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In this episode of Academic Re:View I am interviewing Faun Rice, a researcher from Canada who recently wrote a very interesting blog on AI-tools for Literature Review.
She evaluated several AI-tools by giving them a research prompt modeled on the objectives of a 2017 project where she had manually synthesized all available materials on an Indigenous language in the Sahtú region.
Because she already knew exactly which documents existed and had previously gathered them, she could measure how well each AI tool surfaced those sources. This allowed her to test their reliability for uncovering niche, hard-to-find materials and to illustrate the “long tail” problem that arises when AI is applied to sparse data.
This episode is especially important for anyone writing a thesis, working on a research project, or even just feeling tempted to lean on AI tools to speed up the process. Faun leaves us with a valuable reminder about the research journey itself: that critical thinking, persistence, and curiosity remain at the heart of good scholarship, no matter what new technologies come along.
You can the entire article Faun wrote here:
Here: https://theimportantwork.substack.com/p/why-ai-assisted-literature-reviews
Follow her on LinkedIN:
https://www.linkedin.com/in/faun-rice/
