresponding author

Correspondence to Sean W. Fleming.

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The authors declare no competing interests.

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Fleming, S.W., Watson, J.R., Ellenson, A. et al. Machine learning in Earth and environmental science requires education and research policy reforms. Nat. Geosci. 14, 878–880 (2021). https://doi.org/10.1038/s41561-021-00865-3

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