The National Science Foundation recently announced in its “Notice to Research Community:  Use of Generative Artificial Intelligence Technology in the NSF Merit Review Process” that NSF reviewers are prohibited from uploading any proposal content or review records to non-approved GAI tools (they must be behind NSF’s firewall) out of concern for potential violations of confidentiality and integrity principles of the merit review process. Use of GAI in NSF proposals should be indicated in the project description. Specifically, it states: "Proposers are responsible for the accuracy and authenticity of their proposal submission in consideration for merit review, including content developed with the assistance of generative AI tools. NSF's Proposal and Award Policies and Procedures Guide (PAPPG) addresses research misconduct, which includes fabrication, falsification, or plagiarism in proposing or performing NSF-funded research, or in reporting results funded by NSF. Generative AI tools may create these risks, and proposers and awardees are responsible for ensuring the integrity of their proposal and reporting of research results.”

NIH has issued a Notice: The Use of Generative Artificial Intelligence Technologies is Prohibited for NIH Peer Review Process along with a set of FAQs for the Use of Generative AI in Peer Review. Although NIH specifically prohibits GAI in the peer review process, they do not prohibit the use of GAI in grant proposals. They state an author assumes the risk of using an AI tool to help write an application, noting “[…] when we receive a grant application, it is our understanding that it is the original idea proposed by the institution and their affiliated research team.” If AI generated text includes plagiarism, fabricated citations or falsified information, the NIH “will take appropriate actions to address the non-compliance.”

GAI should not be listed as a co-author, but the use of Generative AI should be disclosed in papers, along with a description of the places and manners of use. Typically, such disclosures will be in a “Methods” section of the paper. See the Committee on Publication Ethics’ Authorship and AI tools webpage for more information. If you rely on GAI output, you should cite it. Good citation style recommendations have been suggested by the American Psychological Association (APA) and the Chicago Manual of Style.

Guiding Principles: 

• Use and develop GAI tools in a manner that is ethical, transparent, and mitigates potential biases.
• Use and develop GAI tools in a manner that promotes institutional and research integrity, including scientific rigor and reproducibility.

GAI is a Technology Tool

• Do not rely on GAI tools in the stead of your own critical thinking and sound judgment.
• Users of GAI are responsible and accountable for any actions or outcomes that result from their use and development of GAI tools.
• Be alert to the potential for research misconduct (i.e., data falsification, data fabrication, and/or plagiarism) when using and developing GAI tools.
• Disclose use of GAI tools when appropriate or required (e.g., a journal that will accept a manuscript developed using GAI, provided such use is disclosed).
• Ensure any experimental data used in connection with an GAI tool are accurate, relevant, legally obtained and, when applicable, have the consent of the individuals from whom the data were obtained.
• Make sure you can clearly explain how any GAI tools you create were developed (e.g., describe the data and machine learning models or deep learning algorithms used to train a Large Language Model AI tool).
• Be mindful of how sampling bias in training data and difficulties in interpreting output can be significant roadblocks for the ethical and transparent usage of GAI.
• Make sure any GAI tools you use or develop are subject to human oversight (e.g., humans are involved in the design, development, and testing of the tool).
• Subject any GAI tools you develop with rigorous quality control measures (e.g., test for accuracy and reliability).
• Exercise caution regarding vendor claims about GAI-enabled products, as definitions of GAI and how it is implemented may vary. GAI-enhanced products may not always outperform non-GAI alternatives.

Privacy, Security, and Rules Apply to GAI Tools

• Do not use GAI tools when prohibited (e.g., a sponsor that does not allow use of GAI for peer review).
• If applicable, be cognizant to identify and protect the privacy and security of individuals when using and developing GAI tools.
• Do not provide or share intellectual property or confidential/sensitive data with GAI tools that incorporate users’ content into their publicly accessible models.
• Report any potential data breaches or confidentiality lapses involving GAI tools to the appropriate UTA authority.
• Any acquisition, deployment, or agreement involving a vendor or vendor product using GAI must follow UTA’s established legal, information security, audit, and procurement rules.