Supporting responsible machine learning in heliophysics

Supporting responsible machine learning in heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional respons...

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Bibliographic Details
Main Authors: Ayris Narock, Christopher Bard, Barbara J. Thompson, Alexa J. Halford, Ryan M. McGranaghan, Daniel da Silva, Burcu Kosar, Mykhaylo Shumko
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-12-01
Series:Frontiers in Astronomy and Space Sciences
Subjects:
machine learning
heliophysics
ethics of artificial intelligence
emerging informatics technologies
community standards
science policy
Online Access:https://www.frontiersin.org/articles/10.3389/fspas.2022.1064233/full

Internet

https://www.frontiersin.org/articles/10.3389/fspas.2022.1064233/full

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