This guide is intended to support researchers as they navigate the emergent landscape of generative artificial intelligence (GenAI) applications that are marketed to students and educators as effective tools for academic research. Resources are mentioned here for informational purposes only; their inclusion is not an endorsement or recommendation of their use by NYU or NYU Libraries. We encourage you to think critically about each tool that you use including how it was created, what it does, how you use it, and how it interacts with the rest of your research materials and processes.
GenAI tools are not a substitute for learning the fundamentals of conducting research. As you start your project, take a look at our related research guides for help with your research process, including:
Academic research is the exploration, evaluation, collection, organization, analysis, and synthesis of sources and materials in support of a scholarly argument.
GenAI tools can be useful for some high-level tasks such as brainstorming, for discovering new terms and unexpected connections between ideas, and, to a certain degree, writing coding, but every output generated by AI must be independently verified. Verification may require different skills depending on the output e.g. evaluating the accuracy of statements, running code without errors, identifying positive or negative bias, confirming a citation or cited source really exists, et al..
Any use and/or the transparency of use must align with the guidelines set forth by your institution and instructors or evaluators.
As with all tools and resources, be sure to follow the policies that your institution has set in place to maintain academic integrity.
If you are a part of the NYU community, Teaching with Generative AI provides guidelines that highlight important considerations when it comes to:
For more information on Generative AI and academic integrity for academic research see our Research Guide: Generative AI and Academic Integrity.
