Use AI to populate reviewer "areas of expertise" and state of potential Regional Engines submitters (members of organizations)
Description
TIP is authorized to use Airtable for project management, including reviewer volunteers and recruitment. Airtable is a no-code platform that includes a built-in database. This system does not store any PII in the database except for "public PII" such as name, position, work email address, areas of professional expertise, etc. We have two specific use-cases for which we would like to employ Airtable AI: 1. People who volunteer sometimes do not list all areas of their expertise, or expertise becomes stale. We have been able to do a proof of concept where Airtable AI is prompted to look at the potential reviewer's Linked In profile and identify or update the potential reviewer's expertise in its database based on recent updates to professional experience in LinkedIn. We would like permission to have AI complete this work. Typically, an admin person or Program Director will do this work and it is time-consuming and burdensome. AI can do it much faster and a member of the staff can check it rather than complete it for 400-500 reviewers. 2. We also have a database of potential Engines submitters in Airtable -- people who have attended a webinar, roadshow, or submitted at an earlier time and asked to be contacted when new funding opportunities are available. We track very similar information in the potential submitters data base as we do for reviewers who volunteer to review for the program. The information is used to support outreach to these potential submitters when new funding opportunities are announced, or a new Engines event is announced. We need to know the state associated with the particular submitters institution to determine which regional Engine they should be mapped to geographically (state in the U.S.). We have found that we can prompt the AI to look at the potential submitter's institution, and the AI can locate the state 100% of the time to identify the region that the submitter would be associated with if they were accepted to the program. Currently, a staff person does this work, and it is burdensome. The AI can do this work much faster, so that a member of the staff can redirect their time to more value-added work and then go back and validate the AI's work. This permits the NSF Regional Innovation Engines program to segment outreach by event and regional engine . The Airtable AI is an Airtable private instance of OpenAI.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Controls / human review
ATO: Not reported; PIA: Not published