IN026-03
Report on a NASA Workshop: Use of AI/ML in Science Strategic Planning and Prioritization

Friday, 11 December 2020: 17:36
Virtual
Brian A. Thomas1, Louis Matthew Barbier2, Harley Thronson3, Nargess Memarsadeghi4, Giulio Varsi5, Alison B Lowndes6, Julie Crooke4, Bill Diamond7 and Kenneth D Wright1, (1)NASA Headquarters, Washington, United States, (2)NASA Headquarters, Washington, DC, United States, (3)Retired, Washington, United States, (4)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (5)Varsi Consulting, Baxter Estates, NY, United States, (6)NVidia, North Yorkshire, United Kingdom, (7)SETI, Washington, United States
Abstract:
We report on a NASA workshop held May 12-13, 2020 that critically assessed the value of Artificial Intelligence (AI) and Machine Learning (ML) to assist current processes for prioritization of the space science goals, program and mission planning, and associated technologies, specifically with respect to the National Academies’ Decadal Surveys. Our workshop included ~40 experts in science planning, science mission execution, the astronomy and planetary sciences Decadal Surveys and leading practitioners of AI/ML. These experts discussed how these technologies might be fruitfully employed and identified key challenges and associated test cases, which could be undertaken to help demonstrate practical value. Derived test cases included ways to determine whether and where AI/ML might be useful for improving understanding of space science research, improving the science planning and prioritization process, reducing mission risk and improving mission execution.

We will provide details of these results and outline the potential advantages and pitfalls of these technologies to complement current processes of selecting science priorities, strategic planning and executing science missions.

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