TAI4ES 2022 Summer School
Trustworthy Artificial Intelligence for Environmental Science
9:00 am – 4:00 pm MDT
The annual Trustworthy Artificial Intelligence for Environmental Science (TAI4ES) Summer School will take place June 27 through June 30. It is organized by the National Science Foundation AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) in conjunction with NCAR.
The TAI4ES Summer School will focus on getting attendees up to speed on how to develop trustworthy AI for the earth and environmental sciences. Participants should have a basic background in AI methods. Each morning, students will participate in lectures from leading researchers in the field. In addition to gaining hands-on experience with evaluating the trustworthiness of AI methods across multiple use cases, participants will gain an understanding of:
- the foundations of trustworthiness for AI
- explanatory AI (XAI) and how explanations, physics, and robustness can help build trust in AI
- the relationship between ethics and trustworthiness
- how machine-learning systems have been developed for a range of environmental science applications
Registration is now closed. Email Taysia Peterson with any questions (firstname.lastname@example.org).
Links to slides will be added each day.
This year’s TAI4ES Summer School will feature a week-long machine learning trust-a-thon. The goal is to evaluate the trustworthiness of pre-trained machine learning algorithms developed to solve real-world environmental science challenges. Participants will develop experience applying a mix of verification, visualization, XAI, and robustness checks to these algorithms to understand how they work and identify biases and failure modes. Both beginner and advanced tracks will be available.
Certificate of Participation
Registered participants can request a certificate of participation by emailing email@example.com the week of July 11th. Certificates will not be sent any earlier.
Amy McGovern, University of Oklahoma
David John Gagne, NCAR
Susan Dubbs, University of Oklahoma
Taysia Peterson (firstname.lastname@example.org)
Code of Conduct
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All participants (and guests) are required to abide by this Code of Conduct. This Code of Conduct is adapted from the one adopted by AGU, complies with the directive from the National Science Foundation, and applies to all UCAR-related events, including those sponsored by organizations other than UCAR but held in conjunction with UCAR events, in any location throughout the world.
Please see our full Code of Conduct.
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