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Region 4 News November 17th, 2024
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NSF’s Generative Artificial Intelligence Update

Posted in: #CC/Academic List, #Health Interest List, #Health Sciences List, Data Science


Please note: This article was originally posted on the U.S. National Science Foundation’s site.

Generative artificial intelligence (GAI) systems have great potential to support the U.S. National Science Foundation’s mission to promote the progress of science. They could facilitate creativity and aid in the development of new scientific insights and streamline agency processes by enhancing productivity through the automation of routine tasks. While NSF will continue to support advances in this new technology, the agency must also consider the potential risks posed by it. The agency cannot protect non-public information disclosed to third-party GAI from being recorded and shared. To safeguard the integrity of the development and evaluation of proposals in the merit review process, this memo establishes guidelines for its use by reviewers and proposers:

  • NSF reviewers are prohibited from uploading any content from proposals, review information and related records to non-approved generative AI tools.
  • Proposers are encouraged to indicate in the project description the extent to which, if any, generative AI technology was used and how it was used to develop their proposal.

A key observation for reviewers is that sharing proposal information with generative AI technology via the open internet violates the confidentiality and integrity principles of NSF’s merit review process. Any information uploaded into generative AI tools not behind NSF’s firewall is considered to be entering the public domain. As a result, NSF cannot preserve the confidentiality of that information. The loss of control over the uploaded information can pose significant risks to researchers and their control over their ideas. In addition, the source and accuracy of the information derived from this technology is not always clear, which can lead to research integrity concerns including the authenticity of authorship.

To read the full story, visit NSF’s news page.

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