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Artificial Intelligence & ChatGPT

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Librarian Jonathan McMichael of SMU outlines some key areas of concern about using ChatGPT for academic research including: "It makes stuff up."   Use the tools with caution. 

Librarians can help with the verification of information.  

Citing

Plagiarism Detection

Considerations

From Dr. Jenna Linskens. "I urge users to be very cautious with relying on these tools as a detection system. Many of them have been proved to be highly inaccurate in detection.  A ChatGPT generated text can be modified with just a few changes in spelling and/or grammar and successfully pass any detection. Here is a recent research paper on text detectors and their lack of ability to accurately determine text generated by large language models (LLM).  Additionally, while many use the term plagiarism for use of an LLM, it has been compared more to academic dishonesty than plagiarism. Plagiarism is the act of knowingly copying someone else’s work without giving credit to the original author, while the use of an LLM to write a 5-paragraph essay is perceived to be the same as paying someone to write a paper on your behalf and saying it is your own."

From Marilyn Dispensa: "Turnitin is beginning to have AI detection but college doesn’t have a license anymore. Whitney Gegg-Harrison of the University of Rochester wrote a long but compelling piece about the problems with AI surveillance tools like this one. Here's an excerpt:

'I don’t have any doubts at all about whose writing is most likely to be viewed with suspicion and thus sent through a tool like GPTZero, because it’s precisely the same sets of students we already subject to this kind of skepticism and policing.  My biggest concern is that schools will listen to the hype and decide to use automated detectors like GPTZero and put their students through 'reverse Turing Tests,' and I know that the students that will be hit hardest are the ones we already police the most: the ones who we think 'shouldn’t' be able to produce clear, clean prose of the sort that LLMs generate. The non-native speakers. The speakers of marginalized dialects. So I’ve been pushing against every suggestion that we should adopt these tools in academic settings.'

Against the use of GPTZero and other LLM-output detection tools "

Information Literacy

Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. Journal of Academic Librarianship, 49(4), N.PAG.  https://doi.org/10.1016/j.acalib.2023.102720

"This article introduces the CLEAR Framework for Prompt Engineering, designed to optimize interactions with AI language models like ChatGPT. The framework encompasses five core principles—Concise, Logical, Explicit, Adaptive, and Reflective—that facilitate more effective AI-generated content evaluation and creation. Additionally, the article discusses technical aspects of prompts, such as tokens, temperature, and top-p settings. By integrating the CLEAR Framework into information literacy instruction, academic librarians can empower students with critical thinking skills for the ChatGPT era and adapt to the rapidly evolving AI landscape in higher education." - Abstract

Cathy Michael

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Cathy Michael
Contact:
Ithaca College Library 953 Danby Rd
Ithaca, NY 14850‑7002
607-274-1293
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