Report on Workshop on Artificial Intelligence in Strategic Planning and Science Prioritization

This report details the observations from a two-day virtual workshop, held May 12-13, 2020, focused on whether, and how, artificial intelligence (AI) could assist humans in strategic planning, specifically in science and technology prioritization. The participants identified several “key challenges” that AI might tackle in this area. To further understand the value of these key challenges the workshop then developed related test cases that would demonstrate specifically how AI/machine learning (ML) could provide assistance to humans. Approximately 40 subject matter experts (SMEs), with backgrounds in AI, strategic planning for science, and scientific data, were gathered for the conference. This report collates the details of the output of the workshop.

The “best” test cases include (in no particular order):Use of AI to assist in selecting Decadal Survey priorities.

* Use of AI to identify new, or previously unidentified, science topics for prioritization.

* Using AI to better label and increase discoverability of scientific literature and proposals.

* Use of AI to enhance current observation capabilities for scientific missions.

* Using AI to mitigate biases in selection of proposal reviewers and membership of advisory committees.

Examination of these test cases indicates that Natural Language Processing (NLP) is a common capability found in most of the ”best” (top-rated) test cases and is a valuable, multi-purpose tool which enables ML in this area.