Machine Learning and Artificial Intelligence to Advance Earth System Science Machine Learning and Artificial Intelligence to Advance Earth System Science

Machine Learning and Artificial Intelligence to Advance Earth System Science

Opportunities and Challenges: Proceedings of a Workshop

    • $22.99
    • $22.99

Publisher Description

The Earth system - the atmospheric, hydrologic, geologic, and biologic cycles that circulate energy, water, nutrients, and other trace substances - is a large, complex, multiscale system in space and time that involves human and natural system interactions. Machine learning (ML) and artificial intelligence (AI) offer opportunities to understand and predict this system. Researchers are actively exploring ways to use ML/AI approaches to advance scientific discovery, speed computation, and link scientific communities. To address the challenges and opportunities around using ML/AI to advance Earth system science, the National Academies convened a workshop in February 2022 that brought together Earth system experts, ML/AI researchers, social and behavioral scientists, ethicists, and decision makers to discuss approaches to improving understanding, analysis, modeling, and prediction. Participants also explored educational pathways, responsible and ethical use of these technologies, and opportunities to foster partnerships and knowledge exchange. This publication summarizes the workshop discussions and themes that emerged throughout the meeting.

GENRE
Computers & Internet
RELEASED
2022
June 13
LANGUAGE
EN
English
LENGTH
68
Pages
PUBLISHER
National Academies Press
SELLER
National Academy of Sciences
SIZE
3.8
MB
Humanity Driven AI Humanity Driven AI
2021
Environmental Software Systems. Frameworks of eEnvironment Environmental Software Systems. Frameworks of eEnvironment
2011
Data Science Thinking Data Science Thinking
2018
Apply Data Science Apply Data Science
2023
Information and Communications Information and Communications
2003
Empirical Software Engineering Issues. Critical Assessment and Future Directions Empirical Software Engineering Issues. Critical Assessment and Future Directions
2007
Biodiversity at Risk Biodiversity at Risk
2022
Traumatic Brain Injury Traumatic Brain Injury
2022
Nutrient Requirements of Beef Cattle Nutrient Requirements of Beef Cattle
2016
Space Studies Board Annual Report 2017 Space Studies Board Annual Report 2017
2018
The Gulf Research Program Annual Report 2013-2014 The Gulf Research Program Annual Report 2013-2014
2015
The Gulf Research Program Annual Report 2017 The Gulf Research Program Annual Report 2017
2018