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Generative AI and Research

Best practices for using AI technology for research

Introduction to AI Research Platforms

AI-powered research tools have become increasingly important in academic research, offering other ways of doing research beside the traditional library databases. Tools like Perplexity, Scite, Elicit, Keenious, Consensus, ResearchRabbit, and OpenAlex provide various features, including citation analysis, literature discovery, and evidence-based insights. While these tools offer significant advantages in streamlining tasks such as literature reviews, identifying relevant papers, and tracking citation networks, they also have limitations, such as coverage gaps, reliance on metadata, and the need for validation of the sources.

AI Research Platforms

Quotations are taken from the Ithaka S+R Generative AI Product Tracker.

Deciphering the AI Research Platform Maze: A Comparative Analysis

               

 

Charles Gallagher and Kevin Gunn, librarians at The Catholic University of America Libraries, gave this workshop to their colleagues at The Washington Research Library Consortium Annual Meeting on May 22, 2024.

Testing AI Tools

As with any tool used in digital scholarship, you should spend some time researching the best tool to answer your research questions. Two excellent resources include:

  • Temple University Libraries has created an AI Tools Report Card assessment rubric for asking questions in evaluating AI-powered research tools.
  • ITHAKA S+R created the Generative AI Product Tracker that lists generative AI products marketed to faculty and students for teaching, learning, or research. This list is updated regularly. Currently 63 pages long!

Rubric for Evaluating AI Tools

Librarians at the State University of New York at Oswego have created a rubric for evaluating AI research tools.

Caico, Marissa; Harris, Laura; O'Shea, Sarah; Mitchell, Emily. 2024. Evaluative Information Literacy Rubric for AI Tools.