Machine Learning and Artificial Intelligence to Advance Earth System Science Opportunities and Challenges: Proceedings of a Workshop (2022) / Chapter Skim
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While many current applications of ML/AI can exacerbate challenges in the existing paradigm, participants identified opportunities to build new infrastructure based on open science and open data principles. In order to achieve a system of truly open knowledge, participants suggested efforts to encourage contributions to community code, build capacity to enable equitable access to science, and foster an inclusive open source community.
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In order for scientific advances at the intersection of ML/AI and Earth system science to be useful for decision making, participants discussed opportunities for further research on how end users understand information provided by an ML/AI algorithm and how best to communicate uncertainty. Earth system science has large and rapidly growing datasets that have enabled the effective use of ML/AI, and an opportunity exists to progress from success with simple problems to the use of ML/AI tools to model and predict complex scenarios.
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